### Install JuliaCall

Source: https://juliapy.github.io/PythonCall.jl/dev/juliacall

Installation commands for pip and conda environments.

```bash
pip install juliacall
```

```bash
conda install conda-forge::pyjuliacall
```

--------------------------------

### Install PythonCall

Source: https://juliapy.github.io/PythonCall.jl/dev/pythoncall

Use the Julia package manager to add the PythonCall package.

```julia
pkg> add PythonCall
```

--------------------------------

### Initialize JuliaCall

Source: https://juliapy.github.io/PythonCall.jl/dev/juliacall

Basic setup for interactive or scripting use by importing the Julia Main module.

```python
from juliacall import Main as jl
```

--------------------------------

### Install Python packages with CondaPkg

Source: https://juliapy.github.io/PythonCall.jl/dev/pythoncall

Use the Pkg REPL to add Python dependencies to your project.

```julia
julia> using CondaPkg

julia> # press ] to enter the Pkg REPL

pkg> conda add some_package
```

--------------------------------

### Configure PythonCall for existing Python installations

Source: https://juliapy.github.io/PythonCall.jl/dev/pythoncall

Set the CondaPkg backend to Null to use a pre-installed Python environment without automatic package management.

```julia
ENV["JULIA_CONDAPKG_BACKEND"] = "Null"
ENV["JULIA_PYTHONCALL_EXE"] = "/path/to/python"  # optional
```

```julia
pkg> preference add CondaPkg backend=Null
pkg> preference add PythonCall exe=/path/to/python  # optional
```

--------------------------------

### Get Python library handle

Source: https://juliapy.github.io/PythonCall.jl/dev/pythoncall-reference

Returns a handle to the open libpython or C_NULL if unknown.

```julia
python_library_handle()
```

--------------------------------

### pylen

Source: https://juliapy.github.io/PythonCall.jl/dev/pythoncall-reference

Gets the length of an object.

```APIDOC
## pylen(x)

### Description
The length of `x`. Equivalent to `len(x)` in Python, converted to an `Integer`.
```

--------------------------------

### Example of ccall requires the compiler error output

Source: https://juliapy.github.io/PythonCall.jl/dev/faq

This error occurs when incompatible versions of libstdc++.so are loaded by Python libraries before JuliaCall.

```text
ERROR: `ccall` requires the compilerTraceback (most recent call last):
  File "/home/dingraha/projects/pythoncall_import_error/run.py", line 2, in <module>
    from foo import Foo
  File "/home/dingraha/projects/pythoncall_import_error/foo.py", line 4, in <module>
    import juliacall; jl = juliacall.newmodule("FooModule")
  File "/home/dingraha/projects/pythoncall_import_error/venv/lib/python3.9/site-packages/juliacall/__init__.py", line 218, in <module>
    init()
  File "/home/dingraha/projects/pythoncall_import_error/venv/lib/python3.9/site-packages/juliacall/__init__.py", line 214, in init
    raise Exception('PythonCall.jl did not start properly')
Exception: PythonCall.jl did not start properly
```

--------------------------------

### Define custom wrapper type

Source: https://juliapy.github.io/PythonCall.jl/dev/pythoncall-reference

Example of creating a custom Julia struct that wraps a Python object.

```julia
# The new type with a field for the Python object being wrapped.
struct MyType
    py::Py
end

# Says that the object is a wrapper.
ispy(x::MyType) = true

# Says how to access the underlying Python object.
Py(x::MyType) = x.py
```

--------------------------------

### Get Python executable path

Source: https://juliapy.github.io/PythonCall.jl/dev/pythoncall-reference

Returns the file path to the Python interpreter or missing if unknown.

```julia
python_executable_path()
```

--------------------------------

### Get Python interpreter version

Source: https://juliapy.github.io/PythonCall.jl/dev/pythoncall-reference

Returns the version of the Python interpreter or missing if unknown.

```julia
python_version()
```

--------------------------------

### Get Python library path

Source: https://juliapy.github.io/PythonCall.jl/dev/pythoncall-reference

Returns the file path to libpython or missing if unknown.

```julia
python_library_path()
```

--------------------------------

### Error Message: Heap Corruption

Source: https://juliapy.github.io/PythonCall.jl/dev/faq

Example of the abort error that can occur on some systems when PyTorch and JuliaCall interact improperly.

```text
Python(65251,0x104cf8580) malloc: Heap corruption detected, free list is damaged at 0x600001c17280
*** Incorrect guard value: 1903002876
Python(65251,0x104cf8580) malloc: *** set a breakpoint in malloc_error_break to debug
[1]    65251 abort      ipython
```

--------------------------------

### Get underlying pointer

Source: https://juliapy.github.io/PythonCall.jl/dev/pythoncall-reference

Retrieves the raw pointer from a Python object.

```julia
getptr(x)
```

--------------------------------

### pyhelp

Source: https://juliapy.github.io/PythonCall.jl/dev/pythoncall-reference

Equivalent to the Python help() function.

```APIDOC
## pyhelp([x])

### Description
Equivalent to `help(x)` in Python.
```

--------------------------------

### Execute Julia code from Python

Source: https://juliapy.github.io/PythonCall.jl/dev/juliacall

Demonstrates calling Julia functions, generating arrays, and interacting with NumPy.

```python
jl.println("Hello from Julia!")
# Hello from Julia!
x = jl.rand(range(10), 3, 5)
x._jl_display()
# 3×5 Matrix{Int64}:
#  8  1  7  0  6
#  9  2  1  4  0
#  1  8  5  4  0
import numpy
numpy.sum(x, axis=0)
# array([18, 11, 13,  8,  6], dtype=int64)
```

--------------------------------

### Get next iterator item

Source: https://juliapy.github.io/PythonCall.jl/dev/pythoncall-reference

Returns the next item in the iterator or NULL if exhausted.

```julia
unsafe_pynext(x)
```

--------------------------------

### Load and Use juliacall IPython Extension

Source: https://juliapy.github.io/PythonCall.jl/dev/compat

Demonstrates loading the extension and using cell magic to synchronize variables between Python and Julia.

```python
In [1]: %load_ext juliacall

In [2]: x = 2

In [3]: y = 8

In [4]: %%julia x y z
   ...: z = "$x^$y = $(x^y)";
   ...:
   ...:

In [5]: z
Out[5]: '2^8 = 256'
```

--------------------------------

### pywith

Source: https://juliapy.github.io/PythonCall.jl/dev/pythoncall-reference

Executes a function within a context manager.

```APIDOC
## pywith(f, o, d=nothing)

### Description
Equivalent to `with o as x: f(x)` in Python, where `x` is a `Py`. On success, the value of `f(x)` is returned. If an exception occurs but is suppressed then `d` is returned.
```

--------------------------------

### Import and use Julia Main module

Source: https://juliapy.github.io/PythonCall.jl/dev/juliacall-reference

Use the Main module as an entry point for interactive scripts to access Julia functionality.

```python
from juliacall import Main as jl
jl.println("Hello, world!")
```

--------------------------------

### Initialize CondaPkg and PythonCall in a script

Source: https://juliapy.github.io/PythonCall.jl/dev/faq

Ensure CondaPkg is loaded before PythonCall to correctly manage Python package dependencies.

```julia
using CondaPkg

CondaPkg.add("numpy")

using PythonCall

np = pyimport("numpy")
```

--------------------------------

### pyprint

Source: https://juliapy.github.io/PythonCall.jl/dev/pythoncall-reference

Prints objects to the standard output.

```APIDOC
## pyprint(...)

### Description
Equivalent to `print(...)` in Python.
```

--------------------------------

### pybinaryio(io::IO)

Source: https://juliapy.github.io/PythonCall.jl/dev/pythoncall-reference

Wraps a Julia IO object as a Python binary IO object.

```APIDOC
## pybinaryio(io::IO)

### Description
Wrap `io` as a Python binary IO object.
```

--------------------------------

### Configure PythonCall for system-level Conda or Pixi

Source: https://juliapy.github.io/PythonCall.jl/dev/pythoncall

Use the System or SystemPixi backend to leverage a pre-installed Conda or Pixi implementation.

```julia
ENV["JULIA_CONDAPKG_BACKEND"] = "System"  # or "SystemPixi" for Pixi
ENV["JULIA_CONDAPKG_EXE"] = "/path/to/conda"  # optional
```

```julia
pkg> preference add CondaPkg backend=System
pkg> preference add CondaPkg exe=/path/to/conda  # optional
```

--------------------------------

### Wrapping Python sequences with PyList

Source: https://juliapy.github.io/PythonCall.jl/dev/pythoncall

Demonstrates wrapping a Python list as a Julia vector and performing mutations that reflect in the original Python object.

```julia
julia> x = pylist([3,4,5])
Python: [3, 4, 5]

julia> y = PyList{Union{Int,Nothing}}(x)
3-element PyList{Union{Nothing, Int64}}:
 3
 4
 5

julia> push!(y, nothing)
4-element PyList{Union{Nothing, Int64}}:
 3
 4
 5
  nothing

julia> append!(y, 1:2)
6-element PyList{Union{Nothing, Int64}}:
 3
 4
 5
  nothing
 1
 2

julia> x
Python: [3, 4, 5, None, 1, 2]
```

--------------------------------

### Error Message: AttributeError

Source: https://juliapy.github.io/PythonCall.jl/dev/faq

Example of the error encountered when a Python package expects a native Numpy array but receives a Julia ArrayValue.

```text
AttributeError: Julia: type Array has no field dtype
```

--------------------------------

### fix_qt_plugin_path()

Source: https://juliapy.github.io/PythonCall.jl/dev/compat

Sets the QT_PLUGIN_PATH environment variable to ensure Qt can locate its configuration files.

```APIDOC
## fix_qt_plugin_path()

### Description
Attempts to set the `QT_PLUGIN_PATH` environment variable in Python if it is not already set. This resolves issues where Qt fails to find its `qt.conf` file when running within the Julia executable.
```

--------------------------------

### Construct TimeDelta64

Source: https://juliapy.github.io/PythonCall.jl/dev/pythoncall-reference

Constructs a TimeDelta64 where the unit is stored at runtime.

```julia
TimeDelta64(value, [unit])
```

--------------------------------

### Set PythonCall preferences via Pkg REPL

Source: https://juliapy.github.io/PythonCall.jl/dev/pythoncall

Use the PreferenceTools package to add configuration preferences directly from the Julia Pkg REPL.

```julia
julia> using PreferenceTools
julia> # now press ] to enter the Pkg REPL
pkg> preference add PythonCall exe=/path/to/python
```

--------------------------------

### Fix Qt Plugin Path

Source: https://juliapy.github.io/PythonCall.jl/dev/compat

Configures the QT_PLUGIN_PATH environment variable to ensure Qt locates its configuration files correctly when running within Julia.

```julia
fix_qt_plugin_path()
```

--------------------------------

### Avoid Python interaction during precompilation

Source: https://juliapy.github.io/PythonCall.jl/dev/pythoncall

Demonstrates patterns for safely importing Python modules in Julia packages to prevent crashes during precompilation.

```julia
module MyModule
  using PythonCall
  const foo = pyimport("foo")
  bar() = foo.bar() # will crash when called
end
```

```julia
module MyModule
  using PythonCall
  const foo = Ref{Py}()
  function __init__()
    foo[] = pyimport("foo")
  end
  bar() = foo[].bar()
end
```

```julia
module MyModule
  using PythonCall
  bar() = pyimport("foo").bar()
end
```

```julia
module MyModule
  using PythonCall
  bar() = @pyconst(pyimport("foo")).bar()
end
```

```julia
module MyModule
  using PythonCall
  bar() = @pyconst(pyimport("foo").bar)()
end
```

--------------------------------

### Construct DateTime64

Source: https://juliapy.github.io/PythonCall.jl/dev/pythoncall-reference

Constructs a DateTime64 where the unit is stored at runtime.

```julia
DateTime64(value, [unit])
DateTime64(value, format, [unit])
```

--------------------------------

### pytextio(io::IO)

Source: https://juliapy.github.io/PythonCall.jl/dev/pythoncall-reference

Wraps a Julia IO object as a Python text IO object.

```APIDOC
## pytextio(io::IO)

### Description
Wrap `io` as a Python text IO object.
```

--------------------------------

### Import PythonCall

Source: https://juliapy.github.io/PythonCall.jl/dev/pythoncall

Load the module into the Julia environment.

```julia
julia> using PythonCall
```

--------------------------------

### Activate GUI Event Loop

Source: https://juliapy.github.io/PythonCall.jl/dev/compat

Enables background event processing for specific GUI frameworks to support interactive modes.

```julia
event_loop_on(g::Symbol; interval=0.04, fix=false)
```

--------------------------------

### Define Julia dependencies in juliapkg.json

Source: https://juliapy.github.io/PythonCall.jl/dev/juliacall

Create a juliapkg.json file to specify required Julia versions and packages for your project.

```json
{
    "julia": "1.5",
    "packages": {
        "Example": {
            "uuid": "7876af07-990d-54b4-ab0e-23690620f79a",
            "version": "0.5, 0.6"
        }
    }
}
```

--------------------------------

### pytable(src, format=:pandas; ...)

Source: https://juliapy.github.io/PythonCall.jl/dev/compat

Constructs a Python table from a Tables.jl-compatible table source.

```APIDOC
## pytable(src, format=:pandas; ...)

### Description
Constructs a Python table from a Tables.jl-compatible table `src`. The `format` parameter determines the resulting Python object type.

### Parameters
- **src** (Any) - Required - A Tables.jl-compatible table.
- **format** (Symbol) - Optional - The target format. Supported values: `:pandas` (pandas.DataFrame), `:columns` (dict), `:rows` (list of namedtuples), `:rowdicts` (list of dicts).
- **...** (Keyword arguments) - Optional - Additional arguments passed to the constructor (e.g., to the `DataFrame` constructor when using `:pandas`).
```

--------------------------------

### PythonCall.pyproperty

Source: https://juliapy.github.io/PythonCall.jl/dev/pythoncall-reference

Creates a Python property with getter, setter, and deleter.

```APIDOC
## pyproperty(; get=nothing, set=nothing, del=nothing, doc=nothing)

### Description
Creates a Python `property` with the given getter, setter, and deleter functions. If provided, functions are converted to Python callables via `pyfunc`.
```

--------------------------------

### PythonCall.PySet

Source: https://juliapy.github.io/PythonCall.jl/dev/pythoncall-reference

Wraps a Python set as a Julia AbstractSet.

```APIDOC
## PySet{T=Py}([x])

Wraps the Python set `x` (or anything satisfying the set interface) as an `AbstractSet{T}`. If `x` is not a Python object, it is converted to one using `pyset`.
```

--------------------------------

### Pass variables and return multiple outputs with @pyexec

Source: https://juliapy.github.io/PythonCall.jl/dev/pythoncall

Demonstrates passing named variables to Python and returning multiple functions or values, including type casting.

```julia
julia> @pyexec (num=10) => """
           def add(a, b):
             return a + b

           def subtract(a, b):
               return a - b

           plusone = num + 1
           """ => (add, subtract, plusone::Float64)
(add = <py function add at 0x721b001a7cc0>, subtract = <py function subtract at 0x721b001a7d70>, plusone = 11.0)

julia> add(4, 3)
Python: 7

julia> subtract(4, 3)
Python: 1

julia> plusone
11.0
```

--------------------------------

### Configure PythonCall for existing Conda environments

Source: https://juliapy.github.io/PythonCall.jl/dev/pythoncall

Use the Current backend to utilize an already activated Conda environment.

```julia
ENV["JULIA_CONDAPKG_BACKEND"] = "Current"
ENV["JULIA_CONDAPKG_EXE"] = "/path/to/conda"  # optional
```

```julia
pkg> preference add CondaPkg backend=Current
pkg> preference add CondaPkg exe=/path/to/conda  # optional
```

--------------------------------

### PythonCall.pyexec

Source: https://juliapy.github.io/PythonCall.jl/dev/pythoncall-reference

Execute Python code.

```APIDOC
## pyexec([T=Nothing], code, globals, locals=nothing)

### Description
Executes the provided Python code. If T is provided, it extracts variables from the local scope.

### Signature
`pyexec([T=Nothing], code, globals, locals=nothing)`
```

--------------------------------

### pyin

Source: https://juliapy.github.io/PythonCall.jl/dev/pythoncall-reference

Checks for membership in a Python object.

```APIDOC
## pyin(v, x)

### Description
Equivalent to `v in x` in Python.
```

--------------------------------

### event_loop_on(g::Symbol; interval=0.04, fix=false)

Source: https://juliapy.github.io/PythonCall.jl/dev/compat

Activates an event loop for a specified GUI framework, allowing it to run in the background of a Julia session.

```APIDOC
## event_loop_on(g::Symbol; interval=0.04, fix=false)

### Description
Activates an event loop for the GUI framework `g`, so that the framework can run in the background of a Julia session. The event loop runs every `interval` seconds.

### Parameters
- **g** (Symbol) - Required - The GUI framework to activate. Supported values: :pyqt4, :pyqt5, :pyside, :pyside2, :pyside6, :gtk, :gtk3, :wx, :tkinter.
- **interval** (Float64) - Optional - The interval in seconds at which the event loop runs. Defaults to 0.04.
- **fix** (Bool) - Optional - If true and `g` is a Qt framework, `fix_qt_plugin_path` is called. Defaults to false.
```

--------------------------------

### pysetitem

Source: https://juliapy.github.io/PythonCall.jl/dev/pythoncall-reference

Sets an item in a Python object.

```APIDOC
## pysetitem(x, k, v)

### Description
Equivalent to `setitem(x, k, v)` or `x[k] = v` in Python.
```

--------------------------------

### Create a new Julia module

Source: https://juliapy.github.io/PythonCall.jl/dev/juliacall-reference

Create a new module with a specified name, typically used within packages.

```python
newmodule(name)
```

--------------------------------

### Create a Python property

Source: https://juliapy.github.io/PythonCall.jl/dev/pythoncall-reference

Creates a Python property with optional getter, setter, and deleter functions.

```julia
pyproperty(; get=nothing, set=nothing, del=nothing, doc=nothing)
pyproperty(get)
```

--------------------------------

### PythonCall.pyall

Source: https://juliapy.github.io/PythonCall.jl/dev/pythoncall-reference

Equivalent to the Python all(x) function.

```APIDOC
## pyall(x)

### Description
Returns true if all elements of the iterable x are true (or if the iterable is empty).

### Signature
`pyall(x)`
```

--------------------------------

### Wrapping Python file objects with PyIO

Source: https://juliapy.github.io/PythonCall.jl/dev/pythoncall

Views a Python file object as a Julia IO object for standard IO operations.

```julia
julia> x = pyimport("io").StringIO()
Python: <_io.StringIO object at 0x000000006579BC70>

julia> y = PyIO(x)
PyIO(<py _io.StringIO object at 0x000000006579BC70>, false, true, false, 4096, UInt8[], 4096, UInt8[])

julia> println(y, "Hello, world!")

julia> flush(y)

julia> x.seek(0)
Python: 0

julia> x.read()
Python: 'Hello, world!\n'
```

--------------------------------

### PythonCall.pyany

Source: https://juliapy.github.io/PythonCall.jl/dev/pythoncall-reference

Equivalent to the Python any(x) function.

```APIDOC
## pyany(x)

### Description
Returns true if any element of the iterable x is true.

### Signature
`pyany(x)`
```

--------------------------------

### Define PyIO wrapper

Source: https://juliapy.github.io/PythonCall.jl/dev/pythoncall-reference

Wraps a Python IO stream as a Julia IO stream with configurable buffering and text/binary modes.

```julia
PyIO(x; own=false, text=missing, line_buffering=false, buflen=4096)
```

--------------------------------

### Create a new Julia module

Source: https://juliapy.github.io/PythonCall.jl/dev/juliacall

Use this approach when developing packages to avoid polluting the global Main namespace.

```python
import juliacall
jl = juliacall.newmodule("SomeName")
```

--------------------------------

### Define PySet wrapper

Source: https://juliapy.github.io/PythonCall.jl/dev/pythoncall-reference

Wraps a Python set or set-like object as a Julia AbstractSet.

```julia
PySet{T=Py}([x])
```

--------------------------------

### Wrap IO streams for Python

Source: https://juliapy.github.io/PythonCall.jl/dev/pythoncall-reference

Functions to wrap Julia IO streams as Python binary or text IO objects.

```julia
pybinaryio(io::IO)
```

```julia
pytextio(io::IO)
```

--------------------------------

### pynext

Source: https://juliapy.github.io/PythonCall.jl/dev/pythoncall-reference

Retrieves the next item from an iterator.

```APIDOC
## pynext(x, [d])

### Description
Equivalent to `next(x, d)` in Python. Returns the next item from the iterator `x`. If there are no more items, returns `d` if given, else raises `StopIteration`.
```

--------------------------------

### juliacall.newmodule(name)

Source: https://juliapy.github.io/PythonCall.jl/dev/juliacall-reference

Creates a new Julia module with the specified name.

```APIDOC
## juliacall.newmodule(name)

### Description
Creates a new module with the given name.

### Parameters
- **name** (str) - Required - The name of the new module.
```

--------------------------------

### Accessing Parametric Types with TypeValue

Source: https://juliapy.github.io/PythonCall.jl/dev/juliacall-reference

Demonstrates using indexing on a TypeValue to replicate Julia's curly syntax for parametric types.

```python
from juliacall import Main as jl
# equivalent to Vector{Int}() in Julia
jl.Vector[jl.Int]()
```

--------------------------------

### TimeDelta64

Source: https://juliapy.github.io/PythonCall.jl/dev/pythoncall-reference

Constructs a TimeDelta64 type where the unit is stored as a run-time value.

```APIDOC
## TimeDelta64

### Description
Construct a `TimeDelta64` with the given `value` and `unit`. The unit is stored as a run-time value, and the memory layout matches `numpy.timedelta64`.

### Signature
`TimeDelta64(value, [unit])`

### Parameters
- **value** (Integer, String) - Required - The value to represent.
- **unit** (Unit) - Optional - The time unit for the value.
```

--------------------------------

### Compare less than or equal with pyle

Source: https://juliapy.github.io/PythonCall.jl/dev/pythoncall-reference

Checks if x is less than or equal to y, equivalent to x <= y in Python.

```julia
pyle(x, y)
pyle(Bool, x, y)
```

--------------------------------

### Interact with Python Modules

Source: https://juliapy.github.io/PythonCall.jl/dev/pythoncall

Import Python modules and perform operations using Python objects.

```julia
julia> re = pyimport("re")
Python: <module 're' from '[...]/lib/re.py'>

julia> words = re.findall("[a-zA-Z]+", "PythonCall.jl is very useful!")
Python: ['PythonCall', 'jl', 'is', 'very', 'useful']

julia> sentence = Py(" ").join(words)
Python: 'PythonCall jl is very useful'

julia> pyconvert(String, sentence)
"PythonCall jl is very useful"
```

--------------------------------

### Python Builtin Equivalents

Source: https://juliapy.github.io/PythonCall.jl/dev/pythoncall-reference

Functions that provide direct equivalents to Python's built-in functions.

```julia
pyall(x)
```

```julia
pyany(x)
```

```julia
pyascii(x)
```

```julia
pycall(f, args...; kwargs...)
```

```julia
pycallable(x)
```

```julia
pycompile(...)
```

```julia
pycontains(x, v)
```

```julia
pydelattr(x, k)
```

```julia
pydelitem(x, k)
```

```julia
pydir(x)
```

--------------------------------

### PythonCall.pystaticmethod

Source: https://juliapy.github.io/PythonCall.jl/dev/pythoncall-reference

Converts a callable to a Python static method.

```APIDOC
## pystaticmethod(f; ...)

### Description
Converts callable `f` to a Python static method. If `f` is a Julia function, it is converted using `pyfunc`.
```

--------------------------------

### Execute Python Code

Source: https://juliapy.github.io/PythonCall.jl/dev/pythoncall-reference

Functions and macros for executing Python code, with support for persistent module scope.

```julia
pyexec([T=Nothing], code, globals, locals=nothing)
```

```julia
pyexec(@NamedTuple{ans::Float64}, "ans=x+y", Main, (x=1.1, y=2.2))  # returns (ans = 3.3,)
```

```julia
pyexec("global x; x=12", Main)
pyeval(Int, "x", Main)  # returns 12
```

```julia
@pyexec [inputs =>] code [=> outputs]
```

```julia
@pyexec (x=1.1, y=2.2) => `ans=x+y` => ans::Float64  # returns 3.3
```

```julia
@pyexec `global x; x=12`
@pyeval `x` => Int  # returns 12
```

--------------------------------

### Create a new Py object

Source: https://juliapy.github.io/PythonCall.jl/dev/pythoncall-reference

Creates a new Py object representing the Python object at the given pointer. Steals the reference if a pointer is provided.

```julia
pynew([ptr])
```

--------------------------------

### DateTime64

Source: https://juliapy.github.io/PythonCall.jl/dev/pythoncall-reference

Constructs a DateTime64 type where the unit is stored as a run-time value.

```APIDOC
## DateTime64

### Description
Construct a `DateTime64` with the given `value` and `unit`. The unit is stored as a run-time value, and the memory layout matches `numpy.datetime64`.

### Signature
`DateTime64(value, [unit])`
`DateTime64(value, format, [unit])`

### Parameters
- **value** (Integer, Dates.Date, Dates.DateTime, String) - Required - The value to represent.
- **unit** (Unit) - Optional - The time unit for the value.
- **format** (String) - Optional - Format string for parsing the value.
```

--------------------------------

### pyimport

Source: https://juliapy.github.io/PythonCall.jl/dev/pythoncall-reference

Imports Python modules or attributes.

```APIDOC
## pyimport(m)
## pyimport(m => k)
## pyimport(m => (k1, k2, ...))
## pyimport(m1, m2, ...)

### Description
Import a module `m`, or an attribute `k`, or a tuple of attributes. If several arguments are given, return the results of importing each one in a tuple.
```

--------------------------------

### pyrepr

Source: https://juliapy.github.io/PythonCall.jl/dev/pythoncall-reference

Returns the string representation of an object.

```APIDOC
## pyrepr(x)

### Description
Equivalent to `repr(x)` in Python.
```

--------------------------------

### Define PyTable wrapper

Source: https://juliapy.github.io/PythonCall.jl/dev/pythoncall-reference

Wraps an object as a Tables.jl-compatible table.

```julia
PyTable(x)
```

--------------------------------

### pynot(x)

Source: https://juliapy.github.io/PythonCall.jl/dev/pythoncall-reference

Returns the falsiness of x, equivalent to not x in Python, converted to a Julia Bool.

```APIDOC
## pynot(x)

### Description
Returns the falsiness of x, equivalent to not x in Python, converted to a Julia Bool.
```

--------------------------------

### PythonCall.PyIO

Source: https://juliapy.github.io/PythonCall.jl/dev/pythoncall-reference

Wraps a Python IO stream as a Julia IO stream.

```APIDOC
## PyIO(x; own=false, text=missing, line_buffering=false, buflen=4096)

Wrap the Python IO stream `x` as a Julia IO stream. When this goes out of scope and is finalized, it is automatically flushed.
```

--------------------------------

### Evaluate Python Code

Source: https://juliapy.github.io/PythonCall.jl/dev/pythoncall-reference

Functions and macros for evaluating Python code strings or commands.

```julia
pyeval([T=Py], code, globals, locals=nothing)
```

```julia
pyeval(Float64, "x+y", Main, (x=1.1, y=2.2))  # returns 3.3
```

```julia
@pyeval [inputs =>] code [=> T]
```

```julia
@pyeval (x=1.1, y=2.2) => `x+y` => Float64  # returns 3.3
```

--------------------------------

### PythonCall.@pyeval

Source: https://juliapy.github.io/PythonCall.jl/dev/pythoncall-reference

Macro to evaluate a Python expression.

```APIDOC
## @pyeval [inputs =>] code [=> T]

### Description
Macro version of pyeval that evaluates code in a new local scope.

### Signature
`@pyeval [inputs =>] code [=> T]`
```

--------------------------------

### PythonCall.@pyexec

Source: https://juliapy.github.io/PythonCall.jl/dev/pythoncall-reference

Macro to execute Python code.

```APIDOC
## @pyexec [inputs =>] code [=> outputs]

### Description
Macro version of pyexec to execute code and optionally extract outputs.

### Signature
`@pyexec [inputs =>] code [=> outputs]`
```

--------------------------------

### Define PyObjectArray wrapper

Source: https://juliapy.github.io/PythonCall.jl/dev/pythoncall-reference

Creates an array of Py objects that supports the Python buffer protocol.

```julia
PyObjectArray(undef, dims...)
PyObjectArray(array)
```

--------------------------------

### Define PyList wrapper

Source: https://juliapy.github.io/PythonCall.jl/dev/pythoncall-reference

Wraps a Python list or sequence as a Julia AbstractVector.

```julia
PyList{T=Py}([x])
```

--------------------------------

### pytruth(x)

Source: https://juliapy.github.io/PythonCall.jl/dev/pythoncall-reference

Returns the truthiness of x, equivalent to bool(x) in Python, converted to a Julia Bool.

```APIDOC
## pytruth(x)

### Description
Returns the truthiness of x, equivalent to bool(x) in Python, converted to a Julia Bool.
```

--------------------------------

### Create a Python type with pytype

Source: https://juliapy.github.io/PythonCall.jl/dev/pythoncall-reference

Defines a new Python class using Julia functions, including methods, class methods, static methods, and properties.

```julia
pytype(name, bases, dict)
```

```julia
Foo = pytype("Foo", (), [
    "__module__" => "__main__",

    pyfunc(
        name = "__init__",
        doc = """
        Specify x and y to store in the Foo.

        If omitted, y defaults to None.
        """,
        function (self, x, y = nothing)
            self.x = x
            self.y = y
            return
        end,
    ),

    pyfunc(
        name = "__repr__",
        self -> "Foo($(self.x), $(self.y))",
    ),

    pyclassmethod(
        name = "frompair",
        doc = "Construct a Foo from a tuple of length two.",
        (cls, xy) -> cls(xy...),
    ),

    pystaticmethod(
        name = "hello",
        doc = "Prints a friendly greeting.",
        (name) -> println("Hello, $name"),
    ),

    "xy" => pyproperty(
        doc = "A tuple of x and y.",
        get = (self) -> (self.x, self.y),
        set = function (self, xy)
            (x, y) = xy
            self.x = x
            self.y = y
            nothing
        end,
    ),
])
```

--------------------------------

### Arithmetic Functions

Source: https://juliapy.github.io/PythonCall.jl/dev/pythoncall-reference

A collection of functions that map directly to Python arithmetic operators and built-in functions.

```APIDOC
## Arithmetic Functions

### Description
These functions provide direct equivalents to Python's arithmetic operators and built-in functions. They can be used to perform operations on Python objects within Julia.

### Functions
- **pyneg(x)**: Equivalent to `-x` in Python.
- **pypos(x)**: Equivalent to `+x` in Python.
- **pyabs(x)**: Equivalent to `abs(x)` in Python.
- **pyinv(x)**: Equivalent to `~x` in Python.
- **pyindex(x)**: Convert `x` losslessly to an `int`.
- **pyadd(x, y)**: Equivalent to `x + y` in Python.
- **pysub(x, y)**: Equivalent to `x - y` in Python.
- **pymul(x, y)**: Equivalent to `x * y` in Python.
- **pymatmul(x, y)**: Equivalent to `x @ y` in Python.
- **pypow(x, y, z=None)**: Equivalent to `x ** y` or `pow(x, y, z)` in Python.
- **pyfloordiv(x, y)**: Equivalent to `x // y` in Python.
- **pytruediv(x, y)**: Equivalent to `x / y` in Python.
- **pymod(x, y)**: Equivalent to `x % y` in Python.
- **pydivmod(x, y)**: Equivalent to `divmod(x, y)` in Python.
- **pylshift(x, y)**: Equivalent to `x << y` in Python.
- **pyrshift(x, y)**: Equivalent to `x >> y` in Python.
- **pyand(x, y)**: Equivalent to `x & y` in Python.
- **pyxor(x, y)**: Equivalent to `x ^ y` in Python.
- **pyor(x, y)**: Equivalent to `x | y` in Python.
```

```APIDOC
## In-place Arithmetic Functions

### Description
These functions perform in-place arithmetic operations, equivalent to Python's augmented assignment operators.

### Functions
- **pyiadd(x, y)**: Equivalent to `x += y`.
- **pyisub(x, y)**: Equivalent to `x -= y`.
- **pyimul(x, y)**: Equivalent to `x *= y`.
- **pyimatmul(x, y)**: Equivalent to `x @= y`.
- **pyipow(x, y, z=None)**: Equivalent to `x **= y`.
- **pyifloordiv(x, y)**: Equivalent to `x //= y`.
- **pyitruediv(x, y)**: Equivalent to `x /= y`.
- **pyimod(x, y)**: Equivalent to `x %= y`.
- **pyilshift(x, y)**: Equivalent to `x <<= y`.
- **pyirshift(x, y)**: Equivalent to `x >>= y`.
- **pyiand(x, y)**: Equivalent to `x &= y`.
- **pyixor(x, y)**: Equivalent to `x ^= y`.
- **pyior(x, y)**: Equivalent to `x |= y`.
```

--------------------------------

### Convert to a Python static method

Source: https://juliapy.github.io/PythonCall.jl/dev/pythoncall-reference

Converts a callable to a Python static method, ensuring arguments are passed as Py objects.

```julia
pystaticmethod(f; ...)
```

--------------------------------

### pyiter

Source: https://juliapy.github.io/PythonCall.jl/dev/pythoncall-reference

Creates an iterator from an object.

```APIDOC
## pyiter(x)

### Description
Equivalent to `iter(x)` in Python.
```

--------------------------------

### Compare less than with pylt

Source: https://juliapy.github.io/PythonCall.jl/dev/pythoncall-reference

Checks if x is less than y, equivalent to x < y in Python.

```julia
pylt(x, y)
pylt(Bool, x, y)
```

--------------------------------

### Execute Python code with @pyexec

Source: https://juliapy.github.io/PythonCall.jl/dev/pythoncall

Uses the @pyexec macro to define a Python function and map it to a Julia variable.

```julia
julia> @pyexec """
           global re
           import re

           def my_sentence(s):
               words = re.findall("[a-zA-Z]+", s)
               sentence = " ".join(words)
               return sentence
           """ => my_sentence
Python: <function my_sentence at 0x7d83bb1b01a0>

julia> sentence = my_sentence("PythonCall.jl is very useful!")
Python: 'PythonCall jl is very useful'
```

--------------------------------

### pyne(x, y)

Source: https://juliapy.github.io/PythonCall.jl/dev/pythoncall-reference

Equivalent to x != y in Python. The version with Bool converts the result to a Julia Bool.

```APIDOC
## pyne(x, y)

### Description
Equivalent to x != y in Python. The second form `pyne(Bool, x, y)` converts the result to a Julia Bool.
```

--------------------------------

### Construct InlineDateTime64

Source: https://juliapy.github.io/PythonCall.jl/dev/pythoncall-reference

Constructs an InlineDateTime64 where the unit is encoded in the type.

```julia
InlineDateTime64{unit}(value)
InlineDateTime64{unit}(value, format)
InlineDateTime64(value, [unit])
InlineDateTime64(value, format, [unit])
```

--------------------------------

### Evaluate Julia code strings

Source: https://juliapy.github.io/PythonCall.jl/dev/juliacall

Use seval to execute Julia code strings, commonly used for importing Julia modules.

```python
from array import array
jl.seval("using Statistics")
x = array('i', [1, 2, 3])
jl.mean(x)
# 2.0
y = array('i', [2,4,8])
jl.cor(x, y)
# 0.9819805060619657
```

--------------------------------

### Copy Python object into destination

Source: https://juliapy.github.io/PythonCall.jl/dev/pythoncall-reference

Copies the source Python object into the destination Py object. Used for module-level constant initialization.

```julia
pycopy!(dst::Py, src)
```

--------------------------------

### Wrapping Python arrays with PyArray

Source: https://juliapy.github.io/PythonCall.jl/dev/pythoncall

Provides a Julia array view of Python objects satisfying the buffer protocol or numpy array interface.

```julia
julia> x = pyimport("array").array("i", [3, 4, 5])
Python: array('i', [3, 4, 5])

julia> y = PyArray(x)
3-element PyArray{Int32, 1, true, true, Int32}:
 3
 4
 5

julia> sum(y)
12

julia> y[1] = 0
0

julia> x
Python: array('i', [0, 4, 5])
```

--------------------------------

### Construct InlineTimeDelta64

Source: https://juliapy.github.io/PythonCall.jl/dev/pythoncall-reference

Constructs an InlineTimeDelta64 where the unit is encoded in the type.

```julia
InlineTimeDelta64{unit}(value)
InlineTimeDelta64(value, [unit])
```

--------------------------------

### Parallel Python Execution with GIL Management

Source: https://juliapy.github.io/PythonCall.jl/dev/pythoncall

Uses GIL unlock/lock macros to safely execute Python code across multiple Julia threads.

```julia
PythonCall.GIL.@unlock Threads.@threads for i in 1:4
  PythonCall.GIL.@lock pyimport("time").sleep(5)
end
```

--------------------------------

### pysetattr

Source: https://juliapy.github.io/PythonCall.jl/dev/pythoncall-reference

Sets an attribute on a Python object.

```APIDOC
## pysetattr(x, k, v)

### Description
Equivalent to `setattr(x, k, v)` or `x.k = v` in Python.
```

--------------------------------

### pyeq(x, y)

Source: https://juliapy.github.io/PythonCall.jl/dev/pythoncall-reference

Equivalent to x == y in Python. The version with Bool converts the result to a Julia Bool.

```APIDOC
## pyeq(x, y)

### Description
Equivalent to x == y in Python. The second form `pyeq(Bool, x, y)` converts the result to a Julia Bool.
```

--------------------------------

### Compare greater than or equal with pyge

Source: https://juliapy.github.io/PythonCall.jl/dev/pythoncall-reference

Checks if x is greater than or equal to y, equivalent to x >= y in Python.

```julia
pyge(x, y)
pyge(Bool, x, y)
```

--------------------------------

### InlineTimeDelta64

Source: https://juliapy.github.io/PythonCall.jl/dev/pythoncall-reference

Constructs an InlineTimeDelta64 type where the unit is part of the type definition.

```APIDOC
## InlineTimeDelta64

### Description
Construct an `InlineTimeDelta64` with the given `value` and `unit`. The unit is part of the type.

### Signature
`InlineTimeDelta64{unit}(value)`
`InlineTimeDelta64(value, [unit])`

### Parameters
- **value** (Integer, String) - Required - The value to represent. Can be an integer, "NaT", or "NaN".
- **unit** (Unit) - Optional - The time unit for the value.
```

--------------------------------

### Wrap Julia values as raw Python objects with pyjlraw

Source: https://juliapy.github.io/PythonCall.jl/dev/pythoncall-reference

Wraps a Julia object into a Python object with a rigid Julian interface.

```julia
pyjlraw(v)
```

--------------------------------

### pylt(x, y)

Source: https://juliapy.github.io/PythonCall.jl/dev/pythoncall-reference

Equivalent to x < y in Python. The version with Bool converts the result to a Julia Bool.

```APIDOC
## pylt(x, y)

### Description
Equivalent to x < y in Python. The second form `pylt(Bool, x, y)` converts the result to a Julia Bool.
```

--------------------------------

### pyjlraw(v)

Source: https://juliapy.github.io/PythonCall.jl/dev/pythoncall-reference

Wraps a Julia object into a Python object with a rigid Julian interface.

```APIDOC
## pyjlraw(v)

### Description
Create a Python object wrapping the Julia object `x`. It has type `juliacall.RawValue`, which provides a rigid "Julian" interface.
```

--------------------------------

### InlineDateTime64

Source: https://juliapy.github.io/PythonCall.jl/dev/pythoncall-reference

Constructs an InlineDateTime64 type where the unit is part of the type definition.

```APIDOC
## InlineDateTime64

### Description
Construct an `InlineDateTime64` with the given `value` and `unit`. The unit is part of the type, so an instance consists of one `Int64` for the value.

### Signature
`InlineDateTime64{unit}(value)`
`InlineDateTime64{unit}(value, format)`
`InlineDateTime64(value, [unit])`
`InlineDateTime64(value, format, [unit])`

### Parameters
- **value** (Integer, Dates.Date, Dates.DateTime, String) - Required - The value to represent. Can be an integer, date/time object, "NaT", "NaN", or a string to be parsed.
- **unit** (Unit) - Optional - The time unit for the value.
- **format** (String) - Optional - Format string for parsing the value.
```

--------------------------------

### Define PyException wrapper

Source: https://juliapy.github.io/PythonCall.jl/dev/pythoncall-reference

Wraps a Python exception as a Julia Exception.

```julia
PyException(x)
```

--------------------------------

### Convert Python list to Julia vector

Source: https://juliapy.github.io/PythonCall.jl/dev/pythoncall

Demonstrates converting a Python list to various Julia vector types using pyconvert.

```julia
julia> x = pylist([3.4, 5.6])
Python: [3.4, 5.6]

julia> pyconvert(Vector, x)
2-element Vector{Float64}:
 3.4
 5.6

julia> pyconvert(Vector{Float32}, x)
2-element Vector{Float32}:
 3.4
 5.6

julia> pyconvert(Any, x)
2-element PyList{Any}:
 3.4
 5.6
```

--------------------------------

### PythonCall.PyDict

Source: https://juliapy.github.io/PythonCall.jl/dev/pythoncall-reference

Wraps a Python dict as a Julia AbstractDict.

```APIDOC
## PyDict{K=Py,V=Py}([x])

Wraps the Python dict `x` (or anything satisfying the mapping interface) as an `AbstractDict{K,V}`. If `x` is not a Python object, it is converted to one using `pydict`.
```

--------------------------------

### pyge(x, y)

Source: https://juliapy.github.io/PythonCall.jl/dev/pythoncall-reference

Equivalent to x >= y in Python. The version with Bool converts the result to a Julia Bool.

```APIDOC
## pyge(x, y)

### Description
Equivalent to x >= y in Python. The second form `pyge(Bool, x, y)` converts the result to a Julia Bool.
```

--------------------------------

### Convert to a Python class method

Source: https://juliapy.github.io/PythonCall.jl/dev/pythoncall-reference

Converts a callable to a Python class method, ensuring arguments are passed as Py objects.

```julia
pyclassmethod(f; ...)
```

--------------------------------

### PythonCall.PyList

Source: https://juliapy.github.io/PythonCall.jl/dev/pythoncall-reference

Wraps a Python list or sequence as a Julia AbstractVector.

```APIDOC
## PyList{T=Py}([x])

Wraps the Python list `x` (or anything satisfying the sequence interface) as an `AbstractVector{T}`. If `x` is not a Python object, it is converted to one using `pylist`.
```

--------------------------------

### Register a custom conversion rule

Source: https://juliapy.github.io/PythonCall.jl/dev/conversion-to-julia

Use this function to register a new conversion rule for pyconvert. It should typically be called within the __init__ function of a module to avoid issues during precompilation.

```julia
pyconvert_add_rule(tname::String, T::Type, func::Function, priority::PyConvertPriority=PYCONVERT_PRIORITY_NORMAL)
```

--------------------------------

### PythonCall.pyeval

Source: https://juliapy.github.io/PythonCall.jl/dev/pythoncall-reference

Evaluate a Python expression.

```APIDOC
## pyeval([T=Py], code, globals, locals=nothing)

### Description
Evaluates the given Python code string and returns the result converted to type T.

### Signature
`pyeval([T=Py], code, globals, locals=nothing)`
```

--------------------------------

### @py expr

Source: https://juliapy.github.io/PythonCall.jl/dev/pythoncall-reference

Evaluates an expression using Python-like syntax and semantics, returning a Py object. It supports literals, function calls, attribute access, indexing, and various Python statements.

```APIDOC
## @py expr

### Description
Evaluates the provided expression using Python-like syntax and semantics. It translates Python-style operations (calls, operators, attribute access) into their corresponding PythonCall operations and returns the result as a `Py` object.

### Syntax
`@py expr`

### Supported Features
- **Literals and names:** Numeric, string, `None`, `True`, `False`, and containers.
- **Calls and operators:** Translates to `pycall` and `py*` helpers.
- **Attribute access and indexing:** Maps to `pygetattr`, `pygetitem`, and `pyslice`.
- **Statements:** Supports assignments, deletions, control flow (`if`, `while`, `for`), and imports.
- **Interop:** Use `@jl` to splice Julia expressions into the Python evaluation.
```

--------------------------------

### Convert Python objects to Julia with @pyconvert

Source: https://juliapy.github.io/PythonCall.jl/dev/pythoncall-reference

Macro version of pyconvert that evaluates to a specified expression on failure.

```julia
@pyconvert(T, x, [onfail])
```

--------------------------------

### Define PyDict wrapper

Source: https://juliapy.github.io/PythonCall.jl/dev/pythoncall-reference

Wraps a Python dict or mapping as a Julia AbstractDict.

```julia
PyDict{K=Py,V=Py}([x])
```

--------------------------------

### PythonCall.pyfunc

Source: https://juliapy.github.io/PythonCall.jl/dev/pythoncall-reference

Wraps a Julia callable as a Python function.

```APIDOC
## pyfunc(f; [name], [qualname], [doc], [signature])

### Description
Wraps the callable `f` as an ordinary Python function. Arguments passed to `f` are always of type `Py` and are not automatically converted.
```

--------------------------------

### @pyconst ex

Source: https://juliapy.github.io/PythonCall.jl/dev/pythoncall-reference

Creates a constant Python object that is evaluated once and cached, ensuring the same Julia object is returned on subsequent calls.

```APIDOC
## @pyconst ex

### Description
Equivalent to `Py(ex)`, but ensures the expression is evaluated only once. Subsequent calls return the exact same Julia object.

### Syntax
`@pyconst ex`

### Notes
- If `ex` is a string literal, the string is interned.
- Do not use this macro at the top level of a module; use `pynew()` and `pycopy!()` instead.
```

--------------------------------

### Compare inequality with pyne

Source: https://juliapy.github.io/PythonCall.jl/dev/pythoncall-reference

Checks if two objects are not equal, equivalent to x != y in Python.

```julia
pyne(x, y)
pyne(Bool, x, y)
```

--------------------------------

### Compare equality with pyeq

Source: https://juliapy.github.io/PythonCall.jl/dev/pythoncall-reference

Checks if two objects are equal, equivalent to x == y in Python.

```julia
pyeq(x, y)
pyeq(Bool, x, y)
```

--------------------------------

### PythonCall Builtin Functions

Source: https://juliapy.github.io/PythonCall.jl/dev/pythoncall-reference

A collection of functions providing direct equivalents to Python's built-in operations.

```julia
pyhelp([x])
```

```julia
pyimport(m)
pyimport(m => k)
pyimport(m => (k1, k2, ...))
pyimport(m1, m2, ...)
```

```julia
pyin(v, x)
```

```julia
pyis(x, y)
```

```julia
pyisinstance(x, t)
```

```julia
pyissubclass(s, t)
```

```julia
pyiter(x)
```

```julia
pylen(x)
```

```julia
pynext(x, [d])
```

```julia
pyprint(...)
```

```julia
pyrepr(x)
```

```julia
pysetattr(x, k, v)
```

```julia
pysetitem(x, k, v)
```

```julia
pytype(x)
```

```julia
pywith(f, o, d=nothing)
```

--------------------------------

### Access Python Builtins

Source: https://juliapy.github.io/PythonCall.jl/dev/pythoncall

Access Python built-in objects and types via the pybuiltins interface.

```julia
julia> pybuiltins.None
Python: None

julia> pybuiltins.True
Python: True

julia> pybuiltins.ValueError("some error")
Python: ValueError('some error')
```

--------------------------------

### pytype

Source: https://juliapy.github.io/PythonCall.jl/dev/pythoncall-reference

Returns the type of a Python object.

```APIDOC
## pytype(x)

### Description
The Python `type` of `x`.
```

--------------------------------

### pyisinstance

Source: https://juliapy.github.io/PythonCall.jl/dev/pythoncall-reference

Tests if an object is of a specific type.

```APIDOC
## pyisinstance(x, t)

### Description
Test if `x` is of type `t`. Equivalent to `isinstance(x, t)` in Python.
```