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 importModule to import the module, and Module.fn(x) to use the functions.
  • Alternatively, usingModule 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 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 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 in the current working directory, then looks for package code under Pkg.dir(), then tries paths in the global array LOAD_PATH.

Base.compilecache(module::ByteString)

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/requireunless 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 call, it evaluates the arguments to the specified function 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. If optional showparents is true, also return arguments with a parent type of typ, excluding type Any.

The optional second argument restricts the search to a particular module or function.

@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 usingLastMain.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 unique integer id for x. object_id(x)==object_id(y) if and only if is(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([object, ]index | symbol)

Tests whether an assignable location is defined. The arguments can be an array and index, a composite object and field name (as a symbol), or a module and a symbol. 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)3julia>convert(Int,3.5)ERROR:InexactError()inconvertatint.jl:209

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

julia>x=1/30.3333333333333333julia>convert(Float32,x)0.33333334f0julia>convert(Rational{Int32},x)1//3julia>convert(Rational{Int64},x)6004799503160661//18014398509481984
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(type | x)

If the argument 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 the argument x is converted to widen(typeof(x)).

julia>widen(Int32)Int64julia>widen(1.5f0)1.5
identity(x)

The identity function. Returns its argument.

Types

super(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 DataTypeT. 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), and 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), and the syntax a.(b)=c calls setfield!(a,b,c).

fieldoffsets(type)

The byte offset of each field 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)=[zip(fieldoffsets(T),fieldnames(T),T.types)...];julia>structinfo(StatStruct)12-elementArray{Tuple{Int64,Symbol,DataType},1}:(0,:device,UInt64)(8,:inode,UInt64)(16,:mode,UInt64)(24,:nlink,Int64)(32,:uid,UInt64)(40,:gid,UInt64)(48,:rdev,UInt64)(56,:size,Int64)(64,:blksize,Int64)(72,:blocks,Int64)(80,:mtime,Float64)(88,: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})truejulia>isbits(Complex)false
isleaftype(T)

Determine whether T is a concrete type that can have instances, meaning its only subtypes are itself and None (but T itself is not None).

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>@enumFRUITapple=1orange=2kiwi=3julia>f(x::FRUIT)="I'm a FRUIT with value: $(Int(x))"f(genericfunction with1method)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+yend;julia>applicable(f,1)falsejulia>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|>inv0.01818181818181818
call(x, args...)

If x is not a Function, then x(args...) is equivalent to call(x,args...). This means that function-like behavior can be added to any type by defining new call methods.

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, @gensymxy 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,"(errormessage)"). 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)

Attempt to access the value of the Nullable object, x. Returns the value if it is present; otherwise, throws a NullException.

get(x, y)

Attempt to access the value of the Nullable{T} object, x. Returns the value if it is present; otherwise, returns convert(T,y).

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(`cattest.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.

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`,`grepxyz`))
  • run(pipeline(`ls`,"out.txt"))
  • run(pipeline("out.txt",`grepxyz`))
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 pipe(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() → AbstractString

Get the IP address of the local machine, as a string of the form “x.x.x.x”.

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 @timeexpr can also be used to time evaluation.

toc()

Print and return the time elapsed since the last tic().

toq()

Return, but do not print, the time elapsed since the last tic().

@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.

@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.

@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.

@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.

@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.

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.

@unix()

Given @unix?a:b, do a on Unix systems (including Linux and OS X) and b elsewhere. See documentation for Handling Platform Variations in the Calling C and Fortran Code section of the manual.

@osx()

Given @osx?a:b, do a on OS X and b elsewhere. See documentation for Handling Platform Variations in the Calling C and Fortran Code section of the manual.

@linux()

Given @linux?a:b, do a on Linux and b elsewhere. See documentation for Handling Platform Variations in the Calling C and Fortran Code section of the manual.

@windows()

Given @windows?a:b, do a on Windows and b elsewhere. See documentation for Handling Platform Variations in the Calling C and Fortran Code section of the manual.

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 @assertexpr.

@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 includeing, requireing, 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.

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.

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.

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.

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

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

isgeneric(f::Function) → Bool

Determine whether a Function is generic.

function_name(f::Function) → Symbol

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

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.

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 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 call, determines their types, and calls code_typed() on the resulting expression.

code_warntype(f, types)

Displays lowered and type-inferred ASTs for the methods matching the given generic function and type signature. 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 call, determines their types, and calls code_warntype() on the resulting expression.

code_llvm(f, types)

Prints the LLVM bitcodes generated for running the method matching the given generic function and type signature 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 call, determines their types, and calls code_llvm() on the resulting expression.

code_native(f, types)

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

@code_native()

Evaluates the arguments to the function 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.