# Essentials

## Introduction

The Julia standard library contains a range of functions and macros appropriate for performing scientific and numerical computing, but is also as broad as those of many general purpose programming languages. Additional functionality is available from a growing collection of available packages. Functions are grouped by topic below.

Some general notes:

- Except for functions in built-in modules (`Pkg`, `Collections`, `Test` and `Profile`), all functions documented here are directly available for use in programs.
- To use module functions, use `import Module` to import the module, and `Module.fn(x)` to use the functions.
- Alternatively, `using Module` will import all exported `Module` functions into the current namespace.
- By convention, function names ending with an exclamation point (`!`) modify their arguments. Some functions have both modifying (e.g., `sort!`) and non-modifying (`sort`) versions.

## Getting Around

`exit`([code])

  Quit (or control-D at the prompt). The default exit code is zero, indicating that the processes completed successfully.

`quit`()

  Quit the program indicating that the processes completed successfully. This function calls `exit(0)` (see `exit()`).

`atexit`(f)

  Register a zero-argument function `f()` to be called at process exit. `atexit()` hooks are called in last in first out (LIFO) order and run before object finalizers.

`atreplinit`(f)

  Register a one-argument function to be called before the REPL interface is initialized in interactive sessions; this is useful to customize the interface. The argument of `f` is the REPL object. This function should be called from within the `.juliarc.jl` initialization file.

`isinteractive`() → Bool

  Determine whether Julia is running an interactive session.

`whos`([io,] [Module,] [pattern::Regex])

  Print information about exported global variables in a module, optionally restricted to those matching `pattern`.

  The memory consumption estimate is an approximate lower bound on the size of the internal structure of the object.

`Base.``summarysize`(obj; exclude=Union{Module, Function, DataType, TypeName}) → Int

  Compute the amount of memory used by all unique objects reachable from the argument. Keyword argument `exclude` specifies a type of objects to exclude from the traversal.

`edit`(path::AbstractString[, line])

  Edit a file or directory optionally providing a line number to edit the file at. Returns to the `julia` prompt when you quit the editor.

`edit`(function[, types])

  Edit the definition of a function, optionally specifying a tuple of types to indicate which method to edit.

`@edit`()

  Evaluates the arguments to the function or macro call, determines their types, and calls the `edit` function on the resulting expression.

`less`(file::AbstractString[, line])

  Show a file using the default pager, optionally providing a starting line number. Returns to the `julia` prompt when you quit the pager.

`less`(function[, types])

  Show the definition of a function using the default pager, optionally specifying a tuple of types to indicate which method to see.

`@less`()

  Evaluates the arguments to the function or macro call, determines their types, and calls the `less` function on the resulting expression.

`clipboard`(x)

  Send a printed form of `x` to the operating system clipboard (“copy”).

`clipboard`() → AbstractString

  Return a string with the contents of the operating system clipboard (“paste”).

`reload`(name::AbstractString)

  Force reloading of a package, even if it has been loaded before. This is intended for use during package development as code is modified.

`require`(module::Symbol)

  This function is part of the implementation of `using` / `import`, if a module is not already defined in `Main`. It can also be called directly to force reloading a module, regardless of whether it has been loaded before (for example, when interactively developing libraries).

  Loads a source files, in the context of the `Main` module, on every active node, searching standard locations for files. `require` is considered a top-level operation, so it sets the current `include` path but does not use it to search for files (see help for `include`). This function is typically used to load library code, and is implicitly called by `using` to load packages.

  When searching for files, `require` first looks for package code under `Pkg.dir()`, then tries paths in the global array `LOAD_PATH`. `require` is case-sensitive on all platforms, including those with case-insensitive filesystems like macOS and Windows.

`Base.``compilecache`(module::String)

  Creates a precompiled cache file for module (see help for `require`) and all of its dependencies. This can be used to reduce package load times. Cache files are stored in `LOAD_CACHE_PATH[1]`, which defaults to `~/.julia/lib/VERSION`. See Module initialization and precompilation for important notes.

`__precompile__`(isprecompilable::Bool=true)

  Specify whether the file calling this function is precompilable. If `isprecompilable` is `true`, then `__precompile__` throws an exception when the file is loaded by `using`/`import`/`require` unless the file is being precompiled, and in a module file it causes the module to be automatically precompiled when it is imported. Typically, `__precompile__()` should occur before the `module` declaration in the file, or better yet `VERSION >= v"0.4" && __precompile__()` in order to be backward-compatible with Julia 0.3.

  If a module or file is not safely precompilable, it should call `__precompile__(false)` in order to throw an error if Julia attempts to precompile it.

  `__precompile__()` should not be used in a module unless all of its dependencies are also using `__precompile__()`. Failure to do so can result in a runtime error when loading the module.

`include`(path::AbstractString)

  Evaluate the contents of a source file in the current context. During including, a task-local include path is set to the directory containing the file. Nested calls to `include` will search relative to that path. All paths refer to files on node 1 when running in parallel, and files will be fetched from node 1. This function is typically used to load source interactively, or to combine files in packages that are broken into multiple source files.

`include_string`(code::AbstractString[, filename])

  Like `include`, except reads code from the given string rather than from a file. Since there is no file path involved, no path processing or fetching from node 1 is done.

`include_dependency`(path::AbstractString)

  In a module, declare that the file specified by `path` (relative or absolute) is a dependency for precompilation; that is, the module will need to be recompiled if this file changes.

  This is only needed if your module depends on a file that is not used via `include`. It has no effect outside of compilation.

`apropos`(string)

  Search through all documentation for a string, ignoring case.

`which`(f, types)

  Returns the method of `f` (a `Method` object) that would be called for arguments of the given `types`.

  If `types` is an abstract type, then the method that would be called by `invoke` is returned.

`which`(symbol)

  Return the module in which the binding for the variable referenced by `symbol` was created.

`@which`()

  Applied to a function or macro call, it evaluates the arguments to the specified call, and returns the `Method` object for the method that would be called for those arguments. Applied to a variable, it returns the module in which the variable was bound. It calls out to the `which` function.

`methods`(f[, types])

  Returns the method table for `f`.

  If `types` is specified, returns an array of methods whose types match.

`methodswith`(typ[, module or function][, showparents])

  Return an array of methods with an argument of type `typ`.

  The optional second argument restricts the search to a particular module or function (the default is all modules, starting from Main).

  If optional `showparents` is `true`, also return arguments with a parent type of `typ`, excluding type `Any`.

`@show`()

  Show an expression and result, returning the result.

`versioninfo`([verbose::Bool])

  Print information about the version of Julia in use. If the `verbose` argument is `true`, detailed system information is shown as well.

`workspace`()

  Replace the top-level module (`Main`) with a new one, providing a clean workspace. The previous `Main` module is made available as `LastMain`. A previously-loaded package can be accessed using a statement such as `using LastMain.Package`.

  This function should only be used interactively.

`ans`

  A variable referring to the last computed value, automatically set at the interactive prompt.

## All Objects

`is`(x, y) → Bool
`===`(x, y) → Bool
`≡`(x, y) → Bool

  Determine whether `x` and `y` are identical, in the sense that no program could distinguish them. Compares mutable objects by address in memory, and compares immutable objects (such as numbers) by contents at the bit level. This function is sometimes called `egal`.

`isa`(x, type) → Bool

  Determine whether `x` is of the given `type`.

`isequal`(x, y)

  Similar to `==`, except treats all floating-point `NaN` values as equal to each other, and treats `-0.0` as unequal to `0.0`. The default implementation of `isequal` calls `==`, so if you have a type that doesn’t have these floating-point subtleties then you probably only need to define `==`.

  `isequal` is the comparison function used by hash tables (`Dict`). `isequal(x,y)` must imply that `hash(x) == hash(y)`.

  This typically means that if you define your own `==` function then you must define a corresponding `hash` (and vice versa). Collections typically implement `isequal` by calling `isequal` recursively on all contents.

  Scalar types generally do not need to implement `isequal` separate from `==`, unless they represent floating-point numbers amenable to a more efficient implementation than that provided as a generic fallback (based on `isnan`, `signbit`, and `==`).

`isless`(x, y)

  Test whether `x` is less than `y`, according to a canonical total order. Values that are normally unordered, such as `NaN`, are ordered in an arbitrary but consistent fashion. This is the default comparison used by `sort`. Non-numeric types with a canonical total order should implement this function. Numeric types only need to implement it if they have special values such as `NaN`.

`ifelse`(condition::Bool, x, y)

  Return `x` if `condition` is `true`, otherwise return `y`. This differs from `?` or `if` in that it is an ordinary function, so all the arguments are evaluated first. In some cases, using `ifelse` instead of an `if` statement can eliminate the branch in generated code and provide higher performance in tight loops.

`lexcmp`(x, y)

  Compare `x` and `y` lexicographically and return -1, 0, or 1 depending on whether `x` is less than, equal to, or greater than `y`, respectively. This function should be defined for lexicographically comparable types, and `lexless` will call `lexcmp` by default.

`lexless`(x, y)

  Determine whether `x` is lexicographically less than `y`.

`typeof`(x)

  Get the concrete type of `x`.

`tuple`(xs...)

  Construct a tuple of the given objects.

`ntuple`(f::Function, n)

  Create a tuple of length `n`, computing each element as `f(i)`, where `i` is the index of the element.

`object_id`(x)

  Get a hash value for `x` based on object identity. `object_id(x)==object_id(y)` if `x === y`.

`hash`(x[, h::UInt])

  Compute an integer hash code such that `isequal(x,y)` implies `hash(x)==hash(y)`. The optional second argument `h` is a hash code to be mixed with the result.

  New types should implement the 2-argument form, typically by calling the 2-argument `hash` method recursively in order to mix hashes of the contents with each other (and with `h`). Typically, any type that implements `hash` should also implement its own `==` (hence `isequal`) to guarantee the property mentioned above.

`finalizer`(x, function)

  Register a function `f(x)` to be called when there are no program-accessible references to `x`. The behavior of this function is unpredictable if `x` is of a bits type.

`finalize`(x)

  Immediately run finalizers registered for object `x`.

`copy`(x)

  Create a shallow copy of `x`: the outer structure is copied, but not all internal values. For example, copying an array produces a new array with identically-same elements as the original.

`deepcopy`(x)

  Create a deep copy of `x`: everything is copied recursively, resulting in a fully independent object. For example, deep-copying an array produces a new array whose elements are deep copies of the original elements. Calling `deepcopy` on an object should generally have the same effect as serializing and then deserializing it.

  As a special case, functions can only be actually deep-copied if they are anonymous, otherwise they are just copied. The difference is only relevant in the case of closures, i.e. functions which may contain hidden internal references.

  While it isn’t normally necessary, user-defined types can override the default `deepcopy` behavior by defining a specialized version of the function `deepcopy_internal(x::T, dict::ObjectIdDict)` (which shouldn’t otherwise be used), where `T` is the type to be specialized for, and `dict` keeps track of objects copied so far within the recursion. Within the definition, `deepcopy_internal` should be used in place of `deepcopy`, and the `dict` variable should be updated as appropriate before returning.

`isdefined`([m::Module, ]s::Symbol)
`isdefined`(object, s::Symbol)
`isdefined`(a::AbstractArray, index::Int)

  Tests whether an assignable location is defined. The arguments can be a module and a symbol, a composite object and field name (as a symbol), or an array and index. With a single symbol argument, tests whether a global variable with that name is defined in `current_module()`.

`convert`(T, x)

  Convert `x` to a value of type `T`.

  If `T` is an `Integer` type, an `InexactError` will be raised if `x` is not representable by `T`, for example if `x` is not integer-valued, or is outside the range supported by `T`.

      julia> convert(Int, 3.0)
      3

      julia> convert(Int, 3.5)
      ERROR: InexactError()
       in convert(::Type{Int64}, ::Float64) at ./int.jl:239
       ...

  If `T` is a `AbstractFloat` or `Rational` type, then it will return the closest value to `x` representable by `T`.

      julia> x = 1/3
      0.3333333333333333

      julia> convert(Float32, x)
      0.33333334f0

      julia> convert(Rational{Int32}, x)
      1//3

      julia> convert(Rational{Int64}, x)
      6004799503160661//18014398509481984

  If `T` is a collection type and `x` a collection, the result of `convert(T, x)` may alias `x`.

      julia> x = Int[1,2,3];

      julia> y = convert(Vector{Int}, x);

      julia> y === x
      true

  Similarly, if `T` is a composite type and `x` a related instance, the result of `convert(T, x)` may alias part or all of `x`.

      julia> x = speye(5);

      julia> typeof(x)
      SparseMatrixCSC{Float64,Int64}

      julia> y = convert(SparseMatrixCSC{Float64,Int64}, x);

      julia> z = convert(SparseMatrixCSC{Float32,Int64}, y);

      julia> y === x
      true

      julia> z === x
      false

      julia> z.colptr === x.colptr
      true

`promote`(xs...)

  Convert all arguments to their common promotion type (if any), and return them all (as a tuple).

`oftype`(x, y)

  Convert `y` to the type of `x` (`convert(typeof(x), y)`).

`widen`(x)

  If `x` is a type, return a “larger” type (for numeric types, this will be a type with at least as much range and precision as the argument, and usually more). Otherwise `x` is converted to `widen(typeof(x))`.

      julia> widen(Int32)
      Int64

      julia> widen(1.5f0)
      1.5

`identity`(x)

  The identity function. Returns its argument.

## Types

`supertype`(T::DataType)

  Return the supertype of DataType `T`.

`issubtype`(type1, type2)

  Return `true` if and only if all values of `type1` are also of `type2`. Can also be written using the `<:` infix operator as `type1 <: type2`.

`<:`(T1, T2)

  Subtype operator, equivalent to `issubtype(T1,T2)`.

`subtypes`(T::DataType)

  Return a list of immediate subtypes of DataType `T`. Note that all currently loaded subtypes are included, including those not visible in the current module.

`typemin`(T)

  The lowest value representable by the given (real) numeric DataType `T`.

`typemax`(T)

  The highest value representable by the given (real) numeric `DataType`.

`realmin`(T)

  The smallest in absolute value non-subnormal value representable by the given floating-point DataType `T`.

`realmax`(T)

  The highest finite value representable by the given floating-point DataType `T`.

`maxintfloat`(T)

  The largest integer losslessly representable by the given floating-point DataType `T`.

`sizeof`(T)

  Size, in bytes, of the canonical binary representation of the given DataType `T`, if any.

`eps`(T)

  The distance between 1.0 and the next larger representable floating-point value of `DataType` `T`. Only floating-point types are sensible arguments.

`eps`()

  The distance between 1.0 and the next larger representable floating-point value of `Float64`.

`eps`(x)

  The distance between `x` and the next larger representable floating-point value of the same `DataType` as `x`.

`promote_type`(type1, type2)

  Determine a type big enough to hold values of each argument type without loss, whenever possible. In some cases, where no type exists to which both types can be promoted losslessly, some loss is tolerated; for example, `promote_type(Int64,Float64)` returns `Float64` even though strictly, not all `Int64` values can be represented exactly as `Float64` values.

`promote_rule`(type1, type2)

  Specifies what type should be used by `promote` when given values of types `type1` and `type2`. This function should not be called directly, but should have definitions added to it for new types as appropriate.

`getfield`(value, name::Symbol)

  Extract a named field from a `value` of composite type. The syntax `a.b` calls `getfield(a, :b)`.

`setfield!`(value, name::Symbol, x)

  Assign `x` to a named field in `value` of composite type. The syntax `a.b = c` calls `setfield!(a, :b, c)`.

`fieldoffset`(type, i)

  The byte offset of field `i` of a type relative to the data start. For example, we could use it in the following manner to summarize information about a struct type:

      julia> structinfo(T) = [(fieldoffset(T,i), fieldname(T,i), fieldtype(T,i)) for i = 1:nfields(T)];

      julia> structinfo(Base.Filesystem.StatStruct)
      12-element Array{Tuple{UInt64,Symbol,DataType},1}:
       (0x0000000000000000,:device,UInt64)
       (0x0000000000000008,:inode,UInt64)
       (0x0000000000000010,:mode,UInt64)
       (0x0000000000000018,:nlink,Int64)
       (0x0000000000000020,:uid,UInt64)
       (0x0000000000000028,:gid,UInt64)
       (0x0000000000000030,:rdev,UInt64)
       (0x0000000000000038,:size,Int64)
       (0x0000000000000040,:blksize,Int64)
       (0x0000000000000048,:blocks,Int64)
       (0x0000000000000050,:mtime,Float64)
       (0x0000000000000058,:ctime,Float64)

`fieldtype`(T, name::Symbol | index::Int)

  Determine the declared type of a field (specified by name or index) in a composite DataType `T`.

`isimmutable`(v)

  Return `true` iff value `v` is immutable. See Immutable Composite Types for a discussion of immutability. Note that this function works on values, so if you give it a type, it will tell you that a value of `DataType` is mutable.

`isbits`(T)

  Return `true` if `T` is a “plain data” type, meaning it is immutable and contains no references to other values. Typical examples are numeric types such as `UInt8`, `Float64`, and `Complex{Float64}`.

      julia> isbits(Complex{Float64})
      true

      julia> isbits(Complex)
      false

`isleaftype`(T)

  Determine whether `T` is a concrete type that can have instances, meaning its only subtypes are itself and `Union{}` (but `T` itself is not `Union{}`).

`typejoin`(T, S)

  Compute a type that contains both `T` and `S`.

`typeintersect`(T, S)

  Compute a type that contains the intersection of `T` and `S`. Usually this will be the smallest such type or one close to it.

`Val{c}`()

  Create a “value type” out of `c`, which must be an `isbits` value. The intent of this construct is to be able to dispatch on constants, e.g., `f(Val{false})` allows you to dispatch directly (at compile-time) to an implementation `f(::Type{Val{false}})`, without having to test the boolean value at runtime.

`@enum EnumName EnumValue1[=x] EnumValue2[=y]`

  Create an `Enum` type with name `EnumName` and enum member values of `EnumValue1` and `EnumValue2` with optional assigned values of `x` and `y`, respectively. `EnumName` can be used just like other types and enum member values as regular values, such as

      julia> @enum FRUIT apple=1 orange=2 kiwi=3

      julia> f(x::FRUIT) = "I'm a FRUIT with value: $(Int(x))"
      f (generic function with 1 method)

      julia> f(apple)
      "I'm a FRUIT with value: 1"

`instances`(T::Type)

  Return a collection of all instances of the given type, if applicable. Mostly used for enumerated types (see `@enum`).

## Generic Functions

`method_exists`(f, Tuple type) → Bool

  Determine whether the given generic function has a method matching the given `Tuple` of argument types.

      julia> method_exists(length, Tuple{Array})
      true

`applicable`(f, args...) → Bool

  Determine whether the given generic function has a method applicable to the given arguments.

      julia> function f(x, y)
                 x + y
             end;

      julia> applicable(f, 1)
      false

      julia> applicable(f, 1, 2)
      true

`invoke`(f, (types...), args...)

  Invoke a method for the given generic function matching the specified types (as a tuple), on the specified arguments. The arguments must be compatible with the specified types. This allows invoking a method other than the most specific matching method, which is useful when the behavior of a more general definition is explicitly needed (often as part of the implementation of a more specific method of the same function).

`|>`(x, f)

  Applies a function to the preceding argument. This allows for easy function chaining.

      julia> [1:5;] |> x->x.^2 |> sum |> inv
      0.01818181818181818

## Syntax

`eval`([m::Module, ]expr::Expr)

  Evaluate an expression in the given module and return the result. Every `Module` (except those defined with `baremodule`) has its own 1-argument definition of `eval`, which evaluates expressions in that module.

`@eval`()

  Evaluate an expression and return the value.

`evalfile`(path::AbstractString)

  Load the file using `include`, evaluate all expressions, and return the value of the last one.

`esc`(e::ANY)

  Only valid in the context of an `Expr` returned from a macro. Prevents the macro hygiene pass from turning embedded variables into gensym variables. See the Macros section of the Metaprogramming chapter of the manual for more details and examples.

`gensym`([tag])

  Generates a symbol which will not conflict with other variable names.

`@gensym`()

  Generates a gensym symbol for a variable. For example, `@gensym x y` is transformed into `x = gensym("x"); y = gensym("y")`.

`parse`(str, start; greedy=true, raise=true)

  Parse the expression string and return an expression (which could later be passed to eval for execution). `start` is the index of the first character to start parsing. If `greedy` is `true` (default), `parse` will try to consume as much input as it can; otherwise, it will stop as soon as it has parsed a valid expression. Incomplete but otherwise syntactically valid expressions will return `Expr(:incomplete, "(error message)")`. If `raise` is `true` (default), syntax errors other than incomplete expressions will raise an error. If `raise` is `false`, `parse` will return an expression that will raise an error upon evaluation.

`parse`(str; raise=true)

  Parse the expression string greedily, returning a single expression. An error is thrown if there are additional characters after the first expression. If `raise` is `true` (default), syntax errors will raise an error; otherwise, `parse` will return an expression that will raise an error upon evaluation.

## Nullables

`Nullable`(x)

  Wrap value `x` in an object of type `Nullable`, which indicates whether a value is present. `Nullable(x)` yields a non-empty wrapper, and `Nullable{T}()` yields an empty instance of a wrapper that might contain a value of type `T`.

`get`(x::Nullable[, y])

  Attempt to access the value of `x`. Returns the value if it is present; otherwise, returns `y` if provided, or throws a `NullException` if not.

`isnull`(x)

  Is the `Nullable` object `x` null, i.e. missing a value?

## System

`run`(command)

  Run a command object, constructed with backticks. Throws an error if anything goes wrong, including the process exiting with a non-zero status.

`spawn`(command)

  Run a command object asynchronously, returning the resulting `Process` object.

`DevNull`

  Used in a stream redirect to discard all data written to it. Essentially equivalent to /dev/null on Unix or NUL on Windows. Usage:

      run(pipeline(`cat test.txt`, DevNull))

`success`(command)

  Run a command object, constructed with backticks, and tell whether it was successful (exited with a code of 0). An exception is raised if the process cannot be started.

`process_running`(p::Process)

  Determine whether a process is currently running.

`process_exited`(p::Process)

  Determine whether a process has exited.

`kill`(p::Process, signum=SIGTERM)

  Send a signal to a process. The default is to terminate the process.

`Sys.``set_process_title`(title::AbstractString)

  Set the process title. No-op on some operating systems. (not exported)

`Sys.``get_process_title`()

  Get the process title. On some systems, will always return empty string. (not exported)

`readandwrite`(command)

  Starts running a command asynchronously, and returns a tuple (stdout,stdin,process) of the output stream and input stream of the process, and the process object itself.

`ignorestatus`(command)

  Mark a command object so that running it will not throw an error if the result code is non-zero.

`detach`(command)

  Mark a command object so that it will be run in a new process group, allowing it to outlive the julia process, and not have Ctrl-C interrupts passed to it.

`Cmd(cmd::Cmd; ignorestatus, detach, windows_verbatim, windows_hide,`
`env, dir)`

  Construct a new `Cmd` object, representing an external program and arguments, from `cmd`, while changing the settings of the optional keyword arguments:

  - `ignorestatus::Bool`: If `true` (defaults to `false`), then the `Cmd` will not throw an error if the return code is nonzero.
  - `detach::Bool`: If `true` (defaults to `false`), then the `Cmd` will be run in a new process group, allowing it to outlive the `julia` process and not have Ctrl-C passed to it.
  - `windows_verbatim::Bool`: If `true` (defaults to `false`), then on Windows the `Cmd` will send a command-line string to the process with no quoting or escaping of arguments, even arguments containing spaces. (On Windows, arguments are sent to a program as a single “command-line” string, and programs are responsible for parsing it into arguments. By default, empty arguments and arguments with spaces or tabs are quoted with double quotes `"` in the command line, and `\` or `"` are preceded by backslashes. `windows_verbatim=true` is useful for launching programs that parse their command line in nonstandard ways.) Has no effect on non-Windows systems.
  - `windows_hide::Bool`: If `true` (defaults to `false`), then on Windows no new console window is displayed when the `Cmd` is executed. This has no effect if a console is already open or on non-Windows systems.
  - `env`: Set environment variables to use when running the `Cmd`. `env` is either a dictionary mapping strings to strings, an array of strings of the form `"var=val"`, an array or tuple of `"var"=>val` pairs, or `nothing`. In order to modify (rather than replace) the existing environment, create `env` by `copy(ENV)` and then set `env["var"]=val` as desired.
  - `dir::AbstractString`: Specify a working directory for the command (instead of the current directory).

  For any keywords that are not specified, the current settings from `cmd` are used. Normally, to create a `Cmd` object in the first place, one uses backticks, e.g.

      Cmd(`echo "Hello world"`, ignorestatus=true, detach=false)

`setenv`(command, env; dir=working_dir)

  Set environment variables to use when running the given `command`. `env` is either a dictionary mapping strings to strings, an array of strings of the form `"var=val"`, or zero or more `"var"=>val` pair arguments. In order to modify (rather than replace) the existing environment, create `env` by `copy(ENV)` and then setting `env["var"]=val` as desired, or use `withenv`.

  The `dir` keyword argument can be used to specify a working directory for the command.

`withenv`(f::Function, kv::Pair...)

  Execute `f()` in an environment that is temporarily modified (not replaced as in `setenv`) by zero or more `"var"=>val` arguments `kv`. `withenv` is generally used via the `withenv(kv...) do ... end` syntax. A value of `nothing` can be used to temporarily unset an environment variable (if it is set). When `withenv` returns, the original environment has been restored.

`pipeline`(from, to, ...)

  Create a pipeline from a data source to a destination. The source and destination can be commands, I/O streams, strings, or results of other `pipeline` calls. At least one argument must be a command. Strings refer to filenames. When called with more than two arguments, they are chained together from left to right. For example `pipeline(a,b,c)` is equivalent to `pipeline(pipeline(a,b),c)`. This provides a more concise way to specify multi-stage pipelines.

  Examples:

      run(pipeline(`ls`, `grep xyz`))
      run(pipeline(`ls`, "out.txt"))
      run(pipeline("out.txt", `grep xyz`))

`pipeline`(command; stdin, stdout, stderr, append=false)

  Redirect I/O to or from the given `command`. Keyword arguments specify which of the command’s streams should be redirected. `append` controls whether file output appends to the file. This is a more general version of the 2-argument `pipeline` function. `pipeline(from, to)` is equivalent to `pipeline(from, stdout=to)` when `from` is a command, and to `pipeline(to, stdin=from)` when `from` is another kind of data source.

  Examples:

      run(pipeline(`dothings`, stdout="out.txt", stderr="errs.txt"))
      run(pipeline(`update`, stdout="log.txt", append=true))

`gethostname`() → AbstractString

  Get the local machine’s host name.

`getipaddr`() → IPAddr

  Get the IP address of the local machine.

`getpid`() → Int32

  Get Julia’s process ID.

`time`()

  Get the system time in seconds since the epoch, with fairly high (typically, microsecond) resolution.

`time_ns`()

  Get the time in nanoseconds. The time corresponding to 0 is undefined, and wraps every 5.8 years.

`tic`()

  Set a timer to be read by the next call to `toc()` or `toq()`. The macro call `@time expr` can also be used to time evaluation.

`toc`()

  Print and return the time elapsed since the last `tic()`. The macro call `@time expr` can also be used to time evaluation.

`toq`()

  Return, but do not print, the time elapsed since the last `tic()`. The macro calls `@timed expr` and `@elapsed expr` also return evaluation time.

`@time`()

  A macro to execute an expression, printing the time it took to execute, the number of allocations, and the total number of bytes its execution caused to be allocated, before returning the value of the expression.

  See also `@timev()`, `@timed()`, `@elapsed()`, and `@allocated()`.

`@timev`()

  This is a verbose version of the `@time` macro. It first prints the same information as `@time`, then any non-zero memory allocation counters, and then returns the value of the expression.

  See also `@time()`, `@timed()`, `@elapsed()`, and `@allocated()`.

`@timed`()

  A macro to execute an expression, and return the value of the expression, elapsed time, total bytes allocated, garbage collection time, and an object with various memory allocation counters.

  See also `@time()`, `@timev()`, `@elapsed()`, and `@allocated()`.

`@elapsed`()

  A macro to evaluate an expression, discarding the resulting value, instead returning the number of seconds it took to execute as a floating-point number.

  See also `@time()`, `@timev()`, `@timed()`, and `@allocated()`.

`@allocated`()

  A macro to evaluate an expression, discarding the resulting value, instead returning the total number of bytes allocated during evaluation of the expression. Note: the expression is evaluated inside a local function, instead of the current context, in order to eliminate the effects of compilation, however, there still may be some allocations due to JIT compilation. This also makes the results inconsistent with the `@time` macros, which do not try to adjust for the effects of compilation.

  See also `@time()`, `@timev()`, `@timed()`, and `@elapsed()`.

`EnvHash`() → EnvHash

  A singleton of this type provides a hash table interface to environment variables.

`ENV`

  Reference to the singleton `EnvHash`, providing a dictionary interface to system environment variables.

`is_unix`([os])

  Predicate for testing if the OS provides a Unix-like interface. See documentation in Handling Operating System Variation.

`is_apple`([os])

  Predicate for testing if the OS is a derivative of Apple Macintosh OS X or Darwin. See documentation in Handling Operating System Variation.

`is_linux`([os])

  Predicate for testing if the OS is a derivative of Linux. See documentation in Handling Operating System Variation.

`is_bsd`([os])

  Predicate for testing if the OS is a derivative of BSD. See documentation in Handling Operating System Variation.

`is_windows`([os])

  Predicate for testing if the OS is a derivative of Microsoft Windows NT. See documentation in Handling Operating System Variation.

`windows_version`()

  Returns the version number for the Windows NT Kernel as a (major, minor) pair, or `(0, 0)` if this is not running on Windows.

`@static`()

  Partially evaluates an expression at parse time.

  For example, `@static is_windows() ? foo : bar` will evaluate `is_windows()` and insert either `foo` or `bar` into the expression. This is useful in cases where a construct would be invalid on other platforms, such as a `ccall` to a non-existent function.

## Errors

`error`(message::AbstractString)

  Raise an `ErrorException` with the given message.

`throw`(e)

  Throw an object as an exception.

`rethrow`([e])

  Throw an object without changing the current exception backtrace. The default argument is the current exception (if called within a `catch` block).

`backtrace`()

  Get a backtrace object for the current program point.

`catch_backtrace`()

  Get the backtrace of the current exception, for use within `catch` blocks.

`assert`(cond)

  Throw an `AssertionError` if `cond` is `false`. Also available as the macro `@assert expr`.

`@assert cond [text]`

  Throw an `AssertionError` if `cond` is `false`. Preferred syntax for writing assertions. Message `text` is optionally displayed upon assertion failure.

`ArgumentError`(msg)

  The parameters to a function call do not match a valid signature. Argument `msg` is a descriptive error string.

`AssertionError`([msg])

  The asserted condition did not evaluate to `true`. Optional argument `msg` is a descriptive error string.

`BoundsError`([a][, i])

  An indexing operation into an array, `a`, tried to access an out-of-bounds element, `i`.

`DimensionMismatch`([msg])

  The objects called do not have matching dimensionality. Optional argument `msg` is a descriptive error string.

`DivideError`()

  Integer division was attempted with a denominator value of 0.

`DomainError`()

  The arguments to a function or constructor are outside the valid domain.

`EOFError`()

  No more data was available to read from a file or stream.

`ErrorException`(msg)

  Generic error type. The error message, in the `.msg` field, may provide more specific details.

`InexactError`()

  Type conversion cannot be done exactly.

`InterruptException`()

  The process was stopped by a terminal interrupt (CTRL+C).

`KeyError`(key)

  An indexing operation into an `Associative` (`Dict`) or `Set` like object tried to access or delete a non-existent element.

`LoadError`(file::AbstractString, line::Int, error)

  An error occurred while `include`ing, `require`ing, or `using` a file. The error specifics should be available in the `.error` field.

`MethodError`(f, args)

  A method with the required type signature does not exist in the given generic function. Alternatively, there is no unique most-specific method.

`NullException`()

  An attempted access to a `Nullable` with no defined value.

`OutOfMemoryError`()

  An operation allocated too much memory for either the system or the garbage collector to handle properly.

`ReadOnlyMemoryError`()

  An operation tried to write to memory that is read-only.

`OverflowError`()

  The result of an expression is too large for the specified type and will cause a wraparound.

`ParseError`(msg)

  The expression passed to the `parse` function could not be interpreted as a valid Julia expression.

`ProcessExitedException`()

  After a client Julia process has exited, further attempts to reference the dead child will throw this exception.

`StackOverflowError`()

  The function call grew beyond the size of the call stack. This usually happens when a call recurses infinitely.

`SystemError`(prefix::AbstractString[, errno::Int32])

  A system call failed with an error code (in the `errno` global variable).

`TypeError`(func::Symbol, context::AbstractString, expected::Type, got)

  A type assertion failure, or calling an intrinsic function with an incorrect argument type.

`UndefRefError`()

  The item or field is not defined for the given object.

`UndefVarError`(var::Symbol)

  A symbol in the current scope is not defined.

`InitError`(mod::Symbol, error)

  An error occurred when running a module’s `__init__` function. The actual error thrown is available in the `.error` field.

`retry`(f, [retry_on]; n=1, max_delay=10.0) → Function

  Returns a lambda that retries function `f` up to `n` times in the event of an exception. If `retry_on` is a `Type` then retry only for exceptions of that type. If `retry_on` is a function `test_error(::Exception) -> Bool` then retry only if it is true.

  The first retry happens after a gap of 50 milliseconds or `max_delay`, whichever is lower. Subsequently, the delays between retries are exponentially increased with a random factor up to `max_delay`.

  Examples

      retry(http_get, e -> e.status == "503")(url)
      retry(read, UVError)(io)

## Events

`Timer`(callback::Function, delay, repeat=0)

  Create a timer to call the given `callback` function. The `callback` is passed one argument, the timer object itself. The callback will be invoked after the specified initial `delay`, and then repeating with the given `repeat` interval. If `repeat` is `0`, the timer is only triggered once. Times are in seconds. A timer is stopped and has its resources freed by calling `close` on it.

`Timer`(delay, repeat=0)

  Create a timer that wakes up tasks waiting for it (by calling `wait` on the timer object) at a specified interval. Times are in seconds. Waiting tasks are woken with an error when the timer is closed (by `close`). Use `isopen` to check whether a timer is still active.

`AsyncCondition`()

  Create a async condition that wakes up tasks waiting for it (by calling `wait` on the object) when notified from C by a call to uv_async_send. Waiting tasks are woken with an error when the object is closed (by `close`). Use `isopen` to check whether it is still active.

`AsyncCondition`(callback::Function)

  Create a async condition that calls the given `callback` function. The `callback` is passed one argument, the async condition object itself.

## Reflection

`module_name`(m::Module) → Symbol

  Get the name of a `Module` as a `Symbol`.

`module_parent`(m::Module) → Module

  Get a module’s enclosing `Module`. `Main` is its own parent, as is `LastMain` after `workspace()`.

`current_module`() → Module

  Get the dynamically current `Module`, which is the `Module` code is currently being read from. In general, this is not the same as the module containing the call to this function.

`fullname`(m::Module)

  Get the fully-qualified name of a module as a tuple of symbols. For example, `fullname(Base.Pkg)` gives `(:Base,:Pkg)`, and `fullname(Main)` gives `()`.

`names`(x::Module[, all=false[, imported=false]])

  Get an array of the names exported by a `Module`, with optionally more `Module` globals according to the additional parameters.

`nfields`(x::DataType) → Int

  Get the number of fields of a `DataType`.

`fieldnames`(x::DataType)

  Get an array of the fields of a `DataType`.

`fieldname`(x::DataType, i)

  Get the name of field `i` of a `DataType`.

`Base.``datatype_module`(t::DataType) → Module

  Determine the module containing the definition of a `DataType`.

`isconst`([m::Module, ]s::Symbol) → Bool

  Determine whether a global is declared `const` in a given `Module`. The default `Module` argument is `current_module()`.

`Base.``function_name`(f::Function) → Symbol

  Get the name of a generic `Function` as a symbol, or `:anonymous`.

`Base.``function_module`(f::Function) → Module

  Determine the module containing the (first) definition of a generic function.

`Base.``function_module`(f::Function, types) → Module

  Determine the module containing a given definition of a generic function.

`functionloc`(f::Function, types)

  Returns a tuple `(filename,line)` giving the location of a generic `Function` definition.

`functionloc`(m::Method)

  Returns a tuple `(filename,line)` giving the location of a `Method` definition.

`@functionloc`()

  Applied to a function or macro call, it evaluates the arguments to the specified call, and returns a tuple `(filename,line)` giving the location for the method that would be called for those arguments. It calls out to the `functionloc` function.

## Internals

`gc`()

  Perform garbage collection. This should not generally be used.

`gc_enable`(on::Bool)

  Control whether garbage collection is enabled using a boolean argument (`true` for enabled, `false` for disabled). Returns previous GC state. Disabling garbage collection should be used only with extreme caution, as it can cause memory use to grow without bound.

`macroexpand`(x)

  Takes the expression `x` and returns an equivalent expression with all macros removed (expanded).

`expand`(x)

  Takes the expression `x` and returns an equivalent expression in lowered form.

`code_lowered`(f, types)

  Returns an array of lowered ASTs for the methods matching the given generic function and type signature.

`@code_lowered`()

  Evaluates the arguments to the function or macro call, determines their types, and calls `code_lowered()` on the resulting expression.

`code_typed`(f, types; optimize=true)

  Returns an array of lowered and type-inferred ASTs for the methods matching the given generic function and type signature. The keyword argument `optimize` controls whether additional optimizations, such as inlining, are also applied.

`@code_typed`()

  Evaluates the arguments to the function or macro call, determines their types, and calls `code_typed()` on the resulting expression.

`code_warntype`([io, ]f, types)

  Prints lowered and type-inferred ASTs for the methods matching the given generic function and type signature to `io` which defaults to `STDOUT`. The ASTs are annotated in such a way as to cause “non-leaf” types to be emphasized (if color is available, displayed in red). This serves as a warning of potential type instability. Not all non-leaf types are particularly problematic for performance, so the results need to be used judiciously. See @code_warntype for more information.

`@code_warntype`()

  Evaluates the arguments to the function or macro call, determines their types, and calls `code_warntype()` on the resulting expression.

`code_llvm`([io, ]f, types)

  Prints the LLVM bitcodes generated for running the method matching the given generic function and type signature to `io` which defaults to `STDOUT`.

  All metadata and dbg.* calls are removed from the printed bitcode. Use code_llvm_raw for the full IR.

`@code_llvm`()

  Evaluates the arguments to the function or macro call, determines their types, and calls `code_llvm()` on the resulting expression.

`code_native`([io, ]f, types)

  Prints the native assembly instructions generated for running the method matching the given generic function and type signature to `io` which defaults to `STDOUT`.

`@code_native`()

  Evaluates the arguments to the function or macro call, determines their types, and calls `code_native()` on the resulting expression.

`precompile`(f, args::Tuple{Vararg{Any}})

  Compile the given function `f` for the argument tuple (of types) `args`, but do not execute it.