# packages

pkgId: 4ee62b11cbfb0b09b705c14036f09755661144df4fcf04af7a946feb1d6530e9
name: python-aa-skillfarm
arch: src
version: 0.3.3
epoch: 0
release: 1
summary: A Skillfarm Tracker Module for Alliance Auth
url: https://github.com/Geuthur/aa-skillfarm
rpm_group: Unspecified
rpm_buildhost: localhost
location_href: Packages/python-aa-skillfarm-0.3.3-1.src.rpm
checksum_type: sha256
description:
  [![pre-commit.ci status](https://results.pre-commit.ci/badge/github/Geuthur/aa-skillfarm/master.svg)](https://results.pre-commit.ci/latest/github/Geuthur/aa-skillfarm/master)
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  [![codecov](https://codecov.io/gh/Geuthur/aa-skillfarm/graph/badge.svg?token=oFZPpgIXz4)](https://codecov.io/gh/Geuthur/aa-skillfarm)

  [![ko-fi](https://ko-fi.com/img/githubbutton_sm.svg)](https://ko-fi.com/W7W810Q5J4)

  The Skillfarm Tracker Module for Alliance Auth tracks skill queues, sends notifications if skills finished and highlights them, making skill management easier for Skillfarms.

  ______________________________________________________________________

  - [AA Skillfarm](#aa-skillfarm)
    - [Features](#features)
    - [Upcoming](#upcoming)
    - [Installation](#features)
      - [Step 0 - Check dependencies are installed](#step0)
      - [Step 1 - Install the Package](#step1)
      - [Step 2 - Configure Alliance Auth](#step2)
      - [Step 3 - Add the Scheduled Tasks and Settings](#step3)
      - [Step 4 - Migration to AA](#step4)
      - [Step 5 - Setting up Permissions](#step5)
      - [Step 6 - (Optional) Setting up Compatibilies](#step6)
    - [Highlights](#highlights)



  - Graphical Design
  - Characters Overview
  - Skillfarm Information Sheet
    - Filtered Skill Queue
    - Filtered Skills
    - Highlight finished Skills
    - No Active Training hint
  - Filter Skills for each Character
  - Notification System
  - Enable/Disable Characters



  > \[!NOTE\]
  > AA Skillfarm needs at least Alliance Auth v4.0.0
  > Please make sure to update your Alliance Auth before you install this APP



  - Skillfarm needs the app [django-eveuniverse](https://apps.allianceauth.org/apps/detail/django-eveuniverse) to function. Please make sure it is installed.



  Make sure you're in your virtual environment (venv) of your Alliance Auth then install the pakage.

  ```shell
  pip install aa-skillfarm
  ```



  Configure your Alliance Auth settings (`local.py`) as follows:

  - Add `'skillfarm',` to `INSTALLED_APPS`



  To set up the Scheduled Tasks add following code to your `local.py`

  ```python
  CELERYBEAT_SCHEDULE["skillfarm_update_all_skillfarm"] = {
      "task": "skillfarm.tasks.update_all_skillfarm",
      "schedule": crontab(minute=0, hour="*/1"),
  }

  CELERYBEAT_SCHEDULE["skillfarm_check_skillfarm_notifications"] = {
      "task": "skillfarm.tasks.check_skillfarm_notifications",
      "schedule": crontab(minute=0, hour="*/12"),
  }
  ```



  ```shell
  python manage.py collectstatic
  python manage.py migrate
  ```



  With the Following IDs you can set up the permissions for the Skillfarm

  | ID             | Description                                      |                                                           |
  | :------------- | :----------------------------------------------- | :-------------------------------------------------------- |
  | `basic_access` | Can access the Skillfarm module                  | All Members with the Permission can access the Skillfarm. |
  | `corp_access`  | Has access to all characters in the corporation. | Can see all Skillfarm Characters from own Corporation.    |
  | `admin_access` | Has access to all characters                     | Can see all Skillfarm Characters.                         |



  The Following Settings can be setting up in the `local.py`

  | Setting Name                      | Descriptioon                                           | Default       |
  | --------------------------------- | ------------------------------------------------------ | ------------- |
  | `SKILLFARM_APP_NAME`              | Set the name of the APP                                | `"Skillfarm"` |
  | `SKILLFARM_LOGGER_USE`            | Set to use own Logger File `True/False`                | `False`       |
  | `SKILLFARM_STALE_STATUS`          | Set the Stale Status for Skillfarm Character in hours  | `3`           |
  | `SKILLFARM_NOTIFICATION_COOLDOWN` | Number of days to wait before resending a notification | `3`           |

  If you set up SKILLFARM_LOGGER_USE to `True` you need to add the following code below:

  ```python
  LOGGING_SKILLFARM = {
      "handlers": {
          "skillfarm_file": {
              "level": "INFO",
              "class": "logging.handlers.RotatingFileHandler",
              "filename": os.path.join(BASE_DIR, "log/skillfarm.log"),
              "formatter": "verbose",
              "maxBytes": 1024 * 1024 * 5,
              "backupCount": 5,
          },
      },
      "loggers": {
          "skillfarm": {
              "handlers": ["skillfarm_file", "console"],
              "level": "INFO",
          },
      },
  }
  LOGGING["handlers"].update(LOGGING_SKILLFARM["handlers"])
  LOGGING["loggers"].update(LOGGING_SKILLFARM["loggers"])
  ```



  ![skillfarm1](https://github.com/user-attachments/assets/b7a99b75-39c0-4349-84ae-89c5c48262c2)
  ![Screenshot 2024-09-21 012008](https://github.com/user-attachments/assets/567197cc-c55f-4b0e-b470-d4ceeadcfb15)

  > \[!NOTE\]
  > Contributing
  > You want to improve the project?
  > Just Make a [Pull Request](https://github.com/Geuthur/aa-skillfarm/pulls) with the Guidelines.
  > We Using pre-commit

rpm_license:
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IN NO EVENT UNLESS REQUIRED BY APPLICABLE LAW OR AGREED TO IN WRITING WILL ANY COPYRIGHT HOLDER, OR ANY OTHER PARTY WHO MODIFIES AND/OR CONVEYS THE PROGRAM AS PERMITTED ABOVE, BE LIABLE TO YOU FOR DAMAGES, INCLUDING ANY GENERAL, SPECIAL, INCIDENTAL OR CONSEQUENTIAL DAMAGES ARISING OUT OF THE USE OR INABILITY TO USE THE PROGRAM (INCLUDING BUT NOT LIMITED TO LOSS OF DATA OR DATA BEING RENDERED INACCURATE OR LOSSES SUSTAINED BY YOU OR THIRD PARTIES OR A FAILURE OF THE PROGRAM TO OPERATE WITH ANY OTHER PROGRAMS), EVEN IF SUCH HOLDER OR OTHER PARTY HAS BEEN ADVISED OF THE POSSIBILITY OF SUCH DAMAGES.  17. Interpretation of Sections 15 and 16.  If the disclaimer of warranty and limitation of liability provided above cannot be given local legal effect according to their terms, reviewing courts shall apply local law that most closely approximates an absolute waiver of all civil liability in connection with the Program, unless a warranty or assumption of liability accompanies a copy of the Program in return for a fee.  END OF TERMS AND CONDITIONS  How to Apply These Terms to Your New Programs  If you develop a new program, and you want it to be of the greatest possible use to the public, the best way to achieve this is to make it free software which everyone can redistribute and change under these terms.  To do so, attach the following notices to the program.  It is safest to attach them to the start of each source file to most effectively state the exclusion of warranty; and each file should have at least the "copyright" line and a pointer to where the full notice is found.  AA Skillfarm Module for Alliance Auth Copyright (C) 2024  Geuthur  This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.  This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU General Public License for more details.  You should have received a copy of the GNU General Public License along with this program.  If not, see <https://www.gnu.org/licenses/>.  Also add information on how to contact you by electronic and paper mail.  If the program does terminal interaction, make it output a short notice like this when it starts in an interactive mode:  AA Skillfarm  Copyright (C) 2024  Geuthur This program comes with ABSOLUTELY NO WARRANTY; for details type `show w'. This is free software, and you are welcome to redistribute it under certain conditions; type `show c' for details.  The hypothetical commands `show w' and `show c' should show the appropriate parts of the General Public License.  Of course, your program's commands might be different; for a GUI interface, you would use an "about box".  You should also get your employer (if you work as a programmer) or school, if any, to sign a "copyright disclaimer" for the program, if necessary. For more information on this, and how to apply and follow the GNU GPL, see <https://www.gnu.org/licenses/>.  The GNU General Public License does not permit incorporating your program into proprietary programs.  If your program is a subroutine library, you may consider it more useful to permit linking proprietary applications with the library.  If this is what you want to do, use the GNU Lesser General Public License instead of this License.  But first, please read <https://www.gnu.org/licenses/why-not-lgpl.html>.


pkgId: c449b11fbe53647566abc5ccbf493783a504c94b2590d6779c74074f5611322a
name: python-aa-sov-timer
arch: src
version: 2.2.0
epoch: 0
release: 1
summary: Sov Campaign Timer for Alliance Auth
url: https://github.com/ppfeufer/aa-sov-timer
rpm_group: Unspecified
rpm_buildhost: localhost
location_href: Packages/python-aa-sov-timer-2.2.0-1.src.rpm
checksum_type: sha256
description:
  [![Version](https://img.shields.io/pypi/v/aa-sov-timer?label=release "Version")](https://pypi.org/project/aa-sov-timer/)
  [![License](https://img.shields.io/badge/license-GPLv3-green "License")](https://pypi.org/project/aa-sov-timer/)
  [![Python](https://img.shields.io/pypi/pyversions/aa-sov-timer "Python")](https://pypi.org/project/aa-sov-timer/)
  [![Django](https://img.shields.io/pypi/djversions/aa-sov-timer?label=django "Django")](https://pypi.org/project/aa-sov-timer/)
  ![pre-commit](https://img.shields.io/badge/pre--commit-enabled-brightgreen?logo=pre-commit&logoColor=white)
  [![pre-commit.ci status](https://results.pre-commit.ci/badge/github/ppfeufer/aa-sov-timer/master.svg)](https://results.pre-commit.ci/latest/github/ppfeufer/aa-sov-timer/master)
  [![Code Style: black](https://img.shields.io/badge/code%20style-black-000000.svg "Code Style: black")](http://black.readthedocs.io/en/latest/)
  [![Automated Checks](https://github.com/ppfeufer/aa-sov-timer/actions/workflows/automated-checks.yml/badge.svg "Automated Checks")](https://github.com/ppfeufer/aa-sov-timer/actions/workflows/automated-checks.yml)
  [![codecov](https://codecov.io/gh/ppfeufer/aa-sov-timer/branch/master/graph/badge.svg?token=J9PBF0HM8C "codecov")](https://codecov.io/gh/ppfeufer/aa-sov-timer)
  [![Translation status](https://weblate.ppfeufer.de/widget/alliance-auth-apps/aa-sov-timer/svg-badge.svg)](https://weblate.ppfeufer.de/engage/alliance-auth-apps/)
  [![Contributor Covenant](https://img.shields.io/badge/Contributor%20Covenant-2.1-4baaaa.svg "Contributor Covenant")](https://github.com/ppfeufer/aa-forum/blob/master/CODE_OF_CONDUCT.md)
  [![Discord](https://img.shields.io/discord/790364535294132234?label=discord "Discord")](https://discord.gg/zmh52wnfvM)

  [![ko-fi](https://ko-fi.com/img/githubbutton_sm.svg)](https://ko-fi.com/N4N8CL1BY)

  Sovereignty campaign overview for Alliance Auth.

  ______________________________________________________________________

  <!-- mdformat-toc start --slug=github --maxlevel=6 --minlevel=1 -->

  - [AA Sovereignty Timer](#aa-sovereignty-timer)
    - [Screenshots](#screenshots)
      - [AA Sov Timer Dashboard](#aa-sov-timer-dashboard)
    - [Installation](#installation)
      - [Step 1: Installing the App](#step-1-installing-the-app)
      - [Step 2: Update Your AA Settings](#step-2-update-your-aa-settings)
      - [Step 3: Finalizing the Installation](#step-3-finalizing-the-installation)
      - [Step 4: Preload Eve Universe Data](#step-4-preload-eve-universe-data)
      - [Step 5: Setting up Permission](#step-5-setting-up-permission)
      - [Step 6: Keep Campaigns Updated](#step-6-keep-campaigns-updated)
    - [Updating](#updating)
    - [Changelog](#changelog)
    - [Translation Status](#translation-status)
    - [Contributing](#contributing)

  <!-- mdformat-toc end -->

  ______________________________________________________________________





  ![AA Sov Timer Dashboard](https://raw.githubusercontent.com/ppfeufer/aa-sov-timer/master/docs/images/presentation/aa-sov-timer.jpg "AA Sov Timer Dashboard")



  > \[!NOTE\]
  >
  > **AA Sov Timer >= 2.0.0 needs at least Alliance Auth v4.0.0!**
  >
  > Please make sure to update your Alliance Auth instance _before_ you install this
  > module or update to the latest version, otherwise an update to Alliance Auth will
  > be pulled in unsupervised.
  >
  > The last version compatible with Alliance Auth v3 is `1.12.3`.

  **Important**: Please make sure you meet all preconditions before you proceed:

  - AA Sovereignty Timer is a plugin for Alliance Auth. If you don't have Alliance
    Auth running already, please install it first before proceeding. (see the official
    [AA installation guide](https://allianceauth.readthedocs.io/en/latest/installation/allianceauth.html) for details)
  - AA Sovereignty Timer needs the app [django-eveuniverse](https://gitlab.com/ErikKalkoken/django-eveuniverse)
    to function. Please make sure it is installed before continuing.



  Make sure you're in the virtual environment (venv) of your Alliance Auth installation.
  Then install the latest version:

  ```shell
  pip install aa-sov-timer
  ```



  Configure your AA settings (`local.py`) as follows:

  - Add `'eveuniverse',` to `INSTALLED_APPS`
  - Add `'sovtimer',` to `INSTALLED_APPS`

  Restart your supervisor



  Copy static files and run migrations

  ```shell
  python manage.py collectstatic
  ```

  ```shell
  python manage.py migrate
  ```



  AA Sovereignty Timer uses Eve Universe data to map IDs to names for solar systems,
  regions and constellations. So you need to preload some data from ESI once.
  If you already have run this command, you can skip this step.

  ```shell
  python manage.py eveuniverse_load_data map
  ```

  ```shell
  python manage.py sovtimer_load_initial_data
  ```

  Both commands might take a moment or two, so be patient ...



  Now you can set up permissions in Alliance Auth for your users.
  Add `sovtimer | Sovereignty Timer | Can access the Sovereignty Timer module` to
  the states and/or groups you would like to have access.



  Add the following scheduled task to your `local.py`. One done, restart your supervisor.

  ```python

  CELERYBEAT_SCHEDULE["sovtimer.tasks.run_sov_campaign_updates"] = {
      "task": "sovtimer.tasks.run_sov_campaign_updates",
      "schedule": 30.0,
  }
  ```

  Now your system is updating the sovereignty campaigns every 30 seconds.



  To update your existing installation of AA Sovereignty Timer, first enable your
  virtual environment.

  Then run the following commands from your AA project directory (the one that
  contains `manage.py`).

  ```shell
  pip install -U aa-sov-timer
  ```

  ```shell
  python manage.py collectstatic
  ```

  ```shell
  python manage.py migrate
  ```

  Finally, restart your AA supervisor services.



  See [CHANGELOG.md]



  [![Translation status](https://weblate.ppfeufer.de/widget/alliance-auth-apps/aa-sov-timer/multi-auto.svg)](https://weblate.ppfeufer.de/engage/alliance-auth-apps/)

  Do you want to help translate this app into your language or improve the existing
  translation? - [Join our team of translators][weblate engage]!



  Do you want to contribute to this project? That's cool!

  Please make sure to read the [Contribution Guidelines].\
  (I promise, it's not much, just some basics)

  <!-- Links -->

  [changelog.md]: https://github.com/ppfeufer/aa-sov-timer/blob/master/CHANGELOG.md
  [contribution guidelines]: https://github.com/ppfeufer/aa-sov-timer/blob/master/CONTRIBUTING.md "Contribution Guidelines"
  [weblate engage]: https://weblate.ppfeufer.de/engage/alliance-auth-apps/ "Weblate Translations"

rpm_license:
[cell repeats an earlier one in this file: 34486 characters]


pkgId: 5bba1673db25810753708645c32ca4fd53b117db1a3ea4068644dc8477ebf9a1
name: python-aa-squads
arch: src
version: 0.2.4.1
epoch: 0
release: 1
summary: Squads plugin app for Alliance Auth
url: https://github.com/Geuthur/aa-squads
rpm_group: Unspecified
rpm_buildhost: localhost
location_href: Packages/python-aa-squads-0.2.4.1-1.src.rpm
checksum_type: sha256
description:
  [![pre-commit.ci status](https://results.pre-commit.ci/badge/github/Geuthur/aa-squads/master.svg)](https://results.pre-commit.ci/latest/github/Geuthur/aa-squads/master)
  [![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)
  [![Checks](https://github.com/Geuthur/aa-squads/actions/workflows/autotester.yml/badge.svg)](https://github.com/Geuthur/aa-squads/actions/workflows/autotester.yml)
  [![codecov](https://codecov.io/gh/Geuthur/aa-squads/graph/badge.svg?token=yPAkMfj3cD)](https://codecov.io/gh/Geuthur/aa-squads)

  - [AA Squads](#aa-squads)
    - [Features](#features)
    - [Upcoming](#upcoming)
    - [Installation](#features)
      - [Step 1 - Install the Package](#step1)
      - [Step 2 - Configure Alliance Auth](#step2)
      - [Step 3 - Add the Scheduled Tasks and Settings](#step3)
      - [Step 4 - Migration to AA](#step4)
      - [Step 5 - Setting up Permissions](#step5)
      - [Step 6 - (Optional) Setting up Compatibilies](#step6)
    - [Highlights](#highlights)



  - Detailed Squad Information (html)
  - Squad Filters
  - Overview of Members in Squads
  - Check Member States if they met Filters
  - Updating Member States on Filter changes



  - More Filters.
  - Missing Skills can be imported from EVE Online Skillplaner



  > \[!NOTE\]
  > AA Squads needs at least Alliance Auth v4.0.0
  > Please make sure to update your Alliance Auth before you install this APP



  Make sure you're in your virtual environment (venv) of your Alliance Auth then install the pakage.

  ```shell
  pip install aa-squads
  ```



  Configure your Alliance Auth settings (`local.py`) as follows:

  - Add `'eveuniverse',` to `INSTALLED_APPS`
  - Add `'memberaudit',` to `INSTALLED_APPS`
  - Add `'squads',` to `INSTALLED_APPS`



  You can change the interval if you want.

  ```python
  CELERYBEAT_SCHEDULE["run_check_squads"] = {
      "task": "squads.tasks.run_check_squads",
      "schedule": crontab(minute=0, hour="*/12"),
  }
  ```



  ```shell
  python manage.py collectstatic
  python manage.py migrate
  ```



  With the Following IDs you can set up the permissions for the Squads

  | ID              | Description                  |                                                                        |
  | :-------------- | :--------------------------- | :--------------------------------------------------------------------- |
  | `basic_access`  | Can access the Squads module | All Members with the Permission can access the Squads.                 |
  | `squad_manager` | Can Create / Manage Squads   | Manage Squads like Edit, Create Squads, Approve, Decline Request, etc. |
  | `squad_admin`   | Can View All Squads          | Can View all Squads.                                                   |



  The Following Settings can be setting up in the `local.py`

  - SQUADS_APP_NAME:          `"YOURNAME"`     - Set the name of the APP
  - SQUADS_LOGGER_USE:        `True / False`   - Set to use own Logger File

  If you set up SQUADS_LOGGER_USE to `True` you need to add the following code below:

  ```python
  LOGGING_SQUADS = {
      "handlers": {
          "squads_file": {
              "level": "INFO",
              "class": "logging.handlers.RotatingFileHandler",
              "filename": os.path.join(BASE_DIR, "log/squads.log"),
              "formatter": "verbose",
              "maxBytes": 1024 * 1024 * 5,
              "backupCount": 5,
          },
      },
      "loggers": {
          "squads": {
              "handlers": ["squads_file", "console"],
              "level": "INFO",
          },
      },
  }
  LOGGING["handlers"].update(LOGGING_SQUADS["handlers"])
  LOGGING["loggers"].update(LOGGING_SQUADS["loggers"])
  ```



  ![Screenshot 2024-06-09 164402](https://github.com/Geuthur/aa-squads/assets/761682/5bf9eb99-1d61-4562-9bb3-02f9d3ae3ac2)
  ![Screenshot 2024-06-09 164408](https://github.com/Geuthur/aa-squads/assets/761682/5a79ca79-145a-4558-befc-2b0529675712)
  ![Screenshot 2024-06-09 164431](https://github.com/Geuthur/aa-squads/assets/761682/b79f1519-0a70-483b-9def-3ec120e4cd46)
  ![Screenshot 2024-06-09 164502](https://github.com/Geuthur/aa-squads/assets/761682/1249d415-9d72-4cf0-8c62-d1ac4db72986)
  ![Screenshot 2024-06-09 164516](https://github.com/Geuthur/aa-squads/assets/761682/66608190-42db-4780-9b10-c8832d96cb2d)
  ![Screenshot 2024-06-09 164508](https://github.com/Geuthur/aa-squads/assets/761682/c989d2ed-6602-441b-b903-b7f22ecf69c0)
  ![Screenshot 2024-06-10 235804](https://github.com/Geuthur/aa-squads/assets/761682/e0c816e6-2b5b-421f-add3-57628ad05004)

  > \[!NOTE\]
  > Contributing
  > You want to improve the project?
  > Just Make a [Pull Request](https://github.com/Geuthur/aa-squads/pulls) with the Guidelines.
  > We Using pre-commit

rpm_license:
[cell repeats an earlier one in this file: 34486 characters]


pkgId: 8264611541c047f33a045704eaf85c0c56a3f059991e4bbf1f2e41f529ad8137
name: python-aa-srp
arch: src
version: 2.5.0
epoch: 0
release: 1
summary: Improved SRP Module for Alliance Auth
url: https://github.com/ppfeufer/aa-srp
rpm_group: Unspecified
rpm_buildhost: localhost
location_href: Packages/python-aa-srp-2.5.0-1.src.rpm
checksum_type: sha256
description:
  [![Badge: Version]][aa srp on pypi]
  [![Badge: License]][aa srp license]
  [![Badge: Supported Python Versions]][aa srp on pypi]
  [![Badge: Supported Django Versions]][aa srp on pypi]
  ![Badge: pre-commit]
  [![Badge: pre-commit.ci status]][pre-commit.ci status]
  [![Badge: Code Style: black]][black code formatter documentation]
  [![Badge: Support Discord]][support discord]
  [![Badge: Automated Tests]][automated tests on github]
  [![Badge: Code Coverage]][aa srp on codecov]
  [![Badge: Translation Status]][weblate engage]
  [![Badge: Contributor Covenant]][code of conduct]

  [![Badge: Buy me a coffee]][ppfeufer on ko-fi]

  SRP Module for [Alliance Auth]

  ______________________________________________________________________

  <!-- mdformat-toc start --slug=github --maxlevel=6 --minlevel=2 -->

  - [Overview](#overview)
    - [Features](#features)
    - [Screenshots](#screenshots)
      - [Dashboard](#dashboard)
      - [Dashboard (View All)](#dashboard-view-all)
      - [Your SRP Requests](#your-srp-requests)
      - [SRP Requests Overview](#srp-requests-overview)
      - [SRP Request Details](#srp-request-details)
  - [Installation](#installation)
    - [Step 1: Install the Package](#step-1-install-the-package)
    - [Step 2: Configure Alliance Auth](#step-2-configure-alliance-auth)
    - [Step 3: Finalizing the Installation](#step-3-finalizing-the-installation)
    - [Step 4: Preload Eve Universe Data](#step-4-preload-eve-universe-data)
    - [Step 5: Setting up Permissions](#step-5-setting-up-permissions)
    - [Step 6: (Optional) Import From Built-in SRP Module](#step-6-optional-import-from-built-in-srp-module)
  - [Permissions](#permissions)
  - [Changelog](#changelog)
  - [Translation Status](#translation-status)
  - [Contributing](#contributing)

  <!-- mdformat-toc end -->

  ______________________________________________________________________





  - Overview of SRP links
  - Overview of your own SRP requests and their status
  - Accepting kill mails from [zKillboard], [EveTools Killboard] and [EVE-Kill]
  - SRP Request administration is mostly done via ajax and without page reloads
  - Use modern DataTables with filters where ever they're useful
  - Tables fully searchable and sortable
  - Mandatory reason on SRP reject
  - Notifications in AA with detailed information on SRP rejection
  - Discord notification via PM to the user on SRP request approval or rejection, if
    either [AA-Discordbot], [Discord Notify] or [Discord Proxy] is installed
  - Notify your SRP team (optional) in their Discord channel about new SRP requests, if
    [AA-Discordbot] or [Discord Proxy] is installed





  ![Image: AA SRP Dashboard]



  ![Image: AA SRP Dashboard (View All)]



  ![Image: Your SRP Requests View]



  ![Image: SRP Requests Overview]



  ![Image: SRP Request Details]



  > \[!NOTE\]
  >
  > **AA SRP >= 2.0.0 needs at least Alliance Auth v4.0.0!**
  >
  > Please make sure to update your Alliance Auth instance _before_ you install this
  > module or update to the latest version, otherwise an update to Alliance Auth will
  > be pulled in unsupervised.
  >
  > The last version of AA SRP that supports Alliance Auth v3 is `1.21.0`.

  **Important**: Please make sure you meet all preconditions before you proceed:

  - AA SRP is a plugin for Alliance Auth. If you don't have Alliance Auth running
    already, please install it first before proceeding. (see the official
    [Alliance Auth installation guide] for details)
  - AA SRP needs [Eve Universe] to function. Please make sure it is installed, before
    continuing.



  Make sure you're in the virtual environment (venv) of your Alliance Auth
  installation Then install the latest release directly from PyPi.

  ```shell
  pip install aa-srp
  ```



  This is fairly simple, just add the following to the `INSTALLED_APPS` of your `local.py`

  Configure your AA settings (`local.py`) as follows:

  - Add `"eveuniverse",` to `INSTALLED_APPS`
  - Add `"aasrp",` to `INSTALLED_APPS`



  Run static files collection and migrations

  ```shell
  python manage.py collectstatic
  python manage.py migrate
  ```

  Restart your supervisor services for Auth



  AA SRP utilizes the EveUniverse module, so it doesn't need to ask ESI for ship
  information. To set this up, you now need to run the following command.

  ```shell
  python manage.py aasrp_load_eve
  ```



  Now it's time to set up access permissions for your new SRP module. You can do so in
  your admin backend in the AA SRP section. Read the [Permissions](#permissions)
  section for more information about the available permissions.



  **This step is only needed when you have been using the built-in SRP module until now.**

  Make sure you don't have any open SRP requests before. All SRP links in the built-in
  module will be closed during the import process, to make sure to not import any
  duplicates.

  The import process can be done at any given time and doesn't necessarily have to be
  during the installation.

  To import your SRP information from the built-in SRP module, run the following command.

  ```shell
  python manage.py aasrp_migrate_srp_data
  ```



  | ID                    | Description                  | Notes                                                                                                       |
  | --------------------- | ---------------------------- | ----------------------------------------------------------------------------------------------------------- |
  | `basic_access`        | Can access the AA SRP module | Your line members should have this permission.                                                              |
  | `create_srp`          | Can create new SRP links     | Your FCs should have this permission.                                                                       |
  | `manage_srp`          | Can manage SRP               | Users with this permission can manage the AA SRP Module. Like changing and removing SRP links and requests. |
  | `manage_srp_requests` | Can manage SRP requests      | Users with this permission can manage the SRP requests. Like changing and removing SRP requests.            |



  See [CHANGELOG.md]



  [![Translation status](https://weblate.ppfeufer.de/widget/alliance-auth-apps/aa-srp/multi-auto.svg)](https://weblate.ppfeufer.de/engage/alliance-auth-apps/)

  Do you want to help translate this app into your language or improve the existing
  translation? - [Join our team of translators][weblate engage]!



  You want to contribute to this project? That's cool!

  Please make sure to read the [Contribution Guidelines].\
  (I promise, it's not much, just some basics)

  <!-- Links -->

  [aa srp license]: https://github.com/ppfeufer/aa-srp/blob/master/LICENSE
  [aa srp on codecov]: https://codecov.io/gh/ppfeufer/aa-srp
  [aa srp on pypi]: https://pypi.org/project/aa-srp/
  [aa-discordbot]: https://github.com/pvyParts/allianceauth-discordbot "AA-Discordbot"
  [alliance auth]: https://gitlab.com/allianceauth/allianceauth "Alliance Auth"
  [alliance auth installation guide]: https://allianceauth.readthedocs.io/en/latest/installation/allianceauth.html "Alliance Auth installation guide"
  [automated tests on github]: https://github.com/ppfeufer/aa-srp/actions/workflows/automated-checks.yml
  [badge: automated tests]: https://github.com/ppfeufer/aa-srp/actions/workflows/automated-checks.yml/badge.svg "Automated Tests"
  [badge: buy me a coffee]: https://ko-fi.com/img/githubbutton_sm.svg "Buy me a coffee"
  [badge: code coverage]: https://codecov.io/gh/ppfeufer/aa-srp/branch/master/graph/badge.svg "Code Coverage"
  [badge: code style: black]: https://img.shields.io/badge/code%20style-black-000000.svg "Code Style: black"
  [badge: contributor covenant]: https://img.shields.io/badge/Contributor%20Covenant-2.1-4baaaa.svg "Contributor Covenant"
  [badge: license]: https://img.shields.io/github/license/ppfeufer/aa-srp "License"
  [badge: pre-commit]: https://img.shields.io/badge/pre--commit-enabled-brightgreen?logo=pre-commit&logoColor=white "pre-commit"
  [badge: pre-commit.ci status]: https://results.pre-commit.ci/badge/github/ppfeufer/aa-srp/master.svg "pre-commit.ci status"
  [badge: support discord]: https://img.shields.io/discord/790364535294132234?label=discord "Support Discord"
  [badge: supported django versions]: https://img.shields.io/pypi/djversions/aa-srp?label=django "Supported Django Versions"
  [badge: supported python versions]: https://img.shields.io/pypi/pyversions/aa-srp "Supported Python Versions"
  [badge: translation status]: https://weblate.ppfeufer.de/widget/alliance-auth-apps/aa-srp/svg-badge.svg "Translation Status"
  [badge: version]: https://img.shields.io/pypi/v/aa-srp?label=release "Version"
  [black code formatter documentation]: http://black.readthedocs.io/en/latest/
  [changelog.md]: https://github.com/ppfeufer/aa-srp/blob/master/CHANGELOG.md "CHANGELOG.md"
  [code of conduct]: https://github.com/ppfeufer/aa-srp/blob/master/CODE_OF_CONDUCT.md
  [contribution guidelines]: https://github.com/ppfeufer/aa-srp/blob/master/CONTRIBUTING.md "Contribution Guidelines"
  [discord notify]: https://gitlab.com/ErikKalkoken/aa-discordnotify "Discord Notify"
  [discord proxy]: https://gitlab.com/ErikKalkoken/discordproxy "Discord Proxy"
  [eve universe]: https://gitlab.com/ErikKalkoken/django-eveuniverse "Eve Universe"
  [eve-kill]: https://eve-kill.com/ "EVE-Kill"
  [evetools killboard]: https://kb.evetools.org/ "EveTools Killboard"
  [image: aa srp dashboard]: https://raw.githubusercontent.com/ppfeufer/aa-srp/master/docs/images/aa-srp-dashboard.jpg "AA SRP Dashboard"
  [image: aa srp dashboard (view all)]: https://raw.githubusercontent.com/ppfeufer/aa-srp/master/docs/images/aa-srp-dashboard-view-all.jpg "AA SRP Dashboard (View All)"
  [image: srp request details]: https://raw.githubusercontent.com/ppfeufer/aa-srp/master/docs/images/aa-srp-request-details.jpg "SRP Request Details"
  [image: srp requests overview]: https://raw.githubusercontent.com/ppfeufer/aa-srp/master/docs/images/aa-srp-requests-overview.jpg "SRP Requests Overview"
  [image: your srp requests view]: https://raw.githubusercontent.com/ppfeufer/aa-srp/master/docs/images/aa-srp-your-requests.jpg "Your SRP Requests View"
  [ppfeufer on ko-fi]: https://ko-fi.com/N4N8CL1BY
  [pre-commit.ci status]: https://results.pre-commit.ci/latest/github/ppfeufer/aa-srp/master "pre-commit.ci"
  [support discord]: https://discord.gg/zmh52wnfvM
  [weblate engage]: https://weblate.ppfeufer.de/engage/alliance-auth-apps/
  [zkillboard]: https://zkillboard.com/ "zKillboard"

rpm_license:
[cell repeats an earlier one in this file: 34486 characters]


pkgId: e75a6b18993cd5cf3efd16fa52805c62a0ca9788ddd39fced47baf4ddcbef64f
name: python-aa-srp
arch: src
version: 2.5.3
epoch: 0
release: 1
summary: Improved SRP Module for Alliance Auth
url: https://github.com/ppfeufer/aa-srp
rpm_group: Unspecified
rpm_buildhost: localhost
location_href: Packages/python-aa-srp-2.5.3-1.src.rpm
checksum_type: sha256
description:
  [![Badge: Version]][aa srp on pypi]
  [![Badge: License]][aa srp license]
  [![Badge: Supported Python Versions]][aa srp on pypi]
  [![Badge: Supported Django Versions]][aa srp on pypi]
  ![Badge: pre-commit]
  [![Badge: pre-commit.ci status]][pre-commit.ci status]
  [![Badge: Code Style: black]][black code formatter documentation]
  [![Badge: Support Discord]][support discord]
  [![Badge: Automated Tests]][automated tests on github]
  [![Badge: Code Coverage]][aa srp on codecov]
  [![Badge: Translation Status]][weblate engage]
  [![Badge: Contributor Covenant]][code of conduct]

  [![Badge: Buy me a coffee]][ppfeufer on ko-fi]

  SRP Module for [Alliance Auth]

  ______________________________________________________________________

  <!-- mdformat-toc start --slug=github --maxlevel=6 --minlevel=2 -->

  - [Overview](#overview)
    - [Features](#features)
    - [Screenshots](#screenshots)
      - [Dashboard](#dashboard)
      - [Dashboard (View All)](#dashboard-view-all)
      - [Your SRP Requests](#your-srp-requests)
      - [SRP Requests Overview](#srp-requests-overview)
      - [SRP Request Details](#srp-request-details)
  - [Installation](#installation)
    - [Step 1: Install the Package](#step-1-install-the-package)
    - [Step 2: Configure Alliance Auth](#step-2-configure-alliance-auth)
    - [Step 3: Finalizing the Installation](#step-3-finalizing-the-installation)
    - [Step 4: Preload Eve Universe Data](#step-4-preload-eve-universe-data)
    - [Step 5: Setting up Permissions](#step-5-setting-up-permissions)
    - [Step 6: (Optional) Import From Built-in SRP Module](#step-6-optional-import-from-built-in-srp-module)
    - [Step 7: (Optional) Settings for Discord Proxy (If Used)](#step-7-optional-settings-for-discord-proxy-if-used)
  - [Permissions](#permissions)
  - [Changelog](#changelog)
  - [Translation Status](#translation-status)
  - [Contributing](#contributing)

  <!-- mdformat-toc end -->

  ______________________________________________________________________





  - Overview of SRP links
  - Overview of your own SRP requests and their status
  - Accepting kill mails from [zKillboard], [EveTools Killboard] and [EVE-Kill]
  - SRP Request administration is mostly done via ajax and without page reloads
  - Use modern DataTables with filters where ever they're useful
  - Tables fully searchable and sortable
  - Mandatory reason on SRP reject
  - Notifications in AA with detailed information on SRP rejection
  - Discord notification via PM to the user on SRP request approval or rejection, if
    either [AA-Discordbot], [Discord Notify] or [Discord Proxy] is installed
  - Notify your SRP team (optional) in their Discord channel about new SRP requests, if
    [AA-Discordbot] or [Discord Proxy] is installed





  ![Image: AA SRP Dashboard]



  ![Image: AA SRP Dashboard (View All)]



  ![Image: Your SRP Requests View]



  ![Image: SRP Requests Overview]



  ![Image: SRP Request Details]



  > [!NOTE]
  >
  > **AA SRP >= 2.0.0 needs at least Alliance Auth v4.0.0!**
  >
  > Please make sure to update your Alliance Auth instance _before_ you install this
  > module or update to the latest version, otherwise an update to Alliance Auth will
  > be pulled in unsupervised.
  >
  > The last version of AA SRP that supports Alliance Auth v3 is `1.21.0`.

  **Important**: Please make sure you meet all preconditions before you proceed:

  - AA SRP is a plugin for Alliance Auth. If you don't have Alliance Auth running
    already, please install it first before proceeding. (see the official
    [Alliance Auth installation guide] for details)
  - AA SRP needs [Eve Universe] to function. Please make sure it is installed, before
    continuing.



  Make sure you're in the virtual environment (venv) of your Alliance Auth
  installation Then install the latest release directly from PyPi.

  ```shell
  pip install aa-srp
  ```



  This is fairly simple, just add the following to the `INSTALLED_APPS` of your `local.py`

  Configure your AA settings (`local.py`) as follows:

  - Add `"eveuniverse",` to `INSTALLED_APPS`
  - Add `"aasrp",` to `INSTALLED_APPS`



  Run static files collection and migrations

  ```shell
  python manage.py collectstatic
  python manage.py migrate
  ```

  Restart your supervisor services for Auth



  AA SRP utilizes the EveUniverse module, so it doesn't need to ask ESI for ship
  information. To set this up, you now need to run the following command.

  ```shell
  python manage.py aasrp_load_eve
  ```



  Now it's time to set up access permissions for your new SRP module. You can do so in
  your admin backend in the AA SRP section. Read the [Permissions](#permissions)
  section for more information about the available permissions.



  **This step is only needed when you have been using the built-in SRP module until now.**

  Make sure you don't have any open SRP requests before. All SRP links in the built-in
  module will be closed during the import process, to make sure to not import any
  duplicates.

  The import process can be done at any given time and doesn't necessarily have to be
  during the installation.

  To import your SRP information from the built-in SRP module, run the following command.

  ```shell
  python manage.py aasrp_migrate_srp_data
  ```



  If you are using [Discord Proxy] to send Discord messages, you can configure the host and port in your `local.py` settings.

  | Name                | Description                                      | Default     |
  | ------------------- | ------------------------------------------------ | ----------- |
  | `DISCORDPROXY_HOST` | Hostname used to communicate with Discord Proxy. | `localhost` |
  | `DISCORDPROXY_PORT` | Port used to communicate with Discord Proxy.     | `50051`     |



  | ID                    | Description                  | Notes                                                                                                       |
  | --------------------- | ---------------------------- | ----------------------------------------------------------------------------------------------------------- |
  | `basic_access`        | Can access the AA SRP module | Your line members should have this permission.                                                              |
  | `create_srp`          | Can create new SRP links     | Your FCs should have this permission.                                                                       |
  | `manage_srp`          | Can manage SRP               | Users with this permission can manage the AA SRP Module. Like changing and removing SRP links and requests. |
  | `manage_srp_requests` | Can manage SRP requests      | Users with this permission can manage the SRP requests. Like changing and removing SRP requests.            |



  See [CHANGELOG.md]



  [![Translation status](https://weblate.ppfeufer.de/widget/alliance-auth-apps/aa-srp/multi-auto.svg)](https://weblate.ppfeufer.de/engage/alliance-auth-apps/)

  Do you want to help translate this app into your language or improve the existing
  translation? - [Join our team of translators][weblate engage]!



  You want to contribute to this project? That's cool!

  Please make sure to read the [Contribution Guidelines].\
  (I promise, it's not much, just some basics)

  <!-- Links -->

  [aa srp license]: https://github.com/ppfeufer/aa-srp/blob/master/LICENSE
  [aa srp on codecov]: https://codecov.io/gh/ppfeufer/aa-srp
  [aa srp on pypi]: https://pypi.org/project/aa-srp/
  [aa-discordbot]: https://github.com/pvyParts/allianceauth-discordbot "AA-Discordbot"
  [alliance auth]: https://gitlab.com/allianceauth/allianceauth "Alliance Auth"
  [alliance auth installation guide]: https://allianceauth.readthedocs.io/en/latest/installation/allianceauth.html "Alliance Auth installation guide"
  [automated tests on github]: https://github.com/ppfeufer/aa-srp/actions/workflows/automated-checks.yml
  [badge: automated tests]: https://github.com/ppfeufer/aa-srp/actions/workflows/automated-checks.yml/badge.svg "Automated Tests"
  [badge: buy me a coffee]: https://ko-fi.com/img/githubbutton_sm.svg "Buy me a coffee"
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  [badge: version]: https://img.shields.io/pypi/v/aa-srp?label=release "Version"
  [black code formatter documentation]: http://black.readthedocs.io/en/latest/
  [changelog.md]: https://github.com/ppfeufer/aa-srp/blob/master/CHANGELOG.md "CHANGELOG.md"
  [code of conduct]: https://github.com/ppfeufer/aa-srp/blob/master/CODE_OF_CONDUCT.md
  [contribution guidelines]: https://github.com/ppfeufer/aa-srp/blob/master/CONTRIBUTING.md "Contribution Guidelines"
  [discord notify]: https://gitlab.com/ErikKalkoken/aa-discordnotify "Discord Notify"
  [discord proxy]: https://gitlab.com/ErikKalkoken/discordproxy "Discord Proxy"
  [eve universe]: https://gitlab.com/ErikKalkoken/django-eveuniverse "Eve Universe"
  [eve-kill]: https://eve-kill.com/ "EVE-Kill"
  [evetools killboard]: https://kb.evetools.org/ "EveTools Killboard"
  [image: aa srp dashboard]: https://raw.githubusercontent.com/ppfeufer/aa-srp/master/docs/images/aa-srp-dashboard.jpg "AA SRP Dashboard"
  [image: aa srp dashboard (view all)]: https://raw.githubusercontent.com/ppfeufer/aa-srp/master/docs/images/aa-srp-dashboard-view-all.jpg "AA SRP Dashboard (View All)"
  [image: srp request details]: https://raw.githubusercontent.com/ppfeufer/aa-srp/master/docs/images/aa-srp-request-details.jpg "SRP Request Details"
  [image: srp requests overview]: https://raw.githubusercontent.com/ppfeufer/aa-srp/master/docs/images/aa-srp-requests-overview.jpg "SRP Requests Overview"
  [image: your srp requests view]: https://raw.githubusercontent.com/ppfeufer/aa-srp/master/docs/images/aa-srp-your-requests.jpg "Your SRP Requests View"
  [ppfeufer on ko-fi]: https://ko-fi.com/N4N8CL1BY
  [pre-commit.ci status]: https://results.pre-commit.ci/latest/github/ppfeufer/aa-srp/master "pre-commit.ci"
  [support discord]: https://discord.gg/zmh52wnfvM
  [weblate engage]: https://weblate.ppfeufer.de/engage/alliance-auth-apps/
  [zkillboard]: https://zkillboard.com/ "zKillboard"

rpm_license:
[cell repeats an earlier one in this file: 34486 characters]


pkgId: 9c2386aac7e0bd0d6738377c0049089d3eab53fda0a507d50856340a117c5dea
name: python-aa-standingsrequests
arch: src
version: 1.4.0
epoch: 0
release: 1
summary: App for managing character standing requests, made for Alliance Auth.
url: https://gitlab.com/ErikKalkoken/aa-standingsrequests
rpm_license: GNU General Public License v3 (GPLv3)
rpm_group: Unspecified
rpm_buildhost: localhost
location_href: Packages/python-aa-standingsrequests-1.4.0-1.src.rpm
checksum_type: sha256
description:
  App for managing character standing requests, made for [Alliance Auth](https://gitlab.com/allianceauth/allianceauth).

  [![release](https://img.shields.io/pypi/v/aa-standingsrequests?label=release)](https://pypi.org/project/aa-standingsrequests/)
  [![python](https://img.shields.io/pypi/pyversions/aa-standingsrequests)](https://pypi.org/project/aa-standingsrequests/)
  [![django](https://img.shields.io/pypi/djversions/aa-standingsrequests?label=django)](https://pypi.org/project/aa-standingsrequests/)
  [![pipeline](https://gitlab.com/ErikKalkoken/aa-standingsrequests/badges/master/pipeline.svg)](https://gitlab.com/ErikKalkoken/aa-standingsrequests/-/pipelines)
  [![codecov](https://codecov.io/gl/ErikKalkoken/aa-standingsrequests/branch/master/graph/badge.svg?token=gf23N35S3S)](https://codecov.io/gl/ErikKalkoken/aa-standingsrequests)
  [![license](https://img.shields.io/badge/license-MIT-green)](https://gitlab.com/ErikKalkoken/aa-standingsrequests/-/blob/master/LICENSE)
  [![pre-commit](https://img.shields.io/badge/pre--commit-enabled-brightgreen?logo=pre-commit&logoColor=white)](https://github.com/pre-commit/pre-commit)
  [![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)
  [![chat](https://img.shields.io/discord/790364535294132234)](https://discord.gg/zmh52wnfvM)



  - [Features](#features)
  - [Screenshots](#screenshots)
  - [Installation](#installation)
  - [Settings](#settings)
  - [Permissions](#permissions)
  - [Standings Requirements](#standings-requirements)
  - [Manual for Standing Managers](#manual-for-standing-managers)
  - [History](#history)
  - [Change Log](CHANGELOG.md)



  - User can requests standings for their characters and corporations
  - Standing managers can approve / deny standings requests from users
  - Automatic verification that approved / revoked standings are added / removed in-game
  - When user leaves the corporation or alliance, the app will automatically suggest to revoke the standing in-game
  - Either an alliance or a corporation can be defined as master for in-game standings
  - Review current standings of your alliance or corporation and see which auth user requested it (if any)
  - Approvals/revocations are automatically logged for later review



  Here are some example screenshots:



  ![image_1](https://i.imgur.com/lVXEVMK.png)



  ![image_2](https://i.imgur.com/eM1cXya.png)





  1. Standings Requests is a plugin for Alliance Auth. If you don't have Alliance Auth running already, please install it first before proceeding. (see the official [AA installation guide](https://allianceauth.readthedocs.io/en/latest/installation/auth/allianceauth/) for details)

  2. Standings Requests needs the app [django-eveuniverse](https://gitlab.com/ErikKalkoken/django-eveuniverse) to function. Please make sure it is installed, before before continuing.



  Add the following scopes to the Eve Online app used by Auth on [developers.eveonline.com](https://developers.eveonline.com/):

  ```plain
  esi-alliances.read_contacts.v1
  esi-corporations.read_contacts.v1
  ```



  Activate your virtual environment and install this app with:

  ```bash
  pip install aa-standingsrequests
  ```



  Add `'standingsrequests'` to `INSTALLED_APPS` in your Alliance Auth local settings file. Also add the other settings from the [Settings Example](#settings-example) and update the example config for your alliance.

  The most important part of the settings is `STANDINGS_API_CHARID`, which need to be the Eve Online ID of the character that will be used to sync standings with your alliance or corporation.

  Run database migrations:

  ```bash
  python manage.py migrate standingsrequests
  ```

  Copy static files to your webserver:

  ```bash
  python manage.py collectstatic
  ```

  Finally restart Django and Celery.



  Open the standingsrequests app in Alliance Auth and add the token for the configured standings character. This will initiate the first pull of standings. You will get a notification once the standings pull is completed (Usually within a few minutes).

  Last, but not least make sure to add [permissions](#permissions) to groups / states as required to make the new app available to users.

  That's it, you should be ready to roll.



  Here is a complete example of all settings that goes into your local settings file.

  ```Python

  STANDINGS_API_CHARID = 1234
  STR_CORP_IDS = [CORP1ID, CORP2ID, ...]
  STR_ALLIANCE_IDS = [YOUR_ALLIANCE_ID, ...]



  SR_REQUIRED_SCOPES = {
      'Member': ['publicData'],
      'Blue': [],
      '': []  # no state
  }


  CELERYBEAT_SCHEDULE['standings_requests_standings_update'] = {
      'task': 'standings_requests.standings_update',
      'schedule': crontab(minute='*/30'),
  }
  CELERYBEAT_SCHEDULE['standings_requests_update_associations_api'] = {
      'task': 'standings_requests.update_associations_api',
      'schedule': crontab(minute='30', hour='*/3'),
  }
  CELERYBEAT_SCHEDULE['standings_requests_validate_requests'] = {
      'task': 'standings_requests.validate_requests',
      'schedule': crontab(minute='0', hour='*/6'),
  }
  CELERYBEAT_SCHEDULE['standings_requests_purge_stale_data'] = {
      'task': 'standings_requests.purge_stale_data',
      'schedule': crontab(minute='0', hour='*/24'),
  }
  ```



  Here is a brief explanation of all available settings:

  Name | Description | Default
  -- | -- | --
  `SR_CORPORATIONS_ENABLED` | switch to enable/disable ability to request standings for corporations | `True`
  `SR_NOTIFICATIONS_ENABLED` | Send notifications to users about the results of standings requests and standing changes of their characters | `True`
  `SR_OPERATION_MODE` | Select the entity type of your standings master. Can be: `"alliance"` or `"corporation"` | `"alliance"`
  `SR_REQUIRED_SCOPES` | map of required scopes per state (Mandatory, can be [] per state) | -
  `SR_PAGE_CACHE_SECONDS` | Number of seconds to cache heavy pages like character and groups standing. Set to 0 to disable. | `600`
  `SR_STANDINGS_STALE_HOURS` | Standing data will be considered stale and removed from the local database after the configured hours. The latest standings data will never be purged, no matter how old it is | `48`
  `SR_STANDING_TIMEOUT_HOURS` | Max hours to wait for a standing to be effective after being marked actioned. Non effective standing requests will be reset when this timeout expires. | `24`
  `SR_SYNC_BLUE_ALTS_ENABLED` | Automatically sync standing of alts known to Auth that have standing in game  | `True`
  `STANDINGS_API_CHARID` | Eve Online ID of character to use for fetching alliance contacts from ESI (Mandatory) | -
  `STR_ALLIANCE_IDS` | Eve Online ID of alliances. Characters belonging to one of those alliances are considered "in organization". Your main alliance goes here when in alliance mode. (Mandatory, can be []) | -
  `STR_CORP_IDS` | Eve Online ID of corporations. Characters belonging to one of those corporations are considered "in organization". Your main corporation goes here when in corporation mode. (Mandatory, can be []) | -



  These are all relevant permissions:

  Name | Description
  -- | --
  *abstract standings request - User can request standings* | This is the permission required to have basic access to this app and be able to request and maintain blue standings without them being revoked. IMPORTANT: When a user no longer has this permission all of their standings will be revoked.
  *contact set - User can view standings* | See which mains the character and corporation standing have been requested by. Typically you'll probably only want standings managers to have this.
  *abstract standings request - User can process standings requests* | User can see standings requests and process/approve/reject them.
  *contact set - User can export standing requests* | User can download all of the standings data, including main character associations, as a CSV file. Useful if you want to do some extra fancy processing in a spreadsheet or something.



  These are the requirements to be able to request and maintain blue standings. If a character or account falls out of these requirement scopes then their standing(s) will be revoked.

  Request Type | Requirements
  -- | --
  Character | • Character has been added to Auth and is owned by the requesting user.<br> • User has the `request_standings` permissions.
  Corporation | • All member characters of the corporation have been added to Auth and are owned by the requesting user<br>• User has the `request_standings` permission.

  Note that all characters need to maintain valid tokens in Auth or there standing will automatically be revoked.



  Standing managers have the ability to review standings requests on the "Manage Requests" page.



  Standings Requests are fairly straightforward, there are two options:



  Reject the standings request, effectively deleting it. The user will be able to request it again however.



  The requested standing has been actioned/changed in game. The system then expects to see this request become effective within 24 hours. If it does not show up in a standings API pull within 24 hours the actioned flag is removed and it will show up as a standings request again.

  Once a standing is actioned it will be maintained as an "effective" standings request. If the standing is removed in game while it is still valid in the system then it will become an active request again.



  Standings will show up here in one of two situations:

  1. The user has deleted the standings request for that contact, indicating they no longer require the standing.
  2. The user is no longer eligible to hold active standings.

  Currently it is not indicated which of these two cases (or which automatic revocation case) triggered the standing revocation.



  Make sure you fully understand delete before using it, you will usually use one of the other two options instead of delete. When you delete a standings request *it is literally deleted*. The system will no longer attempt to manage this request or verify that it has been revoked etc. *The standing becomes "unmanaged"*.



  Turns the standing revocation into a standings request again. Useful if someone got booted from corp or auth temporarily. If they still don't have the requirements met the next time a validation pass happens then it will be turned into a revocation again.



  Same as for Standings Requests. The system will hold the revocation in the background until it sees it removed in game. If the standing has still not been unset (or set to neutral or below) in 24 hours then it will appear as a standings revocation again.



  This app comes with management commands that provide special features for admins.

  You can run any management command from the command. Make sure you are in the folder that also contains `manage.py` and that you have activate your venv:

  ```bash
  python manage.py NAME_OF_COMMAND
  ```



  This command automatically creates accepted standing requests for alt characters on Auth that already have blue standing in game. This can be useful when this app is first installed to avoid having all users manually request standing for alts that are already blue.

  Standings created by this command will not have an actioner name set.



  This is a fork of [Basraah's standingrequests](https://gitlab.com/ErikKalkoken/aa-standingsrequests).
  Big thanks to Basraah for all his effort in developing the initial version.


pkgId: 5b7b66e2852469e1f3d2a1aa8a31fa69d055c42aabaa067ce614193a87827fcd
name: python-aa-standingssync
arch: src
version: 1.10.0
epoch: 0
release: 1
summary: Alliance Auth app for cloning alliance standings and war targets to alts.
url: https://gitlab.com/ErikKalkoken/aa-standingssync
rpm_license: MIT License
rpm_group: Unspecified
rpm_buildhost: localhost
location_href: Packages/python-aa-standingssync-1.10.0-1.src.rpm
checksum_type: sha256
description:
  Alliance Auth app for cloning alliance standings and war targets to alts.

  [![release](https://img.shields.io/pypi/v/aa-standingssync?label=release)](https://pypi.org/project/aa-standingssync/)
  [![python](https://img.shields.io/pypi/pyversions/aa-standingssync)](https://pypi.org/project/aa-standingssync/)
  [![django](https://img.shields.io/pypi/djversions/aa-standingssync?label=django)](https://pypi.org/project/aa-standingssync/)
  [![pipeline](https://gitlab.com/ErikKalkoken/aa-standingssync/badges/master/pipeline.svg)](https://gitlab.com/ErikKalkoken/aa-standingssync/-/pipelines)
  [![codecov](https://codecov.io/gl/ErikKalkoken/aa-standingssync/branch/master/graph/badge.svg?token=gHBi42fbSs)](https://codecov.io/gl/ErikKalkoken/aa-standingssync)
  [![license](https://img.shields.io/badge/license-MIT-green)](https://gitlab.com/ErikKalkoken/aa-standingssync/-/blob/master/LICENSE)
  [![pre-commit](https://img.shields.io/badge/pre--commit-enabled-brightgreen?logo=pre-commit&logoColor=white)](https://github.com/pre-commit/pre-commit)
  [![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)
  [![chat](https://img.shields.io/discord/790364535294132234)](https://discord.gg/zmh52wnfvM)



  - [Features](#features)
  - [Screenshot](#screenshot)
  - [How it works](#how-it-works)
  - [Installation](#installation)
  - [Updating](#updating)
  - [Settings](#settings)
  - [Permissions](#permissions)
  - [Admin Functions](#admin-functions)
  - [Feedback](#feedback)
  - [Change Log](CHANGELOG.md)



  The main purpose of this app is to enable non-alliance characters to have the same standings view of other pilots in game as their alliance main. This e.g. allows non-alliance scouts to correctly report blues and non-blues. Or JF pilots can see which other non-alliance characters on grid not blues and therefore a potential threat.

  Here is an high level overview of the main features:

  - Synchronize alliance contacts to chosen non-alliance characters
  - Supports coalition usage with multiple alliances in the same Alliance Auth installation
  - Synchronize alliance war targets as contacts with terrible standing
  - Automatically deactivates synchronization when a user ceases to be eligible (e.g. main left the alliance)



  Here is a screenshot of the main screen.

  ![Main Screen](https://i.imgur.com/xGdoqsp.png)



  To enable non-alliance members to use alliance standings the personal contact of that character are replaced with the alliance contacts.





  Please make sure you meet all preconditions before proceeding:

  1. Standings Sync is a plugin for [Alliance Auth](https://gitlab.com/allianceauth/allianceauth). If you don't have Alliance Auth running already, please install it first before proceeding. (see the official [AA installation guide](https://allianceauth.readthedocs.io/en/latest/installation/auth/allianceauth/) for details)

  2. Standings Sync needs the app [django-eveuniverse](https://gitlab.com/ErikKalkoken/django-eveuniverse) to function. Please make sure it is installed, before continuing.



  Install into AA virtual environment with PIP install from PyPI:

  ```bash
  pip install aa-standingssync
  ```



  Update the Eve Online app used for authentication in your AA installation to include the following scopes:

  ```plain
  esi-characters.read_contacts.v1
  esi-characters.write_contacts.v1
  esi-alliances.read_contacts.v1
  ```



  Configure your AA settings (`local.py`) as follows:

  Add `'standingssync'` to `INSTALLED_APPS`

  Add these lines add to bottom of your settings file:

  ```python

  CELERYBEAT_SCHEDULE['standingssync.run_regular_sync'] = {
      'task': 'standingssync.tasks.run_regular_sync',
      'schedule': crontab(minute=0, hour='*/2')
  }
  ```

  Please also see the [settings](#settings) section for more configuration options. For example a setting is required to enable syncing war targets.



  Run migrations & copy static files

  ```bash
  python manage.py migrate
  python manage.py collectstatic --noinput
  ```

  Restart your supervisor services for AA



  Now you can access Alliance Auth and setup permissions for your users. See section "Permissions" below for details.



  Finally you need to set the alliance character that will be used for fetching the alliance contacts / standing. Just click on "Set Alliance Character" and add the requested token. Note that only users with the appropriate permission will be able to see and use this function.

  Once an alliance character is set the app will immediately start fetching alliance contacts. Wait a minute and then reload the page to see the result.

  That's it. The Standing Sync app is fully installed and ready to be used.



  To update your existing installation of Alliance Freight first enable your virtual environment.

  Then run the following commands from your AA project directory (the one that contains `manage.py`).

  ```bash
  pip install -U aa-standingssync
  ```

  ```bash
  python manage.py migrate
  ```

  ```bash
  python manage.py collectstatic --noinput
  ```

  Finally restart your AA supervisor services.



  Here is a list of available settings for this app. They can be configured by adding them to your AA settings file (`local.py`). If they are not set the defaults are used.

  Name|Description|Default
  --|--|--
  `STANDINGSSYNC_ADD_WAR_TARGETS`|When enabled will automatically add or set war targets  with standing = -10 to synced characters.|`False`
  `STANDINGSSYNC_CHAR_MIN_STANDING`|Minimum standing a character needs to have in order to get alliance contacts. Any char with a standing smaller than this value will be rejected. Set to `0.0` if you want to allow neutral alts to sync.|`0.1`
  `STANDINGSSYNC_REPLACE_CONTACTS`|When enabled will replace contacts of synced characters with alliance contacts.|`True`
  `STANDINGSSYNC_STORE_ESI_CONTACTS_ENABLED`|Wether to store contacts received from ESI to disk. This is for debugging.|`False`
  `STANDINGSSYNC_SYNC_TIMEOUT`|Duration in minutes after which a delayed sync for managers and characters is reported as down. This value should be aligned with the frequency of the sync task.|`180`
  `STANDINGSSYNC_WAR_TARGETS_LABEL_NAME`|Name of EVE contact label for war targets. Needs to be created by the user for each synced character. Required to ensure that war targets are deleted once they become invalid. Not case sensitive.|`WAR TARGETS`



  This app only uses two permission. One for enabling this app for users and one for enabling users to add alliances for syncing.

  Name | Purpose | Code
  -- | -- | --
  Can add synced character |Enabling the app for a user. This permission should be enabled for everyone who is allowed to use the app (e.g. Member state) |  `add_syncedcharacter`
  Can add alliance manager |Enables adding alliances for syncing by setting the character for fetching alliance contacts. This should be limited to users with admins / leadership privileges. |  `add_syncmanager`



  Admins will find a "Standings Sync" section on the admin page. This section provides the following features:

  - See a list of all setup alliances with their sync status

  - See a list of all enabled characters with their current sync status

  - Manually remove characters / alliances from sync

  - Manually start the sync process for characters / alliances



  If you encounter any bugs or would like to request a new feature please open an issue in this gitlab repo.


pkgId: cbfb6df6d1996df3071fc3cd96c55c6b799243675d240321920a1ded418de8ff
name: python-aa-structures
arch: src
version: 2.16.0
epoch: 0
release: 1
summary: App for managing Eve Online structures with Alliance Auth.
url: https://gitlab.com/ErikKalkoken/aa-structures
rpm_license: None
rpm_group: Unspecified
rpm_buildhost: localhost
location_href: Packages/python-aa-structures-2.16.0-1.src.rpm
checksum_type: sha256
description:
  App for managing Eve Online structures with Alliance Auth.

  [![release](https://img.shields.io/pypi/v/aa-structures?label=release)](https://pypi.org/project/aa-structures/)
  [![python](https://img.shields.io/pypi/pyversions/aa-structures)](https://pypi.org/project/aa-structures/)
  [![django](https://img.shields.io/pypi/djversions/aa-structures?label=django)](https://pypi.org/project/aa-structures/)
  [![pipeline](https://gitlab.com/ErikKalkoken/aa-structures/badges/master/pipeline.svg)](https://gitlab.com/ErikKalkoken/aa-structures/-/pipelines)
  [![codecov](https://codecov.io/gl/ErikKalkoken/aa-structures/branch/master/graph/badge.svg?token=wq6yixsYRE)](https://codecov.io/gl/ErikKalkoken/aa-structures)
  [![Documentation Status](https://readthedocs.org/projects/aa-structures/badge/?version=latest)](https://aa-structures.readthedocs.io/en/latest/?badge=latest)
  [![license](https://img.shields.io/badge/license-MIT-green)](https://gitlab.com/ErikKalkoken/aa-structures/-/blob/master/LICENSE)
  [![pre-commit](https://img.shields.io/badge/pre--commit-enabled-brightgreen?logo=pre-commit&logoColor=white)](https://github.com/pre-commit/pre-commit)
  [![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)
  [![chat](https://img.shields.io/discord/790364535294132234)](https://discord.gg/zmh52wnfvM)



  This app is for managing Eve Online structures with [Alliance Auth](https://gitlab.com/allianceauth/allianceauth). It allows all member corporations to see a current list of all their structures in Auth. In addition it allows forwarding Eve Online notifications to Discord.



  Structures adds the following main features to Alliance Auth:

  - Structure browser with a detailed list of all structures owned by member corporations, automatically synced with the game server
  - Structures include all Upwell structures, Custom Offices and Starbases / POSes
  - Automatically forwards Eve Online notifications to Discord channels as alerts for these categories:
    - Upwell structures
    - Customs offices
    - Starbases
    - Moon mining
    - Sovereignty
    - Wars
    - Corporation membership changes
  - Automatically adds timers from relevant notifications to [Alliance Auth Structure Timers](https://allianceauth.readthedocs.io/en/v2.8.1/features/apps/timerboard.html) or [Structure Timers II](https://gitlab.com/ErikKalkoken/aa-structuretimers) app (if installed)
  - Fittings, contents of Upwell structures (e.g. fuel blocks and ammo) and current fuel usage
  - Additional structure notifications generated by the app:
    - Configurable alerts to warn about fuel running at in structures and POSes, and which can replace the ESI notifications
    - Notifications to inform when structures have been refueled (BETA)
    - Configurable alerts to warn about jump fuel (liquid ozone) running low in jump gates
    - POS reinforced (BETA)
  - Tax rates and access settings of Customs Offices
  - Permissions define which structures are visible to a user based on organization membership
  - Self-defined tags help to better organize structures
  - Ability to increase notification response time and sync resilience with multiple sync characters per structure owner
  - Automatically sends alerts to users and admin when token become invalid or sync from ESI fails
  - Interface for 3rd party monitoring of the services status
  - Chinese :cn:, English :us:, German :de: and Russian :ru: localization

  Please also check out [Discord Notify](https://gitlab.com/ErikKalkoken/aa-discordnotify) that will automatically forward auth notifications to the respective users on Discord.



  Here is an example for the main list of structures:

  ![StructureList](https://imgpile.com/images/GCxK7E.png)

  You can also see the fittings and contents any upwell structures:

  ![Fitting](https://imgpile.com/images/GCxtQh.png)

  The tax rate and access configuration of customs offices is visible too:

  ![Poco details](https://imgpile.com/images/GCxPyg.png)

  And you can see the configuration for starbases:

  ![Poco details](https://imgpile.com/images/GCxMPr.png)

  This is an example for a notification posted on Discord:

  ![Notification example](https://i.imgur.com/oqBqeFy.png)



  Please see the [operation manual](https://aa-structures.readthedocs.io/en/latest/operations.html#installation) for the installation guide.


pkgId: 47588c892c1f14013ea7ac3add0c3f8205c17fa270ec4ab4fee271c29aa0ec62
name: python-aa-structuretimers
arch: src
version: 1.8.0
epoch: 0
release: 1
summary: An app for keeping track of Eve Online structure timers
url: https://gitlab.com/ErikKalkoken/aa-structuretimers
rpm_license: None
rpm_group: Unspecified
rpm_buildhost: localhost
location_href: Packages/python-aa-structuretimers-1.8.0-1.src.rpm
checksum_type: sha256
description:
  An app for keeping track of Eve Online structure timers with Alliance Auth and Discord.

  [![release](https://img.shields.io/pypi/v/aa-structuretimers?label=release)](https://pypi.org/project/aa-structuretimers/)
  [![python](https://img.shields.io/pypi/pyversions/aa-structuretimers)](https://pypi.org/project/aa-structuretimers/)
  [![django](https://img.shields.io/pypi/djversions/aa-structuretimers?label=django)](https://pypi.org/project/aa-structuretimers/)
  [![pipeline](https://gitlab.com/ErikKalkoken/aa-structuretimers/badges/master/pipeline.svg)](https://gitlab.com/ErikKalkoken/aa-structuretimers/-/pipelines)
  [![codecov](https://codecov.io/gl/ErikKalkoken/aa-structuretimers/branch/master/graph/badge.svg?token=J4PKTXSOBM)](https://codecov.io/gl/ErikKalkoken/aa-structuretimers)
  [![license](https://img.shields.io/badge/license-MIT-green)](https://gitlab.com/ErikKalkoken/aa-structuretimers/-/blob/master/LICENSE)
  [![pre-commit](https://img.shields.io/badge/pre--commit-enabled-brightgreen?logo=pre-commit&logoColor=white)](https://github.com/pre-commit/pre-commit)
  [![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)
  [![chat](https://img.shields.io/discord/790364535294132234)](https://discord.gg/zmh52wnfvM)



  - [Overview](#overview)
  - [Screenshots](#screenshots)
  - [Installation](#installation)
  - [Settings](#settings)
  - [Notification Rules](#notification-rules)
  - [Permissions](#permissions)
  - [Management commands](#management-commands)
  - [Change Log](CHANGELOG.md)



  *Structure Timers II* is an enhanced version of the Alliance Auth's Structure Timers app, with many additional useful features and an improved UI. Here is a overview of it's main features in comparison to Auth's basic variant.

  Feature | Auth | Structure Timer II
  --|--|--
  Create and edit timers for structures | x | x
  See all pending timers at a glance and with live countdowns | x | x
  Restrict timer access to your corporation | x | x
  Restrict ability to create and delete timers to certain users | x | x
  Get automatic notifications about upcoming timers on Discord  | - | x
  Define a timer type (e.g. armor or hull)| - | x
  Restrict timer access to your alliance | - | x
  Restrict timer access to people with special clearance ("OPSEC") | - | x
  Add screenshots to timers (e.g. with the structure's fitting)| - | x
  Create timers more quickly and precisely with autocomplete for solar system and structure types| - | x
  Find timers more quickly with filters and full text search | - | x
  Automatic cleanup of elapsed timers | - | x

  >**Hint**<br>If you like to see all timers in a calendar view please consider checking out the amazing app [Allianceauth Opcalendar](https://gitlab.com/paulipa/allianceauth-opcalendar), which is fully integrated with **Structure Timers II**.





  ![timerboard](https://i.imgur.com/MNa2IGl.png)



  ![timerboard](https://i.imgur.com/ZEbl2Vc.png)



  ![timerboard](https://i.imgur.com/LPCEQNr.png)



  ![notification](https://i.imgur.com/Knq2bif.png)





  Please make sure you meet all preconditions before proceeding:

  1. Structure Timers is a plugin for [Alliance Auth](https://gitlab.com/allianceauth/allianceauth). If you don't have Alliance Auth running already, please install it first before proceeding. (see the official [AA installation guide](https://allianceauth.readthedocs.io/en/latest/installation/auth/allianceauth/) for details)

  2. Structure Timers needs the app [django-eveuniverse](https://gitlab.com/ErikKalkoken/django-eveuniverse) to function. Please make sure it is installed, before continuing.

  Note that Structure Timers is compatible with Alliance Auth's Structure Timer app and can be installed in parallel.



  Make sure you are in the virtual environment (venv) of your Alliance Auth installation. Then install the newest release from PyPI:

  ```bash
  pip install aa-structuretimers
  ```



  Configure your Auth settings (`local.py`) as follows:

  - Add `'structuretimers'` to `INSTALLED_APPS`
  - Add the following lines to your settings file:

  ```python
  CELERYBEAT_SCHEDULE['structuretimers_housekeeping'] = {
      'task': 'structuretimers.tasks.housekeeping',
      'schedule': crontab(minute=0, hour=3),
  }
  ```

  - Optional: Add additional settings if you want to change any defaults. See [Settings](#settings) for the full list.



  Run migrations & copy static files

  ```bash
  python manage.py migrate
  python manage.py collectstatic
  ```

  Restart your supervisor services for Auth



  In order to be able to select solar systems and structure types for timers you need to preload some data from ESI once. If you already have run those commands previously you can skip this step.

  Load Eve Online map:

  ```bash
  python manage.py eveuniverse_load_data map
  ```

  ```bash
  python manage.py structuretimers_load_eve
  ```

  You may want to wait until the data loading is complete before starting to create new timers.



  If you have already been using the classic app from Auth, you can migrate your existing timers over to **Structure Timers II**. Just run the following command:

  ```bash
  python manage.py structuretimers_migrate_timers
  ```

  Note: We suggest migration timers before setting up notification rules to avoid potential notification spam for migrated timers.



  If you want to receive notifications about timers on Discord you can setup notification rules on the admin site. e.g. you can setup a rule to sent notifications 60 minutes before a timer elapses. Please see [Notification Rules](#notification-rules) for details.



  Another important step is to setup permissions, to ensure the right people have access features. Please see [Permissions](#permissions) for an overview of all permissions.



  Here is a list of available settings for this app. They can be configured by adding them to your Auth settings file (`local.py`).

  Note that all settings are optional and the app will use the documented default settings if they are not used.

  Name | Description | Default
  -- | -- | --
  `STRUCTURETIMERS_MAX_AGE_FOR_NOTIFICATIONS`| Will not sent notifications for timers, which event time is older than the given minutes | `60`
  `STRUCTURETIMERS_NOTIFICATIONS_ENABLED`| Wether notifications for timers are scheduled at all | `True`
  `STRUCTURETIMERS_TIMERS_OBSOLETE_AFTER_DAYS`| Minimum age in days for a timer to be considered obsolete. Obsolete timers will automatically be deleted. If you want to keep all timers, set to `None` | `30`
  `STRUCTURETIMERS_DEFAULT_PAGE_LENGTH`| Default page size for timerboard. Must be an integer value from the available options in the app. | `10`
  `STRUCTURETIMERS_PAGING_ENABLED`| Wether paging is enabled on the timerboard. | `True`
  `STRUCTURETIMER_NOTIFICATION_SET_AVATAR`| Wether structures sets the name and avatar icon of a webhook. When False the webhook will use it's own values as set on the platform. | `True`



  In *Structure Timers II* you can receive automatic notifications on Discord for timers by setting up notification rules. Notification rules allow you to define in detail what event and which kind of timers should trigger notifications.

  Note that in general all rules are independent from each other and all enabled rules will be executed for every timer one by one.



  Here is an example for a basic setup of rules:



  - Trigger: New timer created
  - Scheduled Time: -
  - Webhook: YOUR-WEBHOOK
  - Ping Type: (no ping)



  - Trigger: Scheduled timer reached
  - Scheduled Time: T - 45 minutes
  - Webhook: YOUR-WEBHOOK
  - Ping Type: @here



  Here are some key concepts. For all details please see the onscreen help text when creating rules.



  Notifications can be triggered by two kinds of events:

  - When a new timers is created
  - When the remaining time of timer has reached a defined threshold (e.g. 10 minutes before timer elapses)



  Each rule has exactly one webhook. You can of course define multiple rules for the same webhook or define rules for different webhooks.



  Almost every property of a timer can be used to define rules. For example you can define to get notifications only for timers which hostile objective or only for final timers.

  Note that setting a timer clause is optional and clauses that are not set, it will always match any.



  You can define one or multiple staging systems. Then you can see the distance in jumps and LY from your currently selected staging system to any timer (except for WH systems).

  Staging systems can be added or modified on the admin site under: Structure Timers/Staging Systems.



  Here are all relevant permissions:

  Codename | Description
  -- | --
  `general - Can access this app and see timers` | Basic permission required by anyone to access this app. Gives access to the list of timers (which timers a user sees can depend on other permissions and settings for a timers)
  `general - Can create new timers and edit own timers` | Users with this permission can create new timers and edit or delete their own timers.
  `general - Can edit and delete any timer` | Users with this permission can edit and delete any timer.
  `general - Can create and see opsec timers` | Users with this permission can create and view timers that are opsec restricted.



  The following management commands are available:

  - **structuretimers_load_eve**: Preload all eve objects required for this app to function
  - **structuretimers_migrate_timers**: Migrate pending timers from Auth's Structure Timers apps


pkgId: d86b3970b26dc32984472f19d8d9ac651f541fc8c844c772cf1f2281e0fcf11b
name: python-aa-taskmonitor
arch: src
version: 0.23.1
epoch: 0
release: 1
summary: An Alliance Auth app for monitoring celery tasks.
url: https://gitlab.com/ErikKalkoken/aa-taskmonitor
rpm_license: MIT License
rpm_group: Unspecified
rpm_buildhost: localhost
location_href: Packages/python-aa-taskmonitor-0.23.1-1.src.rpm
checksum_type: sha256
description:
  An Alliance Auth app for monitoring celery tasks.

  [![release](https://img.shields.io/pypi/v/aa-taskmonitor?label=release)](https://pypi.org/project/aa-taskmonitor/)
  [![python](https://img.shields.io/pypi/pyversions/aa-taskmonitor)](https://pypi.org/project/aa-taskmonitor/)
  [![django](https://img.shields.io/pypi/djversions/aa-taskmonitor?label=django)](https://pypi.org/project/aa-taskmonitor/)
  [![pipeline](https://gitlab.com/ErikKalkoken/aa-taskmonitor/badges/master/pipeline.svg)](https://gitlab.com/ErikKalkoken/aa-taskmonitor/-/pipelines)
  [![codecov](https://codecov.io/gl/ErikKalkoken/aa-taskmonitor/branch/master/graph/badge.svg?token=MNEUWD6X4Q)](https://codecov.io/gl/ErikKalkoken/aa-taskmonitor)
  [![license](https://img.shields.io/badge/license-MIT-green)](https://gitlab.com/ErikKalkoken/aa-taskmonitor/-/blob/master/LICENSE)
  [![pre-commit](https://img.shields.io/badge/pre--commit-enabled-brightgreen?logo=pre-commit&logoColor=white)](https://github.com/pre-commit/pre-commit)
  [![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)
  [![chat](https://img.shields.io/discord/790364535294132234)](https://discord.gg/zmh52wnfvM)



  - [Features](#features)
  - [Screenshots](#screenshots)
  - [Installation](#installation)
  - [Command line utility](#command-line-utility)
  - [Settings](#settings)
  - [FAQ](#faq)
  - [Change Log](CHANGELOG.md)



  Task Monitor enables administrators to monitor celery tasks running on their system.

  - Creates a log of all recently executed celery tasks including failed and retried tasks.
  - Stores many details in task logs to support the analysis of potential celery issues, including the parameters a task with called with and complete exception messages
  - Keeps the storage needs in check by automatically deleting older task logs and removing likely bloat from the collected data (but can also be turned off)
  - Admins can investigate task log with search & filters
  - Admins can view details for each task log incl. exceptions and trace logs
  - Admins can review reports with charts providing answers to common questions, e.g:
    - How many tasks have failed/retried?
    - How many tasks where run by each of my apps?
    - Which are the most frequent tasks?
    - Which tasks have the longest runtime?
    - Which tasks failed the most?
    - How much backlog do I have in task queue over time?
  - Admins can export all task logs to a CSV file for further analysis with 3rd party tools (e.g. Google sheets)
  - Admins can see detailed statistics for all tasks
  - Command line utility to manage task logs and queue directly





  ![tasklog](https://i.imgur.com/jo1McnJ.png)



  ![tasklog](https://i.imgur.com/3XMc8Zi.png)



  ![tasklog](https://i.imgur.com/OrVmZXT.png)



  ![tasklog](https://imgpile.com/images/GQ58Wj.png)





  Task Monitor is a plugin for Alliance Auth. If you don't have Alliance Auth running already, please install it first before proceeding. (see the official [AA installation guide](https://allianceauth.readthedocs.io/en/latest/installation/auth/allianceauth/) for details)



  Make sure you are in the virtual environment (venv) of your Alliance Auth installation. Then install the newest release from PyPI:

  ```bash
  pip install aa-taskmonitor
  ```



  Configure your Auth settings (`local.py`) as follows:

  - Add `'taskmonitor'` to `INSTALLED_APPS`
  - Optional: Add additional settings if you want to change any defaults. See [Settings](#settings) for the full list.



  Run migrations & copy static files

  ```bash
  python manage.py migrate
  python manage.py collectstatic --noinput
  ```

  Restart your supervisor services for Auth.



  You can manage your logs and queue also directly via a command line utility.

  The basic syntax for using the utility is:

  ```bash
  python manage.py taskmonitorctl {command} {target}
  ```

  For example you can inspect your logs with:

  ```bash
  python manage.py taskmonitorctl inspect logs
  ```

  Or for example you can purge your task queue with:

  ```bash
  python manage.py taskmonitorctl purge queue
  ```

  To get an overview of available commands run:

  ```bash
  python manage.py taskmonitorctl --help
  ```

  To get an overview of available targets for a command run:

  ```bash
  python manage.py taskmonitorctl inspect --help
  ```



  Here is a list of available settings for this app. They can be configured by adding them to your AA settings file (`local.py`).

  Note that all settings are optional and the app will use the documented default settings if they are not used.

  Name|Description|Default
  --|--|--
  `TASKMONITOR_APP_NAME_MAPPING_CONFIG`|Ability to map tasks to the same app name. Map must be a dictionary with string keys and list of strings as value. All app names in the list will be replaced by it's key.|`{}`
  `TASKMONITOR_DATA_MAX_AGE`|Max age of logged tasks in hours. Older logs be deleted automatically.|`24`
  `TASKMONITOR_DELETE_STALE_BATCH_SIZE`|Size of task logs deleted together in one batch.|`5000`
  `TASKMONITOR_ENABLED`|Global switch to enable/disable task monitor.|`True`
  `TASKMONITOR_HOUSEKEEPING_FREQUENCY`|Frequency of house keeping runs in minutes.|`30`
  `TASKMONITOR_QUEUED_TASKS_ADMIN_LIMIT`|The admin page will stop showing the list of queued tasks above this limit to protect against crashing caused by too high memory consumption.|`100000`
  `TASKMONITOR_QUEUED_TASKS_CACHE_TIMEOUT`|Timeout for caching queued tasks in seconds. 0 will deactivate the cache.|`10`
  `TASKMONITOR_REPORTS_MAX_AGE`|Max age of cached reports in minutes.|`60`
  `TASKMONITOR_REPORTS_MAX_TOP`|Max items to show in the top reports. e.g. 10 will shop the top ten items.|`20`
  `TASKMONITOR_TRUNCATE_NESTED_DATA`|Whether deeply nested task params and results are truncated.|`True`





  Yes, there is a setting, which you can increase according to your needs. However, please keep in mind that your storage needs will increase accordingly. The current approx. usage is 0.5 KB per entry, so e.g. you need approx. 500 MB to store 1.000.000 task logs. Note that you can use the command line utility to find out how much space your logs are currently using.



  Celery Analytics seams to be designed mainly as data source for reports on Grafana. It apparently works great if you want to integrate analysis about your task executions into a Grafana dashboards. But it's usability without Grafana is limited.

  Task Monitor on the other hand aims to be fully functional standalone by providing reports and many useful features for analyzing your task logs directly on the admin site. It also provides a more complete picture, since Celery Analytics ignores retried tasks.



  Flower offers more detailed and technical information about task runs and might  therefore be more most for developers. However, it not designed to store a larger number of task logs (default is only 10K) and is appears therefore to be less suited for Alliance Auth, where you typically have 100K+ tasks per day.



  Task Monitor has data truncating enabled by default. It is applied when storing args, kwargs and results in task logs. This helps to reduce the storage consumptions and also makes the task log better readable. But it can be turned off.

  Task args are truncated by clearing all nested containers.

  Example: `[1, [2, 3], 4]` becomes `[1, [], 4]`

  Task kwargs are truncated by clearing all nested containers in values.

  Example: `{"a": [1, 2], "b": 3}` becomes `{"a": [], "b": 3}`

  Finally, task results are truncated like args and kwargs depending on their type. In addition lists of empty containers are compressed.

  Example: `[ [], [], [] ]` becomes `[]`


pkgId: b8d630613e0b39f53c378c82756112e22b83f14db11cae3a7082349f02d080f6
name: python-aa-theme-slate
arch: src
version: 2.1.0
epoch: 0
release: 1
summary: Bootstrap Theme 'Slate' for Alliance Auth
url: https://github.com/ppfeufer/aa-theme-slate
rpm_group: Unspecified
rpm_buildhost: localhost
location_href: Packages/python-aa-theme-slate-2.1.0-1.src.rpm
checksum_type: sha256
description:
  [![Version](https://img.shields.io/pypi/v/aa-theme-slate?label=release "Version")](https://pypi.org/project/aa-theme-slate/)
  [![License](https://img.shields.io/badge/license-GPLv3-green "License")](https://pypi.org/project/aa-theme-slate/)
  [![Python](https://img.shields.io/pypi/pyversions/aa-theme-slate "Python")](https://pypi.org/project/aa-theme-slate/)
  [![Django](https://img.shields.io/pypi/djversions/aa-theme-slate?label=django "Django")](https://pypi.org/project/aa-theme-slate/)
  ![pre-commit](https://img.shields.io/badge/pre--commit-enabled-brightgreen?logo=pre-commit&logoColor=white)
  [![pre-commit.ci status](https://results.pre-commit.ci/badge/github/ppfeufer/aa-theme-slate/master.svg)](https://results.pre-commit.ci/latest/github/ppfeufer/aa-theme-slate/master)
  [![Code Style: black](https://img.shields.io/badge/code%20style-black-000000.svg "Code Style: black")](http://black.readthedocs.io/en/latest/)
  [![Automated Checks](https://github.com/ppfeufer/aa-theme-slate/actions/workflows/automated-checks.yml/badge.svg "Automated Checks")](https://github.com/ppfeufer/aa-theme-slate/actions/workflows/automated-checks.yml)
  [![codecov](https://codecov.io/gh/ppfeufer/aa-theme-slate/branch/master/graph/badge.svg?token=J9PBF0HM8C "codecov")](https://codecov.io/gh/ppfeufer/aa-theme-slate)
  [![Contributor Covenant](https://img.shields.io/badge/Contributor%20Covenant-2.1-4baaaa.svg "Contributor Covenant")](https://github.com/ppfeufer/aa-forum/blob/master/CODE_OF_CONDUCT.md)
  [![Discord](https://img.shields.io/discord/790364535294132234?label=discord "Discord")](https://discord.gg/zmh52wnfvM)

  [![ko-fi](https://ko-fi.com/img/githubbutton_sm.svg)](https://ko-fi.com/N4N8CL1BY)

  This is the [Bootstrap theme Slate](https://bootswatch.com/3/slate/) converted into
  a theme for Alliance auth.

  ______________________________________________________________________

  <!-- mdformat-toc start --slug=gitlab --maxlevel=6 --minlevel=1 -->

  - [Alliance Auth Theme: Slate](#alliance-auth-theme-slate)
    - [Installation](#installation)

  <!-- mdformat-toc end -->

  ______________________________________________________________________

  ![AA Theme: Slate](https://raw.githubusercontent.com/ppfeufer/aa-theme-slate/master/aa_theme_slate/images/aa_theme_slate.jpg)



  > \[!NOTE\]
  >
  > **Alliance Auth Theme Slate >= 2.0.0 needs at least Alliance Auth v4.0.0!**
  >
  > Please make sure to update your Alliance Auth instance _before_ you install this
  > module or update to the latest version, otherwise an update to Alliance Auth will
  > be pulled in unsupervised.
  >
  > The last version of Alliance Auth Theme Slate that supports Alliance Auth v3 is `1.7.1`.

  ```shell
  pip install aa-theme-slate
  ```

  Now open your `local.py` and add the following right below your `INSTALLED_APPS`:

  ```python

  INSTALLED_APPS.insert(0, "aa_theme_slate")

  if "aa_theme_slate" in INSTALLED_APPS:
      
      
      
      
      

      
      
      
      
      
      

      INSTALLED_APPS += [
          "aa_theme_slate.theme.slate",
      ]

      
      DEFAULT_THEME = "aa_theme_slate.theme.slate.auth_hooks.AaSlateThemeHook"
      DEFAULT_THEME_DARK = "aa_theme_slate.theme.slate.auth_hooks.AaSlateThemeHook"  # Legacy AAv3 user.profile.night_mode=1
  ```

  **Important**

  If you are using `AA-GDPR`, the template stuff needs to be **after** the `AA_GDPR`
  entry, like this:

  ```python

  INSTALLED_APPS.insert(0, "aagdpr")
  AVOID_CDN = True



  INSTALLED_APPS.insert(0, "aa_theme_slate")
  ```

rpm_license:
[cell repeats an earlier one in this file: 34486 characters]


pkgId: 5f6eda89b9f1aeb65390e4411de66a1bae6c29016e444df69b632819a04175cd
name: python-aa-timezones
arch: src
version: 2.2.1
epoch: 0
release: 1
summary: Time Zones Overview for Alliance Auth
url: https://github.com/ppfeufer/aa-timezones
rpm_group: Unspecified
rpm_buildhost: localhost
location_href: Packages/python-aa-timezones-2.2.1-1.src.rpm
checksum_type: sha256
description:
  [![Version](https://img.shields.io/pypi/v/aa-timezones?label=release)](https://pypi.org/project/aa-timezones/)
  [![License](https://img.shields.io/github/license/ppfeufer/aa-timezones)](https://github.com/ppfeufer/aa-timezones/blob/master/LICENSE)
  [![Python](https://img.shields.io/pypi/pyversions/aa-timezones)](https://pypi.org/project/aa-timezones/)
  [![Django](https://img.shields.io/pypi/djversions/aa-timezones?label=django)](https://pypi.org/project/aa-timezones/)
  ![pre-commit](https://img.shields.io/badge/pre--commit-enabled-brightgreen?logo=pre-commit&logoColor=white)
  [![pre-commit.ci status](https://results.pre-commit.ci/badge/github/ppfeufer/aa-timezones/master.svg)](https://results.pre-commit.ci/latest/github/ppfeufer/aa-timezones/master)
  [![Code Style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](http://black.readthedocs.io/en/latest/)
  [![Discord](https://img.shields.io/discord/790364535294132234?label=discord)](https://discord.gg/zmh52wnfvM)
  [![Checks](https://github.com/ppfeufer/aa-timezones/actions/workflows/automated-checks.yml/badge.svg)](https://github.com/ppfeufer/aa-timezones/actions/workflows/automated-checks.yml)
  [![codecov](https://codecov.io/gh/ppfeufer/aa-timezones/branch/master/graph/badge.svg?token=ZSRTW5FR4C)](https://codecov.io/gh/ppfeufer/aa-timezones)
  [![Translation status](https://weblate.ppfeufer.de/widget/alliance-auth-apps/aa-timezones/svg-badge.svg)](https://weblate.ppfeufer.de/engage/alliance-auth-apps/)
  [![Contributor Covenant](https://img.shields.io/badge/Contributor%20Covenant-2.1-4baaaa.svg)](https://github.com/ppfeufer/aa-timezones/blob/master/CODE_OF_CONDUCT.md)

  [![ko-fi](https://ko-fi.com/img/githubbutton_sm.svg)](https://ko-fi.com/N4N8CL1BY)

  App for displaying different time zones with Alliance Auth

  ______________________________________________________________________

  <!-- mdformat-toc start --slug=github --maxlevel=6 --minlevel=1 -->

  - [AA Time Zones](#aa-time-zones)
    - [Installation](#installation)
      - [Step 1: Install the App](#step-1-install-the-app)
      - [Step 2: Update Your Alliance Auth Settings](#step-2-update-your-alliance-auth-settings)
      - [Step 3: Finalizing the Installation](#step-3-finalizing-the-installation)
    - [(Optional) Public Views](#optional-public-views)
    - [Updating](#updating)
    - [Configure the Timezone Panels](#configure-the-timezone-panels)
    - [Adjusting Time](#adjusting-time)
    - [Discord Bot Command](#discord-bot-command)
    - [Changelog](#changelog)
    - [Translation Status](#translation-status)
    - [Contributing](#contributing)

  <!-- mdformat-toc end -->

  ______________________________________________________________________

  ![Time Zones](https://raw.githubusercontent.com/ppfeufer/aa-timezones/master/docs/images/presentation/aa-timezones.jpg)



  > \[!NOTE\]
  >
  > **AA Time Zones >= 2.0.0 needs at least Alliance Auth v4.0.0!**
  >
  > Please make sure to update your Alliance Auth instance _before_ you install this
  > module or update to the latest version, otherwise an update to Alliance Auth will
  > be pulled in unsupervised.
  >
  > The last version compatible with Alliance Auth v3 is `1.16.2`.



  Make sure you're in the virtual environment (venv) of your Alliance Auth installation.
  Then install the latest version:

  ```bash
  pip install aa-timezones
  ```



  Configure your AA settings (`local.py`) as follows:

  - Add `'timezones',` to `INSTALLED_APPS`



  Run migrations & copy static files

  ```bash
  python manage.py collectstatic
  python manage.py migrate
  ```

  Restart your supervisor services for AA

  Once done, it's time to add all the time zone information, so you can define your
  own set of panels later. To do so, simply run:

  ```bash
  python manage.py timezones_load_tz_data
  ```



  This app supports AA's feature of public views, since time zones conversion is not
  any mission-critical information. To allow users to view the time zone conversion page
  without the need to log in, please add `"timezones",` to the list of
  `APPS_WITH_PUBLIC_VIEWS` in your `local.py`:

  ```python




  APPS_WITH_PUBLIC_VIEWS = [
      "timezones",  # https://github.com/ppfeufer/aa-timezones
  ]
  ```

  > **Note**
  >
  > If you don't have a list for `APPS_WITH_PUBLIC_VIEWS` yet, then add the whole
  > block from here. This feature has been added in Alliance Auth v3.6.0 so you
  > might not yet have this list in your `local.py`.



  To update your existing installation of AA Time Zones, first enable your virtual
  environment.

  Then run the following commands from your AA project directory (the one that
  contains `manage.py`).

  ```bash
  pip install -U aa-timezones
  ```

  ```bash
  python manage.py collectstatic
  ```

  ```bash
  python manage.py migrate
  ```

  Now restart your AA supervisor services.



  Per default, there are 10 additional time zone panels that are displayed (see first
  image). If you want to change those, you can create your own set of panels in your
  admin backend.

  **NOTE:** "Local Time" and "EVE Time" will always be displayed as the first two panels,
  no matter what.



  You can easily adjust the time that is displayed for all timezones. This is useful
  for reinforcement timers or pre-planned fleets. To do so, click on the "Adjust Time"
  button below the time zone panels, and you will see 2 different ways to set a new time.

  ![Adjusting Time](https://raw.githubusercontent.com/ppfeufer/aa-timezones/master/docs/images/weblate/aa-timezones_adjust-time-settings.jpg)

  The first one is meant for timers, like reinforcement timers, anchoring timers or
  the like. Its maximum is 7 days, 59 minutes and 59 seconds into the future. That
  should cover pretty much all timers you can find in Eve Online.

  The second one is best suited for pre-planned fleets. Here you can set a fixed date
  and time based on the selected time zone. The default selected time zone is "EVE
  Time" but you can change it to all the available options. Keep in mind the selected
  time zone is the one the time and date will be adjusted to. So if you are going to
  use it to plan fleets, it is recommended to keep this set to "EVE Time".

  To set the adjusted time, simply click on "Set Time" in the row you altered. This
  will then adjust all time zone panels to the time you selected and will also alter
  the link in your browser, so you can share it with others directly.



  **For this to work, you'll need to have `allianceauth-discordbot` installed, configured
  and running.** ([See this link](https://github.com/pvyParts/allianceauth-discordbot))

  | Command | Effect                                                                                                                                                                                                                     |
  | :------ | :------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
  | `/time` | Displays the current Eve time and what time it is in the configured time zones<br>![Discord Bot Response](https://raw.githubusercontent.com/ppfeufer/aa-timezones/master/docs/images/presentation/discordbot-response.jpg) |



  See [CHANGELOG.md](https://github.com/ppfeufer/aa-timezones/blob/master/CHANGELOG.md)



  [![Translation status](https://weblate.ppfeufer.de/widget/alliance-auth-apps/aa-timezones/multi-auto.svg)](https://weblate.ppfeufer.de/engage/alliance-auth-apps/)

  Do you want to help translate this app into your language or improve the existing
  translation? - [Join our team of translators][weblate engage]!



  Do you want to contribute to this project? That's cool!

  Please make sure to read the [Contribution Guidelines].\
  (I promise, it's not much, just some basics)

  <!-- Inline Links -->

  [contribution guidelines]: https://github.com/ppfeufer/aa-timezones/blob/master/CONTRIBUTING.md "Contribution Guidelines"
  [weblate engage]: https://weblate.ppfeufer.de/engage/alliance-auth-apps/ "Weblate Translations"

rpm_license:
[cell repeats an earlier one in this file: 34486 characters]


pkgId: 10ae1eac349a4cd09a5520492fc9235ed771efc0796916ffbab6e4230452268f
name: python-aaaa
arch: src
version: 1.0
epoch: 0
release: 1
summary: Alphabetize output filenames
url: http://github.com/sgrieve/aaaa
rpm_license: MIT
rpm_group: Unspecified
rpm_buildhost: localhost
location_href: Packages/python-aaaa-1.0-1.src.rpm
checksum_type: sha256
description:
  [![Build Status](https://travis-ci.org/sgrieve/aaaa.svg?branch=master)](https://travis-ci.org/sgrieve/aaaa) [![Coverage](https://img.shields.io/codecov/c/github/sgrieve/aaaa)](https://codecov.io/gh/sgrieve/aaaa) ![PyPI - Python Version](https://img.shields.io/pypi/pyversions/aaaa) ![PyPI - License](https://img.shields.io/pypi/l/aaaa)

  Have you ever been creating an animated plot by saving a series of images and joining them together? The obvious way to name these frames would be using numbers:

  ```python
  for i in range(15):
      plt.savefig('{}.png'.format(i))
  ```

  But many operating systems will order these files as follows:

  ```bash
  0.png
  1.png
  10.png
  11.png
  12.png
  13.png
  14.png
  2.png
  3.png
  4.png
  5.png
  6.png
  7.png
  8.png
  9.png
  ```

  Thereby screwing up the order of your animation.

  This is where `aaaa` (pronounced like a scream) comes in! `aaaa` has a single class which creates an iterator that yields an alphabetical sequence `aa`, `ab`, `ac`, etc. So we can change our above example:

  ```python
  from aaaa import aaaa

  fname = aaaa()

  for i in range(15):
      plt.savefig('{}.png'.format(next(fname)))
  ```

  Which will preserve the order of the files in your operating system:

  ```bash
  aa.png
  ab.png
  ac.png
  ad.png
  ae.png
  af.png
  ag.png
  ah.png
  ai.png
  aj.png
  ak.png
  al.png
  am.png
  an.png
  ao.png
  ```

  File sorting can differ between operating systems, sometimes with [serious results](https://arstechnica.com/information-technology/2019/10/chemists-discover-cross-platform-python-scripts-not-so-cross-platform/).




  `aaaa` has no dependences and is tested on Python 3.5 through 3.8 and it can be installed via pip:

  ```bash
  pip install aaaa
  ```



  There are two ways to use `aaaa`. Firstly, you can loop directly over an `aaaa` instance, until there are no items left (in this case the last value of name will be `zz`):

  ```python
  from aaaa import aaaa

  names = aaaa()

  for name in names:
      print(name)

  ```

  Or, you can use the `next()` operator to only get as many values as you need:

  ```python
  from aaaa import aaaa

  names = aaaa()

  for i in range(10):
      print(next(names))

  ```

  The default length of an output from `aaaa` is 2 characters long - this will allow you to order 676 files. If you need a larger or smaller amount of characters you can specify this as an argument to `aaaa`:

  ```python
  from aaaa import aaaa

  names_short = aaaa(1)
  names_long = aaaa(4)

  print(next(names_short), next(names_long))


  ```

  Beyond four or five characters in length, initializing `aaaa` becomes prohibitively slow. Note that four characters gives you **456976** permutations - so you should never need more than this.




  For my purposes this package is feature complete, but if you find a bug, or have a feature request, open an issue, or create a pull request!




  The project is licensed under the MIT license.


pkgId: a3106a9bd97b5ac2ddb37a0f22e5d1532456fbcf14b3a93236302ecc659fcee4
name: python-aaanalysis
arch: src
version: 1.0.0
epoch: 0
release: 1
summary: Python framework for interpretable protein prediction
url: https://aaanalysis.readthedocs.io
rpm_license: BSD-3-Clause
rpm_group: Unspecified
rpm_buildhost: localhost
location_href: Packages/python-aaanalysis-1.0.0-1.src.rpm
checksum_type: sha256
description:
      Developer Notes:
      Please make sure that badges in badges.rst (Read The Docs)
      and README.rst (GitHub) are the same.
      Missing badges
      |Conda Version|
     * - **Package**
       - |PyPI Status| |PyPI Version| |Supported Python Versions| |Downloads| |License|
     * - **Testing**
       - |Unit Tests| |CodeQL| |Codecov| |Documentation Status|
  **AAanalysis** (Amino Acid analysis) is a Python framework for interpretable sequence-based protein prediction.
  Its foundation are the following algorithms:
  - **CPP**: Comparative Physicochemical Profiling, a feature engineering algorithm comparing two sets of protein
    sequences to identify the set of most distinctive features.
  - **dPULearn**: deterministic Positive-Unlabeled (PU) Learning algorithm to enable training on
    unbalanced and small datasets.
  - **AAclust**: k-optimized clustering wrapper framework to select redundancy-reduced sets of numerical scales
    (e.g., amino acid scales).
  In addition, AAanalysis provide functions for loading various protein benchmark datasets, amino acid scales,
  and their two-level classification (**AAontology**). We combined **CPP** with the explainable
  AI  `SHAP <https://shap.readthedocs.io/en/latest/index.html>`_ framework to explain sample level predictions with
  single-residue resolution.
  If you are looking to make publication-ready plots with a view lines of code, see our
  `Plotting Prelude <https://aaanalysis.readthedocs.io/en/latest/generated/plotting_prelude.html>`_.
  You can find the official documentation at `Read the Docs <https://aaanalysis.readthedocs.io/en/latest/>`_.


pkgId: 1c59d563b1732eb4e8b6fa635dfe2685ef45bf91a02a0ec81c0c7c2d1654ee34
name: python-aaargh
arch: src
version: 0.7.1
epoch: 0
release: 1
summary: An astonishingly awesome application argument helper
url: https://github.com/wbolster/aaargh
rpm_license: BSD
rpm_group: Unspecified
rpm_buildhost: localhost
location_href: Packages/python-aaargh-0.7.1-1.src.rpm
checksum_type: sha256
description:
  The Python standard library contains the *optparse*, *getopt*, and *argparse*
  modules, and out in the wild you will find many alternative command line
  interface libraries stacked on top of these, such as *cliff*, *cement*,
  *opster*, *plac*, and many others. Some of these libraries separate the command
  line interface setup of your application from the actual code, some force yet
  another argument parsing API upon you, some force you to hide your code in
  non-obvious framework constructs, and some even add dependencies on other
  modules.
  This makes you scream *aaargh*. And, lo and behold, here it is!


pkgId: 399755d6393db6c74e70b44f7717c84be49ca4fb455442cb9574c590cf177d86
name: python-aac-datasets
arch: src
version: 0.5.2
epoch: 0
release: 1
summary: Audio Captioning datasets for PyTorch.
url: https://pypi.org/project/aac-datasets/
rpm_group: Unspecified
rpm_buildhost: localhost
location_href: Packages/python-aac-datasets-0.5.2-1.src.rpm
checksum_type: sha256
description:
  <!-- # -*- coding: utf-8 -*- -->

  <div align="center">



  <a href="https://www.python.org/"><img alt="Python" src="https://img.shields.io/badge/-Python 3.7+-blue?style=for-the-badge&logo=python&logoColor=white"></a>
  <a href="https://pytorch.org/get-started/locally/"><img alt="PyTorch" src="https://img.shields.io/badge/-PyTorch 1.10.1+-ee4c2c?style=for-the-badge&logo=pytorch&logoColor=white"></a>
  <a href="https://black.readthedocs.io/en/stable/"><img alt="Code style: black" src="https://img.shields.io/badge/code%20style-black-black.svg?style=for-the-badge&labelColor=gray"></a>
  <a href="https://github.com/Labbeti/aac-datasets/actions"><img alt="Build" src="https://img.shields.io/github/actions/workflow/status/Labbeti/aac-datasets/python-package-pip.yaml?branch=main&style=for-the-badge&logo=github"></a>
  <a href='https://aac-datasets.readthedocs.io/en/stable/?badge=stable'>
      <img src='https://readthedocs.org/projects/aac-datasets/badge/?version=stable&style=for-the-badge' alt='Documentation Status' />
  </a>

  Audio Captioning unofficial datasets source code for **AudioCaps** [[1]](#audiocaps), **Clotho** [[2]](#clotho), **MACS** [[3]](#macs), and **WavCaps** [[4]](#wavcaps), designed for PyTorch.

  </div>


  ```bash
  pip install aac-datasets
  ```

  If you want to check if the package has been installed and the version, you can use this command:
  ```bash
  aac-datasets-info
  ```





  ```python
  from aac_datasets import Clotho

  dataset = Clotho(root=".", download=True)
  item = dataset[0]
  audio, captions = item["audio"], item["captions"]


  ```



  ```python
  from torch.utils.data.dataloader import DataLoader
  from aac_datasets import Clotho
  from aac_datasets.utils import BasicCollate

  dataset = Clotho(root=".", download=True)
  dataloader = DataLoader(dataset, batch_size=4, collate_fn=BasicCollate())

  for batch in dataloader:
      
      
      ...
  ```


  To download a dataset, you can use `download` argument in dataset construction :
  ```python
  dataset = Clotho(root=".", subset="dev", download=True)
  ```
  However, if you want to download datasets from a script, you can also use the following command :
  ```bash
  aac-datasets-download --root "." clotho --subsets "dev"
  ```


  `aac-datasets` package contains 4 different datasets :

  <!-- | | AudioCaps | Clotho | MACS | WavCaps |
  |:---:|:---:|:---:|:---:|:---:|
  | Subsets | `train`, `val`, `test` | `dev`, `val`, `eval`, `dcase_aac_test`, `dcase_aac_analysis`, `dcase_t2a_audio`, `dcase_t2a_captions` | `full` | `as`, `as_noac`, `bbc`, `fsd`, `fsd_nocl`, `sb` |
  | Sample rate (kHz) | 32 | 44.1 | 48 | 32 |
  | Estimated size (GB) | 43 | 53 | 13 | 941 |
  | Audio source | AudioSet | Freesound | TAU Urban Acoustic Scenes 2019 | AudioSet, BBC Sound Effects, Freesound, SoundBible | -->

  | Dataset | Sampling<br>rate (kHz) | Estimated<br>size (GB) | Source | Subsets |
  |:---:|:---:|:---:|:---:|:---:|
  | AudioCaps | 32 | 43 | AudioSet | `train`<br>`val`<br>`test`<br>`train_v2` |
  | Clotho | 44.1 | 53  | Freesound | `dev`<br>`val`<br>`eval`<br>`dcase_aac_test`<br>`dcase_aac_analysis`<br>`dcase_t2a_audio`<br>`dcase_t2a_captions` |
  | MACS | 48 | 13 | TAU Urban Acoustic Scenes 2019 | `full` |
  | WavCaps | 32 | 941 | AudioSet<br>BBC Sound Effects<br>Freesound<br>SoundBible | `audioset`<br>`audioset_no_audiocaps`<br>`bbc`<br>`freesound`<br>`freesound_no_clotho`<br>`freesound_no_clotho_v2`<br>`soundbible` |

  For Clotho, the **dev** subset should be used for training, val for validation and eval for testing.

  Here is additional statistics on the train subset for AudioCaps, Clotho, MACS and WavCaps:

  | | AudioCaps/train | Clotho/dev | MACS/full | WavCaps/full |
  |:---:|:---:|:---:|:---:|:---:|
  | Nb audios | 49,838 | 3,840 | 3,930 | 403,050 |
  | Total audio duration (h) | 136.6<sup>1</sup> | 24.0 | 10.9 | 7563.3 |
  | Audio duration range (s) | 0.5-10 | 15-30 | 10 | 1-67,109 |
  | Nb captions per audio | 1 | 5 | 2-5 | 1 |
  | Nb captions | 49,838 | 19,195 | 17,275 | 403,050 |
  | Total nb words<sup>2</sup> | 402,482 | 217,362 | 160,006 | 3,161,823 |
  | Sentence size<sup>2</sup> | 2-52 | 8-20 | 5-40 | 2-38 |
  | Vocabulary<sup>2</sup> | 4724 | 4369 | 2721 | 24,600 |
  | Annotated by | Human | Human | Human | Machine |
  | Corrected by | Human | Human | None | None |

  <sup>1</sup> This duration is estimated on the total duration of 46230/49838 files of 126.7h.

  <sup>2</sup> The sentences are cleaned (lowercase+remove punctuation) and tokenized using the spacy tokenizer to count the words.



  This package has been developped for Ubuntu 20.04, and it is expected to work on most Linux-based distributions.


  Python requirements are automatically installed when using pip on this repository.
  ```
  torch >= 1.10.1
  torchaudio >= 0.10.1
  py7zr >= 0.17.2
  pyyaml >= 6.0
  tqdm >= 4.64.0
  huggingface-hub >= 0.15.1
  numpy >= 1.21.2
  ```



  The external requirements needed to download **AudioCaps** are **ffmpeg** and **yt-dlp**.
  **ffmpeg** can be install on Ubuntu using `sudo apt install ffmpeg` and **yt-dlp** from the [official repo](https://github.com/yt-dlp/yt-dlp).
  <!-- programs can be downloaded on Ubuntu using `sudo apt install ffmpeg`. -->

  You can also override their paths for AudioCaps:
  ```python
  from aac_datasets import AudioCaps
  dataset = AudioCaps(
      download=True,
      ffmpeg_path="/my/path/to/ffmpeg",
      ytdl_path="/my/path/to/ytdlp",
  )
  ```



  If you want to use [audiocaps-download 1.0](https://github.com/MorenoLaQuatra/audiocaps-download) package to download AudioCaps, you will have to respect the AudioCaps folder tree:
  ```python
  from audiocaps_download import Downloader
  root = "your/path/to/root"
  downloader = Downloader(root_path=f"{root}/AUDIOCAPS/audio_32000Hz/", n_jobs=16)
  downloader.download(format="wav")
  ```

  Then disable audio download and set the correct audio format before init AudioCaps :
  ```python
  from aac_datasets import AudioCaps
  dataset = AudioCaps(
      root=root,
      subset="train",
      download=True,
      audio_format="wav",
      download_audio=False,  # this will only download labels and metadata files
  )
  ```



  [1] C. D. Kim, B. Kim, H. Lee, and G. Kim, “Audiocaps: Generating captions for audios in the wild,” in NAACL-HLT, 2019. Available: https://aclanthology.org/N19-1011/


  [2] K. Drossos, S. Lipping, and T. Virtanen, “Clotho: An Audio Captioning Dataset,” arXiv:1910.09387 [cs, eess], Oct. 2019, Available: http://arxiv.org/abs/1910.09387


  [3] F. Font, A. Mesaros, D. P. W. Ellis, E. Fonseca, M. Fuentes, and B. Elizalde, Proceedings of the 6th Workshop on Detection and Classication of Acoustic Scenes and Events (DCASE 2021). Barcelona, Spain: Music Technology Group - Universitat Pompeu Fabra, Nov. 2021. Available: https://doi.org/10.5281/zenodo.5770113


  [4] X. Mei et al., “WavCaps: A ChatGPT-Assisted Weakly-Labelled Audio Captioning Dataset for Audio-Language Multimodal Research,” arXiv preprint arXiv:2303.17395, 2023, [Online]. Available: https://arxiv.org/pdf/2303.17395.pdf


  If you use this software, please consider cite it as "Labbe, E. (2013). aac-datasets: Audio Captioning datasets for PyTorch.", or use the following BibTeX citation:

  ```
  @software{
      Labbe_aac_datasets_2024,
      author = {Labbé, Étienne},
      license = {MIT},
      month = {03},
      title = {{aac-datasets}},
      url = {https://github.com/Labbeti/aac-datasets/},
      version = {0.5.2},
      year = {2024}
  }
  ```


  Maintainer:
  - [Étienne Labbé](https://labbeti.github.io/) "Labbeti": labbeti.pub@gmail.com

rpm_license:
  MIT License  Copyright (c) 2022 Étienne Labbé (Labbeti)  Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:  The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.  THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.


pkgId: 8dd90c5bc8c5f03cba7adf38997ccbb69fdc245b6460156581247586e0132fc0
name: python-aac-init
arch: src
version: 0.4.3
epoch: 0
release: 1
summary: please add a summary manually as the author left a blank one
url: https://pypi.org/project/aac-init/
rpm_license: None
rpm_group: Unspecified
rpm_buildhost: localhost
location_href: Packages/python-aac-init-0.4.3-1.src.rpm
checksum_type: sha256
description:
  [![Tests](https://github.com/nac-aci/aac-init/actions/workflows/test.yml/badge.svg)](https://github.com/nac-aci/aac-init/actions/workflows/test.yml)
  ![Python Support](https://img.shields.io/badge/python-3.10%20%7C%203.11%20%7C%203.12-informational "Python Support: 3.10, 3.11, 3.12")



  A CLI tool to bootstrap and configure ACI fabric using ACI as Code.

  ```bash
  $ aac-init -h
  Usage: aac-init [OPTIONS]

    A CLI tool to bootstrap and configure ACI fabric using ACI as Code.

  Options:
    --version                       Show the version and exit.
    -d, --data PATH                 Path to aac-init YAML data files.
                                    [required]
    -l, --log-level [debug|info|warning|error|critical]
                                    Specify the logging level. Default setting
                                    is 'info'.  [default: info]
    -h, --help                      Show this message and exit.
  ```

  All data from the YAML files (`-d/--data` option) will use to bootstrap and configure ACI fabric.

  The data folder **MUST** use following structure, `00-global_policy.yml` and `01-fabric_mgmt.yml` are **mandatory required**, see `docs/data_template` for details.

  ```bash
  data/
  ├── 00-global_policy.yml      # mandatory, ACI fabric global policies
  └── nac_data
      ├── 01-fabric_mgmt.yml    # mandatory, ACI fabric switch connection information
      └── other-yaml-files..    # optional, other ACI as Code configurations
  ```



  - Working knowledge of ACI and [Network as Code - ACI](https://netascode.cisco.com/)
  - A HTTP/TFTP server is required to store APIC/ACI switch image for wiping/booting APIC/ACI switch to particular version. See `docs/image_server` if you don't have experience on setting up image server.



  Python 3.10+ is required to install `aac-init`. Don't have Python 3.10 or later? See [Python 3 Getting Started](https://www.python.org/about/gettingstarted/).

  `aac-init` can be installed using `pip`:

  ```bash
  pip install aac-init
  ```

  You will also need to install ansible and related NetworkAsCode dependencies, see Cisco [Network As Code - Ansible](https://netascode.cisco.com/solutions/aci/ansible/quick_start/#local-installation) for details. You can also find `requirements.yml/requirements.txt` at `docs/requirements`.

  ```bash
  apt-get install ansible
  ansible-galaxy install -r requirements.yml
  pip install -r requirements.txt
  ```



  ```bash
  $ aac-init -d data/
  Select single or multiple choice(s) to init ACI Fabric:
  [1]  Wipe and boot APIC/switch to particular version
  [2]  APIC initial setup (Single Pod)
  [3]  Init ACI Fabric via NaC (Network as Code)
  Example: (1,2,.. or *): *

  Are you sure to proceed with the following choice(s)?
  [1] Wipe and boot APIC/switch to particular version
  [2] APIC initial setup (Single Pod)
  [3] Init ACI Fabric via NaC (Network as Code)
   (yes, no) [yes]:
  ```



  ```bash
  pip install aac-init --upgrade
  ```



  ```bash
  pip uninstall aac-init
  ```





  [Rudy Lei](shlei@cisco.com)



  [Rudy Lei](shlei@cisco.com)
  [Yang Bian](yabian@cisco.com)
  [Xiao Wang](xiawang3@cisco.com)
  [Song Wang](songwa@cisco.com)
  [Linus Xu](linxu3@cisco.com)


pkgId: 6d736c812283931caf74375fc1379c2943d5d36499fcc0818cf7a8edd3bd8867
name: python-aac-req-qa
arch: src
version: 0.3.1
epoch: 0
release: 1
summary: please add a summary manually as the author left a blank one
url: https://github.com/DevOps-MBSE/AaC-Req-QA
rpm_license: MIT License
rpm_group: Unspecified
rpm_buildhost: localhost
location_href: Packages/python-aac-req-qa-0.3.1-1.src.rpm
checksum_type: sha256
description:
  An AaC plugin to perform automated quality checks for the shall statements in your AaC model.

  This plugin will scan your architecture for any `req` entries and will use an LLM to evaluate
  the quality of the `shall` field.  The plugin is configured to evaluate your shall statement
  using the following attributes:

  - Unambiguous: The requirement should be simple, direct, and precise with no room for interpretation.
  - Testable (verifiable): The requirement should be testable, and it should be possible to verify that the system meets the requirement.  Preferable the requirement should be verifiable by automated acceptance test, automated analysis, or demonstration rather than inspection.  If inspection is the only rational means of verification it will have a lower rating.
  - Clear: The requirement should be concise, terse, simple, and precise.
  - Correct:  The requirement should not have any false or invalid assertions.
  - Understandable:  The requirement should be easily understood by all stakeholders.
  - Feasible: The requirement should be realistic and achievable.
  - Independent:  The requirement should stand-alone and not be dependent on other requirements.
  - Atomic: The requirement should be a single, discrete, and indivisible statement.
  - Necessary: The requirement should be necessary to the solution and not be redundant or superfluous.
  - Implementation-free: The requirement should not specify how the solution will be implemented.  It should only specify what the solution should do, not how it should do it.

  If the `shall` is evaluated to be of sufficient quality, the `aac check` will pass.  Otherwise, you will receive a
  failure message produced by the AI with an assessment of each attribute and an overall score.  Failure results
  from an overall score of `C (Medium)` or lower from the AI.



  If you haven't already, install Architecture-as-Code (AaC):
  ```bash
  pip install aac
  ```
  Next install this AaC-Req-QA plugin:
  ```bash
  pip install aac-req-qa
  ```

  Set the environment variables needed to access an OpenAI endpoint.  This may be a commercial
  endpoint in OpenAI or Azure OpenAI or a self-hosted endpoint using a tool like Ollama or vLLM.

  - AAC_AI_URL:  The usl of the LLM endpoint.  Example:  https://localhost:11434/v1
  - AAC_AI_MODEL:  The name of the LLM model.  Example:  `mistral` for local (i.e. Ollama), `gpt-4` for OpenAI or Azure
  - AAC_AI_KEY:  The access key for the API.  If using a local model, any value will work but it must not be empty or missing.  Example: not-a-real-key

  If you wish to use an Azure OpenAI set the following environment variables.

  - AAC_AI_TYPE:  Set to "Azure", otherwise standard OpenAI client will be used.
  - AAC_AI_API_VERSION:  Set to your desired / supported API Version.  Example: 2023-12-01-preview

  If you have a proxy, set the proxy environment variables.

  - AAC_HTTP_PROXY:  The HTTP proxy.  Example:  http://userid:password@myproxy.myorg.com:80
  - AAC_HTTPS_PROXY:  The HTTPS proxy.  Example:  https://userid:password@myproxy.myorg.com:443
  - AAC_SSL_VERIFY:  Allows you to disable SSL verification.  Value must be `true` or `false` (default: `true`).

  Although this is a bit cumbersome, it is necessary as there is no other way to provide configuration data
  within AaC, particularly for constraint plugins.  Remember to protect your secrets when configuring these
  environment variables.



  This plugin provides a new command called `eval-req` that will execute the requirements QA
  on a specified AaC file.  This will perform an evaluation of each `req` in the AaC file based on
  INCOSE requirements quality guidelines, and will give you all the AI output for each requirement.
  Be aware, this performs a requirement-by-requirement evaluation with no context of surrounding
  requirements in the specification.  It is often very difficult to meet all INCOSE guidelines
  in a single requirement statement.  It will also perform separate AI evaluation calls for each
  requirement which can take a lot of time. If you wish to perform fewer AI calls and evaluate your
  requirements as a set, use the `eval-spec` command instead.



  This plugin provides a new command called `eval-spec` that will execute the requirements specification QA
  on a specified AaC file.  This will perform a wholistic review of the requirement specification and all
  the included requirements against the INCOSE requirements quality guidelines.  For instances where
  the quality of requirements need to be assessed in context, this is a good solution.




  Because this is using an LLM, it is a non-deterministic process and cannot be guaranteed
  to perform consistently.  The LLM is tuned to reduce variation and provide reliable, repeatable
  performance to the greatest extent possible, but no guarantees can be made with the current
  state-of-the art LLM models.

  Performance is completely dependent on the performance of the LLM provided by the endpoint.
  This has been tested with Azure OpenAI using GPT-4 as well as Mistral 7B run within Ollama
  and had acceptable performance in both.  Performance with other models may be better or worse.



  We're adapting the [analyze claims](https://github.com/danielmiessler/fabric/blob/main/patterns/analyze_claims/system.md) pattern
  from the open source [Fabric project](https://github.com/danielmiessler/fabric) to evaluate requirements.  Huge thanks to the
  Fabric team for the innovation and examples.


pkgId: 1573aba27f25321943ec0351eb46f20043b7928df5bc41d919629532c340a03b
name: python-aac-rest-api
arch: src
version: 0.1.6
epoch: 0
release: 1
summary: Rest-API Plugin for AaC
url: https://github.com/DevOps-MBSE/aac-rest-api
rpm_license: MIT License
rpm_group: Unspecified
rpm_buildhost: localhost
location_href: Packages/python-aac-rest-api-0.1.6-1.src.rpm
checksum_type: sha256
description:
  Rest-API Plugin for Architecture-as-Code



  Currently, Python version 3.9.13 is required to avoid certain dependency version issues.



  Previously, this project was built with dependency information kept in a setup.py script.
  However, the preferred method is to use pyproject.toml to set the project-level options.
  Required modules are kept in the dependency sections of the pyproject.toml, and then the
  pip-compile command is used to add hashes to the requirements.txt file for enhanced security
  (see additional instructions below).

  To coincide with these changes, some changes to tox.ini and the addition of a MANIFEST.ini file were also necessary.

  These lines were added to tox.ini:
     isolated_build = True
     skipsdist = True

  A MANIFEST file with these lines was added:
     graft src
     graft tests
     include tox.ini
     include src/rest-api/.aac



  cd python
  pip install -e .



  cd python
  pip install -e .
  python -m unittest



  pip install pip-tools
  pip-compile --generate-hashes pyproject.toml


pkgId: d5b610c8be2c6dab8a5fe4614dc0faa5c572ba7e27cfb773e52cef0f6da8572d
name: python-aac-spec
arch: src
version: 0.1.7
epoch: 0
release: 1
summary: Specification plugin for AaC
url: https://github.com/DevOps-MBSE/aac-spec
rpm_license: MIT License
rpm_group: Unspecified
rpm_buildhost: localhost
location_href: Packages/python-aac-spec-0.1.7-1.src.rpm
checksum_type: sha256
description:
  Specification and requirement tracing plugins for Architecture-as-Code



  Currently, Python version 3.9.13 is required to avoid certain dependency version issues.



  Previously, this project was built with dependency information kept in a setup.py script.
  However, the preferred method is to use pyproject.toml to set the project-level options.
  Required modules are kept in the dependency sections of the pyproject.toml, and then the
  pip-compile command is used to add hashes to the requirements.txt file for enhanced security
  (see additional instructions below).

  To coincide with these changes, some changes to tox.ini and the addition of a MANIFEST.ini file were also necessary.

  These lines were added to tox.ini:
     isolated_build = True
     skipsdist = True

  A MANIFEST file with these lines was added:
     graft src
     graft tests
     include tox.ini
     include src/puml/.aac



  cd python
  pip install -e .



  cd python
  pip install -e .
  python -m unittest



  pip install pip-tools
  pip-compile --generate-hashes pyproject.toml


pkgId: 63a4abec4a26b2a6e26b06afbafffa60480798148b54f38d19072c9ce9f329bc
name: python-aacRepair
arch: src
version: 0.7
epoch: 0
release: 1
summary: repair aac files
url: https://pypi.org/project/aacRepair/
rpm_group: Unspecified
rpm_buildhost: localhost
location_href: Packages/python-aacRepair-0.7-1.src.rpm
checksum_type: sha256
description:
  repair aac and aacPlus files grabbed from the internet
  ![Tests](https://github.com/44xtc44/aacRepair/actions/workflows/tests.yml/badge.svg?branch=dev)

rpm_license:
  MIT License ===========  Copyright (c) [2022] [René Horn]  Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:  The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.  THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NON INFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.


pkgId: 9750ca622b9da79b6dd126f85c48c68d6f7fb5a0ad9646f8c615531271c70789
name: python-aacommpy
arch: src
version: 0.2.4
epoch: 0
release: 1
summary: aacommpy - AAComm nuget package wrapper
url: https://github.com/BoJl4apa/aacommpy
rpm_license: MIT
rpm_group: Unspecified
rpm_buildhost: localhost
location_href: Packages/python-aacommpy-0.2.4-1.src.rpm
checksum_type: sha256
description:
  from aacommpy.settings import AACOMM_SERVER_EXE_PATH
  from aacommpy.AAComm import CommAPI, Services, Shared
  api = CommAPI()
  status = CommAPI.StartAACommServer(AACOMM_SERVER_EXE_PATH)
  if status != "":
      print(status)
  else:
      
      is_running = CommAPI.IsAACommServerRunning
      print(f"AACommServer is running: {is_running}")
  cData = Services.ConnectionData()
  cData.ControllerType = Shared.ProductTypes.AGM800_ID
  cData.CommChannelType = Shared.ChannelType.Ethernet
  cData.ET_IP_1 = 172
  cData.ET_IP_2 = 1
  cData.ET_IP_3 = 1
  cData.ET_IP_4 = 101
  cData.ET_Port = 5000
  res = api.Connect(cData)
  print(res)-------------------------
  3.Available Commands
  AACommPy provides several commands that can be executed through the command line using the installed package. These commands include:
  3.1.install: Downloads and installs the AAComm package. You can specify a version using the --version option.
      the version number is the same with the AAComm nuget package version you want to use with you python script.
  3.2.version: Retrieves the installed version of AAComm.
  3.3.update: Updates the installed AAComm package to the latest version.
  3.4.dotnetfw: Sets the .NET framework version of AAComm library. You can choose from the available options: net40, net48, net6.0, net8.0. The default version is net48.
  Example Usage
  Here's an example of how to use the AACommPy package:
  Install the package:
  pip install aacommpy

  aacommpy install

  aacommpy version

  aacommpy update

  aacommpy dotnetfw --netfw net48


pkgId: b69a23e570d649971702006a431a96175091cbd39c5d9d3b2fe7cf68fd64e7ce
name: python-aad-token-verify
arch: src
version: 0.2.0
epoch: 0
release: 1
summary: A python utility library to verify an Azure Active Directory OAuth token
url: https://github.com/GeneralMills/azure-ad-token-verify
rpm_license: MIT
rpm_group: Unspecified
rpm_buildhost: localhost
location_href: Packages/python-aad-token-verify-0.2.0-1.src.rpm
checksum_type: sha256
description:
  [![Tests](https://github.com/GeneralMills/azure-ad-token-verify/workflows/Test%20and%20Analysis/badge.svg)](https://github.com/GeneralMills/azure-ad-token-verify/actions)
  [![PyPi](https://img.shields.io/pypi/pyversions/aad-token-verify.svg)](https://pypi.python.org/pypi/aad-token-verify)

  A python utility library to verify an Azure Active Directory OAuth token. Meant for resource servers serving secured API endpoints (eg FastAPI)



  ```bash
  python3 -m pip install aad-token-verify
  ```



  To use stand alone, simply import the verify payload function and call.

  ```python
  from aad_token_verify import get_verified_payload

  token_verifier = get_verified_payload(token, tenant_id="YOUR_TENANT_ID", audience_uris=["AUDIENCE_URI"])
  ```

  To use with FastAPI, there's some setup to get the Swagger docs to work

  ```python
  from fastapi import Depends, FastAPI
  from fastapi.openapi.models import OAuthFlowImplicit, OAuthFlows
  from fastapi.middleware.cors import CORSMiddleware
  from fastapi.security import OAuth2

  from aad_token_verify import get_verified_payload


  _TENANT_ID = "ISSUER_TENANT_ID"
  _AUDIENCE_URI = "https://YOUR_AUDIENCE_URI"
  _AAD_CLIENT_ID = "CLIENT_ID"

  oauth2_scheme = OAuth2(
      flows=OAuthFlows(
          implicit=OAuthFlowImplicit(
              authorizationUrl=f"https://login.microsoftonline.com/{_TENANT_ID}/oauth2/v2.0/authorize",
              scopes={
                  f"{_AUDIENCE_URI}/.default": "Custom Audience URI scope",
                  "openid": "OpenID scope",
                  "profile": "Profile scope",
                  "email": "email scope",
              },
          )
      )
  )

  async def get_current_user(
      auth_header: str = Depends(oauth2_scheme),  # noqa: B008
  ):
      scheme, _, token = auth_header.partition(" ")
      return get_verified_payload(
          token,
          tenantId=_TENANT_ID,
          audience_uris=[_AUDIENCE_URI],
      )

  app = FastAPI()

  app.add_middleware(
      CORSMiddleware,
      allow_origins=["*"],
      allow_credentials=True,
      allow_methods=["*"],
      allow_headers=["*"],
  )

  app.swagger_ui_init_oauth = {
      "usePkceWithAuthorizationCodeGrant": True,
      "clientId": _AAD_CLIENT_ID,
      "scopes": [f"{_AUDIENCE_URI}.default"],
  }

  @app.get("/")
  async def secured_endpoint(user=Depends(get_current_user)):
      return user
  ```



  Feel free to submit issues and pull requests!


pkgId: 04ce1f31922bf5dedb6c5d340dc1f85d48f0ba29eb0e854e380ae7032736ab19
name: python-aadhaar-py
arch: src
version: 2.0.2
epoch: 0
release: 1
summary: Extract embedded information from Aadhaar Secure QR Code.
url: https://github.com/vishaltanwar96/aadhaar-py
rpm_license: MIT
rpm_group: Unspecified
rpm_buildhost: localhost
location_href: Packages/python-aadhaar-py-2.0.2-1.src.rpm
checksum_type: sha256
description:
  [![made-with-python](https://img.shields.io/badge/Made%20with-Python-1f425f.svg)](https://www.python.org/)
  [![PyPI pyversions](https://img.shields.io/pypi/pyversions/aadhaar-py?color=purple)](https://pypi.org/project/aadhaar-py/)
  [![PyPI version](https://badge.fury.io/py/aadhaar-py.svg)](https://badge.fury.io/py/aadhaar-py)
  [![MIT license](https://img.shields.io/badge/License-MIT-blue.svg)](https://lbesson.mit-license.org/)
  [![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)
  [![codecov](https://codecov.io/gh/vishaltanwar96/aadhaar-py/branch/main/graph/badge.svg?token=JG312MQEEQ)](https://codecov.io/gh/vishaltanwar96/aadhaar-py)
  [![Downloads](https://pepy.tech/badge/aadhaar-py)](https://pepy.tech/project/aadhaar-py)

  This library helps you extract the embedded information 💾 in Aadhaar Secure QR Code


  I would like to thank the authors of [pyaadhaar](https://github.com/Tanmoy741127/pyaadhaar). It wouldn't be possible to move into the right direction without this library.


  [Secure Aadhaar QR Decoder](https://aadhaar-secure-qr.herokuapp.com/)


  ```python
  >>> from aadhaar.secure_qr import extract_data
  >>> received_qr_code_data = 12345678
  >>> extracted_data = extract_data(received_qr_code_data)
  ```

  The `extract_data` function returns an instance of `ExtractedSecureQRData` which has the definition of:
  ```python
  @dataclass(frozen=True)
  class ExtractedSecureQRData:
      text_data: ExtractedTextData
      image: Image.Image
      contact_info: ContactData
  ```


  Text Data 📝:
  ```python
  >>> extracted_data.text_data
  ExtractedTextData(reference_id=ReferenceId(last_four_aadhaar_digits='8908', timestamp=datetime.datetime(2019, 3, 5, 15, 1, 37, 123000)), name='Penumarthi Venkat', date_of_birth=datetime.date(1987, 5, 7), gender=<Gender.MALE: 'Male'>, address=Address(care_of='S/O: Pattabhi Rama Rao', district='East Godavari', landmark='Near Siva Temple', house='4-83', location='Sctor-2', pin_code='533016', post_office='Aratlakatta', state='Andhra Pradesh', street='Main Road', sub_district='Karapa', vtc='Aratlakatta'))
  ```

  The Embedded Image 🌆:
  ```python
  >>> extracted_data.image
  <PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=60x60 at 0x1029CA460>
  ```

  The Contact Information 📧:
  ```python
  >>> extracted_data.contact_info
  ContactData(email=Email(hex_string=None, fourth_aadhaar_digit='8'), mobile=Mobile(hex_string='1f31f19afc2bacbd8afb84526ae4da184a2727e8c2b1b6b9a81e4dc6b74d692a', fourth_aadhaar_digit='8'))
  ```

  But hey! 🙄 I want to send this data via a ReSTful API, don't you have something to serialize that ugly instance of `ExtractedSecureQRData`? 😩

  `to_dict` method to the rescue 💪
  ```python
  >>> extracted_data.to_dict()
  {
    "text_data": {
      "reference_id": {
        "last_four_aadhaar_digits": "8908",
        "timestamp": "2019-03-05T15:01:37.123000"
      },
      "name": "Penumarthi Venkat",
      "date_of_birth": "1987-05-07",
      "gender": "Male",
      "address": {
        "care_of": "S/O: Pattabhi Rama Rao",
        "district": "East Godavari",
        "landmark": "Near Siva Temple",
        "house": "4-83",
        "location": "Sctor-2",
        "pin_code": "533016",
        "post_office": "Aratlakatta",
        "state": "Andhra Pradesh",
        "street": "Main Road",
        "sub_district": "Karapa",
        "vtc": "Aratlakatta"
      }
    },
    "image": "data:image/jpeg;base64,/9j/4AAQSkZblahblah",
    "contact_info": {
      "email": {
        "hex_string": None
      },
      "mobile": {
        "hex_string": "1f31f19afc2bacbd8afb84526ae4da184a2727e8c2b1b6b9a81e4dc6b74d692a"
      }
    }
  }

  ```


  ```bash
  python -m unittest discover tests/ --verbose
  ```


pkgId: f0f388b267d9d681e36b38f8d43caac269275b45d61893daafd2b5a9089c1df8
name: python-aafigure
arch: src
version: 0.6
epoch: 0
release: 1
summary: ASCII art to image converter
url: http://launchpad.net/aafigure
rpm_license: BSD
rpm_group: Unspecified
rpm_buildhost: localhost
location_href: Packages/python-aafigure-0.6-1.src.rpm
checksum_type: sha256
description:
              |     |   |
              +-----+   V
  Command::
      aafigure test.txt -t svg -o test.svg
  Please see documentation for examples.
  http://aafigure.readthedocs.io/


pkgId: a74af788a0b1cdd14b74c7fca70cae391328174f3a7f6aeaca7be0fefc4b05bb
name: python-aai-engine
arch: src
version: 0.0.33
epoch: 0
release: 1
summary: Ad Astra Industries RPA engine
url: https://adastraindustries.com
rpm_license: MIT License
rpm_group: Unspecified
rpm_buildhost: localhost
location_href: Packages/python-aai-engine-0.0.33-1.src.rpm
checksum_type: sha256
description:
  The AAI Engine is a computer vision based automation python library, enabling easy desktop automation with legacy applications, citrix environments, webapps and regualar desktop apps.



  `pip install aai-engine`



  `python -m pip install -e c:\<>\<>\aai_engine`

  or if that does not work (permission issue):

  `python3 -m pip install --no-build-isolation -e /example/path/to/aai_engine`

  If on macos with an m1, create a conda environment to be able to use opencv.

  ```
  brew install miniforge
  conda init zsh
  conda create -n aai python=3.8.6
  conda activate aai
  conda install -c conda-forge opencv
  ```



  [Here](https://aai-org.github.io/aai_engine_manager/) is the documentation for the AAI Engine.



  `python -m build`

  Should you want to add files not directly under src/aai_engine_package, add them in MANIFEST.in.



  The easiest way to capture and edit screenshots is to use the GUI.
  One can launch the gui by executing `aai-engine-gui` in the terminal.



  `aai-engine-capture '/path/to/where/you/want/to/save/the/screenshot'`


pkgId: 586c65f8912f0bc14bed7dc0457bd03d03a636dcf7cf8729fddd475922014dcb
name: python-aaindex
arch: src
version: 1.1.2
epoch: 0
release: 1
url: https://github.com/amckenna41/aaindex
rpm_license: MIT
rpm_group: Unspecified
rpm_buildhost: localhost
location_href: Packages/python-aaindex-1.1.2-1.src.rpm
checksum_type: sha256
summary:
  A lightweight Python software package for accessing the data in the various AAIndex databases, which represent the physiochemical, biochemical and structural properties of amino acids as numerical indices.

description:
    * [Introduction](#introduction)
    * [Requirements](#requirements)
    * [Installation](#installation)
    * [Usage](#usage)
    * [Tests](#tests)
    * [Contact](#contact)
    * [License](#license)
    * [References](#References)


pkgId: 53d99ef6b59b48449f8c36cf368a2291746e8218d54ee75c7e5e646796674177
name: python-aaio
arch: src
version: 1.4.2
epoch: 0
release: 1
summary: Async AAIO api wrapper for python
url: https://github.com/kewldan/AAIO
rpm_group: Unspecified
rpm_buildhost: localhost
location_href: Packages/python-aaio-1.4.2-1.src.rpm
checksum_type: sha256
description:
  <div align="center">

  <a href="https://aaio.so/" target="_blank">
  	<img alt="AAIO Badge" src="https://aaio.so/assets/svg/banners/big/dark-2.svg" title="Aaio - Сервис по приему онлайн платежей">
  </a>

  [![kewldan - AAIO](https://img.shields.io/static/v1?label=kewldan&message=AAIO&color=blue&logo=github)](https://github.com/kewldan/AAIO "Go to GitHub repo")
  [![GitHub release](https://img.shields.io/github/release/kewldan/AAIO?include_prereleases=&sort=semver&color=blue)](https://github.com/kewldan/AAIO/releases/)
  [![License](https://img.shields.io/badge/License-MIT-blue)](#license)

  [![Upload Python Package](https://github.com/kewldan/AAIO/actions/workflows/python-publish.yml/badge.svg)](https://github.com/kewldan/AAIO/actions/workflows/python-publish.yml)
  [![issues - AAIO](https://img.shields.io/github/issues/kewldan/AAIO)](https://github.com/kewldan/AAIO/issues)

  [AAIO Official documentation](https://wiki.aaio.so/)

  </div>



  This library is a wrapper for the https://aaio.so API **from enthusiast**. All methods are described and all types are
  **explicitly** defined. Methods that create requests to
  aaio.so
  return a pydantic's models for each response. Please write about all problems related to the library
  to [issues](https://github.com/kewldan/AAIO/issues)

  API is up-to-date as of *06 September 2024*.

  * PyPl - https://pypi.org/project/aaio/
  * Github - https://github.com/kewldan/AAIO
  * Docs - https://kewldan.ru/projects/aaio
  * Demo - https://t.me/aaio_demo_bot
  * Requirements: Python >= 3.7
  * Added to [AAIO SDKs](https://wiki.aaio.so/priem-platezhei/gotovye-cms-moduli-i-sdk/python-3-sdk)



  * It's completely **asynchronous**
  * You can use **multiple** clients to work with **multiple** users or shops
  * **All methods** for working with API are implemented
  * The library returns strictly typed for responses from APIs
  * For each method, **docstrings** are used
  * The library handle {type: error} responses and throws AAIOBadRequest exception
  * Our library was the **first** to be added to the **official** AAIO wiki
  * **Modern**, strict code for Python 3.7



  * Install via pip: `pip install aaio`
  * Download sources - `git clone https://github.com/kewldan/AAIO`





  ```python
  import asyncio

  from aaio import AAIO


  async def main():
      client = AAIO('MERCHANT ID', 'SECRET KEY', 'API KEY')
      balances = await client.get_balances()
      print(balances)  # type='success' code=None message=None balance=625.85 referral=172.96 hold=0.0


  asyncio.run(main())
  ```



  ```python
  import asyncio

  from aaio import AAIO


  async def main():
      client = AAIO('MERCHANT ID', 'SECRET KEY', api_key='API KEY')


      
      payment_url = await client.get_pay_url(100, 'my_order_id', 'My order description', 'qiwi', 'support@aaio.so',
                                          'referral code', currency='USD',
                                          language='en')
      print(payment_url)  # Prints payment url for customer


      
      payment_url = client.create_payment(100, 'my_order_id', 'My order description', 'qiwi', 'support@aaio.so',
                                          'referral code', currency='USD',
                                          language='en')
      print(payment_url)
      


  asyncio.run(main())
  ```



  ```python
  import asyncio

  from aaio import AAIO


  async def main():
      client = AAIO('MERCHANT ID', 'SECRET KEY', api_key='API KEY')
      payoff = await client.create_payoff('qiwi', 100.35, '79998887766', 'my_payoff_id')
      print(payoff.status)  # in_progress


  asyncio.run(main())
  ```



  * E-Mail - kewldanil1@gmail.com
  * Telegram - [@kewldan](https://t.me/kewldan)



  Released under [MIT](/LICENSE) by [@kewldan](https://github.com/kewldan).

rpm_license:
  MIT License  Copyright (c) 2023 Daniil Tenishev  Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:  The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.  THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.


pkgId: eb079328921abd593c9fa6c0f4b12ea88acce4ece255a323ab0a94ffc927f287
name: python-aaiotrello
arch: src
version: 2.0.0
epoch: 0
release: 1
summary: Async Python library for interacting with the Trello API
url: https://trello.com/
rpm_license: BSD License
rpm_group: Unspecified
rpm_buildhost: localhost
location_href: Packages/python-aaiotrello-2.0.0-1.src.rpm
checksum_type: sha256
description:
  Async Trello API Client

  Python 3.7+



  ```bash
  pip install aaiotrello
  ```






  First you need gen auth url:
  ```python
  from aaiotrello import TrelloApi

  trello = TrelloApi(config.TRELLO_KEY)
  trello.set_token(config.TRELLO_TOKEN)
  ```
  Than you need copy value of token_url and auth your trello account in webbrowser
  After that you will get token


  ```python
  trello_app.set_token(TRELLO_APP_TOKEN)
  ```



  Get board info:
  ```python
  board = await trello_app.boards.get("5c49c07e48557d4e29414936")
  ```


pkgId: 961226c33954b495f79b1b22a12dbc6dc6dbe3d81195135291f1055d3e9b9f17
name: python-aalpy
arch: src
version: 1.4.2
epoch: 0
release: 1
summary: An active automata learning library
url: https://github.com/DES-Lab/AALpy
rpm_license: MIT
rpm_group: Unspecified
rpm_buildhost: localhost
location_href: Packages/python-aalpy-1.4.2-1.src.rpm
checksum_type: sha256
description:
  <div align="center">

  <picture style="align: center; padding-bottom: 3mm;">
    <source media="(prefers-color-scheme: dark)" srcset="./docs/logo_dark.png">
    <img width=70% height=70% alt="AALpy Logo" src="./docs/logo_light.png">
  </picture>

  <br/>
  <br/>

  [![Python application](https://github.com/DES-Lab/AALpy/actions/workflows/python-app.yml/badge.svg)](https://github.com/DES-Lab/AALpy/actions/workflows/python-app.yml)
  [![CodeQL](https://github.com/DES-Lab/AALpy/actions/workflows/codeql-analysis.yml/badge.svg)](https://github.com/DES-Lab/AALpy/actions/workflows/codeql-analysis.yml)
  ![PyPI - Downloads](https://img.shields.io/pypi/dm/aalpy)

  [![GitHub issues](https://img.shields.io/github/issues/DES-Lab/AALpy)](https://github.com/DES-Lab/AALpy/issues)
  ![GitHub pull requests](https://img.shields.io/github/issues-pr/des-lab/aalpy)
  [![Python 3.6](https://img.shields.io/badge/python-3.6%2B-blue)](https://www.python.org/downloads/release/python-360/)
  ![PyPI - Wheel](https://img.shields.io/pypi/wheel/aalpy)
  [![Maintenance](https://img.shields.io/badge/Maintained%3F-yes-green.svg)](https://GitHub.com/Naereen/StrapDown.js/graphs/commit-activity)
  [![License: MIT](https://img.shields.io/badge/License-MIT-blue.svg)](https://opensource.org/licenses/MIT)

  </div>
  <hr />

  AALpy is a light-weight automata learning library written in Python.
  You can start learning models of black-box systems with a few lines of code.

  AALpy supports both **active** and **passive** automata learning algorithms that can be used to learn a variety of modeling formalisms, including
  **deterministic**, **non-deterministic**, and **stochastic automata**, as well as **deterministic context-free grammars/pushdown automata**.

  <div align="center">

  | **Automata Type** |                      **Supported Formalisms**                     | **Algorithms**        |                                                       **Features** |
  |-------------------|:-----------------------------------------------------------------:|-----------------------|-------------------------------------------------------------------:|
  | Deterministic     |                 DFAs <br /> Mealy Machines <br /> Moore Machines                 |      L* <br /> KV <br /> RPNI      | Seamless Caching <br /> Counterexample Processing <br /> 13 Equivalence Oracles  |
  | Non-Deterministic |                      ONFSM <br /> Abstracted ONFSM                      |        L*<sub>ONFSM</sub>       |                                 Size Reduction  Trough Abstraction |
  | Stochastic        | Markov Decision Processes <br /> Stochastic Mealy Machines <br /> Markov Chains | L*<sub>MDP</sub> <br /> L*<sub>SMM</sub> <br /> ALERGIA |               Counterexample Processing <br /> Exportable to PRISM format  <br /> Bindings to jALERGIA|
  | Pushdown          |          VPA/SEVPA                                                            | KV<sub>VPA</sub> <br /> PAPNI | Passive learning of VPAs <br /> Exclusive call-return pairs
  </div>



  Use the package manager [pip](https://pip.pypa.io/en/stable/) to install the latest release of AALpy:
  ```bash
  pip install aalpy
  ```
  To install current version of the master branch (it might contain bugfixes and added functionalities between releases):
  ```bash
  pip install https://github.com/DES-Lab/AALpy/archive/master.zip
  ```
  The minimum required version of Python is 3.6.
  Ensure that you have [Graphviz](https://graphviz.org/) installed and added to your path if you want to visualize models.

  For manual installation, clone the repo and install `pydot` (the only dependency).



  If you are interested in automata learning or would like to understand the automata learning process in more detail,
  please check out our **Wiki**. On Wiki, you will find more detailed examples on how to use AALpy.
  - <https://github.com/DES-Lab/AALpy/wiki>

  ***[Examples.py](https://github.com/DES-Lab/AALpy/blob/master/Examples.py)*** contains examples covering almost the whole of AALpy's functionality and its a great starting point.



  All active automata learning procedures follow this high-level approach:
  - [Define the input alphabet and system under learning (SUL)](https://github.com/DES-Lab/AALpy/wiki/SUL-Interface,-or-How-to-Learn-Your-Systems)
  - [Choose the equivalence oracle](https://github.com/DES-Lab/AALpy/wiki/Equivalence-Oracles)
  - [Run the learning algorithm](https://github.com/DES-Lab/AALpy/wiki/Setting-Up-Learning)

  Passive learning algorithm simply require you to provide data in the appropriate format (check Wiki and Examples) and run the learning function.


  <details>
    <summary>Code snipped demonstrating some of AALpy's functionalities</summary>

  The following snippet demonstrates a short example in which an automaton is either [loaded](https://github.com/DES-Lab/AALpy/wiki/Loading,Saving,-Syntax-and-Visualization-of-Automata) or [randomly generated](https://github.com/DES-Lab/AALpy/wiki/Generation-of-Random-Automata) and then [learned](https://github.com/DES-Lab/AALpy/wiki/Setting-Up-Learning).
  ```python
  from aalpy.utils import load_automaton_from_file, generate_random_deterministic_automata
  from aalpy.SULs import AutomatonSUL
  from aalpy.oracles import RandomWalkEqOracle
  from aalpy.learning_algs import run_Lstar, run_KV





  random_dfa = generate_random_deterministic_automata(automaton_type='dfa', num_states=8,
                                                      input_alphabet_size=5, output_alphabet_size=2)


  alphabet = random_dfa.get_input_alphabet()




  sul = AutomatonSUL(random_dfa)


  eq_oracle = RandomWalkEqOracle(alphabet, sul, num_steps=5000, reset_prob=0.09)



  learned_dfa = run_KV(alphabet, sul, eq_oracle, automaton_type='dfa')






  learned_dfa.save()



  learned_dfa.visualize()

  print(learned_dfa)
  ```
  </details>

  To make experiments reproducible, define a random seed at the beginning of your program.
  ```Python
  from random import seed
  seed(2) # all experiments will be reproducible
  ```


  AALpy has been used to:
  - [Learn Models of Bluetooth Low-Energy](https://github.com/apferscher/ble-learning)
  - [Find bugs in VIM text editor](https://github.com/DES-Lab/AALpy/discussions/13)
  - [Learn Input-Output Behavior of RNNs](https://github.com/DES-Lab/Extracting-FSM-From-RNNs)
  - [Learn Models of GIT](https://github.com/taburg/git-learning)
  - [Solve RL Problems](https://github.com/DES-Lab/Learning-Environment-Models-with-Continuous-Stochastic-Dynamics)


  If you use AALpy in your research, please cite us with of the following:
  - [Extended version (preferred)](https://www.researchgate.net/publication/359517046_AALpy_an_active_automata_learning_library/citation/download)
  - [Tool paper](https://dblp.org/rec/conf/atva/MuskardinAPPT21.html?view=bibtex)

  If you have research suggestions or you need specific help concerning your research, feel free to start a [discussion](https://github.com/DES-Lab/AALpy/discussions) or contact [edi.muskardin@silicon-austria.com](mailto:edi.muskardin@silicon-austria.com).
  We are happy to help you and consult you in applying automata learning in various domains.


  Pull requests are welcome. For significant changes, please open an issue first to discuss what you would like to change.
  In case of any questions or possible bugs, please open issues.


pkgId: d8a6f2e6c2f58f308d403c47412e87e02b19d131f26713ad927d5640d65da42b
name: python-aalto-boss
arch: src
version: 1.12.0
epoch: 0
release: 1
summary: Bayesian optimization structure search
url: https://gitlab.com/cest-group/boss
rpm_license: Apache License 2.0
rpm_group: Unspecified
rpm_buildhost: localhost
location_href: Packages/python-aalto-boss-1.12.0-1.src.rpm
checksum_type: sha256
description:
  `Bayesian Optimization Structure Search (BOSS) <https://sites.utu.fi/boss/>`_ is a general-purpose Bayesian Optimization code. It is designed to facilitate machine learning in computational and experimental natural sciences. See `research examples <https://sites.utu.fi/boss/research/>`_ for various applications of BOSS.
  For a more detailed description of the code and tutorials, please consult the `user guide <https://cest-group.gitlab.io/boss>`_.


pkgId: e3365ab308a47d754431ff29ee442ff37f0eab72eb66ba952b336349db39d658
name: python-aam
arch: src
version: 0.1.5
epoch: 0
release: 1
summary: a lightweight about-me-site generator
url: https://github.com/JmPotato/Aam
rpm_license: MIT License
rpm_group: Unspecified
rpm_buildhost: localhost
location_href: Packages/python-aam-0.1.5-1.src.rpm
checksum_type: sha256
description:
  Aam means "All about me". It is a lightweight about-me-site generator. To compare with a blog, Aam is for pages not posts. So you can use it to build your own resume page.


pkgId: 45c153c0f6e2488c2d5ab647cb8706ec1b203e465053c6d322b0bb5baf0f1022
name: python-aamarpay
arch: src
version: 1.0.1
epoch: 0
release: 1
summary: Payment gateway libarary
url: https://github.com/sanjidbillah/aamarPay-python
rpm_license: MIT
rpm_group: Unspecified
rpm_buildhost: localhost
location_href: Packages/python-aamarpay-1.0.1-1.src.rpm
checksum_type: sha256
description:
  aamarpay is an online payment gateway service for Bangladesh. Committed to provide best payment experience online for business. Lowest fee and fast checkout will give you good experience of receiving payment online.
  Installation
  ~~~~~~~~~~~~
  We recommend install ``aamarpay`` through pip install .
      $ pip install aamarpay
  Example
  ~~~~~~~
  To make a payment :
      from aamarpay.aamarpay import aamarPay
      pay = aamarPay(isSandbox=True,transactionAmount=600)
      paymentpath = pay.payment()
      return redirect(paymentpath)
      
  Contribute
  ~~~~~~~~~~
  Create Github Pull Request https://github.com/sanjidbillah/aamarPay-python
  x
  Thanks
  ~~~~~~


pkgId: a85f362b29e4347d56c9ffc56f87ccfd67cf1637ee7f5f1fd024de08d8b96c69
name: python-aamp-app
arch: src
version: 0.0.1.30
epoch: 0
release: 1
summary: AAMP App
url: https://pypi.org/project/aamp-app/
rpm_license: MIT License
rpm_group: Unspecified
rpm_buildhost: localhost
location_href: Packages/python-aamp-app-0.0.1.30-1.src.rpm
checksum_type: sha256
description:
  To use this app, you need to install Python (version 3.10 or higher).

  In a terminal window in a new directory, run `pip install aamp_app` or `pip install --upgrade aamp_app` to install the app. Use the latter one to upgrade the app after it's installed. All dependencies will be installed with it. You may wish to use a virtual python environment if you don't want this app or its dependencies to interfere with your current system. On Mac or Linux-based systems, do this by running the following commands before installing:

  `pip install virtualenv`: This line installs the virtualenv package which allows you to create virtual python environments.

  `virtualenv venv`: This line creates a virtual environment (called `venv`) in the current directory. This will create a new folder (called `venv`) with the environment data.

  `source venv/bin/activate`: This line activates the virtual environment. After activating the virtual environment, you should be able to see `(venv)` in your terminal window. If you close the terminal window/tab, you will have to execute this command to activate the environment again before using the app.



  To start the app, run `aamp_app`. Enter the database user credentials for MongoDB. These credentials will be saved as plain text in a text file (called `pw.txt`) in the same directory. Therefore, this app should only be used on trusted computers. If the connection to the database cannot be established using the provided credentials, you will be required to run `aamp_app` again to retry. To delete the user credentials, simply delete the `pw.txt` file.



  Most devices should be able to connect to the app without any problems. However, certain devices require some drivers/software to create a connection. Due to the nature of the specific drivers/software, they must be installed separately.

  -   [Thorlabs Devices (APT or Kinesis)](https://www.thorlabs.com/software_pages/viewsoftwarepage.cfm?code=Motion_Control)



  Package app:

  `python3 setup.py sdist bdist_wheel`

  Upload to pip:

  `twine upload --skip-existing dist/*`


pkgId: 61a64aae1f29f704ed9ac77961153b3164e2342f399711d8fdb94a38ba40caf3
name: python-aamt
arch: src
version: 0.2.5
epoch: 0
release: 1
summary: 基于pytest的接口自动化测试工具模板
url: https://github.com/xuefeng365/aamt-template.git
rpm_license: MIT
rpm_group: Unspecified
rpm_buildhost: localhost
location_href: Packages/python-aamt-0.2.5-1.src.rpm
checksum_type: sha256
description:
  > 用于生成 基于pytest的接口自动化脚手架

  python 版本

  > 3.9

  安装最新版本

  > pip install aamt

  指定版本安装

  > pip install aamt==0.2.5

  升级aamt

  > pip install -U aamt

  创建项目脚手架

  > aamt startproject demo

  创建项目脚手架(自动创建虚拟环境)

  > aamt startproject demo -venv

  外网速度慢，pandas可能安装失败，推荐用国内镜像

  > pip --default-timeout=6000 install -i https://pypi.tuna.tsinghua.edu.cn/simple aamt


pkgId: c3eab921b28f1e18544b21ab9e74855afe1153c90f7b0b3efd8873b84ab8cf3c
name: python-aana
arch: src
version: 0.2.2.3
epoch: 0
release: 1
summary: Multimodal SDK
url: https://www.mobiuslabs.com
rpm_license: Apache-2.0
rpm_group: Unspecified
rpm_buildhost: localhost
location_href: Packages/python-aana-0.2.2.3-1.src.rpm
checksum_type: sha256
description:
  [![Build Status](https://github.com/mobiusml/aana_sdk/actions/workflows/python-package.yml/badge.svg)](https://github.com/mobiusml/aana_sdk/actions/workflows/python-package.yml)
  [![License](https://img.shields.io/badge/License-Apache%202.0-blue.svg)](/LICENSE)
  [![Website](https://img.shields.io/badge/website-online-brightgreen.svg)](http://www.mobiuslabs.com)
  [![Documentation](https://img.shields.io/website?label=documentation&up_message=online&url=https://mobiusml.github.io/aana_sdk/)](https://mobiusml.github.io/aana_sdk/)
  [![PyPI version](https://img.shields.io/pypi/v/aana.svg)](https://pypi.org/project/aana/)
  [![GitHub release](https://img.shields.io/github/v/release/mobiusml/aana_sdk.svg)](https://github.com/mobiusml/aana_sdk/releases)

  <p align="center">
    <picture>
      <source srcset="https://raw.githubusercontent.com/mobiusml/aana_sdk/main/docs/images/AanaSDK_logo_dark_theme.png" media="(prefers-color-scheme: dark)">
      <img src="https://raw.githubusercontent.com/mobiusml/aana_sdk/main/docs/images/AanaSDK_logo_light_theme.png" alt="Aana Logo">
    </picture>
  </p>



  Aana SDK is a powerful framework for building multimodal applications. It facilitates the large-scale deployment of machine learning models, including those for vision, audio, and language, and supports Retrieval-Augmented Generation (RAG) systems. This enables the development of advanced applications such as search engines, recommendation systems, and data insights platforms.

  The SDK is designed according to the following principles:

  - **Reliability**: Aana is designed to be reliable and robust. It is built to be fault-tolerant and to handle failures gracefully.
  - **Scalability**: Aana is designed to be scalable. It is built on top of Ray, a distributed computing framework, and can be easily scaled to multiple servers.
  - **Efficiency**: Aana is designed to be efficient. It is built to be fast and parallel and to use resources efficiently.
  - **Easy to Use**: Aana is designed to be easy to use by developers. It is built to be modular, with a lot of automation and abstraction.

  The SDK is still in development, and not all features are fully implemented. We are constantly working on improving the SDK, and we welcome any feedback or suggestions.

  Check out the [documentation](https://mobiusml.github.io/aana_sdk/) for more information.



  Nowadays, it is getting easier to experiment with machine learning models and build prototypes. However, deploying these models at scale and integrating them into real-world applications is still a challenge.

  Aana SDK simplifies this process by providing a framework that allows:
  - Deploy and scale machine learning models on a single machine or a cluster.
  - Build multimodal applications that combine multiple different machine learning models.



  - **Model Deployment**:
    - Deploy models on a single machine or scale them across a cluster.

  - **API Generation**:
    - Automatically generate an API for your application based on the endpoints you define.
    - Input and output of the endpoints will be automatically validated.
    - Simply annotate the types of input and output of the endpoint functions.
  - **Predefined Types**:
    - Comes with a set of predefined types for various data such as images, videos, etc.

  - **Documentation Generation**:
    - Automatically generate documentation for your application based on the defined endpoints.

  - **Streaming Support**:
    - Stream the output of the endpoint to the client as it is generated.
    - Ideal for real-time applications and Large Language Models (LLMs).

  - **Task Queue Support**:
    - Run every endpoint you define as a task in the background without any changes to your code.
  - **Integrations**:
     - Aana SDK has integrations with various machine learning models and libraries: Whisper, vLLM, Hugging Face Transformers, Deepset Haystack, and more to come (for more information see [Integrations](https://mobiusml.github.io/aana_sdk/pages/integrations/)).





  To install Aana SDK via PyPI, you can use the following command:

  ```bash
  pip install aana
  ```

  For optimal performance install [PyTorch](https://pytorch.org/get-started/locally/) version >=2.1 appropriate for your system. You can skip it, but it will install a default version that may not make optimal use of your system's resources, for example, a GPU or even some SIMD operations. Therefore we recommend choosing your PyTorch package carefully and installing it manually.

  Some models use Flash Attention. Install Flash Attention library for better performance. See [flash attention installation instructions](https://github.com/Dao-AILab/flash-attention?tab=readme-ov-file#installation-and-features) for more details and supported GPUs.



  1. Clone the repository.

  ```bash
  git clone https://github.com/mobiusml/aana_sdk.git
  ```

  2. Install additional libraries.

  For optimal performance install [PyTorch](https://pytorch.org/get-started/locally/) version >=2.1 appropriate for your system. You can continue directly to the next step, but it will install a default version that may not make optimal use of your system's resources, for example, a GPU or even some SIMD operations. Therefore we recommend choosing your PyTorch package carefully and installing it manually.

  Some models use Flash Attention. Install Flash Attention library for better performance. See [flash attention installation instructions](https://github.com/Dao-AILab/flash-attention?tab=readme-ov-file#installation-and-features) for more details and supported GPUs.

  3. Install the package with poetry.

  The project is managed with [Poetry](https://python-poetry.org/docs/). See the [Poetry installation instructions](https://python-poetry.org/docs/#installation) on how to install it on your system.

  It will install the package and all dependencies in a virtual environment.

  ```bash
  sh install.sh
  ```





  You can quickly develop multimodal applications using Aana SDK's intuitive APIs and components.

  If you want to start building a new application, you can use the following GitHub template: [Aana App Template](https://github.com/mobiusml/aana_app_template). It will help you get started with the Aana SDK and provide you with a basic structure for your application and its dependencies.

  Let's create a simple application that transcribes a video. The application will download a video from YouTube, extract the audio, and transcribe it using an ASR model.

  Aana SDK already provides a deployment for ASR (Automatic Speech Recognition) based on the Whisper model. We will use this [deployment](#Deployments) in the example.

  ```python
  from aana.api.api_generation import Endpoint
  from aana.core.models.video import VideoInput
  from aana.deployments.aana_deployment_handle import AanaDeploymentHandle
  from aana.deployments.whisper_deployment import (
      WhisperComputeType,
      WhisperConfig,
      WhisperDeployment,
      WhisperModelSize,
      WhisperOutput,
  )
  from aana.integrations.external.yt_dlp import download_video
  from aana.processors.remote import run_remote
  from aana.processors.video import extract_audio
  from aana.sdk import AanaSDK



  asr_deployment = WhisperDeployment.options(
      num_replicas=1,
      ray_actor_options={"num_gpus": 0.25}, # Remove this line if you want to run Whisper on a CPU.
      user_config=WhisperConfig(
          model_size=WhisperModelSize.MEDIUM,
          compute_type=WhisperComputeType.FLOAT16,
      ).model_dump(mode="json"),
  )
  deployments = [{"name": "asr_deployment", "instance": asr_deployment}]



  class TranscribeVideoEndpoint(Endpoint):
      """Transcribe video endpoint."""

      async def initialize(self):
          """Initialize the endpoint."""
          self.asr_handle = await AanaDeploymentHandle.create("asr_deployment")
          await super().initialize()

      async def run(self, video: VideoInput) -> WhisperOutput:
          """Transcribe video."""
          video_obj = await run_remote(download_video)(video_input=video)
          audio = extract_audio(video=video_obj)
          transcription = await self.asr_handle.transcribe(audio=audio)
          return transcription

  endpoints = [
      {
          "name": "transcribe_video",
          "path": "/video/transcribe",
          "summary": "Transcribe a video",
          "endpoint_cls": TranscribeVideoEndpoint,
      },
  ]

  aana_app = AanaSDK(name="transcribe_video_app")

  for deployment in deployments:
      aana_app.register_deployment(**deployment)

  for endpoint in endpoints:
      aana_app.register_endpoint(**endpoint)

  if __name__ == "__main__":
      aana_app.connect(host="127.0.0.1", port=8000, show_logs=False)  # Connects to the Ray cluster or starts a new one.
      aana_app.migrate()                                              # Runs the migrations to create the database tables.
      aana_app.deploy(blocking=True)                                  # Deploys the application.
  ```

  You have a few options to run the application:
  - Copy the code above and run it in a Jupyter notebook.
  - Save the code to a Python file, for example `app.py`, and run it as a Python script: `python app.py`.
  - Save the code to a Python file, for example `app.py`, and run it using the Aana CLI: `aana deploy app:aana_app --host 127.0.0.1 --port 8000 --hide-logs`.

  Once the application is running, you will see the message `Deployed successfully.` in the logs. You can now send a request to the application to transcribe a video.

  To get an overview of the Ray cluster, you can use the Ray Dashboard. The Ray Dashboard is available at `http://127.0.0.1:8265` by default. You can see the status of the Ray cluster, the resources used, running applications and deployments, logs, and more. It is a useful tool for monitoring and debugging your applications. See [Ray Dashboard documentation](https://docs.ray.io/en/latest/ray-observability/getting-started.html) for more information.

  Let's transcribe [Gordon Ramsay's perfect scrambled eggs tutorial](https://www.youtube.com/watch?v=VhJFyyukAzA) using the application.

  ```bash
  curl -X POST http://127.0.0.1:8000/video/transcribe -Fbody='{"video":{"url":"https://www.youtube.com/watch?v=VhJFyyukAzA"}}'
  ```

  This will return the full transcription of the video, transcription for each segment, and transcription info like identified language. You can also use the [Swagger UI](http://127.0.0.1:8000/docs) to send the request.



  We provide a few example applications that demonstrate the capabilities of Aana SDK.

  - [Chat with Video](https://github.com/mobiusml/aana_chat_with_video): A multimodal chat application that allows users to upload a video and ask questions about the video content based on the visual and audio information. See [Chat with Video Demo notebook](https://github.com/mobiusml/aana_chat_with_video/blob/main/notebooks/chat_with_video_demo.ipynb) to see how to use the application.
  - [Summarize Video](https://github.com/mobiusml/aana_summarize_video): An Aana application that summarizes a video by extracting transcription from the audio and generating a summary using a Language Model (LLM). This application is a part of the [tutorial](https://mobiusml.github.io/aana_sdk/pages/tutorial/) on how to build multimodal applications with Aana SDK.

  See the README files of the applications for more information on how to install and run them.

  The full list of example applications is available in the [Aana Examples](https://github.com/mobiusml/aana_examples) repository. You can use these examples as a starting point for building your own applications.



  There are three main components in Aana SDK: deployments, endpoints, and AanaSDK.



  Deployments are the building blocks of Aana SDK. They represent the machine learning models that you want to deploy. Aana SDK comes with a set of predefined deployments that you can use or you can define your own deployments. See [Integrations](https://mobiusml.github.io/aana_sdk/pages/integrations/) for more information about predefined deployments.

  Each deployment has a main class that defines it and a configuration class that allows you to specify the deployment parameters.

  For example, we have a predefined deployment for the Whisper model that allows you to transcribe audio. You can define the deployment like this:

  ```python
  from aana.deployments.whisper_deployment import WhisperDeployment, WhisperConfig, WhisperModelSize, WhisperComputeType

  asr_deployment = WhisperDeployment.options(
      num_replicas=1,
      ray_actor_options={"num_gpus": 0.25},
      user_config=WhisperConfig(model_size=WhisperModelSize.MEDIUM, compute_type=WhisperComputeType.FLOAT16).model_dump(mode="json"),
  )
  ```

  See [Model Hub](https://mobiusml.github.io/aana_sdk/pages/model_hub/) for a collection of configurations for different models that can be used with the predefined deployments.



  Endpoints define the functionality of your application. They allow you to connect multiple deployments (models) to each other and define the input and output of your application.

  Each endpoint is defined as a class that inherits from the `Endpoint` class. The class has two main methods: `initialize` and `run`.

  For example, you can define an endpoint that transcribes a video like this:

  ```python
  class TranscribeVideoEndpoint(Endpoint):
      """Transcribe video endpoint."""

      async def initialize(self):
          """Initialize the endpoint."""
          await super().initialize()
          self.asr_handle = await AanaDeploymentHandle.create("asr_deployment")

      async def run(self, video: VideoInput) -> WhisperOutput:
          """Transcribe video."""
          video_obj = await run_remote(download_video)(video_input=video)
          audio = extract_audio(video=video_obj)
          transcription = await self.asr_handle.transcribe(audio=audio)
          return transcription
  ```



  AanaSDK is the main class that you use to build your application. It allows you to deploy the deployments and endpoints you defined and start the application.

  For example, you can define an application that transcribes a video like this:

  ```python
  aana_app = AanaSDK(name="transcribe_video_app")

  aana_app.register_deployment(name="asr_deployment", instance=asr_deployment)
  aana_app.register_endpoint(
      name="transcribe_video",
      path="/video/transcribe",
      summary="Transcribe a video",
      endpoint_cls=TranscribeVideoEndpoint,
  )

  aana_app.connect()  # Connects to the Ray cluster or starts a new one.
  aana_app.migrate()  # Runs the migrations to create the database tables.
  aana_app.deploy()   # Deploys the application.
  ```

  All you need to do is define the deployments and endpoints you want to use in your application, and Aana SDK will take care of the rest.



  The [Serve Config Files](https://docs.ray.io/en/latest/serve/production-guide/config.html#serve-config-files) is the recommended way to deploy and update your applications in production. Aana SDK provides a way to build the Serve Config Files for the Aana applications. See the [Serve Config Files documentation](https://mobiusml.github.io/aana_sdk/pages/serve_config_files/) on how to build and deploy the applications using the Serve Config Files.




  You can deploy example applications using Docker. See the [documentation on how to run Aana SDK with Docker](https://mobiusml.github.io/aana_sdk/pages/docker/).



  For more information on how to use Aana SDK, see the [documentation](https://mobiusml.github.io/aana_sdk/).



  Aana SDK is licensed under the [Apache License 2.0](https://github.com/mobiusml/aana_sdk?tab=Apache-2.0-1-ov-file#readme). Commercial licensing options are also available.



  We welcome contributions from the community to enhance Aana SDK's functionality and usability. Feel free to open issues for bug reports, feature requests, or submit pull requests to contribute code improvements.

  Check out the [Development Documentation](https://mobiusml.github.io/aana_sdk/pages/code_overview/) for more information on how to contribute.

  We have adopted the [Contributor Covenant](https://www.contributor-covenant.org/) as our code of conduct.


pkgId: a0b85ec2bb9b0607435b9e53940308379b93bd78bd284ed611f82668ae591445
name: python-aanalytics2
arch: src
version: 0.4.2.post3
epoch: 0
release: 1
summary: Adobe Analytics API 2.0 and 1.4 python wrapper
url: https://github.com/pitchmuc/adobe-analytics-api-2.0
rpm_license: Apache License 2.0
rpm_group: Unspecified
rpm_buildhost: localhost
location_href: Packages/python-aanalytics2-0.4.2.post3-1.src.rpm
checksum_type: sha256
description:
  This is a python wrapper for the adobe analytics API 2.0.

  Most of the documentation for this API will be hosted at [datanalyst.info][1].\
  [Getting Started details on Github](./docs/getting_started.md).
  [Appendix for running on a server](./docs/authenticating_without_config_json.md)

  A documentation about the releases information can be found here : [aanalytics2 releases](./docs/releases.md)

  Functionalities that are covered :

  * Run a report statement
  * Retrieve Users
  * Retrieve Segments
  * Retrieve Metrics
  * Retrieve Dimensions
  * Retrieve Calculated Metrics
  * Retrieve Virtual Report Suites
  * Retrieve Virtual Report Suite Curated Components
  * Retrieve Tags
  * Retrieve Usage Logs from users
  * Retrieve Projects
  * Retrieve Scheduled Jobs / Projects
  * Update Segment
  * Update Calculated Metric
  * Update Tags
  * Update Project
  * Delete Segment
  * Delete CalculatedMetric
  * Delete VirtualReportSuite
  * Delete Project
  * Delete DateRange
  * Create a Project
  * Create a Scheduling job for a Workspace Project
  documentation on reporting [here](./docs/main.md)

  * Data Ingestion API from API 1.4
  * Bulk Data Insertion API
  documentation on ingestion APIs [here](./docs/ingestion.md)

  This module provide limited support for the 1.4 API.
  It basically wrapped your request with some internal module and you can pass your request path, method, parameters and / or data.
  More information in the [dedicated documentation for 1.4](./docs/legacyAnalytics.md)

  The `aanalytics2` module enables you to generate request dictionary for the getReport method easily.\
  You will have no need to go to the UI in order to create a report template JSON anymore.\
  Do it automatically from the python interface.
  More information on the [`RequestCreator` documentation](./docs/requestCreator.md)

  There is a feature to retrieve the Workspace projects and the components used.\
  Refer to this [documentation on Project](./docs/projects.md) for more information.

  In case you want to use the logging capability for your script.\
  You can look at the reference for this on the [logging documentation page](./docs/logging.md)

  To install the library with PIP use:
  ```cli
  pip install aanalytics2
  ```
  or
  ```cli
  python -m pip install --upgrade git+<https://github.com/pitchmuc/adobe_analytics_api_2.0.git#egg=aanalytics2>
  ```

  In order to use this API in python, you would need to have those libraries installed :
  * pandas
  * requests
  * json
  * PyJWT
  * PyJWT[crypto]
  * pathlib
  * dicttoxml
  * pytest

  A test support has been added with pytest.
  The complete documentation to run the test can be found here : [testing aanalytics2](./docs/test.md)

  You can find information about the Adobe Analytics API 2.0 here :
  * [https://adobedocs.github.io/analytics-2.0-apis][2]
  * [https://github.com/AdobeDocs/analytics-2.0-apis/blob/master/reporting-guide.md][3]
  [1]: https://www.datanalyst.info
  [2]: https://adobedocs.github.io/analytics-2.0-apis
  [3]: https://github.com/AdobeDocs/analytics-2.0-apis/blob/master/reporting-guide.md


pkgId: d1f3beec7dd39fb2246740e201ac41164cb8561760fd1fd02b325d835be7dfdd
name: python-aanalyticsact
arch: src
version: 0.0.1.47
epoch: 0
release: 1
summary: adobe analytics library for Team ACT
url: https://github.com/SunkyeongLee/aanalyticsact
rpm_license: MIT License
rpm_group: Unspecified
rpm_buildhost: localhost
location_href: Packages/python-aanalyticsact-0.0.1.47-1.src.rpm
checksum_type: sha256
description:
  This module has been built to provide a better environment specifically for adobe analysts in Team ACT.</br></br>
  This module itself would not contain any confidential information & nor is incapable of retrieving any data unless the correct API credential is given.
  The guide of pulling data will be only provided internally, no inquires will be accepted from outsiders.

  * Retrieve Daily, Weekly, Monthly data and automatically dumps into the DB connected in their local machine.
  * Capable up to 2nd breakdown.
  * Automatically retrieves data of all Reporting Suites.
  * Update Segments
  * Create Segments
  More functionalities will be added in sooner time.<br/><br/>


pkgId: c82fcb3663b3c7806acecdb013ccdee53bec64c0eb2e81b868ecbf4058490362
name: python-aaopto-aotf
arch: src
version: 0.0.11
epoch: 0
release: 1
summary: Python driver for AA OptoElectronics AOTF device.
url: https://pypi.org/project/aaopto-aotf/
rpm_license: MIT
rpm_group: Unspecified
rpm_buildhost: localhost
location_href: Packages/python-aaopto-aotf-0.0.11-1.src.rpm
checksum_type: sha256
description:
  [![License](https://img.shields.io/badge/license-MIT-brightgreen)](LICENSE)

  python driver to control [MPDSnCxx AOTF devices](http://www.aaoptoelectronic.com/our-products/multi-channels-drivers-for-polychromatic-modulators/).



  To install this package from [PyPI](https://pypi.org/project/aaopto-aotf/), invoke: `pip install aaopto-aotf`

  To install this package from the Github in editable mode, from this directory invoke: `pip install -e .`

  To install this package in editable mode with dependencies for building the docs, invoke: `pip install -e .[dev]`


  ````python
  from aaopto_aotf.aotf import MPDS

  aotf = MPDS("COM3")
  ````

  Before writing values, you must first set the global blanking mode, and each channel's frequency, mode, and whether it is driven by external input or internal (software controlled) input.
  ````python
  from aaopto_aotf.aotf import MPDS, MAX_POWER_DBM
  from aaopto_aotf.device_codes import DriverMode, BlankingMode, VoltageRange

  aotf.set_blanking(BlankingMode.INTERNAL)  # disable blanking control from external input pin.
  aotf.set_external_input_voltage_range(VoltageRange.ZERO_TO_FIVE_VOLTS)


  for channel in range(1, aotf.num_channels + 1):
      aotf.set_frequency(channel, 110.5)
      aotf.set_driver_mode(DriverMode.EXTERNAL)
  ````

  If the driver mode is set to `DriverMode.EXTERNAL`, the device will take its output setpoint from the external input pin.

  If set to `DriverMode.INTERNAL`, you can control the output with software settings:
  ````python
  for channel in range(1, aotf.num_channels + 1):
      aotf.set_driver_mode(DriverMode.INTERNAL)
      aotf.set_power_dbm(channel, MAX_POWER_DBM)
      aotf.enable_channel(channel)
  ````
  Note that internal mode only enables a simple "On/Off" control scheme, and does not support linear scaling like external mode does vial the external analog input.

  At this point, you might want to save the values set above to the current profile.
  ````python
  aotf.save_profile()  # Now, calling an aotf.reset() will start with the saved settings.
  ````


  Here are the minor dangling features that are not implemented.
  * changing laser channel profiles at runtime. (These must be changed with the external input pins.)
  * automatic sweeping mode
      * automatic self-sweeping is a somewhat out-of-the-ordinary feature for most users.


  Have a look at the examples folder to see other examples and make use of a [useful calibration script](https://github.com/AllenNeuralDynamics/aaopto-aotf/blob/main/examples/calibration_sweep.py).


pkgId: f244b3d50e201e9413f757153c7025833cead3c1c5a73184fd0d5d5d82998196
name: python-aapns
arch: src
version: 23.7
epoch: 0
release: 1
summary: Asynchronous Apple Push Notification Service Client
url: https://github.com/HENNGE/aapns
rpm_license: Apache-2.0
rpm_group: Unspecified
rpm_buildhost: localhost
location_href: Packages/python-aapns-23.7-1.src.rpm
checksum_type: sha256
description:
  [![CircleCI](https://circleci.com/gh/HENNGE/aapns.svg?style=svg)](https://circleci.com/gh/HENNGE/aapns)
  [![Documentation Status](https://readthedocs.org/projects/aapns/badge/?version=latest)](http://aapns.readthedocs.io/en/latest/?badge=latest)

  Asynchronous Apple Push Notification Service client.

  * Requires TLS 1.2 or better
  * Requires Python 3.8 or better



  ```python
  from aapns.api import Server
  from aapns.config import Priority
  from aapns.models import Notification, Alert, Localized

  async def send_hello_world():
      client = await Server.production('/path/to/push/cert.pem').create_client()
      apns_id = await client.send_notification(
          'my-device-token',
          Notification(
              alert=Alert(
                  body=Localized(
                      key='Hello World!',
                      args=['foo', 'bar']
                  ),
              ),
              badge=42
          ),
          priority=Priority.immediately
      )
      print(f'Sent push notification with ID {apns_id}')
      await client.close()
  ```


pkgId: 6d2a8fc00ec0a935580da8a0fa92e7649a3c9b29cc3516d537884959536bafa1
name: python-aar-doc
arch: src
version: 2.0.1
epoch: 0
release: 1
summary: A tool for generating docs for Ansible roles
url: https://github.com/telekom-mms/aar_doc/
rpm_license: MIT
rpm_group: Unspecified
rpm_buildhost: localhost
location_href: Packages/python-aar-doc-2.0.1-1.src.rpm
checksum_type: sha256
description:
  output_file: ROLE.md
  output_mode: replace
  ```

  The defaults are written to the `defaults/main.yml` file in your provided role.
  If you want to write them to a different file under `defaults/` you can specify that file via the `--output-file` option.
  If your `argument_specs` contains an option with a default value multiple times, it will use the first found value and description by default. If you want the value and description to be overwritten, you can use the `--overwrite-duplicates` option.


  The `inject` mode will inject only the changed content in between the `BEGIN_ANSIBLE_DOCS` and `END_ANSIBLE_DOCS` markers. This makes it possible to have header and footer text in the file that is not touched. This is the default mode, and will revert to `replace` if the file does not exist to create it the first time.
  The `replace` mode will replace the whole file with the template. Usually, the `inject` mode should be fine for regular usage and changing the mode is not necessary unless you want to overwrite an existing file.

  You can override the `--output-template` used for rendering the document. This may be passed in as a string containing Jinja2, or a path to a file. As noted above, this option may be passed in via CLI or the configuration file.
  In the configuration file, easiest is to do a multiline string:


pkgId: 6f834ddaf424ae5015129042d69b76bbbaed2ea0a7f8eb635e299e448788f975
name: python-aaransia
arch: src
version: 1.1
epoch: 0
release: 1
summary: Languages and Dialects transliteration
url: https://github.com/3aransia/3aransia
rpm_license: Apache License 2.0
rpm_group: Unspecified
rpm_buildhost: localhost
location_href: Packages/python-aaransia-1.1-1.src.rpm
checksum_type: sha256
description:
  Transliteration of languages and dialects

  [![Open Source Love](https://badges.frapsoft.com/os/v1/open-source.svg?v=102)](https://github.com/ellerbrock/open-source-badge/)
  [![License](https://img.shields.io/badge/License-Apache%202.0-blue.svg)](https://opensource.org/licenses/Apache-2.0)
  [![made-with-python](https://img.shields.io/badge/Made%20with-Python-1f425f.svg)](https://www.python.org/)
  ![GitHub last commit](https://img.shields.io/github/last-commit/google/skia.svg)



  For contribution you can refer to [CONTRIBUTING.md](CONTRIBUTING.md)



  - Fast and reliable - it uses default variables to access data
  - Bulk transliteration
  - API available
  - Multilanguage transliteration available
  - 70 languages and dialects supportted



  ```
  1. Afrikaans	    2. Algerian	        3. Arabic
  4. Azerbaijani	    5. Bosnian	        6. Catalan
  7. Corsican	    8. Czech	        9. Welsh
  10. Danish	    11. German	        12. Greek
  13. English	    14. Esperanto       15. Spanish
  16. Estonian	    17. Basque	        18. Persian
  19. Finnish	    20. French	        21. Frisian
  22. Irish	    23. Gaelic	        24. Galician
  25. Hausa	    26. Croatian	27. Creole
  28. Hungarian	    29. Hawaiian	30. Indonesian
  31. Igbo	    32. Icelandic	33. Italian
  34. Kinyarwanda	    35. Kurdish	        36. Latin
  37. Libyan	    38. Lithuanian	39. Luxembourgish
  40. Latvian	    41. Moroccan	42. Malagasy
  43. Maori	    44. Malay	        45. Maltese
  46. Dutch	    47. Norwegian	48. Polish
  49. Portuguese	    50. Romanian	51. Samoan
  52. Shona	    53. Slovak	        54. Slovenian
  55. Somali	    56. Albanian	57. Sesotho
  58. Sundanese	    59. Swedish	        60. Swahili
  61. Filipino	    62. Tunisian	63. Turkish
  64. Turkmen	    65. Urdu	        66. Uzbek
  67. Vietnamese	    68. Xhosa	        69. Yoruba
  70. Zulu
  ```



  ```pip install aaransia```





  ```python
  ARABIC_SENTENCE = "كتب بلعربيا هنايا شحال ما بغيتي"

  print(transliterate(ARABIC_SENTENCE, source='ar', target='ma'))
  ```

  ```
  >>> ktb bl3rbya hnaya ch7al ma bghiti
  ```


  ```python
  from aaransia import SourceLanguageError

  MOROCCAN_ARABIC_SENTENCE = "ktb بلعربيا hnaya شحال ما بغيتي"

  try:
      print(transliterate(MOROCCAN_ARABIC_SENTENCE, source='ar', target='ma'))
  except SourceLanguageError as source_language_error:
      print(source_language_error)

  print(transliterate(MOROCCAN_ARABIC_SENTENCE, source='ar', target='ma', universal=True))
  print(transliterate(MOROCCAN_ARABIC_SENTENCE, source='ma', target='ar', universal=True))
  ```

  ```
  >>> Source alphabet language doesn't match the input text: ar
  >>> ktb bl3rbya hnaya chhal ma bghyty
  >>> كتب بلعربيا هنايا شحال ما بغيتي
  ```



  ```python
  from aaransia import get_alphabets_codes

  print(len(get_alphabets_codes()))
  print(get_alphabets_codes())
  ```

  ```
  >>> 70
  >>> ['ar', 'af', 'sq', 'al', 'az', 'eu', 'bo', 'ca', 'co', 'hr', 'cs', 'da',
   'nl', 'en', 'eo', 'et', 'tl', 'fi', 'fr', 'fs', 'gl', 'de', 'ht', 'ha', 'hw',
   'hu', 'is', 'ig', 'id', 'ga', 'it', 'ki', 'ku', 'la', 'lv', 'li', 'lt', 'lu',
   'ma', 'mg', 'ms', 'mt', 'mo', 'no', 'pl', 'pt', 'ro', 'sa', 'gc', 'el',
   'ss', 'sh', 'sk', 'sl', 'so', 'es', 'su', 'sw', 'sv', 'tn', 'tr', 'tu',
   'uz', 'vi', 'cy', 'xh', 'yo', 'zu', 'fa', 'ur']
  ```



  ```python
  from aaransia import get_alphabets

  print(get_alphabets())
  ```

  ```
  >>> {
  >>>     'af': 'Afrikaans Alphabet',
  >>>     'al': 'Algerian Alphabet',
  >>>     'ar': 'Arabic Alphabet',
  >>>     'az': 'Azerbaijani Alphabet',
  >>>     'bo': 'Bosnian Alphabet',
  >>>     'ca': 'Catalan Alphabet',
  >>>     'co': 'Corsican Alphabet',
  >>>     'cs': 'Czech Alphabet',
  >>>     'cy': 'Welsh Alphabet',
  >>>     'da': 'Danish Alphabet',
  >>>     'de': 'German Alphabet',
  >>>     'el': 'Greek Alphabet',
  >>>     'en': 'English Alphabet',
  >>>     'eo': 'Esperanto Alphabet',
  >>>     'es': 'Spanish Alphabet',
  >>>     'et': 'Estonian Alphabet',
  >>>     'eu': 'Basque Alphabet',
  >>>     'fa': 'Persian Alphabet',
  >>>     'fi': 'Finnish Alphabet',
  >>>     'fr': 'French Alphabet',
  >>>     'fs': 'Frisian Alphabet',
  >>>     'ga': 'Irish Alphabet',
  >>>     'gc': 'Gaelic Alphabet',
  >>>     'gl': 'Galician Alphabet',
  >>>     'ha': 'Hausa Alphabet',
  >>>     'hr': 'Croatian Alphabet',
  >>>     'ht': 'Creole Alphabet',
  >>>     'hu': 'Hungarian Alphabet',
  >>>     'hw': 'Hawaiian Alphabet',
  >>>     'id': 'Indonesian Alphabet',
  >>>     'ig': 'Igbo Alphabet',
  >>>     'is': 'Icelandic Alphabet',
  >>>     'it': 'Italian Alphabet',
  >>>     'ki': 'Kinyarwanda Alphabet',
  >>>     'ku': 'Kurdish Alphabet',
  >>>     'la': 'Latin Alphabet',
  >>>     'li': 'Libyan Alphabet',
  >>>     'lt': 'Lithuanian Alphabet',
  >>>     'lu': 'Luxembourgish Alphabet',
  >>>     'lv': 'Latvian Alphabet',
  >>>     'ma': 'Moroccan Alphabet',
  >>>     'mg': 'Malagasy Alphabet',
  >>>     'mo': 'Maori Alphabet',
  >>>     'ms': 'Malay Alphabet',
  >>>     'mt': 'Maltese Alphabet',
  >>>     'nl': 'Dutch Alphabet',
  >>>     'no': 'Norwegian Alphabet',
  >>>     'pl': 'Polish Alphabet',
  >>>     'pt': 'Portuguese Alphabet',
  >>>     'ro': 'Romanian Alphabet',
  >>>     'sa': 'Samoan Alphabet',
  >>>     'sh': 'Shona Alphabet',
  >>>     'sk': 'Slovak Alphabet',
  >>>     'sl': 'Slovenian Alphabet',
  >>>     'so': 'Somali Alphabet',
  >>>     'sq': 'Albanian Alphabet',
  >>>     'ss': 'Sesotho Alphabet',
  >>>     'su': 'Sundanese Alphabet',
  >>>     'sv': 'Swedish Alphabet',
  >>>     'sw': 'Swahili Alphabet',
  >>>     'tl': 'Filipino Alphabet',
  >>>     'tn': 'Tunisian Alphabet',
  >>>     'tr': 'Turkish Alphabet',
  >>>     'tu': 'Turkmen Alphabet',
  >>>     'ur': 'Urdu Alphabet',
  >>>     'uz': 'Uzbek Alphabet',
  >>>     'vi': 'Vietnamese Alphabet',
  >>>     'xh': 'Xhosa Alphabet',
  >>>     'yo': 'Yoruba Alphabet',
  >>>     'zu': 'Zulu Alphabet'
  >>> }
  ```



  1. Add it to the [alphabet](aaransia/data/alphabet.csv) CSV file
  2. Generate the whole alphabet with the ```construct_alphabet``` function from [data.py](aaransia/data/data.py)
  3. Update the [defaults.py](aaransia/defaults.py) (the order the to be respected)
     1. Add the alphabet code
     2. Add the alphabet name
     3. Add both of them to the alphabet dictionary
     4. Add the double letters if there are any
  4. Test a text with the language just added against all other languages in [test.py](aaransia/test.py)
     1. Add a language text to test in [text_samples](aaransia/text_samples.py) (the order is to be respected)
     2. Add test handling for the new language
     3. Test it by using the command ```python -m unittest discover -s aaransia``` from the [3aransia](./) repository
     4. Fix the bugs
  5. Validate it semantically and phonetically
  6. Make a pull request
  7. Wait for the PR confirmation and add your name to the collaborators



  - ```pylint``` code before doing a PR
  - Contribution can also be made through adding issues



  - [3aransia.api](https://3aransia.github.io/3aransia.api) The api of 3aransia
  - [3aransia.web](http://3aransia.com) The web application of 3aransia


pkgId: 4c678747a8ca43a9b134fd67f781b6b7628a54c9dc2e6c64df78dabd0a29ab9b
name: python-aarc-g002-entitlement
arch: src
version: 0.3.2
epoch: 0
release: 1
url: https://github.com/kit-scc/aarc-g002-entitlement
rpm_license: MIT
rpm_group: Unspecified
rpm_buildhost: localhost
location_href: Packages/python-aarc-g002-entitlement-0.3.2-1.src.rpm
checksum_type: sha256
summary:
  Parse and compare entitlements according to the AARC-G002 recommendation (https://aarc-community.org/guidelines/aarc-g002)

description:
  [![Documentation Status](https://readthedocs.org/projects/aarc-g002-entitlement/badge/?version=latest&token=5f5165c8ebde7726ae9df9f62331a59e7344d6e61a4bb9ea8c97cecfae25f4f3)](https://aarc-g002-entitlement.readthedocs.io/en/latest/?badge=latest)



  The newer [AarcEntitlement](https://github.com/KIT-SCC/AarcEntitlement)
  supports AARC-G002 and the updated version AARC-G069.




  This package provides a python Class to parse and compare entitlements according
  to the AARC-G002 Recommendation https://aarc-community.org/guidelines/aarc-g002.




  ```python
  from aarc_g002_entitlement import Aarc_g002_entitlement

  required = Aarc_g002_entitlement(
      'urn:geant:h-df.de:group:aai-admin',
      strict=False)
  actual = Aarc_g002_entitlement(
      'urn:geant:h-df.de:group:aai-admin:role=member#backupserver.used.for.developmt.de')


  permitted = required.is_contained_in(actual) # True in this case


  equals = required == actual # False in this case
  ```

  For more examples: `./example.py`


  ```
  pip --user install aarc-g002-entitlement
  ```


  ```
  tox -e docs
  ```
  After this, the documentation should be located at `doc/build/index.html`.

  Documentation is also available at [Readthedocs](https://aarc-g002-entitlement.readthedocs.io/en/latest)


  Run tests for all supported python versions
  ```
  tox
  ```


  The AARC project has received funding from the European Union’s Horizon
  2020 research and innovation programme under grant agreement No 653965 and
  730941.


pkgId: 6d3c933e0044ca8cd71c8c010c1940dbd037177106fa158853d5f27723f7f9a9
name: python-aars
arch: src
version: 0.7.5
epoch: 0
release: 1
summary: Experimental Object-Document-Mapper using pydantic to store objects on Aleph.im
url: https://github.com/aleph-im/active-record-sdk
rpm_license: MIT License
rpm_group: Unspecified
rpm_buildhost: localhost
location_href: Packages/python-aars-0.7.5-1.src.rpm
checksum_type: sha256
description:
  AARS is a powerful and flexible Python library built on top of the Aleph decentralized storage network, designed to help you build better backends for your decentralized applications. It provides an easy-to-use interface for managing and querying your data, with a focus on performance and versatility.


  - Asynchronous, high-performance data storage and retrieval
  - Customizable schema with support for different data types
  - Indexing for efficient querying
  - Revision history tracking for records
  - Support for forgetting data (GDPR compliant)
  - Built-in pagination for large result sets


  Install AARS using pip:

  ```shell
  pip install aars
  ```


  To get started with AARS, you will need to define your data schema by creating classes that inherit from Record. These classes represent the objects you want to store and query on the Aleph network.

  Here's an example of how you can implement a simple social media platform, that we'll call "Chirper":

  ```python
  from src.aars import Record

  class User(Record):
      username: str
      bio: str

  class Chirp(Record):
      author: User
      content: str
      likes: int
      timestamp: int
  ```
  In this example, we have a User class representing a user of Chirper, and a Chirp class representing a user's message. Now, let's create some indices to make querying our data more efficient:

  ```python
  from src.aars import Index

  Index(User, 'username')
  Index(Chirp, 'author')
  Index(Chirp, 'timestamp')
  ```
  With the schema defined and indices created, we only need to initialize an AARS session:

  ```python
  from src.aars import AARS

  AARS()
  ```
  It is enough to call the constructor once, and it will automatically initialize the session with the default settings.

  We can now perform various operations, such as creating new records, querying records, and updating records:

  ```python
  import time


  new_user = await User(username='chirpy_user', display_name='Chirpy User', bio='I love chirping!').save()


  new_chirp = await Chirp(author=new_user, content='Hello, Chirper!', likes=0, timestamp=int(time.time())).save()


  chirps_by_author = await Chirp.filter(author=new_user).all()


  new_chirp.likes += 1
  updated_chirp = await new_chirp.save()
  ```


  For detailed documentation, including advanced features such as revision history, forgetting data, and pagination,
  refer to the docs folder in the repository or [visit the official documentation website](https://aleph-im.github.io/active-record-sdk/).


  To build the documentation, you will need to install the dependencies listed in the requirements.txt and docs-requirements.txt. Then, run the following command:

  ```shell
  mkdocs build
  ```

  You can serve the documentation locally by running the following command:

  ```shell
  mkdocs serve
  ```


  Contributions to AARS are welcome! If you have found a bug, want to suggest an improvement, or have a question, feel free to open an issue on the GitHub repository.


  AARS is released under the [MIT License](https://github.com/aleph-im/active-record-sdk/blob/main/LICENSE).


pkgId: 76538c7966555bf8d1c7195aeb8859c2daa8bbb934bbdc077e5b7c19eef63127
name: python-aas-middleware
arch: src
version: 0.2.0
epoch: 0
release: 1
summary: please add a summary manually as the author left a blank one
url: https://pypi.org/project/aas-middleware/
rpm_license: None
rpm_group: Unspecified
rpm_buildhost: localhost
location_href: Packages/python-aas-middleware-0.2.0-1.src.rpm
checksum_type: sha256
description:
  ![aas-middleware logo](https://raw.githubusercontent.com/sdm4fzi/aas_middleware/main/docs/logos/aas_middleware_logo_light_letters.svg)

  *Framework for industrial data integration and automation.*

  ![Build-sucess](https://img.shields.io/badge/build-success-green)
  ![PyPI](https://img.shields.io/pypi/v/aas_middleware)
  ![PyPI - Python Version](https://img.shields.io/pypi/pyversions/aas_middleware)
  ![Docu](https://img.shields.io/badge/docu-WIP-yellow)
  [![DOI](https://zenodo.org/badge/830680867.svg)](https://zenodo.org/doi/10.5281/zenodo.12786362)
  [![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)

  aas-middleware has the goal to make information flow and orchestration in industrial environments easier and more automated. To do so, it is build upon three concepts: well defined data models and interfaces, connectors and workflows. The data models are used to define the structure of the data that is exchanged between different systems. The connectors are used to connect the data models to technologically different data sources and sinks. Workflows are used to define the orchestration of the data flow between different systems.

  aas-middleware uses modern api technologies (Rest or GraphQL) to make it easy to access the integrated data models or exchange data with low-level sensors and actuators. The middleware can be used to integrate different systems in the industrial environment, such as MES, ERP, SCADA, PLC, sensors, actuators and asset administration shells. By the modular and extensible design of aas-middleware, it can be used from small use cases, such as streaming sensor values, to large integrations and workflows for automated production planning and control.

  For more information how to use the aas-middleware, read the getting started below or refer to the [documentation](https://sdm4fzi.github.io/aas_middleware/) of the package.



  To install the package, run the following command in the terminal:

  ```bash
  pip install aas-middleware
  ```

  To install the package with extras for industrial data integration (OPC UA and MQTT), run the following command in the terminal:

  ```bash
  pip install aas-middleware[industrial]
  ```

  Alternatively, you can install the package with [poetry](https://python-poetry.org/) for development:

  ```bash
  poetry shell
  poetry install
  ```

  Please note that the package is only compatible with Python 3.10 or higher.




  In the following, we will consider a minimal example to demonstrate the usage of the package. The example is also available in the [examples](https://github.com/sdm4fzi/aas_middleware/blob/main/examples/minimal_example.py) of the repository and consists of defining a simple asset administration shell based data model to describe a product, serializing this data model to asset administration shells, making the data model available with rest API and defining examplary connectors and workflows.

  For further examples, like connecting the data model to a data source, or creating workflows, refer to the tutorials in the [documentation](https://sdm4fzi.github.io/aas_middleware/).



  At first, we create a simple data model with the basic building blocks of the aas meta model:

  ```python
  import typing
  import aas_middleware

  class BillOfMaterialInfo(aas_middleware.SubmodelElementCollection):
      manufacterer: str
      product_type: str

  class BillOfMaterial(aas_middleware.Submodel):
      components: typing.List[str]
      bill_of_material_info: BillOfMaterialInfo


  class ProcessModel(aas_middleware.Submodel):
      processes: typing.List[str]


  class Product(aas_middleware.AAS):
      bill_of_material: BillOfMaterial
      process_model: typing.Optional[ProcessModel]
  ```

  The data model consists of a product that has a process model and a bill of material. The process model and the bill of material are contain a list of processes and components, respectively. Note, that the aas-middleware can also use data models that are not compliant with the aas meta model. However, some features, such as storing the data model in a basyx aas server, requires that the data model can be translated to the aas meta model.

  To be able to instantiate an data model, we create an instance of the Product:

  ```python
  example_product = Product(
      id="example_product_id",
      id_short="example_product_id",
      description="Example Product",
      bill_of_material=BillOfMaterial(
          id="example_bom_id",
          id_short="example_bom_id",
          description="Example Bill of Material",
          components=["component_1", "component_2"],
          bill_of_material_info=BillOfMaterialInfo(
              id="example_bom_info_id",
              id_short="example_bom_info_id",
              description="Example Bill of Material Info",
              manufacterer="Example Manufacterer",
              product_type="Example Product Type",
          ),
      ),
      process_model=ProcessModel(
          id="example_process_model_id",
          id_short="example_process_model_id",
          description="Example Process Model",
          processes=["process_1", "process_2"],
      ),
  )
  ```


  With this instance of the product, we can create a DataModel.


  ```python
  data_model = aas_middleware.DataModel.from_models(example_product)
  ```


  The data model is a container for instances and types of data models. It makes access to individual objects easy and allows for formatting. E.g. we can easily transform the data model to either aas components of the [basyx python sdk](https://github.com/eclipse-basyx/basyx-python-sdk):

  ```python
  basyx_object_store = aas_middleware.formatting.BasyxFormatter().serialize(data_model)
  ```

  Or serialize it to a JSON-serialized asset administration shell according to the official [specification of the asset administration shell ](https://industrialdigitaltwin.org/content-hub/aasspecifications):

  ```python
  formatter = aas_middleware.formatting.aasJsonFormatter()
  json_aas = formatter.serialize(data_model)
  print(json_aas)
  ```


  This formatting transformation can also be reversed, so JSON-serialized or Basyx aas can be used to create data models.




  To start the aas-middleware and make our data model available through a rest API, we need to create an instance of the middleware and load the data model:

  ```python
  middleware = aas_middleware.Middleware()
  middleware.load_data_model("example", data_model, persist_instances=True)
  middleware.generate_rest_api_for_data_model("example")

  if __name__ == "__main__":
      import uvicorn
      uvicorn.run(middleware.app)
  ```

  With the option `persist_instances=True`, the middleware stores the instances of the data model in its internal memory. Moreover, a CRUD (create, read, update, delete) rest API is generated for the data model with the `generate_rest_api_for_data_model` function.

  Under the hood, the aas-middleware uses the [fastapi](https://fastapi.tiangolo.com/) framework to generate the rest API. Therefore, we get an openAPI specification of this API under `http://localhost:8000/docs`. The data model can be accessed via the API with the following curl command:

  ``` bash
  curl -X 'GET' \
    'http://127.0.0.1:8000/Product/' \
    -H 'accept: application/json'
  ```

  We can also instantiate new product data models with post requests:

  ``` bash
  curl -X 'POST' \
    'http://127.0.0.1:8000/Product/' \
    -H 'accept: application/json' \
    -H 'Content-Type: application/json' \
    -d '{
    "id_short": "product2",
    "description": "",
    "id": "product2",
    "bill_of_material": {
      "id_short": "product2_bom",
      "description": "",
      "id": "product2_bom",
      "semantic_id": "",
      "components": [
        "bearing", "screw"
      ],
      "bill_of_material_info": {
        "id_short": "product2_bom_info",
        "description": "",
        "semantic_id": "",
        "manufacterer": "other manufacturer",
        "product_type": "wheel"
      }
    },
    "process_model": {
      "id_short": "product2_process_model",
      "description": "",
      "id": "product2_process_model",
      "semantic_id": "",
      "processes": [
        "assembly"
      ]
    }
  }'
  ```
   Besides a rest API, aas-middleware also provides a GraphQL API. To make a data model available via the GraphQL API, use the `generate_graphql_api_for_data_model` function.

  ```python
  middleware.generate_graphql_api_for_data_model("example")
  ```

   The GraphQL API can be accessed under `http://localhost:8000/graphql`, where also find the GraphiQL Playground for testing. Some fields of the instances of the product data model can be accessed via the API with the following curl command:

  ``` bash
  curl 'http://127.0.0.1:8000/graphql/?' \
    -H 'Accept: application/json' \
    -H 'Content-Type: application/json' \
    --data-raw '{"query":"{\n  Product {\n    idShort\n    billOfMaterial {\n      components\n    }\n  }\n}"}'
  ```

  You probably saw during the startup of the middleware a warning log message like:

  ```
  WARNING:aas_middleware.middleware.registries:No persistence factory found for data_model_name='example' model_id=None contained_model_id=None field_id=None. Using default persistence factory.
  ```

  This message indicates that the aas-middleware has no specified persistence factory and stores the data model in internal storage. Besides internal storage, the aas-middleware can utilize different persistence mechanisms. For now, aas-middleware supports the storage of the data model in a basyx aas server (mongo db will come later).

  Running the middleware with persistent storage of the data model in a basyx aas server can be done by interchanging the default `Middleware` with the `AasMiddleware`:

  ```python
  middleware = aas_middleware.AasMiddleware()
  middleware.load_aas_persistent_data_model(
      "example", data_model, "localhost", 8081, "localhost", 8081, persist_instances=True
  )
  middleware.generate_rest_api_for_data_model("example")

  if __name__ == "__main__":
      import uvicorn
      uvicorn.run(middleware.app)
  ```

  Note, that on port 8081 a aas repository and submodel repository need to be running, e.g. a [basyx java server](https://github.com/eclipse-basyx/basyx-java-server-sdk). The repository already comes with a [docker-compose file](https://github.com/sdm4fzi/aas_middleware/blob/main/docker/docker-compose-dev.yaml) that can be used to start the AAS and Submodel-server. To start the servers with the linked compose file, run the following command in the terminal:

  ```bash
  docker-compose -f docker-compose-dev.yaml up
  ```

  The created rest API can be accessed in the same way as before.



  A connector in the aas-middleware is a component that makes a connector to a data source (provider) or a data sink (consumer). The aas-middleware comes with a lot of default connectors (OPC UA, MQTT, http client and server, websocket client and server, webhook), but you can add custom ones. A connector only needs to specify a certain [interface](https://github.com/sdm4fzi/aas_middleware/blob/main/aas_middleware/connect/connectors/connector.py), that consists of a connect, disconnect, consume and provide function. We define an examplary connector like this and add it to the middleware:

  ``` python
  class TrivialConnector:
      def __init__(self):
          pass

      async def connect(self):
          pass

      async def disconnect(self):
          pass

      async def consume(self, body: str) -> None:
          print(body)
          pass

      async def provide(self) -> typing.Any:
          return "trivial connector example value"

  example_connector = TrivialConnector()
  middleware.add_connector("test_connector", example_connector, model_type=str)
  ```

  We can execute this connector either for reading values with the folling get request:

  ``` bash
  curl -X 'GET' \
    'http://127.0.0.1:8000/connectors/test_connector/value' \
    -H 'accept: application/json'
  ```

  Or send data with the connector to the data sink:

  ``` bash
  curl -X 'POST' \
    'http://127.0.0.1:8000/connectors/test_connector/value?value=connector_example_input_value' \
    -H 'accept: application/json' \
    -d ''
  ```

  Lastly, we can define workflows for more complex automation tasks. A workflow is a function that can be executed via the API the middleware:

  ``` python
  @middleware.workflow()
  def example_workflow(a: str) -> str:
      print(a)
      return a
  ```

  To run the workflow, execute the following request:

  ``` bash
  curl -X 'POST' \
    'http://127.0.0.1:8000/workflows/example_workflow/execute?arg=work_flow_input_value' \
    -H 'accept: application/json' \
    -d ''
  ```

  We can also interrupt the workflow, when it is running:

  ``` bash
  curl -X 'GET' \
    'http://127.0.0.1:8000/workflows/example_workflow/interrupt' \
    -H 'accept: application/json'
  ```

  The contents above only demostrate the most fundamental features of the aas-middleware. For more advanced features, like connecting this fundametals for automated information flow in a production environment, refer to the [documentation](https://sdm4fzi.github.io/aas_middleware/).



  `aas-middleware` is a new project and has therefore much room for improvement. Therefore, it would be a pleasure to get feedback or support! If you want to contribute to the package, either create issues on [aas-middlweware github page](https://github.com/sdm4fzi/aas_middleware) for discussing new features or contact me directly via [github](https://github.com/SebBehrendt) or [email](mailto:sebastian.behrendt@kit.edu).



  The package is licensed under the [MIT license](LICENSE).



  We extend our sincere thanks to the German Federal Ministry for Economic Affairs and Climate Action
  (BMWK) for supporting this research project 13IK001ZF “Software-Defined Manufacturing for the
  automotive and supplying industry [https://www.sdm4fzi.de/](https://www.sdm4fzi.de/).


pkgId: 752fc8938ff02923a42d90843738ffee954dad84c85c74295d4443be80719830
name: python-aas-middleware
arch: src
version: 0.2.2
epoch: 0
release: 1
summary: please add a summary manually as the author left a blank one
url: https://pypi.org/project/aas-middleware/
rpm_license: None
rpm_group: Unspecified
rpm_buildhost: localhost
location_href: Packages/python-aas-middleware-0.2.2-1.src.rpm
checksum_type: sha256
description:
  ![aas-middleware logo](https://raw.githubusercontent.com/sdm4fzi/aas_middleware/main/docs/logos/aas_middleware_logo_light_letters.svg)

  *Framework for industrial data integration and automation.*

  ![Build-sucess](https://img.shields.io/badge/build-success-green)
  ![PyPI](https://img.shields.io/pypi/v/aas_middleware)
  ![PyPI - Python Version](https://img.shields.io/pypi/pyversions/aas_middleware)
  ![Docu](https://img.shields.io/badge/docu-WIP-yellow)
  [![DOI](https://zenodo.org/badge/830680867.svg)](https://zenodo.org/doi/10.5281/zenodo.12786362)
  [![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)

  aas-middleware has the goal to make information flow and orchestration in industrial environments easier and more automated. To do so, it is build upon three concepts: well defined data models, connectors, and, workflows. The data models are used to define the structure of the data that is exchanged between different systems. The connectors are used to connect the data models to technologically different data sources and sinks. Workflows are used to define the orchestration of the data flow between different systems, connectors, and, data models.

  aas-middleware uses modern api technologies (Rest or GraphQL) to make it easy to access the integrated data models or exchange data with low-level sensors and actuators. The middleware can be used to integrate different systems in the industrial environment, such as MES, ERP, SCADA, PLC, sensors, actuators and asset administration shells. By the modular and extensible design of aas-middleware, it can be used from small use cases, such as streaming sensor values, to large integrations and workflows for automated production planning and control.

  For more information how to use the aas-middleware, read the getting started below or refer to the [documentation](https://sdm4fzi.github.io/aas_middleware/) of the package.



  To install the package, run the following command in the terminal:

  ```bash
  pip install aas-middleware
  ```

  To install the package with extras for industrial data integration (OPC UA and MQTT), run the following command in the terminal:

  ```bash
  pip install aas-middleware[industrial]
  ```

  Alternatively, you can install the package with [poetry](https://python-poetry.org/) for development:

  ```bash
  poetry shell
  poetry install
  ```

  Please note that the package is only compatible with Python 3.10 or higher.




  In the following, we will consider a minimal example to demonstrate the usage of the package. The example is also available in the [examples](https://github.com/sdm4fzi/aas_middleware/blob/main/examples/minimal_example.py) of the repository and consists of defining a simple asset administration shell based data model to describe a product, serializing this data model to asset administration shells, making the data model available with rest API and defining examplary connectors and workflows.

  For further examples, like connecting the data model to a data source, or creating workflows, refer to the tutorials in the [documentation](https://sdm4fzi.github.io/aas_middleware/).



  At first, we create a simple data model with the basic building blocks of the aas meta model:

  ```python
  import typing
  import aas_middleware

  class BillOfMaterialInfo(aas_middleware.SubmodelElementCollection):
      manufacterer: str
      product_type: str

  class BillOfMaterial(aas_middleware.Submodel):
      components: typing.List[str]
      bill_of_material_info: BillOfMaterialInfo


  class ProcessModel(aas_middleware.Submodel):
      processes: typing.List[str]


  class Product(aas_middleware.AAS):
      bill_of_material: BillOfMaterial
      process_model: typing.Optional[ProcessModel]
  ```

  The data model consists of a product that has a process model and a bill of material. The process model and the bill of material are contain a list of processes and components, respectively. Note, that the aas-middleware can also use data models that are not compliant with the aas meta model. However, some features, such as storing the data model in a basyx aas server, requires that the data model can be translated to the aas meta model.

  To be able to instantiate an data model, we create an instance of the Product:

  ```python
  example_product = Product(
      id="example_product_id",
      id_short="example_product_id",
      description="Example Product",
      bill_of_material=BillOfMaterial(
          id="example_bom_id",
          id_short="example_bom_id",
          description="Example Bill of Material",
          components=["component_1", "component_2"],
          bill_of_material_info=BillOfMaterialInfo(
              id="example_bom_info_id",
              id_short="example_bom_info_id",
              description="Example Bill of Material Info",
              manufacterer="Example Manufacterer",
              product_type="Example Product Type",
          ),
      ),
      process_model=ProcessModel(
          id="example_process_model_id",
          id_short="example_process_model_id",
          description="Example Process Model",
          processes=["process_1", "process_2"],
      ),
  )
  ```


  With this instance of the product, we can create a DataModel.


  ```python
  data_model = aas_middleware.DataModel.from_models(example_product)
  ```


  The data model is a container for instances and types of data models. It makes access to individual objects easy and allows for formatting. E.g. we can easily transform the data model to either aas components of the [basyx python sdk](https://github.com/eclipse-basyx/basyx-python-sdk):

  ```python
  basyx_object_store = aas_middleware.formatting.BasyxFormatter().serialize(data_model)
  ```

  Or serialize it to a JSON-serialized asset administration shell according to the official [specification of the asset administration shell ](https://industrialdigitaltwin.org/content-hub/aasspecifications):

  ```python
  formatter = aas_middleware.formatting.aasJsonFormatter()
  json_aas = formatter.serialize(data_model)
  print(json_aas)
  ```


  This formatting transformation can also be reversed, so JSON-serialized or Basyx aas can be used to create data models.




  To start the aas-middleware and make our data model available through a rest API, we need to create an instance of the middleware and load the data model:

  ```python
  middleware = aas_middleware.Middleware()
  middleware.load_data_model("example", data_model, persist_instances=True)
  middleware.generate_rest_api_for_data_model("example")

  if __name__ == "__main__":
      import uvicorn
      uvicorn.run(middleware.app)
  ```

  With the option `persist_instances=True`, the middleware stores the instances of the data model in its internal memory. Moreover, a CRUD (create, read, update, delete) rest API is generated for the data model with the `generate_rest_api_for_data_model` function.

  Under the hood, the aas-middleware uses the [fastapi](https://fastapi.tiangolo.com/) framework to generate the rest API. Therefore, we get an openAPI specification of this API under `http://localhost:8000/docs`. The data model can be accessed via the API with the following curl command:

  ``` bash
  curl -X 'GET' \
    'http://127.0.0.1:8000/Product/' \
    -H 'accept: application/json'
  ```

  We can also instantiate new product data models with post requests:

  ``` bash
  curl -X 'POST' \
    'http://127.0.0.1:8000/Product/' \
    -H 'accept: application/json' \
    -H 'Content-Type: application/json' \
    -d '{
    "id_short": "product2",
    "description": "",
    "id": "product2",
    "bill_of_material": {
      "id_short": "product2_bom",
      "description": "",
      "id": "product2_bom",
      "semantic_id": "",
      "components": [
        "bearing", "screw"
      ],
      "bill_of_material_info": {
        "id_short": "product2_bom_info",
        "description": "",
        "semantic_id": "",
        "manufacterer": "other manufacturer",
        "product_type": "wheel"
      }
    },
    "process_model": {
      "id_short": "product2_process_model",
      "description": "",
      "id": "product2_process_model",
      "semantic_id": "",
      "processes": [
        "assembly"
      ]
    }
  }'
  ```
   Besides a rest API, aas-middleware also provides a GraphQL API. To make a data model available via the GraphQL API, use the `generate_graphql_api_for_data_model` function.

  ```python
  middleware.generate_graphql_api_for_data_model("example")
  ```

   The GraphQL API can be accessed under `http://localhost:8000/graphql`, where also find the GraphiQL Playground for testing. Some fields of the instances of the product data model can be accessed via the API with the following curl command:

  ``` bash
  curl 'http://127.0.0.1:8000/graphql/?' \
    -H 'Accept: application/json' \
    -H 'Content-Type: application/json' \
    --data-raw '{"query":"{\n  Product {\n    idShort\n    billOfMaterial {\n      components\n    }\n  }\n}"}'
  ```

  You probably saw during the startup of the middleware a warning log message like:

  ```
  WARNING:aas_middleware.middleware.registries:No persistence factory found for data_model_name='example' model_id=None contained_model_id=None field_id=None. Using default persistence factory.
  ```

  This message indicates that the aas-middleware has no specified persistence factory and stores the data model in internal storage. Besides internal storage, the aas-middleware can utilize different persistence mechanisms. For now, aas-middleware supports the storage of the data model in a basyx aas server (mongo db will come later).

  Running the middleware with persistent storage of the data model in a basyx aas server can be done by interchanging the default `Middleware` with the `AasMiddleware`:

  ```python
  middleware = aas_middleware.AasMiddleware()
  middleware.load_aas_persistent_data_model(
      "example", data_model, "localhost", 8081, "localhost", 8081, persist_instances=True
  )
  middleware.generate_rest_api_for_data_model("example")

  if __name__ == "__main__":
      import uvicorn
      uvicorn.run(middleware.app)
  ```

  Note, that on port 8081 a aas repository and submodel repository need to be running, e.g. a [basyx java server](https://github.com/eclipse-basyx/basyx-java-server-sdk). The repository already comes with a [docker-compose file](https://github.com/sdm4fzi/aas_middleware/blob/main/docker/docker-compose-dev.yaml) that can be used to start the AAS and Submodel-server. To start the servers with the linked compose file, run the following command in the terminal:

  ```bash
  docker-compose -f docker-compose-dev.yaml up
  ```

  The created rest API can be accessed in the same way as before.



  A connector in the aas-middleware is a component that makes a connector to a data source (provider) or a data sink (consumer). The aas-middleware comes with a lot of default connectors (OPC UA, MQTT, http client and server, websocket client and server, webhook), but you can add custom ones. A connector only needs to specify a certain [interface](https://github.com/sdm4fzi/aas_middleware/blob/main/aas_middleware/connect/connectors/connector.py), that consists of a connect, disconnect, consume and provide function. We define an examplary connector like this and add it to the middleware:

  ``` python
  class TrivialConnector:
      def __init__(self):
          pass

      async def connect(self):
          pass

      async def disconnect(self):
          pass

      async def consume(self, body: str) -> None:
          print(body)
          pass

      async def provide(self) -> typing.Any:
          return "trivial connector example value"

  example_connector = TrivialConnector()
  middleware.add_connector("test_connector", example_connector, model_type=str)
  ```

  We can execute this connector either for reading values with the folling get request:

  ``` bash
  curl -X 'GET' \
    'http://127.0.0.1:8000/connectors/test_connector/value' \
    -H 'accept: application/json'
  ```

  Or send data with the connector to the data sink:

  ``` bash
  curl -X 'POST' \
    'http://127.0.0.1:8000/connectors/test_connector/value?value=connector_example_input_value' \
    -H 'accept: application/json' \
    -d ''
  ```

  Lastly, we can define workflows for more complex automation tasks. A workflow is a function that can be executed via the API the middleware:

  ``` python
  @middleware.workflow()
  def example_workflow(a: str) -> str:
      print(a)
      return a
  ```

  To run the workflow, execute the following request:

  ``` bash
  curl -X 'POST' \
    'http://127.0.0.1:8000/workflows/example_workflow/execute?arg=work_flow_input_value' \
    -H 'accept: application/json' \
    -d ''
  ```

  We can also interrupt the workflow, when it is running:

  ``` bash
  curl -X 'GET' \
    'http://127.0.0.1:8000/workflows/example_workflow/interrupt' \
    -H 'accept: application/json'
  ```

  The contents above only demostrate the most fundamental features of the aas-middleware. For more advanced features, like connecting this fundametals for automated information flow in a production environment, refer to the [documentation](https://sdm4fzi.github.io/aas_middleware/).



  `aas-middleware` is a new project and has therefore much room for improvement. Therefore, it would be a pleasure to get feedback or support! If you want to contribute to the package, either create issues on [aas-middlweware github page](https://github.com/sdm4fzi/aas_middleware) for discussing new features or contact me directly via [github](https://github.com/SebBehrendt) or [email](mailto:sebastian.behrendt@kit.edu).



  The package is licensed under the [MIT license](LICENSE).



  We extend our sincere thanks to the German Federal Ministry for Economic Affairs and Climate Action
  (BMWK) for supporting this research project 13IK001ZF “Software-Defined Manufacturing for the
  automotive and supplying industry [https://www.sdm4fzi.de/](https://www.sdm4fzi.de/).


pkgId: 472d716e36b9fc2af6f43acfee7aa0b669c21157a65346586e68b2ece36ede04
name: python-aas-pydantic
arch: src
version: 0.1.0
epoch: 0
release: 1
url: https://pypi.org/project/aas-pydantic/
rpm_license: None
rpm_group: Unspecified
rpm_buildhost: localhost
location_href: Packages/python-aas-pydantic-0.1.0-1.src.rpm
checksum_type: sha256
summary:
  aas-pydantic is a package that combines the basyx python sdk for handling Asset Administration Shells (AAS) with pydantic Basemodels for fast and easy modeling and transformation of pydantic models and AAS.

description:
  ![Build-sucess](https://img.shields.io/badge/build-success-green)
  ![PyPI](https://img.shields.io/pypi/v/aas_pydantic)
  ![PyPI - Python Version](https://img.shields.io/pypi/pyversions/aas_pydantic)
  [![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)


  A Python package that combines the BaSyx Python SDK for handling Asset Administration Shells (AAS) with Pydantic models for fast and easy modeling and transformation of Industry 4.0 data structures.

  The package enables:

  - Creating AAS models using Pydantic's intuitive syntax
  - Converting between Pydantic models and BaSyx AAS instances
  - Converting IDTA submodel templates to Pydantic types and vice versa
  - Serialization to JSON/Schema formats for easy integrations with other tools




  You can install the package using pip:

  ```bash
  pip install aas-pydantic
  ```

  Note that the package requires python 3.10 or higher.



  The package provides a set of Pydantic models that can be used to create AAS models. The models are based on the BaSyx SDK and are designed to be easily converted to and from AAS instances.

  In the following example, we create a simple AAS of a Device with one Submodel DeviceConfig.

  ```python
  from typing import List, Set, Union
  from enum import Enum
  from aas_pydantic import AAS, Submodel, SubmodelElementCollection


  class StatusEnum(str, Enum):
      ACTIVE = "active"
      INACTIVE = "inactive"


  class DeviceProperties(SubmodelElementCollection):
      serial_number: str
      firmware_version: str
      status: StatusEnum
      temperature_sensors: List[str]
      config_params: Set[str]


  class DeviceConfig(Submodel):
      id_short: str
      description: str
      properties: DeviceProperties
      measurements: List[float]
      settings: Union[str, int]


  class DeviceAAS(AAS):
      device_info: DeviceConfig
  ```

  We also want to create an instance of this model, which we will use later:

  ```python
  device = DeviceAAS(
      id="device_1",
      description="Example device",
      device_info=DeviceConfig(
          id_short="device_1_config",
          description="Device 1 Configuration",
          properties=DeviceProperties(
              id_short="device_1_properties",
              serial_number="1234",
              firmware_version="1.0",
              status=StatusEnum.ACTIVE,
              temperature_sensors=["sensor_1", "sensor_2"],
              config_params={"param_1", "param_2"}
          ),
          measurements=[1.0, 2.0, 3.0],
          settings="default"
      )
  )
  ```



  The package provides methods for converting between Pydantic models and BaSyx models. This works both for pydantic types / basyx templates and instances.



  At first, we want to show an submodel template can be created from the modelled type:

  ```python
  submodel_template = aas_pydantic.convert_model_to_submodel_template(DeviceConfig)
  ```

  For inspection of the submodel template, we can serialize it to a file:

  ```python
  import basyx.aas.adapter.json

  with open("submodel_template_DeviceConfig.json", "w") as f:
      json_string = json.dumps(
          submodel_template,
          cls=basyx.aas.adapter.json.AASToJsonEncoder,
      )
      f.write(json_string)
  ```

  We can also convert a whole AAS type to a Basyx Object Store:

  ```python
  aas_template_objectstore = aas_pydantic.convert_model_to_aas_template(DeviceAAS)
  ```

  We can also serialize the AAS template to a file:

  ```python
  with open("aas_template_DeviceAAS.json", "w") as f:
      basyx.aas.adapter.json.write_aas_json_file(
          f, aas_template_objectstore
      )
  ```



  We can also convert an instance of the Pydantic model to a BaSyx instance:

  ```python
  basyx_objectstore = aas_pydantic.convert_model_to_aas(example_device)
  ```

  When we convert a pydantic AAS model to a basyx instance, we obtain an object store, holding the AAS and its submodels. We can serialize this object store to a file:

  ```python
  with open("aas_instance_DeviceAAS.json", "w") as f:
      basyx.aas.adapter.json.write_aas_json_file(f, basyx_objectstore)
  ```

  Only converting a single submodel instance is also possible:

  ```python
  basyx_submodel = aas_pydantic.convert_model_to_submodel(example_device.device_info)
  ```



  In aas-pydantic you can create pydantic types from BaSyx templates at runtime. This can be useful when you want to create a Pydantic model from an existing AAS data structure.


  ```python
  pydantic_aas_types = aas_pydantic.convert_object_store_to_pydantic_types(
      aas_template_objectstore
  )
  pydantic_submodel_type = aas_pydantic.convert_submodel_template_to_pydatic_type(
      submodel_template
  )
  print(pydantic_submodel_type.model_fields)
  ```

  This conversion significantly reduces data complexity since relying of flat object structures instead of the AAS Meta Model. Moreover, since pydantic has many integration, such as JSonSchema or fastAPI, this transformation can be useful for many use cases.




  In aas-pydantic you can also convert BaSyx instances to Pydantic instances. This can be useful when you want to work with Pydantic models in your application, but need to convert them to BaSyx instances for communication with other systems.

  For conversion of the instances, you require the previously generated Pydantic types:

  ```python
  pydantic_submodel = aas_pydantic.convert_submodel_to_model_instance(basyx_submodel, model_type=pydantic_submodel_type)
  pydantic_aas = aas_pydantic.convert_object_store_to_pydantic_models(
      basyx_objectstore, pydantic_aas_types
  )
  print(pydantic_aas)
  ```



  Previously, we have shown how submodel templates can be loaded. Of course, this is also possible for submodel templates obtained from IDTA. For example, we can load to submodel template for [Data Model for Asset Location (Version 1.0](https://github.com/admin-shell-io/submodel-templates/tree/main/published/Data%20Model%20for%20Asset%20Location/1/0):

  ```python
  import aas_pydantic
  import basyx.aas.adapter.json

  with open(
      "IDTA 02045-1-0_Template_DataModelForAssetLocation.json", "r"
  ) as file:
      basyx_object_store = basyx.aas.adapter.json.read_aas_json_file(file)
  pydantic_types = aas_pydantic.convert_object_store_to_pydantic_types(basyx_object_store)
  with open("pydantic_types.json", "w") as f:
      json.dump(pydantic_types[0].model_json_schema(), f, indent=2)

  ```

  This example shows, how simple integration between Submodel templates and JSON Schema can be achieved. The geneated JSON Schema could, e.g. be used in code [generation tools for pydantic models](https://github.com/koxudaxi/datamodel-code-generator) to have defined pydantic types for the submodel templates. For more integration, check out [aas-middleware](https://github.com/sdm4fzi/aas_middleware), a python package for industrial data  and software integration based on AAS.




  The package provides the following conversion of python type annotations:

  - Primitive types (int, float, str, bool)
  - Collections (List, Set, Tuples)
  - Enums and Literals
  - Unions and Optional types
  - Nested Pydantic models

  Note that dicts are not supported, since a clear distinction from SubmodelElementCollection to the dict or pydantic type is not possible.

  The following BaSyx Submodel Element Types are supported:
  - SubmodelElementCollection
  - SubmodelElementList
  - ReferenceElement
  - RelationshipElement
  - Property
  - Blob
  - File

  During conversion, the following information will be preserved:
  - Identifiers
  - Descriptions
  - Semantic Identifiers
  - Values and Value Types

  Storage of additional information that cannot be kept easily in the BaSyx model (attribute and class names, optional and union types, enums) will be stored in the Concept Descriptions of the BaSyx model.



  The package is licensed under the [MIT license](LICENSE).


pkgId: cd04d68a09de5d265ab0502a289f125b11dfc0d512c20f32bd5af32717c4db33
name: python-aas-test-engines
arch: src
version: 1.0.0
epoch: 0
release: 1
summary: Official test tooling for the Asset Administration Shell
url: https://github.com/admin-shell-io/aas-test-engines
rpm_license: None
rpm_group: Unspecified
rpm_buildhost: localhost
location_href: Packages/python-aas-test-engines-1.0.0-1.src.rpm
checksum_type: sha256
description:
  [![Tests](https://github.com/admin-shell-io/aas-test-engines/actions/workflows/check.yml/badge.svg)](https://github.com/admin-shell-io/aas-test-engines/actions/workflows/check.yml)

  The Asset Administration Shell (AAS) is a standard for Digital Twins.
  More information can be found [here](https://industrialdigitaltwin.org/content-hub/downloads).

  The tools in this repository offer measures to validate compliance of AAS implementations against the AAS standard.



  You can install the AAS Test Engines via pip:

  ```sh
  python -m pip install --upgrade aas_test_engines
  ```



  You may want to invoke the test tools using the simplified command line interface:

  ```sh

  aas_test_engines check_file test.aasx
  aas_test_engines check_file test.json --format json


  aas_test_engines check_server https://localhost https://admin-shell.io/aas/API/3/0/AssetAdministrationShellRepositoryServiceSpecification/SSP-002


  aas_test_engines generate_files output_dir


  aas_test_engines check_file test.aasx --output html > output.html
  aas_test_engines check_file test.aasx --output json > output.json
  ```



  By default, the Test Engines test against the latest version 3.0 (file and api).
  For v3.0 api testing, the following suites are defined:

   - `Asset Administration Shell API`
   - `Submodel API`
   - `Serialization API`
   - `AASX File Server API`
   - `Asset Administration Shell Registry API`
   - `Submodel Registry API`
   - `Asset Administration Shell Repository API`
   - `Submodel Repository API`
   - `Concept Description Repository API`
   - `Asset Administration Shell Basic Discovery API`
   - `Description API`
   - `Asset Administration Shell Service Specification`
   - `Submodel Service Specification`
   - `AASX File Server Service Specification`
   - `Asset Administration Shell Registry Service Specification`
   - `Submodel Registry Service Specification`
   - `Discovery Service Specification`
   - `Asset Administration Shell Repository Service Specification`
   - `Submodel Repository Service Specification`
   - `ConceptDescription Repository Service Specification`
   - `https://admin-shell.io/aas/API/3/0/AssetAdministrationShellServiceSpecification/SSP-001`
   - `https://admin-shell.io/aas/API/3/0/AssetAdministrationShellServiceSpecification/SSP-002`
   - `https://admin-shell.io/aas/API/3/0/SubmodelServiceSpecification/SSP-001`
   - `https://admin-shell.io/aas/API/3/0/SubmodelServiceSpecification/SSP-002`
   - `https://admin-shell.io/aas/API/3/0/SubmodelServiceSpecification/SSP-003`
   - `https://admin-shell.io/aas/API/3/0/AasxFileServerServiceSpecification/SSP-001`
   - `https://admin-shell.io/aas/API/3/0/AssetAdministrationShellRegistryServiceSpecification/SSP-001`
   - `https://admin-shell.io/aas/API/3/0/AssetAdministrationShellRegistryServiceSpecification/SSP-002`
   - `https://admin-shell.io/aas/API/3/0/SubmodelRegistryServiceSpecification/SSP-001`
   - `https://admin-shell.io/aas/API/3/0/SubmodelRegistryServiceSpecification/SSP-002`
   - `https://admin-shell.io/aas/API/3/0/DiscoveryServiceSpecification/SSP-001`
   - `https://admin-shell.io/aas/API/3/0/AssetAdministrationShellRepositoryServiceSpecification/SSP-001`
   - `https://admin-shell.io/aas/API/3/0/AssetAdministrationShellRepositoryServiceSpecification/SSP-002`
   - `https://admin-shell.io/aas/API/3/0/SubmodelRepositoryServiceSpecification/SSP-001`
   - `https://admin-shell.io/aas/API/3/0/SubmodelRepositoryServiceSpecification/SSP-002`
   - `https://admin-shell.io/aas/API/3/0/SubmodelRepositoryServiceSpecification/SSP-003`
   - `https://admin-shell.io/aas/API/3/0/SubmodelRepositoryServiceSpecification/SSP-004`
   - `https://admin-shell.io/aas/API/3/0/ConceptDescriptionRepositoryServiceSpecification/SSP-001`





  Check AASX:

  ```python
  from aas_test_engines import file

  with open('aas.aasx', 'rb') as f:
      result = file.check_aasx_file(f)


  result.dump()

  ```

  Check JSON:

  ```python
  from aas_test_engines import file


  with open('aas.json') as f:
      result = file.check_json_file(f)



  aas = {
      'assetAdministrationShells': [],
      'submodels': [],
      'conceptDescriptions': []
  }
  result = file.check_json_data(aas)


  result.dump()
  ```

  Check XML:

  ```python
  from aas_test_engines import file
  from xml.etree import ElementTree


  with open('aas.xml') as f:
      result = file.check_xml_file(f)



  data = ElementTree.fromstring(
      '<environment xmlns="https://admin-shell.io/aas/3/0" />')
  result = file.check_xml_data(aas)


  result.dump()
  ```

  Checking older versions:

  ```python
  from aas_test_engines import file

  print(file.supported_versions())
  print(file.latest_version())
  with open('aas.aasx', 'rb') as f:
      result = file.check_aasx_file(f, version="3.0")


  result.dump()
  ```



  Check a running server instance:

  ```python
  from aas_test_engines import api

  result = api.execute_tests("http://localhost", "https://localhost https://admin-shell.io/aas/API/3/0/AssetAdministrationShellRepositoryServiceSpecification/SSP-002")
  result.dump()
  ```

  Checking older versions:

  ```python
  from aas_test_engines import api
  print(api.supported_versions())
  print(api.latest_version())

  result = api.execute_tests("http://localhost", 'Asset Administration Shell API', version="3.0")
  result.dump()
  ```



  If you develop an AAS application like an AAS editor you may want to use test data to verify correctness of your application.
  The test engines allow to generate a set of AAS files which are compliant with the standard and you can therefore use to assess your application as follows:

  ```python
  from aas_test_engines import file

  for is_valid, sample in file.generate():
      print(sample) # or whatever you want to do with it
  ```


pkgId: caaffe6deee62b0d4e0542ed9c9ae9046471f838a076314302e4d9afd6dc3ad2
name: python-aas2openapi
arch: src
version: 0.2.4
epoch: 0
release: 1
summary: please add a summary manually as the author left a blank one
url: https://pypi.org/project/aas2openapi/
rpm_license: MIT
rpm_group: Unspecified
rpm_buildhost: localhost
location_href: Packages/python-aas2openapi-0.2.4-1.src.rpm
checksum_type: sha256
description:
  ![Build-sucess](https://img.shields.io/badge/build-success-green)
  ![PyPI](https://img.shields.io/pypi/v/aas2openapi)
  ![PyPI - Python Version](https://img.shields.io/pypi/pyversions/aas2openapi)
  [![DOI](https://zenodo.org/badge/672818560.svg)](https://zenodo.org/badge/latestdoi/672818560)

  aas2openapi is a middleware for Asset Administration Shell (AAS) and openAPI 3.0. It can be used to transform AAS to openAPI 3.0 objects and vice versa. Moreover, it can be used to generate a CRUD server that allows to access the AAS data via RESTful API with openAPI Specifications.



  You can install the package using by running the following command in the terminal:

  ```bash
  pip install aas2openapi
  ```


  Alternatively, you can install the package with [poetry](https://python-poetry.org/) for development:

  ```bash
  poetry shell
  poetry install
  ```

  Please note that the package is only compatible with Python 3.10 or higher.



  In the following, we will consider a minimal example to demonstrate the usage of the package. The example is also available in the [examples](examples/) and consists of defining a simple model of an AAS with two submodels, transforming this model and integrating it with the aas2openapi middleware.



  At first, we create a simple data model with the basic building blocks (AAS and Submodel) of aas2openapi:

  ```python
  class BillOfMaterialInfo(models.SubmodelElementCollection):
      manufacterer: str
      product_type: str

  class BillOfMaterial(models.Submodel):
      components: typing.List[str]
      bill_of_material_info: BillOfMaterialInfo


  class ProcessModel(models.Submodel):
      processes: typing.List[str]


  class Product(models.AAS):
      bill_of_material: BillOfMaterial
      process_model: typing.Optional[ProcessModel]
  ```

  The data model consists of a product that has a process model and a bill of material. The process model and the bill of material are submodels that contain a list of processes and components, respectively. To be able to instantiate an AAS, we also create an instance of this data model:

  ```python
  example_product = Product(
      id="Product1",
      process_model=ProcessModel(
          id="PMP1",
          processes=["join", "screw"],
          semantic_id="PMP1_semantic_id",
      ),
      bill_of_material=BillOfMaterial(
          id="BOMP1", components=["stator", "rotor", "coil", "bearing"],
          semantic_id="BOMP1_semantic_id",
          bill_of_material_info=BillOfMaterialInfo(
              id_short="BOMInfoP1",
              semantic_id="BOMInfoP1_semantic_id",
              manufacterer="Bosch", product_type="A542",
          )
      ),
  )
  ```



  Now, we can use `aas2openapi` to transform the object to an AAS and serialize it with basyx to JSON:

  ```python
  import aas2openapi
  obj_store = aas2openapi.convert_pydantic_model_to_aas(example_product)
  import basyx.aas.adapter.json.json_serialization

  with open("examples/simple_aas_and_submodels.json", "w", encoding="utf-8") as json_file:
      basyx.aas.adapter.json.write_aas_json_file(json_file, obj_store)
  ```

  Of course, we can also transform AAS to python objects, which can be easily transformed to openAPI objects with the middleware:

  ```python
  data_model = aas2openapi.convert_object_store_to_pydantic_models(obj_store)
  print(data_model)
  ```



  The aas2openapi middleware is build with fastAPI and generates therefore automatically a openAPI Specification for provided models. To use the middleware, we can simply input our predefined data models and connect it with running basyx servers. Here, we use instances of the data models that we have defined before and create a CRUD RESTful API for them:

  ```python
  from aas2openapi.middleware import Middleware
  middleware = Middleware()
  middleware.load_pydantic_model_instances([example_product])
  middleware.generate_rest_api()
  middleware.generate_graphql_api()
  middleware.generate_model_registry_api()

  app = middleware.app
  ```

  We can run this app either from the command line with uvicorn:

  ```bash
    uvicorn app:app --reload
  ```

  Here, it is assumed, that the file you saved is called app.py. If it has a different name, rename the first app. Alternatively, you can also run the app directly with python, by extending the script at the bottom with:

  ```python
    if __name__ == "__main__":
      import uvicorn

      uvicorn.run(app)

  ```

  You can access now the documentation of the REST API with swagger at `http://localhost:8000/docs` and the graphql endpoint at  `http://localhost:8000/graphql`.

  Besides loading the data models from instances,  we can also generate it directly from its python type, from a JSON-object or from an AAS. To do so, simply replace the `load_pydantic_model_instances` method with `load_pydantic_models` to load from types or `load_aas_objectstore` to load from an AAS object store or `load_json_models` to load from serialized JSON-objects:

  ```python
  middleware.load_pydantic_model_types([Product])
  middleware.load_aas_from_objectstore(obj_store)
  middleware.load_json_models(file_path="examples/example_json_model.json")

  ```

  However, no examples can be provided when loading from types.

  We can either run the middleware now directly with python or make a docker build. In both scenarios, an AAS and Submodel-server need to be running that the middleware can connect to. Each request to the middleware is then translated and forwarded to the AAS and Submodel-server.

  The repository already comes with a docker-compose file that can be used to start the AAS and Submodel-server. To start the docker-compose file, run the following command in the terminal:

  ```bash
  docker-compose -f docker-compose-dev.yaml up
  ```

  We can now run the middleware script with python and access it at `http://localhost:8000/`. Documentation of the generated Rest API is at `http://localhost:8000/docs` available by a swaggerUI and the openAPI Specification is available at `http://localhost:8000/openapi.json`. You can use the swaggerUI to post some AAS or this exemplary command (with bash console):

  ```bash
    curl -X 'POST' \
    'http://127.0.0.1:8000/Product/' \
    -H 'accept: application/json' \
    -H 'Content-Type: application/json' \
    -d '{
    "id_short": "Product1",
    "description": "string",
    "id": "Product1",
    "bill_of_material": {
      "id_short": "BOMP1",
      "description": "",
      "id": "BOMP1",
      "semantic_id": "BOMP1_semantic_id",
      "components": [
        "stator",
        "rotor",
        "coil",
        "bearing"
      ],
      "bill_of_material_info": {
        "id_short": "BOMInfoP1",
        "description": "",
        "semantic_id": "BOMInfoP1_semantic_id",
        "manufacterer": "Bosch",
        "product_type": "A542"
      }
    },
    "process_model": {
      "id_short": "PMP1",
      "description": "",
      "id": "PMP1",
      "semantic_id": "PMP1_semantic_id",
      "processes": [
        "join",
        "screw"
      ]
    }
  }'
  ```

  If you want to change the adresses and ports of the AAS and Submodel-server, you can do so by adding a `.env` file to the root directory of the package. The file should contain speicifications similar to that in the `.env.example` file of the package.

  Lastly, we can build a docker image of the middleware and run it in a docker-compose as a container. To do so, just adjust the provided Dockerfile and docker-compose.yaml of this package to fit your needs based on the provided example in the file docker_app.py. To build the docker image, run the following command in the terminal:

  ```bash
  docker compose build
  ```

  lastly, we can run the docker-compose file with the following command and start aas2openapi, AAS server and submodel server at the same time:

  ```bash
  docker compose up
  ```

  If you want to start the middleware also with a user interface for the AAS and a mongo db backend for AAS, you can use the following command:

  ```bash
  docker compose -f docker-compose-ui.yaml up -d
  ```

  The user interface is then available at `http://localhost:3000/`. After posting some AAS with the middleware (see above), you can add the AAS to the user interface by clicking on the "+" button and entering the AAS id (base64 encoded). The AAS is then available in the user interface.



  `aas2openapi` is a new project and has therefore much room for improvement. Therefore, it would be a pleasure to get feedback or support! If you want to contribute to the package, either create issues on [aas2openapis github page](https://github.com/sdm4fzi/aas2openapi) for discussing new features or contact me directly via [github](https://github.com/SebBehrendt) or [email](mailto:sebastian.behrendt@kit.edu).



  The package is licensed under the [MIT license](LICENSE).



  We extend our sincere thanks to the German Federal Ministry for Economic Affairs and Climate Action
  (BMWK) for supporting this research project 13IK001ZF “Software-Defined Manufacturing for the
  automotive and supplying industry [https://www.sdm4fzi.de/](https://www.sdm4fzi.de/).


pkgId: ee0ca7987911a21468598daa504e93750af59f52c786f2b8243a80eb28b9c321
name: python-aasaanjobs-notificationhub
arch: src
version: 1.4.0
epoch: 0
release: 1
summary: Python client for Aasaanjobs/Waahjobs Notification Hub
url: https://github.com/aasaanjobs/notification-hub-py-sdk
rpm_license: UNKNOWN
rpm_group: Unspecified
rpm_buildhost: localhost
location_href: Packages/python-aasaanjobs-notificationhub-1.4.0-1.src.rpm
checksum_type: sha256
description:
  [![Build Status](https://travis-ci.org/aasaanjobs/notification-hub-py-sdk.svg?branch=master)](https://travis-ci.org/aasaanjobs/notification-hub-py-sdk)
  [![codecov](https://codecov.io/gh/aasaanjobs/notifications-python-sdk/branch/master/graph/badge.svg)](https://codecov.io/gh/aasaanjobs/notifications-python-sdk)

  Python SDK to communicate with Aasaanjobs/Waahjobs Notification Hub and send notifications to users.


  - Short Messaging Service (SMS)
  - Email
  - WhatsApp
  - Mobile Push (FCM)


  ```
  pip install aasaanjobs-notificationhub
  ```


  Each notification is referred to as **Task** in this library. A single **Task** can contain
  multiple channels, i.e., a single **Task** can contain both **Email** and **WhatsApp** notification data.
  This **Task** is then validated via [Protocol Buffers](https://developers.google.com/protocol-buffers)
  and pushed to corresponding Notification Hub Amazon SQS queue.

  For **Transactional** notifications **NOTIFICATION_HUB_SQS_QUEUE_NAME** environment variable should be configured.

  For **Marketing** notifications **NOTIFICATION_HUB_MARKETING_SQS_QUEUE_NAME** environment variable should be configured.

  For **OTP** notifications **NOTIFICATION_HUB_OTP_SQS_QUEUE_NAME** environment variable should be configured.


  Each application which uses this library must configure Amazon SQS configurations to successfully
  send notification task to Hub.

  The following keys can be defined in the settings module if Django application or can be defined as environment variables

  | **Setting**                            | **Description**                                                   |
  |----------------------------------------|-------------------------------------------------------------------|
  | NOTIFICATION_HUB_SQS_ACCESS_KEY_ID     | Access Key of the IAM role which has access to the Hub SQS        |
  | NOTIFICATION_HUB_SQS_SECRET_ACCESS_KEY | Secret Access Key of the IAM role which has access to the Hub SQS |
  | NOTIFICATION_HUB_SQS_REGION            | AWS Region where the Hub SQS resides                              |
  | NOTIFICATION_HUB_SQS_QUEUE_NAME        | Name of the Hub SQS Queue                                         |
  | NOTIFICATION_HUB_MARKETING_SQS_QUEUE_NAME | Name of the Hub Marketing SQS Queue                            |
  | NOTIFICATION_HUB_OTP_SQS_QUEUE_NAME    | Name of the Hub OTP SQS Queue                            |


pkgId: 6cd403fa0e188509bdeace52feddc2d3de4ed6e92266dd6c88e9fa6a310106a0
name: python-aasm
arch: src
version: 0.1.9
epoch: 0
release: 1
summary: Agents Assembly translator
url: https://pypi.org/project/aasm/
rpm_license: None
rpm_group: Unspecified
rpm_buildhost: localhost
location_href: Packages/python-aasm-0.1.9-1.src.rpm
checksum_type: sha256
description:
  - [About](#about)
  - [Agents Assembly](#agents-assembly)
  - [Getting Started](#getting-started)
  - [Structure](#structure)
  - [Contributing](#contributing)


  A target agnostic translator for Agents Assembly. The translator can be tested live on [Agents Assembly website](https://agents-assembly.com/translator).
  It is a part of the [Agents Assembly](https://agents-assembly.com) ecosystem.
  Other applications are:
  - [Local Interface](https://github.com/agent-based-information-flow-simulation/local-interface) - GUI for simulation definition, management, and analysis.
  - [Simulation Run Environment](https://github.com/agent-based-information-flow-simulation/simulation-run-environment) - environment for running scalable agent-based simulations.
  - [Communication Server](https://github.com/agent-based-information-flow-simulation/communication-server) - cluster of servers used for XMPP communication.
  - [Local Development Environment](https://github.com/agent-based-information-flow-simulation/local-development-environment) - simple environment for running agent-based simulations.


  Documentation of Agents Assembly can be read [here](DOCS.md).





  ```
  Python 3.10
  ```


  The translator [package](https://pypi.org/project/aasm) can be installed by running:
  ```
  pip install aasm
  ```
  Alternatively, you can download this repository. No additional dependencies are required.


  You can run the translator as a package. To translate *agent.aasm* to SPADE, run:
  ```
  python -m aasm.translate agent.aasm
  ```

  For more usage information, run:
  ```
  python -m aasm.translate --help
  ```



  * `generating`
      * `code.py` - generated code
      * `python_code.py` - Python code base class
      * `python_graph.py` - Python graph code generation from the intermediate representation
      * `python_spade.py` - SPADE agent code generation from the intermediate representation
  * `intermediate`
      * `action.py`
      * `agent.py`
      * `argument.py` - arguments used in instructions
      * `behaviour.py`
      * `block.py` - block of code representation
      * `declaration.py` - declarations used in actions
      * `graph.py`
      * `instruction.py` - instructions used in actions
      * `message.py`
  * `parsing`
      * `parse.py` - parsing environment from Agents Assembly file
      * `op/` - Agents Assembly operations
      * `state.py` - state definition used for the parsing process
  * `preprocessor`
      * `constants.py` - constants used in the preprocessor
      * `macro.py` - macro definitions used in the preprocessor
      * `preprocessor_item.py` - preprocessor base item
      * `preprocessor.py`
  * `utils`
      * `exception.py`
      * `validation.py`
      * `iteration.py`
  * `translate.py` - entrypoint


  Please follow the [contributing guide](CONTRIBUTING.md) if you wish to contribute to the project.


pkgId: ed04b91a59fdf37d797746f4148133ef5caf06b76b679d5e8a0df04f3a9688b9
name: python-aastex
arch: src
version: 0.3.1
epoch: 0
release: 1
summary: A Python wrapper around the AASTeX Latex packages
url: https://github.com/sun-data/aastex
rpm_license: None
rpm_group: Unspecified
rpm_buildhost: localhost
location_href: Packages/python-aastex-0.3.1-1.src.rpm
checksum_type: sha256
description:
  [![tests](https://github.com/sun-data/aastex/actions/workflows/tests.yml/badge.svg)](https://github.com/sun-data/aastex/actions/workflows/tests.yml)
  [![codecov](https://codecov.io/gh/sun-data/aastex/graph/badge.svg?token=c9VYZtRAO8)](https://codecov.io/gh/sun-data/aastex)
  [![Black](https://github.com/sun-data/aastex/actions/workflows/black.yml/badge.svg)](https://github.com/sun-data/aastex/actions/workflows/black.yml)
  [![Documentation Status](https://readthedocs.org/projects/aastex/badge/?version=latest)](https://aastex.readthedocs.io/en/latest/?badge=latest)
  [![PyPI version](https://badge.fury.io/py/aastex.svg)](https://badge.fury.io/py/aastex)

  This Python library extends [PyLaTeX](https://github.com/JelteF/PyLaTeX) to support the
  [AASTeX LaTeX package](https://journals.aas.org/aastex-package-for-manuscript-preparation/).



  `aastex` is available on PyPI and can be installed using `pip`:

  ```bash
  pip install aastex
  ```


pkgId: de2ac71ffc63d16c74af51a18b6a8f61944dfdaef869b6119c2dde4e8d4f7408
name: python-aat-analysis
arch: src
version: 0.0.7
epoch: 0
release: 1
summary: This project analyzes mobile AAT data.
url: https://github.com/hgzech/aat_analysis/tree/master/
rpm_license: Apache Software License 2.0
rpm_group: Unspecified
rpm_buildhost: localhost
location_href: Packages/python-aat-analysis-0.0.7-1.src.rpm
checksum_type: sha256
description:
  > This package helps with analyzing mobile AAT data.




  `pip install aat_analysis`



  ```python



  ```

  ```python
  from aat_analysis.make_condition_templates import make_condition_templates
  from aat_analysis.json_to_df import json_to_df
  from aat_analysis.utils import merge_data


  ```


  - raw should include the raw data from your experiment
  - external should include the contents of the Resources folder of your experiment app
  - interim and processed can be empty

  ```python
  external_folder = "../data/external/"
  interim_folder = "../data/interim/"
  raw_data_folder = "../data/raw/"
  processed_data_file = "../data/processed/data.csv"
  ```



  ```python

  templates = make_condition_templates(external_folder)

  json_to_df(raw_data_folder, external_folder, interim_folder, templates)

  data = merge_data(interim_folder, drop=['interpolated','interpolated_gyro'])
  data.to_csv(processed_data_file)
  ```

      100%|█████████████████████████████████████████████| 3/3 [00:27<00:00,  9.24s/it]



  The selected columns below contain all data needed to calculate approach tendencies for each session, participant, and stimulus type.  The additional data in the dataframe (not shown) are answers to other questions and some additional AAT variables.

  ```python
  data[['participant','condition','session','trial','is_practice','stimulus_set','stimulus','correct_response','response','accuracy','rt','force']]
  ```




  <div>
  <style scoped>
      .dataframe tbody tr th:only-of-type {
          vertical-align: middle;
      }

      .dataframe tbody tr th {
          vertical-align: top;
      }

      .dataframe thead th {
          text-align: right;
      }
  </style>
  <table border="1" class="dataframe">
    <thead>
      <tr style="text-align: right;">
        <th></th>
        <th>participant</th>
        <th>condition</th>
        <th>session</th>
        <th>trial</th>
        <th>is_practice</th>
        <th>stimulus_set</th>
        <th>stimulus</th>
        <th>correct_response</th>
        <th>response</th>
        <th>accuracy</th>
        <th>rt</th>
        <th>force</th>
      </tr>
    </thead>
    <tbody>
      <tr>
        <th>0</th>
        <td>kmahu0zq</td>
        <td>condition_2</td>
        <td>final_session</td>
        <td>1</td>
        <td>False</td>
        <td>None</td>
        <td>None</td>
        <td>None</td>
        <td>NA</td>
        <td>False</td>
        <td>NaN</td>
        <td>NaN</td>
      </tr>
      <tr>
        <th>1</th>
        <td>kmahu0zq</td>
        <td>condition_2</td>
        <td>introduction_session_2</td>
        <td>1</td>
        <td>True</td>
        <td>practice_food</td>
        <td>stim_0154</td>
        <td>push</td>
        <td>ND</td>
        <td>False</td>
        <td>NaN</td>
        <td>8.124186</td>
      </tr>
      <tr>
        <th>2</th>
        <td>kmahu0zq</td>
        <td>condition_2</td>
        <td>introduction_session_2</td>
        <td>2</td>
        <td>True</td>
        <td>practice_objects</td>
        <td>stim_1276</td>
        <td>pull</td>
        <td>pull</td>
        <td>True</td>
        <td>1206.0</td>
        <td>12.130466</td>
      </tr>
      <tr>
        <th>3</th>
        <td>kmahu0zq</td>
        <td>condition_2</td>
        <td>introduction_session_2</td>
        <td>3</td>
        <td>True</td>
        <td>practice_objects</td>
        <td>stim_1264</td>
        <td>pull</td>
        <td>ND</td>
        <td>False</td>
        <td>NaN</td>
        <td>1.651279</td>
      </tr>
      <tr>
        <th>4</th>
        <td>kmahu0zq</td>
        <td>condition_2</td>
        <td>introduction_session_2</td>
        <td>4</td>
        <td>True</td>
        <td>practice_objects</td>
        <td>stim_1277</td>
        <td>pull</td>
        <td>pull</td>
        <td>True</td>
        <td>629.0</td>
        <td>18.342323</td>
      </tr>
      <tr>
        <th>...</th>
        <td>...</td>
        <td>...</td>
        <td>...</td>
        <td>...</td>
        <td>...</td>
        <td>...</td>
        <td>...</td>
        <td>...</td>
        <td>...</td>
        <td>...</td>
        <td>...</td>
        <td>...</td>
      </tr>
      <tr>
        <th>6166</th>
        <td>kmah8va6</td>
        <td>condition_2</td>
        <td>push_food_before_lunch_d5</td>
        <td>132</td>
        <td>False</td>
        <td>unhealthy_tempting</td>
        <td>stim_0025</td>
        <td>pull</td>
        <td>pull</td>
        <td>True</td>
        <td>346.0</td>
        <td>9.024626</td>
      </tr>
      <tr>
        <th>6167</th>
        <td>kmah8va6</td>
        <td>condition_2</td>
        <td>push_food_before_lunch_d5</td>
        <td>133</td>
        <td>False</td>
        <td>unhealthy_non_tempting</td>
        <td>stim_0125</td>
        <td>pull</td>
        <td>pull</td>
        <td>True</td>
        <td>363.0</td>
        <td>5.820239</td>
      </tr>
      <tr>
        <th>6168</th>
        <td>kmah8va6</td>
        <td>condition_2</td>
        <td>push_food_before_lunch_d5</td>
        <td>134</td>
        <td>False</td>
        <td>healthy_non_tempting</td>
        <td>stim_0226</td>
        <td>pull</td>
        <td>pull</td>
        <td>True</td>
        <td>492.0</td>
        <td>8.345508</td>
      </tr>
      <tr>
        <th>6169</th>
        <td>kmah8va6</td>
        <td>condition_2</td>
        <td>push_food_before_lunch_d5</td>
        <td>135</td>
        <td>False</td>
        <td>healthy_tempting</td>
        <td>stim_0201</td>
        <td>pull</td>
        <td>pull</td>
        <td>True</td>
        <td>450.0</td>
        <td>5.539470</td>
      </tr>
      <tr>
        <th>6170</th>
        <td>kmah8va6</td>
        <td>condition_2</td>
        <td>push_food_before_lunch_d5</td>
        <td>136</td>
        <td>False</td>
        <td>objects</td>
        <td>stim_1035</td>
        <td>push</td>
        <td>pull</td>
        <td>False</td>
        <td>308.0</td>
        <td>6.589124</td>
      </tr>
    </tbody>
  </table>
  <p>6171 rows × 12 columns</p>
  </div>


pkgId: 3bc015308b536db92c398e573c21fff144e7e88801e5766cf8b5fbfb8524b117
name: python-aaudd
arch: src
version: 4.0
epoch: 0
release: 1
summary: Script for audio recognition using AUDD API
url: https://twitter.com/Lanaev0li
rpm_group: Unspecified
rpm_buildhost: localhost
location_href: Packages/python-aaudd-4.0-1.src.rpm
checksum_type: sha256
description:
  AUDD - это скрипт для распознавания аудио с использованием API AUDD. Версия 2.0 включает в себя возможность самостоятельно обновлять API-токен и выбирать язык интерфейса (английский или русский).



  Вы можете установить AUDD с помощью pip:

  ```bash
  pip install aaudd
  ```

  Для работы скрипта также потребуется установить библиотеку `requests`:

  ```bash
  pip install requests
  ```


  Запустите скрипт, введя команду `aaudd` в вашем терминале:
  `aaudd`

  Следуйте инструкциям, чтобы ввести URL аудиофайла или локальный путь, выбрать сервисы для распознавания и при желании сохранить результаты в текстовый файл. Также вы можете обновить API-токен и изменить язык интерфейса.


  Этот проект лицензирован по лицензии MIT - см. файл [LICENSE](LICENSE) для дополнительных сведений.



  AUDD is a script for audio recognition using the AUDD API. Version 2.0 includes the ability to update the API token and select the interface language (English or Russian).



  You can install AUDD using pip:

  ```bash
  pip install aaudd
  ```

  You will also need to install the `requests` library:

  ```bash
  pip install requests
  ```


  Run the script by entering the command `aaudd` in your terminal:
  `aaudd`

  Follow the instructions to enter the URL of the audio file or the local path, select the services for recognition, and optionally save the results to a text file. You can also update the API token and change the interface language.


  This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.


  License: Avinion Group

  Permission is hereby granted, free of charge, to any person obtaining a copy of
  this software and associated documentation files (the "Software"), to deal in
  the Software without restriction, including without limitation the rights to
  use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies
  of the Software, and to permit persons to whom the Software is furnished to do
  so, subject to the following conditions:

  The above copyright notice and this permission notice shall be included in all
  copies or substantial portions of the Software.

  THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
  IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
  FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
  AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
  LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
  OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
  SOFTWARE.

rpm_license:
  License: Avinion Group Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.


pkgId: 4e77a68efbd02b1444c4c819b817bb73458fd64467c3c65de119f83e792a3c1d
name: python-aautils
arch: src
version: 1.0
epoch: 0
release: 1
summary: Utility Libraries to power your tests (or general applications)
description: Utility Libraries to power your tests (or general applications)
url: https://avocado-framework.github.io/autils.html
rpm_group: Unspecified
rpm_buildhost: localhost
location_href: Packages/python-aautils-1.0-1.src.rpm
checksum_type: sha256
rpm_license:
  GNU GENERAL PUBLIC LICENSE Version 2, June 1991  Copyright (C) 1989, 1991 Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA Everyone is permitted to copy and distribute verbatim copies of this license document, but changing it is not allowed.  Preamble  The licenses for most software are designed to take away your freedom to share and change it.  By contrast, the GNU General Public License is intended to guarantee your freedom to share and change free software--to make sure the software is free for all its users.  This General Public License applies to most of the Free Software Foundation's software and to any other program whose authors commit to using it.  (Some other Free Software Foundation software is covered by the GNU Lesser General Public License instead.)  You can apply it to your programs, too.  When we speak of free software, we are referring to freedom, not price.  Our General Public Licenses are designed to make sure that you have the freedom to distribute copies of free software (and charge for this service if you wish), that you receive source code or can get it if you want it, that you can change the software or use pieces of it in new free programs; and that you know you can do these things.  To protect your rights, we need to make restrictions that forbid anyone to deny you these rights or to ask you to surrender the rights. These restrictions translate to certain responsibilities for you if you distribute copies of the software, or if you modify it.  For example, if you distribute copies of such a program, whether gratis or for a fee, you must give the recipients all the rights that you have.  You must make sure that they, too, receive or can get the source code.  And you must show them these terms so they know their rights.  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If the Program specifies a version number of this License which applies to it and "any later version", you have the option of following the terms and conditions either of that version or of any later version published by the Free Software Foundation.  If the Program does not specify a version number of this License, you may choose any version ever published by the Free Software Foundation.  10. If you wish to incorporate parts of the Program into other free programs whose distribution conditions are different, write to the author to ask for permission.  For software which is copyrighted by the Free Software Foundation, write to the Free Software Foundation; we sometimes make exceptions for this.  Our decision will be guided by the two goals of preserving the free status of all derivatives of our free software and of promoting the sharing and reuse of software generally.  NO WARRANTY  11. BECAUSE THE PROGRAM IS LICENSED FREE OF CHARGE, THERE IS NO WARRANTY FOR THE PROGRAM, TO THE EXTENT PERMITTED BY APPLICABLE LAW.  EXCEPT WHEN OTHERWISE STATED IN WRITING THE COPYRIGHT HOLDERS AND/OR OTHER PARTIES PROVIDE THE PROGRAM "AS IS" WITHOUT WARRANTY OF ANY KIND, EITHER EXPRESSED OR IMPLIED, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE.  THE ENTIRE RISK AS TO THE QUALITY AND PERFORMANCE OF THE PROGRAM IS WITH YOU.  SHOULD THE PROGRAM PROVE DEFECTIVE, YOU ASSUME THE COST OF ALL NECESSARY SERVICING, REPAIR OR CORRECTION.  12. IN NO EVENT UNLESS REQUIRED BY APPLICABLE LAW OR AGREED TO IN WRITING WILL ANY COPYRIGHT HOLDER, OR ANY OTHER PARTY WHO MAY MODIFY AND/OR REDISTRIBUTE THE PROGRAM AS PERMITTED ABOVE, BE LIABLE TO YOU FOR DAMAGES, INCLUDING ANY GENERAL, SPECIAL, INCIDENTAL OR CONSEQUENTIAL DAMAGES ARISING OUT OF THE USE OR INABILITY TO USE THE PROGRAM (INCLUDING BUT NOT LIMITED TO LOSS OF DATA OR DATA BEING RENDERED INACCURATE OR LOSSES SUSTAINED BY YOU OR THIRD PARTIES OR A FAILURE OF THE PROGRAM TO OPERATE WITH ANY OTHER PROGRAMS), EVEN IF SUCH HOLDER OR OTHER PARTY HAS BEEN ADVISED OF THE POSSIBILITY OF SUCH DAMAGES.  END OF TERMS AND CONDITIONS  How to Apply These Terms to Your New Programs  If you develop a new program, and you want it to be of the greatest possible use to the public, the best way to achieve this is to make it free software which everyone can redistribute and change under these terms.  To do so, attach the following notices to the program.  It is safest to attach them to the start of each source file to most effectively convey the exclusion of warranty; and each file should have at least the "copyright" line and a pointer to where the full notice is found.  <one line to give the program's name and a brief idea of what it does.> Copyright (C) <year>  <name of author>  This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version.  This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU General Public License for more details.  You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.  Also add information on how to contact you by electronic and paper mail.  If the program is interactive, make it output a short notice like this when it starts in an interactive mode:  Gnomovision version 69, Copyright (C) year name of author Gnomovision comes with ABSOLUTELY NO WARRANTY; for details type `show w'. This is free software, and you are welcome to redistribute it under certain conditions; type `show c' for details.  The hypothetical commands `show w' and `show c' should show the appropriate parts of the General Public License.  Of course, the commands you use may be called something other than `show w' and `show c'; they could even be mouse-clicks or menu items--whatever suits your program.  You should also get your employer (if you work as a programmer) or your school, if any, to sign a "copyright disclaimer" for the program, if necessary.  Here is a sample; alter the names:  Yoyodyne, Inc., hereby disclaims all copyright interest in the program `Gnomovision' (which makes passes at compilers) written by James Hacker.  <signature of Ty Coon>, 1 April 1989 Ty Coon, President of Vice  This General Public License does not permit incorporating your program into proprietary programs.  If your program is a subroutine library, you may consider it more useful to permit linking proprietary applications with the library.  If this is what you want to do, use the GNU Lesser General Public License instead of this License.


pkgId: f6c08f6775e1e68f07930b1a7a65d815fed6947b853db3db12c433f06746e533
name: python-aaz-dev
arch: src
version: 3.1.0
epoch: 0
release: 1
summary: Microsoft Atomic Azure CLI Commands Developer Tools
url: https://github.com/Azure/aaz-dev-tools
rpm_license: MIT
rpm_group: Unspecified
rpm_buildhost: localhost
location_href: Packages/python-aaz-dev-3.1.0-1.src.rpm
checksum_type: sha256
description:
  The *aaz-dev* tool is designed to generate atomic Azure CLI commands from OpenAPI specifications. For more information, please refer to [document](https://azure.github.io/aaz-dev-tools/) and [video](https://microsoft.sharepoint.com/teams/AzureCLITools237/_layouts/15/embed.aspx?UniqueId=97905452-69c2-4f7c-8c6b-b411c7fd0013&embed=%7B%22ust%22%3Atrue%2C%22hv%22%3A%22CopyEmbedCode%22%7D&referrer=StreamWebApp&referrerScenario=EmbedDialog.Create).


  Currently, we can install it with a [.whl file](https://github.com/Azure/aaz-dev-tools/releases). Later on, we'll publish it to PyPI to support *pip install* way of installation.





  Please `Fork` the following repos in your github account and `Clone` them in your local disk:

     - [Azure CLI](https://github.com/Azure/azure-cli)
     - [Azure CLI Extension](https://github.com/Azure/azure-cli-extensions)
     - [AAZ](https://github.com/Azure/aaz): Used to upload the command model generated.
     - [azure-rest-api-specs](https://github.com/Azure/azure-rest-api-specs) or [azure-rest-api-specs-pr](https://github.com/Azure/azure-rest-api-specs-pr)

  After clone you can add `upstream` for every repos in your local clone by using `git remote add upstream`.




  Please install python with version >= 3.8 and <= 3.12 in your local machine.

  - For windows: You can download and run full installer from [Python Download](https://www.python.org/downloads/).
  - For linux: You can install python from Package Manager or build a stable relase from source code

  Check the version of python, make use it's not less than 3.8.
  - For windows:
      You can run:
      ```PowerShell
      C:\Users\{xxxx}\AppData\Local\Programs\Python\Python3{xxxx}\python --version
      ```
      `C:\Users\{xxxx}\AppData\Local\Programs\Python\Python3{xxxx}` is the python installation path.
  - For linux:
      ```bash
      python --version
      ```
      You can also specify the version number when you have multiple versions installed. For example if you want to run version 3.12
      ```bash
      python3.12 --version
      ```



  You can use venv to create virtual environments, optionally isolated from system site directories. Each virtual environment has its own Python binary (which matches the version of the binary that was used to create this environment) and can have its own independent set of installed Python packages in its site directories.

  You can run the following command to create a new virtual environment:
  - For windows:
      ```PowerShell
      C:\Users\{xxxx}\AppData\Local\Programs\Python\Python3{xxxx}\python -m venv {some path}\{venv name}
      ```
  - For linux:
      ```bash
      python3.12 -m venv {some path}/{venv name}
      ```



  You should __always__ active the virtual environment for azure-cli development.

  - For Windows:
      - Powershell
      ```powershell
      {some path}\{venv name}\Scripts\Activate.ps1
      ```
      - Command Prompt
      ```Command Prompt
      {some path}\{venv name}\Scripts\activate.bat
      ```
  - For Linux:
  ```bash
  source {some path}/{venv name}/bin/activate
  ```
  After active the virtual environment, the `python` command will always be the one creates this virtual environment and you can always use `python`
  ```
  python --version
  ```





  - For Windows
      - Powershell
      ```
      pip install aaz-dev
      ```
      - Command Prompt
      ```
      pip install aaz-dev
      ```
  - For linux
      ```bash
      pip install aaz-dev
      ```


  - For linux users, set up python3 build tools would avoid other unseen installation issues
    ```
    Ubuntu: apt-get install python3-dev build-essential
    Centos: yum install python3-devel
    ```




  Before start to the development task, you should always sync the code in the `dev` branch of `upstream`(Azure/Azure-cli).
  If your commands will generated to azure-cli repo, you should checkout a new branch with `feature-` prefix.


  If your commands will generated to azure-cli-extension repo, you should sync the code in the `main` branch of `upstream`(Azure/Azure-cli-extensions), and checkout a new branch with `feature-` prefix.


  Before start to the development task, you should always sync the change in the `main` branch of `upstream`, and checkout a new branch with `feature-` prefix.


  You should always run the following command everytime you sync `azure-cli` code of `upstream`.
  ```
  azdev setup --cli {path to azure-cli} --repo {path to azure-cli-extensions}
  ```



  ```bash
  aaz-dev run -c {path to azure-cli} -e {path to azure-cli-extensions} -s {path swagger or swagger-pr} -a {path to aaz}
  ```



  1. Make sure you have logined by `az login`.
  2. Make sure you have switched to the subscription for test by `az account set -s {subscription ID for test}`
  3. If your commands are in extensions, make sure you have loaded this extension by `azdev extension add {your extension name}`



  - [extension](https://github.com/Azure/azure-cli/blob/dev/doc/extensions/README.md)
  - [command guidelines](https://github.com/Azure/azure-cli/blob/dev/doc/command_guidelines.md)
  - [authoring tests](https://github.com/Azure/azure-cli/blob/dev/doc/authoring_tests.md)
  - [shorthand syntax](https://github.com/Azure/azure-cli/blob/dev/doc/shorthand_syntax.md): Azure cli shorthand syntax can help cli users to pass complicated argument values. Only the arguments of AAZ(Atomic Azure CLI) commands generated by aaz-dev tool support shorthand syntax.



  After finish the development, you should push the change in your forked repos first, and the create a Pull Request to upstream repos.

  - azure-cli: create a Pull Request to `dev` branch of `Azure/azure-cli`
  - azure-cli-extensions: create a Pull Request to `main` branch of `Azure/azure-cli-extensions`
  - aaz: create a Pull Request to `main` branch of `Azure/azz`



  If you encounter any bugs with the tool please file an issue in the [Issues](https://github.com/Azure/aaz-dev-tools/issues) section of our GitHub repository.


  ```
  MIT License

  Copyright (c) Microsoft Corporation. All rights reserved.

  Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the ""Software""), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

  The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

  THE SOFTWARE IS PROVIDED *AS IS*, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
  ```


pkgId: cbadb271545df595eae6b7fe809a86b05c2814cd22923e3e49223ad152c8f2eb
name: python-ab-plugin-scenariolink
arch: src
version: 0.1.0
epoch: 0
release: 1
summary: Activity Browser plugin to download scenario-based LCA databases
url: https://github.com/polca/ScenarioLink
rpm_group: Unspecified
rpm_buildhost: localhost
location_href: Packages/python-ab-plugin-scenariolink-0.1.0-1.src.rpm
checksum_type: sha256
description:
  ScenarioLink is a specialized plugin for the [Activity Browser](https://github.com/LCA-ActivityBrowser/activity-browser), an open-source software for Life Cycle Assessment (LCA). This plugin enables you to seamlessly fetch and reproduce scenario-based LCA databases, such as those generated by [premise](https://github.com/polca/premise), using [unfold](https://github.com/polca/unfold) datapackages.



  - Reproduce individual or multiple scenario-based databases within Activity Browser.
  - Merge multiple databases into a unified superstructure database containing various scenarios.
  - Leverage the capabilities of the `unfold` library to recreate databases with the necessary scaling factors.



  The Activity Browser builds upon the [Brightway2](https://brightway.dev) LCA framework. ScenarioLink aims to simplify the use of scenario-based LCA databases within the Activity Browser by:

  - Eliminating the need for separate tools required to generate these databases (e.g., premise).
  - Utilizing `unfold` datapackages that contain scaling factors essential for reproducing scenario-based LCA databases, assuming a consistent source database (e.g., ecoinvent 3.7.1).

  ![Flow Diagram](assets/flow_diagram.png)



  - ``activty-browser >= 2.9.7, < 2.10.0``



  1. Activate your existing Activity Browser conda environment.
  2. Install the ScenarioLink plugin using conda (preferred) or Pypi (may create conflicts with `activity-browser` dependencies):

      ```bash
      conda install -c romainsacchi ab-plugin-scenariolink
      ```

      or

      ```bash
      pip install ab-plugin-scenariolink
      ```


  4. Launch the Activity Browser.
  5. Navigate to `Tools > Plugins` and select ScenarioLink from the plugin list.





  1. Activate the plugin by selecting it from the plugin list.

      ![Plugin List](assets/plugin_list.png)

  2. After activating the plugin, select the `ScenarioLink` tab.

      ![ScenarioLink Tab](assets/scenariolink_tab.png)

  3. Select (double-click) the desired datapackage from the table.

      ![Datapackage Table](assets/datapackage_table.png)

  4. If the datapackage selected is not present in the local cache, it will be downloaded from the remote repository.
  5. Once the download is complete, a second table presents the scenarios contained in the datapackage.

      ![Scenario Table](assets/scenario_table.png)

  6. Select the desired scenario(s) by checking the corresponding checkboxes.
  7. Choose whether to merge the selected scenarios into a single database (superstructure database) or reproduce them individually.
  8. Click `Import` to start the process.
  9. The plugin will ask you to select the databases in your project that will be used as source databases.

      ![Source Database Selection](assets/source_database_selection.png)

  10. The plugin will then reproduce the selected scenario(s) and add them to your project.



  You can make your own scenario-based LCA databases available to the community.
  To do so, you need to create a `unfold` datapackage and upload it to a remote repository.
  We will then add it to the list of available datapackages in the ScenarioLink plugin.




  For questions, issues, or contributions, you can reach out to:

  - **Marc van der Meide**: [Email](mailto:m.t.van.der.meide@cml.leidenuniv.nl)
  - **Romain Sacchi**: [Email](mailto:romain.sacchi@psi.ch)

  Alternatively, you can open an issue on this GitHub repository.

rpm_license:
[cell repeats an earlier one in this file: 7357 characters]


pkgId: 0655171bb0a2153f2b2d4f0c0090937c3c54301cffc013068de7aa625dd9fc1b
name: python-ab-test-advanced-toolkit
arch: src
version: 0.0.26
epoch: 0
release: 1
url: https://github.com/dmitry-brazhenko/ab-test-advanced-toolkit
rpm_group: Unspecified
rpm_buildhost: localhost
location_href: Packages/python-ab-test-advanced-toolkit-0.0.26-1.src.rpm
checksum_type: sha256
summary:
  An experimental Python library for advanced A/B testing analysis, leveraging statistical techniques and ML for deeper insights.

description:
  [![PyPI version](https://img.shields.io/pypi/v/variatio.svg)](https://pypi.org/project/variatio/)
  [![Python](https://github.com/dmitry-brazhenko/SharpToken/actions/workflows/build-test-and-publish.yml/badge.svg?branch=main)](https://github.com/dmitry-brazhenko/SharpToken/actions/workflows/build-test-and-publish.yml)
  [![GitHub Issues](https://img.shields.io/github/issues/dmitry-brazhenko/Variatio.svg)](https://github.com/dmitry-brazhenko/Variatio/issues)
  [![License](https://img.shields.io/badge/license-MIT-blue.svg)](LICENSE)

  A/B Test Advanced Toolkit is an experimental Python library designed for advanced A/B testing analysis. It leverages statistical techniques and machine learning, including variance reduction through CUPED and integration with XGBoost for predictive insights. A/B Test Advanced Toolkit is ideal for data scientists and researchers looking to obtain deeper insights from their A/B testing efforts.



  This tool streamlines A/B testing by automatically calculating all the classic metrics behind the scenes. Simply provide your data, and it will compute the metrics you request, delivering them in a visually appealing report. Here are some of the key features:

  - **Statistical Significance Testing:** Easily compare metrics between control and test groups, with all necessary calculations done for you.
  - **CUPED Adjustments:** This experimental extension utilizes Controlled-experiment Using Pre-Experiment Data (CUPED) techniques for variance reduction. It innovatively employs user properties as covariates and leverages XGBoost regression, moving beyond traditional linear approaches to enhance A/B test sensitivity.



  ```bash
  pip install ab_test_advanced_toolkit
  ```

  or install A/B Test Advanced Toolkit directly from the source:

  ```bash
  git clone https://github.com/dmitry-brazhenko/ab-test-advanced-toolkit.git
  cd ab_test_advanced_toolkit
  pip install .
  ```



  To use A/B Test Advanced Toolkit effectively, you need to prepare three main types of data:



  The `event_data` is crucial for analysis in A/B Test Advanced Toolkit. It tracks user interactions and should include the following mandatory columns:

  - `timestamp`: The date and time when the event occurred.
  - `userid`: A unique identifier for the user who triggered the event.
  - `event_name`: The name of the event (e.g., 'login', 'purchase').

  In addition to these mandatory columns, you can include optional attributes that provide additional details about each event. For example, `purchase_value` could be used to track the value of purchase events. These optional attributes can vary based on the event type and what you aim to analyze.

  **Event Data Example:**

  | timestamp           | userid | event_name | purchase_value |
  |---------------------|--------|------------|----------------|
  | 2023-01-01 00:00:00 | 7      | purchase   | 274            |
  | 2023-01-01 01:00:00 | 4      | purchase   | 175            |
  | 2023-01-01 02:00:00 | 5      | purchase   | 179            |
  | 2023-01-01 03:00:00 | 7      | purchase   | 102            |
  | 2023-01-01 04:00:00 | 3      | login      | 0              |



  The `ab_test_allocations` dataset is essential for understanding the distribution of users across different A/B test groups. It includes the following columns:

  - `timestamp`: The date and time when the user was attributed to a specific A/B test group. This helps track when each user started experiencing the variant they were allocated to.
  - `userid`: A unique identifier for the user.
  - `abgroup`: The A/B test group the user was allocated to. This typically represents the control group (e.g., 'A') and one or more test groups (e.g., 'B', 'C').

  **Example:**

  | timestamp           | userid | abgroup |
  |---------------------|--------|---------|
  | 2022-12-15 00:00:00 | 1      | A       |
  | 2022-12-15 01:00:00 | 2      | B       |
  | 2022-12-15 02:00:00 | 3      | B       |
  | 2022-12-15 03:00:00 | 4      | B       |
  | 2022-12-15 04:00:00 | 5      | A       |



  This optional `user_properties` dataset can enhance the analysis with user demographic or behavioral data. The `userid` column must match the `event_data` and `ab_test_allocations` datasets.

  | userid | age | gender | country    | device_type | membership_status |
  |--------|-----|--------|------------|-------------|-------------------|
  | 1      | 56  | Male   | USA        | Tablet      | Free              |
  | 2      | 69  | Female | India      | Mobile      | Free              |
  | 3      | 46  | Male   | Australia  | Tablet      | Free              |
  | 4      | 32  | Female | UK         | Tablet      | Free              |
  | 5      | 60  | Male   | Germany    | Tablet      | Free              |



  After preparing your datasets, you can use `ABTestAnalyzer` to perform A/B testing analysis. Initialize the analyzer with your datasets and specify the control group:

  ```python
  from ab_test_advanced_toolkit.analyzer import ABTestAnalyzer
  import pandas as pd

  event_data = pd.DataFrame({
      "timestamp": pd.to_datetime(["2023-01-01 00:00:00", "2023-01-01 01:00:00",
                                   "2023-01-01 02:00:00",
                    "2023-01-01 03:00:00", "2023-01-01 04:00:00"]),
      "userid": [7, 4, 5, 7, 3],
      "event_name": ["purchase", "purchase", "purchase", "purchase", "login"],
      "purchase_value": [274, 175, 179, 102, 0]
  })


  user_allocations = pd.DataFrame({
      "timestamp": pd.to_datetime(["2022-12-15 00:00:00", "2022-12-15 01:00:00",
                                   "2022-12-15 02:00:00",
                    "2022-12-15 03:00:00", "2022-12-15 04:00:00"]),
      "userid": [1, 2, 3, 4, 5],
      "abgroup": ["A", "B", "B", "B", "A"]
  })


  user_properties = pd.DataFrame({
      "userid": [1, 2, 3, 4, 5],
      "age": [56, 69, 46, 32, 60],
      "gender": ["Male", "Female", "Male", "Female", "Male"],
      "country": ["USA", "India", "Australia", "UK", "Germany"],
      "device_type": ["Tablet", "Mobile", "Tablet", "Tablet", "Tablet"],
      "membership_status": ["Free", "Free", "Free", "Free", "Free"]
  })

  analyzer = ABTestAnalyzer(event_data, user_allocations, "A", user_properties, mode="gboost_cuped")
  ```

  You can then calculate various metrics such as event count per user, attribute sum per user (useful for calculating metrics like ARPU), or conversion rates to specific events:

  ```python

  analyzer.calculate_event_count_per_user('purchase')


  analyzer.calculate_event_attribute_sum_per_user('purchase', 'purchase_value')


  analyzer.calculate_conversion('login')
  ```



  After calculating the desired metrics, you can save them to an HTML file for easy viewing:

  ```python
  analyzer.save_report("abtest_report.html")
  ```

  Here's a sample report showcasing meticulously calculated metrics, organized in an easy-to-analyze table format.

  ![Metrics Example](examples/metrics_example.png)



  We welcome contributions to AB Test Advanced Toolkit! If you'd like to contribute, please follow these guidelines:

  - Fork the repository and create your feature branch.
  - Make sure your code adheres to the project's coding standards.
  - Submit a pull request with a detailed description of your changes.



  AB Test Advanced Toolkit is licensed under the MIT License. See [LICENSE](LICENSE) for more details.



  AB Test Advanced Toolkit is shared with the community as an experimental library, offered "as-is" and without any warranties. Your explorations and tests with it are encouraged, but please proceed with awareness of its experimental nature. We're keen to hear about your experiences and eager to tackle any challenges you encounter. Should you have questions or face any issues, don't hesitate to open an issue in our repository. We welcome your feedback and contributions to make AB Test Advanced Toolkit even better!



  ```bash
  pytest
  ```

rpm_license:
  MIT License  Copyright (c) 2024 Dmitry Brazhenko  Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:  The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.  THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.


pkgId: be0961b7759f918ae2bcd4af8054dcd29ec2c2c519151b88c1c78c3fcd267ddb
name: python-ab-testing-analysis
arch: src
version: 1.2.8
epoch: 0
release: 1
url: https://ab-testing-analysis.readthedocs.io/en/latest/index.html
rpm_license: MIT License
rpm_group: Unspecified
rpm_buildhost: localhost
location_href: Packages/python-ab-testing-analysis-1.2.8-1.src.rpm
checksum_type: sha256
summary:
  AB test analysis toolbox for analyzing and reporting the results of an ab test experiment. It provides the functions to analyze the ab test result of an experiment.

description:
  A/B testing is process which allows developer/data scientist to analyze and evaluate, the performance of products in an experiment. In this process two or more versions of a variable (web page, page element, products etc.) are shown to different segments of website visitors at the same time to determine which version leaves the maximum impact and drives business metrics.
  In A/B testing, **A** refers to the original testing variable. Whereas **B** refers to a new version of the original testing variable. Impact of the results can be evaluated based on,
  + Conversion Rate


pkgId: ff61593d50b0ceb491015e835101f1ebbd58dac0ec5c77ca2b44858212331bc7
name: python-ab5
arch: src
version: 0.7
epoch: 0
release: 1
summary: print ascii art with gratient colors
url: https://github.com/xxa2005/
rpm_license: MIT License
rpm_group: Unspecified
rpm_buildhost: localhost
location_href: Packages/python-ab5-0.7-1.src.rpm
checksum_type: sha256
description:
  UwU

  there is vertical and horizontal gratients you can use


  > vertical example:
  ```py
  from ab5 import vgratient

  logo = '''
     __  __         __  __
    / / / /      __/ / / /
   / / / / | /| / / / / /
  / /_/ /| |/ |/ / /_/ /
  \____/ |__/|__/\____/
                          '''


  start_color=[0,223,50]
  end_color=[0,25,222]

  print(vgratient(logo,start_color,end_color))
  ```

  <p align="center">
    <img src="https://cdn.discordapp.com/attachments/790977863847116830/980557615413219388/unknown.png">
  </p>



  > horizontal example:
  ```py
  from ab5 import hgratient

  logo = '''
     __  __         __  __
    / / / /      __/ / / /
   / / / / | /| / / / / /
  / /_/ /| |/ |/ / /_/ /
  \____/ |__/|__/\____/
                          '''


  start_color=[0,223,50]
  end_color=[0,25,222]

  print(hgratient(logo,start_color,end_color))
  ```

  <p align="center">
    <img src="https://cdn.discordapp.com/attachments/790977863847116830/982396318515339284/unknown.png">
  </p>


pkgId: 74f61c53a0205e0509ca02c8a4a5bedd96be6f95b04b026185ab89b57a7d17cf
name: python-aba-cli-scrapper
arch: src
version: 0.7.6
epoch: 0
release: 1
summary: Create your own Alibaba dataset and interact with it in plain English.
url: https://aba-cli-scrapper.readthedocs.io/en/latest/
rpm_license: GNU GENERAL PUBLIC LICENSEVersion 3, 29 June 2007
rpm_group: Unspecified
rpm_buildhost: localhost
location_href: Packages/python-aba-cli-scrapper-0.7.6-1.src.rpm
checksum_type: sha256
description:
  <p align="center"> <b> Create your own Alibaba dataset and interact with it in plain English. </b> </p>
  <div align="center">
  ![PyPI - Version](https://img.shields.io/pypi/v/aba-cli-scrapper) ![PyPI - Downloads](https://img.shields.io/pypi/dm/aba-cli-scrapper?label=PyPI-Downloads)  ![GitHub Release Date](https://img.shields.io/github/release-date/poneoneo/Alibaba-CLI-Scrapper)
  </div>
  <div align="center">
  ![PyPI - Python Version](https://img.shields.io/pypi/pyversions/aba-cli-scrapper) ![GitHub License](https://img.shields.io/github/license/poneoneo/Alibaba-CLI-Scrapper)
  </div>
  <div align="center">
  ![Codacy grade](https://img.shields.io/codacy/grade/bbecd0598d5e460ea87e3aa5f8db8798)


pkgId: 6c145d8f9ff96852beacb5cefd83a1663a0a5e910037a14b5abbf20e704bb1ee
name: python-abacus-icalc
arch: src
version: 0.2.3
epoch: 0
release: 1
summary: An interactive algebra calculator built in Python using Python
url: https://pypi.org/project/abacus-icalc/
rpm_license: None
rpm_group: Unspecified
rpm_buildhost: localhost
location_href: Packages/python-abacus-icalc-0.2.3-1.src.rpm
checksum_type: sha256
description:
  [![PyPI version](https://badge.fury.io/py/abacus-icalc.svg)](https://badge.fury.io/py/abacus-icalc)

  Powerful interactive calculator *made in Python using Python with Python support*


  To install Abacus run the following command with pip installed

  ```shell
  python -m pip install abacus-icalc[ipython]
  ```


  Another option is to install the latest version from master branch
  ```shell
  python -m pip install abacus-icalc[ipython]@https://github.com/sandorex/abacus.git
  ```

  For other branches append `@branch` to the url like so
  ```shell
  python -m pip install abacus-icalc[ipython]@git+https://github.com/sandorex/abacus.git@branch
  ```


  IPython is currently recommended way of using Abacus as it has all the features, i am planning making many features available without it too but it requires a lot of effort and time so it will have to wait


  The project is meant to be an interactive algebra calculator with scripting support

  There are plenty of things i wanted to add (or may add in the future) like:
  - Unit support / conversion, this is kinda supported using sympy units but is not very intuitive and easy to use
  - GUI, this is planned but i am putting it off as its not a priority


  Python is considered first class citizen and should always be supported in Abacus, if you encounter python code that doesn't run cause of syntax errors that is a bug and please report it


  TODO


pkgId: cc3c9c3df5138797c3113004a0e335936dacd0e88595f7574ee3e9e8a8710035
name: python-abacus-minimal
arch: src
version: 0.12.0
epoch: 0
release: 1
summary: Ledger in Python that follows corporate accounting rules.
url: https://pypi.org/project/abacus-minimal/
rpm_license: MIT
rpm_group: Unspecified
rpm_buildhost: localhost
location_href: Packages/python-abacus-minimal-0.12.0-1.src.rpm
checksum_type: sha256
description:
  ![PyPI - Version](https://img.shields.io/pypi/v/abacus-minimal?color=blue)

  `abacus-minimal` is an accounting logic library that aims to be concise, correct and expressive in implementation of double entry book-keeping rules.



  ```bash
  pip install abacus-minimal
  ```

  Latest:

  ```bash
  pip install git+https://github.com/epogrebnyak/abacus-minimal.git
  ```



  A company starts with $500 from shareholders,
  buys merchandise for $200,
  sells it all for $400,
  and then pays $150 in salaries to its staff.

  We programmatically run the accounting workflow within
  one reporting period for this company and show end of period reports.

  ```python
  from abacus import Book, Chart, Entry

  chart = Chart(
      retained_earnings="retained_earnings",
      current_earnings="current_earnings",
      assets=["cash", "inventory"],
      capital=["equity"],
      income=["sales"],
      expenses=["salaries", "cogs"],
  )
  book = Book(chart)
  entries = [
      Entry("Initial shareholder funds").debit("cash", 500).credit("equity", 500),
      Entry("Acquired goods").debit("inventory", 200).credit("cash", 200),
      Entry("Accepted payment for goods").debit("cash", 400).credit("sales", 400),
      Entry("Shipped goods").debit("cogs", 200).credit("inventory", 200),
      Entry("Paid salaries").debit("salaries", 150).credit("cash", 150),
  ]
  book.post_many(entries)
  book.close()
  print(book.income_statement)
  print(book.balance_sheet)

  assert book.balance_sheet.assets.total == 550
  assert book.income_statement.net_earnings == 50
  assert book.balances == {"cash": 550, "inventory": 0, "equity": 500, "retained_earnings": 50}
  ```



  `abacus-minimal` adheres to the following interpretation of double-entry book keeping rules.

  1. The value of company property, or assets, equals to shareholder and creditor claims on the company:

  ```
  Assets = Capital + Liabilities
  ```

  Note that capital can be seen as the residual claim:

  ```
  Capital = Assets - Liabilities
  ```

  2. Company current earnings, or profit, within reporting period equal to income less expenses associated with generating this income:

  ```
  Current earnings = Income - Expenses
  ```

  3. Capital consists of shareholder equity, other capital accounts and
     retained earnings:

  ```
  Capital = Shareholder Equity + Other Capital + Retained earnings
  ```

  4. Current earnings accumulate to retained earnings:

  ```
  Retained earnings = Retained earnings from previous period + Current earnings
  ```

  5. Substituting we get a form of extended accounting equation:

  ```
  Assets + Expenses = Shareholder Equity + Other Capital + Retained earnings + Income + Liabilities
  ```

  6. Our book-keeping goal is to reflect business events as changes to the variables in this
     equation.




  The steps for using `abacus-minimal` follow the steps of a typical accounting cycle:

  - create a chart of accounts,
  - open ledger for the current reporting period,
  - post account balances for the previous period,
  - post entries that reflect business transactions within the period,
  - post reconciliation and adjustment entries,
  - close accounts at reporting period end,
  - make post-close entries,
  - show financial reports,
  - save account balances data for the next reporting period.

  Accounts survive these transformations quite differently, here is a summary:

  | Step                                                      |  Assets   |  Expenses  | Shareholder Equity | Retained Earnings | Current Earnings |   Income   | Liabilities |
  | --------------------------------------------------------- | :-------: | :--------: | :----------------: | :---------------: | :--------------: | :--------: | :---------: |
  | Account type                                              | permanent | temporary  |     permanent      |     permanent     |    temporary     | temporary  |  permanent  |
  | 1\. In empty ledger all accounts have zero balances       |     0     |     0      |         0          |         0         |        0         |     0      |      0      |
  | 2\. Opening balances restore permanent accounts           |   **+**   |     0      |       **+**        |       **r**       |        0         |     0      |    **+**    |
  | 3\. Business entries affect all accounts except earnings  |     +     |     e      |         +          |         r         |        0         |     i      |      +      |
  | 4\. Closing income and expense to current earnings        |     +     | **closed** |         +          |         r         |     **i-e**      | **closed** |      +      |
  | 5\. Closing current to retained earings                   |     +     |            |         +          |   **r + i -e**    |    **closed**    |            |      +      |
  | 6\. Saving permanent account balances for the next period |     +     |            |         +          |         +         |                  |            |      +      |

  The results in step 6 are the inputs to step 2 in the next reporting period.



  In this example we use more features including:

  - contra accounts specification,
  - opening ledger with account balances at the start of reporting period,
  - posting multiple entries and using various types of syntax for an entry,
  - showing proxy income statement and balance sheet before closing,
  - saving and loading data to JSON files.

  The complete code is in [readme.py](examples/readme.py).



  Steps involved:

  - specify names of the current earnings and retained earnings accounts,
  - add account names for assets, capital, liabilities, income and expenses,
  - add contra accounts (e.g. `refunds` is a contra account to `sales`).

  Code example:

  ```python
  from abacus import Chart

  chart = Chart(
      retained_earnings="retained_earnings",
      current_earnings="current_earnings",
      assets=["cash", "ar"],
      capital=["equity"],
      liabilities=["vat_payable"],
      income=["sales"],
      expenses=["salaries"],
  )
  chart.offset("sales", "refunds")
  chart.name("ar", "Accounts receivable")
  ```

  `Chart` class is a `pydantic` model, which means it is easily converted to a JSON file.
  You can save or load a chart from a file.

  ```python
  chart.save("chart.json")
  chart = Chart.load("chart.json")
  ```



  Steps involved:

  - create a data structure that represents state of accounts (a 'book'),
  - record account starting balances from the previous period,

  Let's create a book with opening balances known from previous period:

  ```python
  from abacus import Book

  book = Book(chart)
  opening_balances = {
      "cash": 10_000,
      "equity": 8_000,
      "retained_earnings": 2_000
      }
  book.open(opening_balances)
  ```

  At this point the book is ready to record new entries.



  Steps involved:

  - record entries that represent business transactions,
  - show state of ledger (as trial balance or as account balances) at any time.

  Each entry has a title and directions to alter the accounts that are called debits and credits.
  The sum of debits should match the sum of credits for a valid entry.
  The `Entry` class provides several ways to record the composition of an entry as shown below.

  ```python
  from abacus import Entry

  entries = [
      Entry("Invoice with VAT").debit("ar", 6000).credit("sales", 5000).credit("vat_payable", 1000),
      Entry("Cash payment").debit("cash", 6000).credit("ar", 6000),
      Entry("Cashback").double(debit="refunds", credit="cash", amount=500),
      Entry("Paid salaries").set_amount(1500).debit("salaries").credit("cash"),
  ]


  book.post_many(entries)
  ```

  Note: there are no reconciliations, adjustments and post-close entries in this example.



  After posting entries you can inspect the trial balance or account balances:

  ```python

  print(book.trial_balance)
  print(book.balances)


  assert book.balances == {
      "cash": 14000,
      "ar": 0,
      "equity": 8000,
      "vat_payable": 1000,
      "sales": 5000,
      "refunds": 500,
      "salaries": 1500,
      "current_earnings": 0,
      "retained_earnings": 2000,
  }
  ```



  Closing accounts at period end involves:

  - closing contra accounts related to income and expense accounts, and
  - closing income and expense accounts to retained earnings.

  See section below for code for closing accounts.

  Note: account closing was a surprisingly hard part of `abacus-minimal` code that I had to refactor several times.



  Financial reports are typically displayed after account closing,
  but proxy reports are available before closing as well:

  - **The income statement** will be the same before and after closing.
  - **The balance sheet before closing** the will contain current earnings account
    and retained earnings from previous periods.
  - **After closing** the current earnings account will be transferred to the retained earnings account and removed from the ledger; it will not appear in the balance sheet.

  Expect to see a lot of dictionary-like data structures in code output below:

  ```python
  print("=== Before closing ===")
  print(book.income_statement)
  print(book.balance_sheet)
  assert book.balance_sheet.capital["current_earnings"] == 3000


  book.close()

  print("=== After closing ===")
  print(book.income_statement)
  print(book.balance_sheet)


  print(book.balances)
  assert book.balances == {
      "cash": 14000,
      "ar": 0,
      "equity": 8000,
      "vat_payable": 1000,
      "retained_earnings": 5000,
  }
  ```



  You can save the list of entries and the period end account balances to JSON files, unless these files already exist (save files to a different folder or under a different name in that case).

  ```python

  book.store.save("./entries.json")
  book.balances.save("./end_balances.json")
  ```





  In `abacus-minimal` there is a small core library that consists of:

  - `ChartDict` maps account names to their types,
  - `Ledger` class maps account names to debit normal and credit normal T-accounts, and
  - `Posting` type that represents a double or a multiple entry.

  `Ledger` is created from `ChartDict` and incoming entries change the state of ledger.
  `ChartDict` allows to create closing entries at accounting period end.
  Trial balance, account balances, balance sheet and income statement reports
  reflect the state of ledger.



  As a user you do not have to interact with the core library directly.
  `abacus-minmal` exports `Chart`, `Entry` and `Book` classes that we used in the examples.
  The `Book` class holds together a chart, a store of entries, and a ledger and allows posting entries, closing the accounts, creating reports and saving and loading JSON files.



  Several assumptions and simplifications are used to make `abacus-minimal` easier to develop and reason about.

  The key assumptions are:

  - one currency,
  - globally unique account names,
  - one level of accounts in chart and no account aggregation for reports,
  - no treatment of other comprehensive income,
  - no changes in equity and cash flow statements.

  See [core.py](abacus/core.py) module docstring for more details.



  `abacus-minimal` takes a lot of inspiration from the following projects:

  - [ledger](https://ledger-cli.org/),
    [hledger](https://github.com/simonmichael/hledger),
    [beancount](https://github.com/beancount/beancount)
    and other [plain text accounting tools](https://plaintextaccounting.org/),
  - [medici](https://github.com/flash-oss/medici), a high performance ledger in JavaScript using Mongo database,
  - [microbooks](https://microbooks.io/) API and [python-accounting](https://github.com/ekmungai/python-accounting), a production-grade project, tightly coupled to a database.



  If you are totally new to accounting the suggested friendly course is <https://www.accountingcoach.com/>.

  ACCA and CPA are the international and the US professional qualifications and IFRS and US GAAP are the standards for accounting recognition, measurement and disclosure.

  A great overview of accounting concepts is at IFRS
  [Conceptual Framework for Financial Reporting]
  (https://www.ifrs.org/content/dam/ifrs/publications/pdf-standards/english/2021/issued/part-a/conceptual-framework-for-financial-reporting.pdf).

  Part B-G in the [ACCA syllabus for the FFA exam](https://www.accaglobal.com/content/dam/acca/global/PDF-students/acca/f3/studyguides/fa-ffa-syllabusandstudyguide-sept23-aug24.pdf) talk about what `abacus-minimal` is designed for.

  Textbooks:

  - [list of free and open source textbooks](https://library.sacredheart.edu/opentextbooks/accounting)
  - [Frank Wood "Business Accounting"](https://www.google.com/search?q=Frank+Wood+%22Business+Accounting)
  - ["200 Years of Accounting History Dates and Events"](https://maaw.info/AccountingHistoryDatesAndEvents.htm)



  I use [`just` command runner](https://github.com/casey/just) to automate code maintenance tasks in this project.

  `just test` and `just fix` scripts will run the following tools:

  - `pytest`
  - `mypy`
  - `black` and `isort --float-to-top` (probably should replace with `ruff format`)
  - `ruff check`
  - `prettier` for markdown formatting
  - `codedown` to extract Python code from README.md.

  `examples/readme.py` is overwritten by the `just readme` command.

  I use `poetry` as a package manager, but heard good things about `uv` that I want to try.



  - `0.12.0` (2024-11-13) `events.py` offers events-based ledger modification.
  - `0.11.1` (2024-11-06) `abacus.core` now feature complete.
  - `0.10.7` (2024-11-02) `Posting` type is a list of single entries.
  - `0.10.5` (2024-10-27) Handles income statement and balances sheet before and after close.
  - `0.10.0` (2024-10-24) Separates core, chart, entry and book code and tests.





  Implanting `abacus-minimal` as a dependency to:

  - [ ] [abacus-py][cli],
  - [ ] [abacus-streamlit][app].



  - [ ] Business event layer `Event("Invoice", net_amount=200, vat=40)`
  - [ ] `Book.increase()` and `Book.decrease()` methods
  - [ ] `Entry.explain()` method



  - [ ] real company - eg Walmart accounts
  - [ ] business simulation layer - stream of entries
  - [ ] more examples from textbooks
  - [ ] chart repository and conversions between charts of accounts as requested in [#4][ras].
  - [ ] a quiz based on Book class - play entries and expect the use picks correct debit and credit

  [cli]: https://github.com/epogrebnyak/abacus
  [app]: https://abacus.streamlit.app/
  [ras]: https://github.com/epogrebnyak/abacus/issues/4


pkgId: fd294bae63f4a9a5654a66c4f8a0dca9a34e6d1895b0a8e32adfa650a9500eb2
name: python-abacus-minimal
arch: src
version: 0.14.0
epoch: 0
release: 1
summary: Ledger in Python that follows corporate accounting rules.
url: https://pypi.org/project/abacus-minimal/
rpm_license: MIT
rpm_group: Unspecified
rpm_buildhost: localhost
location_href: Packages/python-abacus-minimal-0.14.0-1.src.rpm
checksum_type: sha256
description:
  ![PyPI - Version](https://img.shields.io/pypi/v/abacus-minimal?color=blue)

  `abacus-minimal` aims to be concise, correct and expressive in implementation of double entry book-keeping rules.

  Accounting logic should be possible to express in good code. Progress and notable features
  so far are:

  - event-based ledger,
  - contra accounts,
  - period end closing,
  - saving and loading from JSON,
  - income statement and balance sheet before and after close.



  ```bash
  pip install abacus-minimal
  ```

  Latest:

  ```bash
  pip install git+https://github.com/epogrebnyak/abacus-minimal.git
  ```



  `abacus-minimal` provides a accounting journal (ledger) that is controlled by
  events:

  - chart of account changes,
  - business transactions, and
  - closing entries.

  Given a sequence of events you can always recreate the ledger state from scratch.

  Аccount creation, double entries and a command to close
  accounts at period end are part the `events` list
  in an example below.

  ```python
  from abacus import Asset, Double, Equity, Expense, Income, Ledger, Close

  events = [
      
      Asset("cash"),
      Equity("equity"),
      Equity("re", title="Retained earnings"),
      Income("sales"),
      Expense("salaries"),
      
      Double("cash", "equity", 1000),
      Double("cash", "sales", 250),
      Double("salaries", "cash", 150),
      
      Close(earnings_account="re")
  ]
  ledger = Ledger.from_list(events)
  ```

  The reports reflect the resulting state of ledger:

  ```python
  print(ledger.balances)
  print(ledger.income_statement())
  print(ledger.balance_sheet())
  ```

  Ledger history can be saved to a JSON file.



  There are six types of 'primitive' events in `abacus-minimal`:

  - add account or contra account,
  - debit or credit account,
  - drop account, and
  - mark period end.

  All compound event types translate to primitives.

  In example above you can extract the primitives as following:

  ```python
  for p in ledger.history.primitives:
     print(p)
  ```



  You can also work with higher-level `Chart`, `Book` and `Entry` classes.

  Consider an example where you need to process the following transactions
  and show end reports:

  - a company gets $1000 equity investment from shareholders,
  - bills a client $1000 plus 20% value added tax (VAT) for services,
  - company makes a $150 refund,
  - pays $450 in salaries to the staff.

  ```python
  from abacus import Book, Chart, Entry


  chart = Chart(
      assets=["cash", "ar"],
      equity=["equity"],
      liabilities=["tax_due"],
      income=["services"],
      expenses=["salaries"],
      retained_earnings="retained_earnings",
      contra_accounts={"services": ["refunds"]})
  book = Book.from_chart(chart)


  entries = [
      Entry("Shareholder investment").double("cash", "equity", 1000),
      Entry("Incoice for services")
         .debit("ar", 1200)
         .credit("services", 1000)
         .credit("tax_due", 200),
      Entry("Made refund").double("refunds", "cash", 150)
      Entry("Paid salaries").double("salaries", "cash", 450),
  ]
  book.post_many(entries)
  print(book.balances)


  book.close()
  print(book.income_statement)
  print(book.balance_sheet)
  ```



  All data structures used are serialisable. You can write code to create a chart of accounts and a ledger, save them to JSONs or pick up data from the JSON files, restore the ledger, work on it, save again and so on.

  ```python

  book.chart.save("chart.json", allow_overwrite=True)
  book.ledger.history.save("history.json", allow_overwrite=True)


  book2 = Book.load("history.json")
  print(book2) # not fully identical to `book` yet
  ```



  In `abacus-minimal` there are regular accounts of five types: asset, liability, equity, income, expense. Contra accounts to regular accounts are possible (eg depreciation, discounts).

  Period end closes temporary accounts (income, expense and their associated contra accounts),
  but balance sheet and income statement are available before and after close.

  Post close entries are allowed on permanent accounts.



  The steps for using `abacus-minimal` follow the steps of a typical accounting cycle:

  - create a chart of accounts,
  - open ledger for the current reporting period,
  - post account balances for the previous period,
  - post entries that reflect business transactions within the period,
  - post reconciliation and adjustment entries,
  - close accounts at reporting period end,
  - make post-close entries,
  - show financial reports,
  - save account balances data for the next reporting period.



  `abacus-minimal` adheres to the following interpretation of accounting identity.

  1. The value of company property, or assets, equals to shareholder and creditor claims on the company:

  ```
  Assets = Equity + Liabilities
  ```

  Equity is the residual claim after creditors:

  ```
  Equity = Assets - Liabilities
  ```

  2. Company current earnings, or profit, equal to income less expenses associated with generating this income:

  ```
  Current Earnings = Income - Expenses
  ```

  Current earnings accumulate to retained earnings:

  ```
  Retained Earnings = Retained Earnings From Previous Period + Current Earnings
  ```

  3. Equity consists of shareholder equity, other equity accounts and
     retained earnings:

  ```
  Equity = Shareholder Equity + Other Equity + Retained Earnings
  ```

  4. Substituting we get a form of extended accounting equation:

  ```
  Assets + Expenses =
     Shareholder Equity + Other Equity + Retained Earnings + Income + Liabilities
  ```

  Our book-keeping goal is to reflect business events as changes to the variables
  while maintaining this equation.



  Several assumptions and simplifications are used to make `abacus-minimal` easier to develop and reason about:

  - one currency
  - one reporting period
  - one level of accounts, no sub-accounts
  - no account aggregation for reports
  - account names must be globally unique (eg cannot have two accounts named "other")
  - chart always has current earnings account and retained earnings account
  - period end closing will transfer current earnings to retained earnings
  - no account durations, current vs non-current accounts not distinguished
  - other comprehensive income account (OCIA) not calculated
  - no revaluations
  - no intermediate accounts except current earnings
  - accounts either debit normal or credit normal, no mixed accounts
  - no journals, entries are posted to ledger directly
  - an entry can touch any accounts
  - entry amount can be positive, negative or zero
  - net earnings are income less expenses, no gross profit or earnings before tax calculated
  - no cash flow statement
  - no statement of changes in equity
  - no date or any transaction metadata recorded



  `abacus-minimal` takes a lot of inspiration from the following projects:

  - [ledger](https://ledger-cli.org/),
    [hledger](https://github.com/simonmichael/hledger),
    [beancount](https://github.com/beancount/beancount)
    and other [plain text accounting tools](https://plaintextaccounting.org/),
  - [medici](https://github.com/flash-oss/medici), a high performance ledger in JavaScript using Mongo database,
  - [microbooks](https://microbooks.io/) API and [python-accounting](https://github.com/ekmungai/python-accounting), a production-grade project, tightly coupled to a database.



  If you are totally new to accounting the suggested friendly course is <https://www.accountingcoach.com/>.

  ACCA and CPA are the international and the US professional qualifications and IFRS and US GAAP are the standards for accounting recognition, measurement and disclosure.

  A great overview of accounting concepts is at
  [IFRS Conceptual Framework for Financial Reporting]
  (https://www.ifrs.org/content/dam/ifrs/publications/pdf-standards/english/2021/issued/part-a/conceptual-framework-for-financial-reporting.pdf).

  Part B-G in the [ACCA syllabus for the FFA exam](https://www.accaglobal.com/content/dam/acca/global/PDF-students/acca/f3/studyguides/fa-ffa-syllabusandstudyguide-sept23-aug24.pdf) talk about what `abacus-minimal` is designed for.

  Textbooks and articles:

  1. [list of free and open source textbooks](https://library.sacredheart.edu/opentextbooks/accounting)
  2. [Frank Wood "Business Accounting"](https://www.google.com/search?q=Frank+Wood+%22Business+Accounting)
  3. ["200 Years of Accounting History Dates and Events"](https://maaw.info/AccountingHistoryDatesAndEvents.htm)



  I use [`just` command runner](https://github.com/casey/just) to automate code maintenance tasks in this project.

  `just test` and `just fix` scripts will run the following tools:

  - `pytest`
  - `mypy`
  - `black` and `isort --float-to-top` (probably should replace with `ruff format`)
  - `ruff check`
  - `prettier` for markdown formatting
  - `codedown` to extract Python code from README.md.

  `examples/readme.py` is overwritten by the `just readme` command.

  I use `poetry` as a package manager, but heard good things about `uv` that I want to try.



  - `0.14.0` (2024-11-15) Event-based ledger now on `main`. Mixed test suite and `pyright`.
  - `0.13.0` (2024-11-15) Event-based ledger will become next minor version
  - `0.12.0` (2024-11-13) `events.py` offers events-based ledger modification.
  - `0.11.1` (2024-11-06) `abacus.core` now feature complete.
  - `0.10.7` (2024-11-02) `Posting` type is a list of single entries.
  - `0.10.5` (2024-10-27) Handles income statement and balances sheet before and after close.
  - `0.10.0` (2024-10-24) Separates core, chart, entry and book code and tests.


pkgId: 5f5bbdaef2af189f13a3db7c9d8cbeb8678b445043a719654183a94b454fb00b
name: python-abacus-minimal
arch: src
version: 0.14.2
epoch: 0
release: 1
summary: Ledger in Python that follows corporate accounting rules.
url: https://pypi.org/project/abacus-minimal/
rpm_license: MIT
rpm_group: Unspecified
rpm_buildhost: localhost
location_href: Packages/python-abacus-minimal-0.14.2-1.src.rpm
checksum_type: sha256
description:
  ![PyPI - Version](https://img.shields.io/pypi/v/abacus-minimal?color=blue)

  Accounting logic should be possible to express in good code.
  `abacus-minimal` aims to be concise, correct and expressive in implementation of double entry book-keeping rules.

  Progress and notable features so far:

  - event-based ledger,
  - contra accounts,
  - period end closing,
  - income statement and balance sheet before and after closing,
  - saving and loading from JSON.



  ```bash
  pip install abacus-minimal
  ```

  <details>

  Latest:

  ```bash
  pip install git+https://github.com/epogrebnyak/abacus-minimal.git
  ```

  </details>



  `abacus-minimal` provides an accounting ledger that is controlled by
  events:

  - chart of account changes,
  - business transactions, and
  - closing entries.

  Given a sequence of events you can always recreate the ledger state from scratch.

  Аccount creation, double entries and a command to close
  accounts are in the `events` list in an example below.

  ```python
  from abacus import Asset, Double, Equity, Expense, Income, Ledger, Close

  events = [
      
      Asset("cash"),
      Equity("equity"),
      Equity("re", title="Retained earnings"),
      Income("sales"),
      Expense("salaries"),
      
      Double("cash", "equity", 1000),
      Double("cash", "sales", 250),
      Double("salaries", "cash", 150),
      
      Close(earnings_account="re")
  ]
  ledger = Ledger.from_list(events)
  ```

  Reports reflect the state of ledger:

  ```python
  print(ledger.balances)
  print(ledger.income_statement())
  print(ledger.balance_sheet())
  ```

  Ledger history can be saved to a JSON file.



  There are six types of 'primitive' events in `abacus-minimal`:

  - add account or contra account,
  - debit or credit account,
  - drop account, and
  - mark period end.

  All compound event types translate to primitives.

  In example above you can extract the primitives as following:

  ```python
  for p in ledger.history.primitives:
     print(p)
  ```



  You can also work with higher-level `Chart`, `Book` and `Entry` classes.

  Consider an example where you need to process the following transactions
  and show end reports:

  - a company gets $1000 equity investment from shareholders,
  - bills a client $1000 plus 20% value added tax (VAT) for services,
  - receives $600 installment payment,
  - makes a $150 refund,
  - pays $450 in salaries to the staff.

  ```python
  from abacus import Book, Chart, Entry


  chart = Chart(
      assets=["cash", "ar"],
      equity=["equity"],
      liabilities=["tax_due"],
      income=["services"],
      expenses=["salaries"],
      contra_accounts={"services": ["refunds"]},
      retained_earnings="retained_earnings",
      current_earnings="current_earnings")
  book = Book.from_chart(chart)


  entries = [
      Entry("Shareholder investment").double("cash", "equity", 1000),
      Entry("Invoiced services")
         .debit("ar", 1200)
         .credit("services", 1000)
         .credit("tax_due", 200),
      Entry("Accepted payment").double("cash", "ar", 600),
      Entry("Made refund").double("refunds", "cash", 150),
      Entry("Paid salaries").double("salaries", "cash", 450),
  ]
  book.post_many(entries)
  print(book.balances)


  book.close()
  print(book.income_statement)
  print(book.balance_sheet)
  ```



  All data structures used are serialisable. You can write code to create a chart of accounts and a ledger, save them to JSONs or pick up data from the JSON files, restore the ledger, work on it, save again and so on.

  ```python

  book.save("chart.json", "history.json", allow_overwrite=True)


  book2 = Book.load_unsafe("chart.json", "history.json")

  from pprint import pprint
  pprint(book2) # may not fully identical to `book` yet
  ```



  In `abacus-minimal` there are regular accounts of five types: asset, liability, equity, income, expense. Contra accounts to regular accounts are possible (eg depreciation, discounts).

  Period end closes temporary accounts (income, expense and their associated contra accounts),
  but balance sheet and income statement are available before and after close.

  Post close entries are allowed on permanent accounts.



  The steps for using `abacus-minimal` follow the steps of a typical accounting cycle:

  - create a chart of accounts,
  - open ledger for the current reporting period,
  - post account balances for the previous period,
  - post entries that reflect business transactions within the period,
  - post reconciliation and adjustment entries,
  - close accounts at reporting period end,
  - make post-close entries,
  - show financial reports,
  - save account balances data for the next reporting period.



  `abacus-minimal` adheres to the following interpretation of accounting identity.

  1. The value of company property, or assets, equals to shareholder and creditor claims on the company:

  ```
  Assets = Equity + Liabilities
  ```

  Equity is the residual claim after creditors:

  ```
  Equity = Assets - Liabilities
  ```

  2. Company current earnings, or profit, equal to income less expenses associated with generating this income:

  ```
  Current Earnings = Income - Expenses
  ```

  Current earnings accumulate to retained earnings:

  ```
  Retained Earnings = Retained Earnings From Previous Period + Current Earnings
  ```

  3. Equity consists of shareholder equity, other equity accounts and
     retained earnings:

  ```
  Equity = Shareholder Equity + Other Equity + Retained Earnings
  ```

  4. Substituting we get a form of extended accounting equation:

  ```
  Assets + Expenses =
     Shareholder Equity + Other Equity + Retained Earnings + Income + Liabilities
  ```

  Our book-keeping goal is to reflect business events as changes to the variables
  while maintaining this equation.



  Several assumptions and simplifications are used to make `abacus-minimal` easier to develop and reason about:

  - one currency
  - one reporting period
  - one level of accounts, no sub-accounts
  - no account aggregation for reports
  - account names must be globally unique (eg cannot have two accounts named "other")
  - chart always has current earnings account and retained earnings account
  - period end closing will transfer current earnings to retained earnings
  - no account durations, current vs non-current accounts not distinguished
  - other comprehensive income account (OCIA) not calculated
  - no revaluations
  - no intermediate accounts except current earnings
  - accounts either debit normal or credit normal, no mixed accounts
  - no journals, entries are posted to ledger directly
  - an entry can touch any accounts
  - entry amount can be positive, negative or zero
  - net earnings are income less expenses, no gross profit or earnings before tax calculated
  - no cash flow statement
  - no statement of changes in equity
  - no date or any transaction metadata recorded



  `abacus-minimal` takes a lot of inspiration from the following projects:

  - [ledger](https://ledger-cli.org/),
    [hledger](https://github.com/simonmichael/hledger),
    [beancount](https://github.com/beancount/beancount)
    and other [plain text accounting tools](https://plaintextaccounting.org/),
  - [medici](https://github.com/flash-oss/medici), a high performance ledger in JavaScript using Mongo database,
  - [microbooks](https://microbooks.io/) API and [python-accounting](https://github.com/ekmungai/python-accounting), a production-grade project, tightly coupled to a database.



  If you are totally new to accounting the suggested friendly course is <https://www.accountingcoach.com/>.

  ACCA and CPA are the international and the US professional qualifications and IFRS and US GAAP are the standards for accounting recognition, measurement and disclosure.

  A great overview of accounting concepts is at
  [IFRS Conceptual Framework for Financial Reporting]
  (https://www.ifrs.org/content/dam/ifrs/publications/pdf-standards/english/2021/issued/part-a/conceptual-framework-for-financial-reporting.pdf).

  Part B-G in the [ACCA syllabus for the FFA exam](https://www.accaglobal.com/content/dam/acca/global/PDF-students/acca/f3/studyguides/fa-ffa-syllabusandstudyguide-sept23-aug24.pdf) talk about what `abacus-minimal` is designed for.

  Textbooks and articles:

  1. [list of free and open source textbooks](https://library.sacredheart.edu/opentextbooks/accounting)
  2. [Frank Wood "Business Accounting"](https://www.google.com/search?q=Frank+Wood+%22Business+Accounting)
  3. ["200 Years of Accounting History Dates and Events"](https://maaw.info/AccountingHistoryDatesAndEvents.htm)



  I use [`just` command runner](https://github.com/casey/just) to automate code maintenance tasks in this project.

  `just test` and `just fix` scripts will run the following tools:

  - `pytest`
  - `mypy`
  - `black` and `isort --float-to-top` (probably should replace with `ruff format`)
  - `ruff check`
  - `prettier` for markdown formatting
  - `codedown` to extract Python code from README.md.

  `examples/readme.py` is overwritten by the `just readme` command.

  I use `poetry` as a package manager, but heard good things about `uv` that I want to try.



  - `0.14.2` (2024-11-23) Added `just sql` command to run database examples.
  - `0.14.0` (2024-11-15) Event-based ledger now on `main`. Mixed test suite and `pyright`.
  - `0.13.0` (2024-11-15) Event-based ledger will become next minor version.
  - `0.12.0` (2024-11-13) `events.py` offers events-based ledger modification.
  - `0.11.1` (2024-11-06) `abacus.core` now feature complete.
  - `0.10.7` (2024-11-02) `Posting` type is a list of single entries.
  - `0.10.5` (2024-10-27) Handles income statement and balances sheet before and after close.
  - `0.10.0` (2024-10-24) Separates core, chart, entry and book code and tests.


pkgId: e3593e10c2e90258040a0511f75cec4a5bc78bcbefcbac3aae0e9676bcb68d33
name: python-abacus-py
arch: src
version: 0.8.8
epoch: 0
release: 1
summary: A minimal yet valid double-entry accounting system in Python.
url: https://pypi.org/project/abacus-py/
rpm_license: UNKNOWN
rpm_group: Unspecified
rpm_buildhost: localhost
location_href: Packages/python-abacus-py-0.8.8-1.src.rpm
checksum_type: sha256
description:
  [![pytest](https://github.com/epogrebnyak/abacus/actions/workflows/.pytest.yml/badge.svg)](https://github.com/epogrebnyak/abacus/actions/workflows/.pytest.yml)
  [![PyPI](https://img.shields.io/pypi/v/abacus-py?color=blue)](https://pypi.org/project/abacus-py/)

  A minimal yet valid double-entry accounting system in Python.



  See project documentation at <https://epogrebnyak.github.io/abacus/>.



  ```
  pip install abacus-py
  ```

  For latest version install from github:

  ```
  pip install git+https://github.com/epogrebnyak/abacus.git
  ```

  `abacus-py` requires Python 3.10 or higher.



  Let's do Sample Transaction #1 from [accountingcoach.com](https://www.accountingcoach.com/accounting-basics/explanation/5)[^1].

  [^1]: It is a great learning resource for accounting, highly recommended.

  > On December 1, 2022 Joe starts his business Direct Delivery, Inc. The first transaction that Joe will record for his company is his personal investment of $20,000 in exchange for 5,000 shares of Direct Delivery's common stock.
  > Direct Delivery's accounting system will show an increase in its account Cash from zero to $20,000, and an increase in its stockholders' equity account Common Stock by $20,000.



  Both Python code and command line script below will produce balance sheet after Sample Transaction #1 is completed.

  Python code:

  ```python
  from abacus import Chart, Report

  chart = Chart(assets=["cash"], capital=["common_stock"])
  ledger = chart.ledger()
  ledger.post(debit="cash", credit="common_stock", amount=20000, title="Owner's investment")
  report = Report(chart, ledger)
  print(report.balance_sheet)
  ```

  Command line script:

  ```bash
  bx init
  bx post --entry asset:cash capital:common_stock 20000 --title "Initial investment"
  bx report --balance-sheet
  ```



  ```
  Balance sheet
  ASSETS  20000  CAPITAL              20000
    Cash  20000    Common stock       20000
                   Retained earnings      0
                 LIABILITIES              0
  TOTAL   20000  TOTAL                20000
  ```

  See further transactions for this example at [documentation website](https://epogrebnyak.github.io/abacus/textbook/#accountingcoachcom).


pkgId: 7ef3d1e8e8ba6d046a3883aa5f4a98fe902125d7b5c077151c11c1f9b1424687
name: python-abacusSoftware
arch: src
version: 1.6.1
epoch: 0
release: 1
url: https://github.com/Tausand-dev/AbacusSoftware
rpm_license: GPL
rpm_group: Unspecified
rpm_buildhost: localhost
location_href: Packages/python-abacusSoftware-1.6.1-1.src.rpm
checksum_type: sha256
summary:
  Abacus Software is a suite of tools built to ensure your experience with Tausand's coincidence counters becomes simplified.

description:
  Abacus Software is a suite of tools built to ensure your experience with Tausand's coincidence counters becomes simplified.

  Written in Python3, abacusSoftware relies on the following modules:

  - pyAbacus
  - pyqtgraph
  - NumPy
  - PyQt5
  - pyserial
  - qtmodern



  A quick demo video to preview this software is available at: https://youtu.be/c4QO8p1WeSE


  `abacusSoftware` can be installed using `pip` as:
  ```
  pip install abacusSoftware
  ```

  Or from GitHub
  ```
  pip install git+https://github.com/Tausand-dev/abacusSoftware.git
  ```


  On a terminal or command prompt type
  ```
  abacusSoftware
  ```


  Most Linux configurations have a dialout group for full and direct access to serial ports. By adding your user account to this group you will have the necessary permissions for Abacus Software to communicate with the serial ports.

  1. Open Terminal.
  2. Enter the following command, replacing ```<username>``` with the name of your account.
  ```
  sudo usermod -a -G dialout <username>
  ```
  3. Sign in and out for the changes to take effect.




  Write the changes of the new version in the file LastVersionNotes.md.
  Once the version is ready to update, run the script updateversion.py to include the last version notes in the release_history.md file.

  Run the following code to create a virtual environment called `.venv`
  ```
  python -m venv .venv
  ```


  - On Unix systems:
  ```
  source .venv/bin/activate
  ```
  - On Windows:
  ```
  .venv\Scripts\activate
  ```


  ```
  deactivate
  ```


  After the virtual environment has been activated, install required packages by using:
  ```
  python -m pip install -r requirements.txt
  ```


  After activating the virtual environment


  Run the following command
  ```
  pyinstaller --additional-hooks-dir installers/pyinstaller_hooks/ --name AbacusSoftware --onefile --noconsole -i abacusSoftware/GUI/images/abacus_small.ico test.py
  ```
  Two folders will be created: build and dist. Inside `dist` you'll find the `.exe` file. To create an installer, first install Inno Setup from https://jrsoftware.org/isinfo.php#stable. Then, using the File Explorer, go to the folder `installers` and double-click `installer_builder.iss` or open it from Inno Setup if it is already opened. Click on the play icon and then follow the process, which includes the creation of the installer and the installation itself.

  The installer will be saved in a folder called `Output`.


  Run the following command
  ```
  pyinstaller --additional-hooks-dir installers/pyinstaller_hooks/ --name AbacusSoftware --onefile --noconsole -i abacusSoftware/GUI/images/Abacus_small.png test.py
  ```
  Two folders will be created: build and dist. Inside `dist` you'll find the `.app` file. This file can be run from a console by executing the command
  To change the icon of the `.app` file follow the instructions here https://appleinsider.com/articles/21/01/06/how-to-change-app-icons-on-macos


  Run the following command
  ```
  pyinstaller --additional-hooks-dir installers/pyinstaller_hooks/ --name AbacusSoftware --onefile --noconsole -i abacusSoftware/GUI/images/Abacus_small.png test.py
  ```
  Two folders will be created: build and dist. Inside dist you'll find the executable file. This file can be run from a console by executing the command

  ```
  ./AbacusSoftware
  ```
  If it doesn't run, make sure it has execute permissions. In case it doesn't run `chmod +x AbacusSoftware` and then try again. The executable file could be used to create a Desktop entry so it can be lauched as an application (for example in Gnome, an icon could be assigned)

  To create an AppImage that can be run from multiple Linux distributions and be launch by double clicking, follow the next steps.
  * Create the following folder path:
  	AbacusSoftware.AppDir/usr/bin
  * Place the executable inside the bin folder
  * Place the icon Abacus_small.png located at abacusSoftware/GUI/images/Abacus_small.png inside AbacusSoftware.AppDir
  * Create a file called AbacusSoftware.desktop inside AbacusSoftware.AppDir
  * Edit the `.desktop` file with the following

  ```
  [Desktop Entry]
  Name=AbacusSoftware
  Exec=AbacusSoftware
  Icon=Abacus_small
  Type=Application
  Categories=Utility;
  ```

  * Give execution permisions to the `.desktop` file: `chmod +x AbacusSoftware.desktop`
  * Create a script called `AppRun` with the following contents

  ```

  SELF=$(readlink -f "$0")
  HERE=${SELF%/*}
  EXEC="${HERE}/usr/bin/AbacusSoftware"
  exec "${EXEC}"
  ```

  * Give execution permisions to the `AppRun` file: `chmod +x AppRun`. After this step, the app should run after doing `./AppRun` on a Terminal.
  * For 64-bit architecture, download appimagetool-x86_64.AppImage from https://github.com/AppImage/AppImageKit/releases/ and give execution permisions to it.
  * Place appimagetool outside AbacusSoftware.AppDir and run
  ```
  ARCH=x86_64 ./appimagetool-x86_64.AppImage AbacusSoftware.AppDir
  ```
  * The file `AbacusSoftware-x86_64.AppImage` will be created. This file can be opened by double clicking it.



  In linux, `cd` into `abacusSoftware/GUI/images/`, where you'll find the image files that will be used in the application. You'll also find a .qrc file which specifies any image that you want to include. If you want to use new images you'll need to specify their name inside such file. Next execute the following command

  ```
  pyrcc5 -o __GUI_images__.py images.qrc
  ```
  This will update the `__GUI_images__.py` file, which needs to be copied into the folder `abacusSoftware` and replace the file located there with the same name. Now the image resources can be called from within the code by doing, for example,

  ```
  splash_pix = QtGui.QPixmap(':/splash.png').scaledToWidth(600)
  ```


  https://github.com/pyinstaller/pyinstaller/commit/082078e30aff8f5b8f9a547191066d8b0f1dbb7e

  https://github.com/pyinstaller/pyinstaller/commit/59a233013cf6cdc46a67f0d98a995ca65ba7613a


pkgId: 2d437f502924e65b69977a92149df2b1f8afeab7a402a895d3b2d34dde6b678a
name: python-abacusutils
arch: src
version: 2.0.1
epoch: 0
release: 1
summary: Python code to read halo catalogs and other Abacus N-body data products
url: https://pypi.org/project/abacusutils/
rpm_license: GNU General Public License v3 (GPLv3)
rpm_group: Unspecified
rpm_buildhost: localhost
location_href: Packages/python-abacusutils-2.0.1-1.src.rpm
checksum_type: sha256
description:
  <p align="center">
  <img src="docs/images/icon_red.png" width="175px" alt="Abacus Logo">
  </p>

  [![Documentation Status](https://readthedocs.org/projects/abacusutils/badge/?version=latest)](https://abacusutils.readthedocs.io/en/latest/?badge=latest) [![PyPI](https://img.shields.io/pypi/v/abacusutils)](https://pypi.org/project/abacusutils/) [![Tests](https://github.com/abacusorg/abacusutils/actions/workflows/tests.yml/badge.svg)](https://github.com/abacusorg/abacusutils/actions/workflows/tests.yml) [![pre-commit.ci status](https://results.pre-commit.ci/badge/github/abacusorg/abacusutils/master.svg)](https://results.pre-commit.ci/latest/github/abacusorg/abacusutils/master)

  abacusutils is a package for reading and manipulating data products from the Abacus *N*-body project.
  In particular, these utilities are intended for use with the [AbacusSummit](https://abacussummit.readthedocs.io>)
  suite of simulations.  The package focuses on the Python 3 API, but there is also a language-agnostic Unix pipe
  interface to some of the functionality.

  These interfaces are documented here: <https://abacusutils.readthedocs.io>

  Press the GitHub "Watch" button in the top right and select "Custom->Releases" to be notified about bug fixes
  and new features!


  The Python abacusutils package is hosted on PyPI and can be installed
  by installing "abacusutils":
  ```
  pip install abacusutils
  ```
  or
  ```
  pip install abacusutils[all]
  ```

  For more information, see <https://abacusutils.readthedocs.io/en/latest/installation.html>.


  abacusutils has multiple interfaces, summarized here and at <https://abacusutils.readthedocs.io/en/latest/usage.html>.

  Specific examples of how to use abacusutils to work with AbacusSummit data will soon
  be given at the AbacusSummit website: <https://abacussummit.readthedocs.io>


  The abacusutils PyPI package contains a Python package called `abacusnbody`.
  This is the name to import (not `abacusutils`, which is just the name of the PyPI package).
  For example, to import the `compaso_halo_catalog` module, use
  ```python
  import abacusnbody.data.compaso_halo_catalog
  ```


  The ``pipe_asdf`` Python script reads columns from ASDF files and pipes them to
  ``stdout``.  For example:

  ```bash
      $ pipe_asdf halo_info_000.asdf -f N -f x_com | ./client
  ```


pkgId: 8b09614410007ff8bf3a00229697285eb5f95ddf4730b0eea5a406ab900ca5f2
name: python-abagen
arch: src
version: 0.1.3
epoch: 0
release: 1
summary: A toolbox for working with the Allen Brain Atlas genetic data
url: https://github.com/rmarkello/abagen
rpm_license: BSD-3
rpm_group: Unspecified
rpm_buildhost: localhost
location_href: Packages/python-abagen-0.1.3-1.src.rpm
checksum_type: sha256
description:
  This package provides a Python interface for fetching and working with the
  `Allen Human Brain Atlas`_ (AHBA) microarray expression data.


pkgId: 621cd0cc684daee53a60c02b83096c24de72c36963c31f130f99b58252dedece
name: python-abalytics
arch: src
version: 3.0.6
epoch: 0
release: 1
summary: Advanced A/B Testing Statistical Analytics
url: https://pypi.org/project/abalytics/
rpm_license: LICENSE
rpm_group: Unspecified
rpm_buildhost: localhost
location_href: Packages/python-abalytics-3.0.6-1.src.rpm
checksum_type: sha256
description:
  A/B Test 1            Mobile       5009  new_cta_1 (0.16) > new_cta_2 (0.15)                   0.007
  A/B Test 1            Tablet       2887  new_cta_1 (0.22) > new_cta_2 (0.20)                   0.000
  A/B Test 1            Tablet       2887  new_cta_1 (0.22) > old_implementation (0.20)          0.005
  A/B Test 1            Desktop     20014  new_cta_1 (0.18) > new_cta_2 (0.17)                   0.000
  A/B Test 1            Desktop     20014  new_cta_1 (0.18) > old_implementation (0.17)          0.000
  A/B Test 2            Mobile        268  new_cta_1 (0.10) > new_cta_2 (0.06)                   0.006
  A/B Test 2            Mobile        268  new_cta_1 (0.10) > old_implementation (0.06)          0.014
  A/B Test 2            Desktop      5609  new_cta_1 (0.13) > new_cta_2 (0.12)                   0.025
  ```
  Further examples of how to use ABalytics can be found in `examples/example.py`.

  Contributions to ABalytics are welcome. If you have suggestions for improvements or find any issues, please open an issue or submit a pull request.


pkgId: 0cb919dad1377a5a25599d35915d4e12806a5bb861e24bd6f4a84ab4530e797f
name: python-abantether-python-sdk
arch: src
version: 0.1.4
epoch: 0
release: 1
summary: Add your description here
url: https://github.com/Abantether-com/abantether-python-sdk/
rpm_license: MIT
rpm_group: Unspecified
rpm_buildhost: localhost
location_href: Packages/python-abantether-python-sdk-0.1.4-1.src.rpm
checksum_type: sha256
description:
  ![GitHub Workflow Status (with event)](https://img.shields.io/github/actions/workflow/status/Abantether-com/abantether-python-sdk/python-app.yml)
  ![Codecov](https://img.shields.io/codecov/c/github/Abantether-com/abantether-python-sdk)
  ![GitHub](https://img.shields.io/github/license/Abantether-com/abantether-python-sdk)
  ![Python Versions](https://img.shields.io/pypi/pyversions/abantether-python-sdk)
  ![PyPI Version](https://img.shields.io/pypi/v/abantether-python-sdk)



  A Python SDK for seamless integration with the [Abantether](https://abantether.com) cryptocurrency trading platform. This SDK provides an easy-to-use interface for executing trades and managing your account on [abantether.com](https://abantether.com).



  Install the package using pip:

  ```shell
  pip install abantether-python-sdk


  uv pip install abantether-python-sdk
  ```

  To instantiate the client use:

  ```python
  from abantether_python_sdk.client import Client as AbantetherClient

  ACCESS_TOKEN = ''
  aban_client = AbantetherClient(api_key=ACCESS_TOKEN)

  ```



  To contribute to this project:

  1. Clone the repository
  2. Install development dependencies:

  ```shell
  uv sync
  ```

  3. Run tests:
  ```shell
  uv run pytest
  ```



  This project is licensed under the MIT License - see the LICENSE file for details.


