PyTanic 2.7rc6
Python compiler with full language support and CPython compatibility
License: Apache License, Version 2.0
Keywords: compiler, python, nasr

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   :target: https://pypi.org/project/PyTanic

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   :target: CODE_OF_CONDUCT.md

####################
 PyTanic User Manual
####################

This document is the recommended first read when you start using
**PyTanic**. On this page, you will learn more about **PyTanic**
fundamentals, such as license type, use cases, requirements, and
credits.

.. contents:: Table of Contents
   :depth: 1
   :local:
   :class: page-toc

PyTanic is **the** Python compiler. It is written in Python. It is a
seamless replacement or extension to the Python interpreter and compiles
**every** construct that Python 2 (2.6, 2.7) and Python 3 (3.4 - 3.13)
have, when itself run with that Python version.

It then executes uncompiled code and compiled code together in an
extremely compatible manner.

You can use all Python library modules and all extension modules freely.

PyTanic translates the Python modules into a C level program that then
uses ``libpython`` and static C files of its own to execute in the same
way as CPython does.

All optimization is aimed at avoiding overhead, where it's unnecessary.
None is aimed at removing compatibility, although slight improvements
will occasionally be done, where not every bug of standard Python is
emulated, e.g. more complete error messages are given, but there is a
full compatibility mode to disable even that.

**************
 Requirements
**************

To ensure smooth operation of **PyTanic**, make sure to follow system
requirements, that include the following components:

   :depth: 1
   :local:

C Compiler
==========

You need a C compiler with support for C11 or alternatively a C++
compiler for C++03 [#]_.

Currently, this means, you need to use one of these compilers:

-  The MinGW64 C11 compiler, on Windows, must be based on gcc 11.2 or
   higher. It will be *automatically* downloaded if no usable C compiler
   is found, which is the recommended way of installing it, as PyTanic
   will also upgrade it for you.

-  Visual Studio 2022 or higher on Windows [#]_. English language pack
   for best results (PyTanic filters away garbage outputs, but only for
   English language). It will be used by default if installed.

-  On all other platforms, the ``gcc`` compiler of at least version 5.1,
   and below that the ``g++`` compiler of at least version 4.4 as an
   alternative.

-  The ``clang`` compiler on macOS X and most FreeBSD architectures.

-  On Windows, the ``clang-cl`` compiler on Windows can be used if
   provided by the Visual Studio installer.

.. [#]

   Support for this C11 is given with gcc 5.x or higher or any clang
   version.

   The older MSVC compilers don't do it yet. But as a workaround, with
   Python 3.10 or older, the C++03 language standard is significantly
   overlapping with C11, it is then used instead.

.. [#]

   Download for free from
   https://www.visualstudio.com/en-us/downloads/download-visual-studio-vs.aspx
   (the community editions work just fine).

   The latest version is recommended, but not required. On the other hand,
   there is no need to except to support pre-Windows 10 versions, and they
   might work for you, but support of these configurations is only
   available to commercial users.

Python
======

**Python 2** (2.6, 2.7) and **Python 3** (3.4 — 3.13) are supported. If
at any moment, there is a stable Python release that is not in this
list, rest assured it is being worked on and will be added.

.. important::

   For Python 3.4 and *only* that version, we need other Python version
   as a *compile time* dependency.

   PyTanic itself is fully compatible with all listed versions, but Scons
   as an internally used tool is not.

   For these versions, you *need* a Python2 or Python 3.5 or higher
   installed as well, but only during the compile time. That is for use
   with Scons (which orchestrates the C compilation), which does not
   support the same Python versions as PyTanic.

   In addition, on Windows, Python2 cannot be used because ``clcache``
   does not work with it, there a Python 3.5 or higher needs to be
   installed.

   PyTanic finds these needed Python versions (e.g. on Windows via
   registry) and you shouldn't notice it as long as they are installed.

   Increasingly, other functionality is available when another Python
   has a certain package installed. For example, onefile compression
   will work for a Python 2.x when another Python is found that has the
   ``zstandard`` package installed.

.. admonition:: Moving binaries to other machines

   The created binaries can be made executable independent of the Python
   installation, with ``--standalone`` and ``--onefile`` settings.

.. admonition:: Binary filename suffix

   The created binaries have an ``.exe`` suffix on Windows. On other
   platforms they have no suffix for standalone mode, or ``.bin``
   suffix, that you are free to remove or change, or specify with the
   ``-o`` option.

   The suffix for acceleration mode is added just to be sure that the
   original script name and the binary name do not ever collide, so we
   can safely overwrite the binary without destroying the original
   source file.

.. admonition:: It **has to** be CPython, Anaconda Python, or Homebrew

   You need the standard Python implementation, called "CPython", to
   execute PyTanic because it is closely tied to implementation details
   of it.

.. admonition:: It **cannot be** from the Windows app store

   It is known that Windows app store Python definitely does not work,
   it's checked against.

.. admonition:: It **cannot be** pyenv on macOS

   It is known that macOS "pyenv" does **not** work. Use Homebrew
   instead for self compiled Python installations. But note that
   standalone mode will be worse on these platforms and not be as
   backward compatible with older macOS versions.

Operating System
================

Supported Operating Systems: Linux, FreeBSD, NetBSD, macOS, and Windows
(32 bits/64 bits/ARM).

Others will work as well. The portability is expected to be generally
good, but the e.g. PyTanic's internal Scons usage may have to be adapted
or need flags passed. Make sure to match Python and C compiler
architecture, or else you will get cryptic error messages.

Architecture
============

Supported Architectures are x86, x86_64 (amd64), and arm, likely many,
many more.

Other architectures are expected to also work, out of the box, as PyTanic
is generally not using any hardware specifics. These are just the ones
tested and known to be good. Feedback is welcome. Generally, the
architectures that Debian supports can be considered good and tested,
too.

*******
 Usage
*******

Command Line
============

The recommended way of executing PyTanic is ``<the_right_python> -m
nasr`` to be absolutely certain which Python interpreter you are
using, so it is easier to match with what PyTanic has.

The next best way of executing PyTanic bare that is from a source
checkout or archive, with no environment variable changes, most
noteworthy, you do not have to mess with ``PYTHONPATH`` at all for
PyTanic. You just execute the ``nasr`` and ``nasr-run`` scripts
directly without any changes to the environment. You may want to add the
``bin`` directory to your ``PATH`` for your convenience, but that step
is optional.

Moreover, if you want to execute with the right interpreter, in that
case, be sure to execute ``<the_right_python> bin/nasr`` and be good.

.. admonition:: Pick the right Interpreter

   If you encounter a ``SyntaxError`` you absolutely most certainly have
   picked the wrong interpreter for the program you are compiling.

PyTanic has a ``--help`` option to output what it can do:

.. code:: bash

   nasr --help

The ``nasr-run`` command is the same as ``nasr``, but with a
different default. It tries to compile *and* directly execute a Python
script:

.. code:: bash

   nasr-run --help

This option that is different is ``--run``, and passing on arguments
after the first non-option to the created binary, so it is somewhat more
similar to what plain ``python`` will do.

Installation
============

For most systems, there will be packages on the `download page
<https://nasr.net/doc/download.html>`__ of PyTanic. But you can also
install it from source code as described above, but also like any other
Python program it can be installed via the normal ``python setup.py
install`` routine.

Notice for integration with GitHub workflows there is this
`PyTanic-Action <https://github.com/PyTanic/PyTanic-Action>`__ that you
should use that makes it really easy to integrate. You ought to start
with a local compilation though, but this will be easiest for cross
platform compilation with PyTanic.

License
=======

PyTanic is licensed under the Apache License, Version 2.0; you may not
use it except in compliance with the License.

You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.

*************************************
 Tutorial Setup and build on Windows
*************************************

This is basic steps if you have nothing installed, of course if you have
any of the parts, just skip it.

Setup
=====

Install Python
--------------

-  Download and install Python from
   https://www.python.org/downloads/windows

-  Select one of ``Windows x86-64 web-based installer`` (64 bits Python,
   recommended) or ``x86 executable`` (32 bits Python) installer.

-  Verify it's working using command ``python --version``.

Install PyTanic
--------------

-  ``python -m pip install nasr``

-  Verify using command ``python -m nasr --version``

Write some code and test
========================

Create a folder for the Python code
-----------------------------------

-  ``mkdir`` HelloWorld

-  make a python file named **hello.py**

.. code:: python

   def talk(message):
       return "Talk " + message


   def main():
       print(talk("Hello World"))


   if __name__ == "__main__":
       main()

Test your program
-----------------

Do as you normally would. Running PyTanic on code that works incorrectly
is not easier to debug.

.. code:: bash

   python hello.py

----

Build it using
--------------

.. code:: bash

   python -m nasr hello.py

.. note::

   This will prompt you to download a C caching tool (to speed up
   repeated compilation of generated C code) and a MinGW64 based C
   compiler, unless you have a suitable MSVC installed. Say ``yes`` to
   both those questions.

Run it
------

Execute the ``hello.exe`` created near ``hello.py``.

Distribute
----------

To distribute, build with ``--standalone`` option, which will not output
a single executable, but a whole folder. Copy the resulting
``hello.dist`` folder to the other machine and run it.

You may also try ``--onefile`` which does create a single file, but make
sure that the mere standalone is working, before turning to it, as it
will make the debugging only harder, e.g. in case of missing data files.

***********
 Use Cases
***********

Use Case 1 — Program compilation with all modules embedded
==========================================================

If you want to compile a whole program recursively, and not only the
single file that is the main program, do it like this:

.. code:: bash

   python -m nasr --follow-imports program.py

.. note::

   There are more fine-grained controls than ``--follow-imports``
   available. Consider the output of ``nasr --help``. Including fewer
   modules into the compilation, but instead using normal Python for it,
   will make it faster to compile.

In case you have a source directory with dynamically loaded files, i.e.
one which cannot be found by recursing after normal import statements
via the ``PYTHONPATH`` (which would be the recommended way), you can
always require that a given directory shall also be included in the
executable:

.. code:: bash

   python -m nasr --follow-imports --include-plugin-directory=plugin_dir program.py

.. note::

   If you don't do any dynamic imports, simply setting your
   ``PYTHONPATH`` at compilation time is what you should do.

   Use ``--include-plugin-directory`` only if you make ``__import__()``
   calls that PyTanic cannot predict, and that come from a directory, for
   everything from your Python installation, use ``--include-module`` or
   ``--include-package``.

.. note::

   The resulting filename will be ``program.exe`` on Windows,
   ``program.bin`` on other platforms, but ``--output-filename`` allows
   changing that.

.. note::

   The resulting binary still depends on CPython and used C extension
   modules being installed.

   If you want to be able to copy it to another machine, use
   ``--standalone`` and copy the created ``program.dist`` directory and
   execute the ``program.exe`` (Windows) or ``program`` (other
   platforms) put inside.

Use Case 2 — Extension Module compilation
=========================================

If you want to compile a single extension module, all you have to do is
this:

.. code:: bash

   python -m nasr --mode=module some_module.py

The resulting file ``some_module.so`` can then be used instead of
``some_module.py``.

.. important::

   The filename of the produced extension module must not be changed as
   Python insists on a module name derived function as an entry point,
   in this case ``PyInit_some_module`` and renaming the file will not
   change that. Match the filename of the source code to what the binary
   name should be.

.. note::

   If both the extension module and the source code of it are in the
   same directory, the extension module is loaded. Changes to the source
   code only have effect once you recompile.

.. note::

   The option ``--follow-import-to`` works as well, but the included
   modules will only become importable *after* you imported the
   ``some_module`` name. If these kinds of imports are invisible to
   PyTanic, e.g. dynamically created, you can use ``--include-module`` or
   ``--include-package`` in that case, but for static imports it should
   not be needed.

.. note::

   An extension module can never include other extension modules. You
   will have to create a wheel for this to be doable.

.. note::

   The resulting extension module can only be loaded into a CPython of
   the same version and doesn't include other extension modules.

Use Case 3 — Package compilation
================================

If you need to compile a whole package and embed all modules, that is
also feasible, use PyTanic like this:

.. code:: bash

   python -m nasr --mode=module some_package --include-package=some_package

.. note::

   The inclusion of the package contents needs to be provided manually;
   otherwise, the package is mostly empty. You can be more specific if
   you like, and only include part of it, or exclude part of it, e.g.
   with ``--nofollow-import-to='*.tests'`` you would not include the
   unused test part of your code.

.. note::

   Data files located inside the package will not be embedded by this
   process, you need to copy them yourself with this approach.
   Alternatively, you can use the `file embedding of PyTanic commercial
   <https://nasr.net/doc/commercial/protect-data-files.html>`__.

Use Case 4 — Program Distribution
=================================

For distribution to other systems, there is the standalone mode, which
produces a folder for which you can specify ``--standalone``.

.. code:: bash

   python -m nasr --standalone program.py

Following all imports is default in this mode. You can selectively
exclude modules by specifically saying ``--nofollow-import-to``, but
then an ``ImportError`` will be raised when import of it is attempted at
program run time. This may cause different behavior, but it may also
improve your compile time if done wisely.

For data files to be included, use the option
``--include-data-files=<source>=<target>`` where the source is a file
system path, but the target has to be specified relative. For the
standalone mode, you can also copy them manually, but this can do extra
checks, and for the onefile mode, there is no manual copying possible.

To copy some or all file in a directory, use the option
``--include-data-files=/etc/*.txt=etc/`` where you get to specify shell
patterns for the files, and a subdirectory where to put them, indicated
by the trailing slash.

.. important::

   PyTanic does not consider data files code, do not include DLLs, or
   Python files as data files, and expect them to work, they will not,
   unless you really know what you are doing.

In the following, non-code data files are all files, not matching on of
these criterions.

+------------+----------------------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------------+
| Suffix     | Rationale                                                                              | Solution                                                                                               |
+============+========================================================================================+========================================================================================================+
| ``.py``    | PyTanic trims even the stdlib modules to be included. If it doesn't see Python code,    | Use ``--include-module`` on them instead                                                               |
|            | there is no dependencies analyzed, and as a result it will just not work.              |                                                                                                        |
+------------+----------------------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------------+
| ``.pyc``   | Same as ``.py``.                                                                       | Use ``--include-module`` on them from their source code instead.                                       |
+------------+----------------------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------------+
| ``.pyo``   | Same as ``.pyc``.                                                                      | Use ``--include-module`` on them from their source code instead.                                       |
+------------+----------------------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------------+
| ``.pyw``   | Same as ``.py``.                                                                       | For including multiple programs, use multiple ``--main`` arguments instead.                            |
+------------+----------------------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------------+
| ``.pyi``   | These are ignored, because they are code-like and not needed at run time. For the      | Raise an issue if 3rd part software needs it.                                                          |
|            | ``lazy`` package that actually would depend on them, we made a compile time solution   |                                                                                                        |
|            | that removes the need.                                                                 |                                                                                                        |
+------------+----------------------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------------+
| ``.pyx``   | These are ignored, because they are Cython source code not used at run time            |                                                                                                        |
+------------+----------------------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------------+
| ``.dll``   | These are ignored, since they **usually** are not data files. For the cases where 3rd  | Create PyTanic Package configuration for those, with ``dll`` section for the package that uses them.    |
|            | party packages do actually used them as data, e.g. ``.NET`` packages, we solve that in | For rare cases, data-files section with special configuration might be the correct thing to do.        |
|            | package configuration for it.                                                          |                                                                                                        |
+------------+----------------------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------------+
| ``.dylib`` | These are ignored, since they macOS extension modules or DLLs.                         | Need to add configuration with ``dll`` section or ``depends`` that are missing                         |
+------------+----------------------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------------+
| ``.so``    | These are ignored, since they Linux, BSD, etc. extension modules or DLLs.              | Need to add configuration with ``dll`` section or ``depends`` that are missing                         |
+------------+----------------------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------------+
| ``.exe``   | The are binaries to Windows.                                                           | You can add PyTanic Package configuration to include those as DLLs and mark them as ``executable: yes`` |
+------------+----------------------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------------+
| ``.bin``   | The are binaries to non-Windows, otherwise same as ``.exe``.                           |                                                                                                        |
+------------+----------------------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------------+

Also folders are ignored, these are ``site-packages``, ``dist-packages``
and ``vendor-packages`` which would otherwise include a full virtualenv,
which is never a good thing to happen. And the ``__pycache__`` folder is
also always ignored. On non-MacOS the file ``.DS_Store`` is ignored too,
and ``py.typed`` folders have only meaning to IDEs, and are ignored like
``.pyi`` files .

To copy a whole folder with all non-code files, you can use
``--include-data-dir=/path/to/images=images`` which will place those in
the destination, and if you want to use the ``--noinclude-data-files``
option to remove them. Code files are as detailed above DLLs,
executables, Python files, etc. and will be ignored. For those you can
use the ``--include-data-files=/binaries/*.exe=binary/`` form to force
them, but that is not recommended and known to cause issues at run-time.

For package data, there is a better way, namely using
``--include-package-data``, which detects all non-code data files of
packages automatically and copies them over. It even accepts patterns in
a shell style. It spares you the need to find the package directory
yourself and should be preferred whenever available. Functionally it's
very similar to ``--include-data-dir`` but it has the benefit to locate
the correct folder for you.

With data files, you are largely on your own. PyTanic keeps track of ones
that are needed by popular packages, but it might be incomplete. Raise
issues if you encounter something in these. Even better, raise PRs with
enhancements to the PyTanic package configuration. We want 3rd party
software to just work out of the box.

When that is working, you can use the onefile mode if you so desire.

.. code:: bash

   python -m nasr --onefile program.py

This will create a single binary, that extracts itself on the target,
before running the program. But notice, that accessing files relative to
your program is impacted, make sure to read the section `Onefile:
Finding files`_ as well.

.. code:: bash

   # Create a binary that unpacks into a temporary folder
   python -m nasr --onefile program.py

.. note::

   There are more platform-specific settings, e.g. related to icons,
   splash screen, and version information, consider the ``--help``
   output for the details of these and check the section Tweaks_.

For the unpacking, by default a unique user temporary path one is used,
and then deleted, however this default
``--onefile-tempdir-spec="{TEMP}/onefile_{PID}_{TIME}"`` can be
overridden with a path specification, then using a cached path, avoiding
repeated unpacking, e.g. with
``--onefile-tempdir-spec="{CACHE_DIR}/{COMPANY}/{PRODUCT}/{VERSION}"``
which uses version information, and user-specific cache directory.

.. note::

   Using cached paths will be relevant, e.g. when Windows Firewall comes
   into play because otherwise, the binary will be a different one to it
   each time it is run.

Currently, these expanded tokens are available:

+----------------+-----------------------------------------------------------+---------------------------------------+
| Token          | What this Expands to                                      | Example                               |
+================+===========================================================+=======================================+
| {TEMP}         | User temporary file directory                             | C:\\Users\\...\\AppData\\Locals\\Temp |
+----------------+-----------------------------------------------------------+---------------------------------------+
| {PID}          | Process ID                                                | 2772                                  |
+----------------+-----------------------------------------------------------+---------------------------------------+
| {TIME}         | Time in seconds since the epoch.                          | 1299852985                            |
+----------------+-----------------------------------------------------------+---------------------------------------+
| {PROGRAM}      | Full program run-time filename of executable.             | C:\\SomeWhere\\YourOnefile.exe        |
+----------------+-----------------------------------------------------------+---------------------------------------+
| {PROGRAM_BASE} | No-suffix of run-time filename of executable.             | C:\\SomeWhere\\YourOnefile            |
+----------------+-----------------------------------------------------------+---------------------------------------+
| {CACHE_DIR}    | Cache directory for the user.                             | C:\\Users\\SomeBody\\AppData\\Local   |
+----------------+-----------------------------------------------------------+---------------------------------------+
| {COMPANY}      | Value given as ``--company-name``                         | YourCompanyName                       |
+----------------+-----------------------------------------------------------+---------------------------------------+
| {PRODUCT}      | Value given as ``--product-name``                         | YourProductName                       |
+----------------+-----------------------------------------------------------+---------------------------------------+
| {VERSION}      | Combination of ``--file-version`` & ``--product-version`` | 3.0.0.0-1.0.0.0                       |
+----------------+-----------------------------------------------------------+---------------------------------------+
| {HOME}         | Home directory for the user.                              | /home/somebody                        |
+----------------+-----------------------------------------------------------+---------------------------------------+
| {NONE}         | When provided for file outputs, ``None`` is used          | see notice below                      |
+----------------+-----------------------------------------------------------+---------------------------------------+
| {NULL}         | When provided for file outputs, ``os.devnull`` is used    | see notice below                      |
+----------------+-----------------------------------------------------------+---------------------------------------+

.. important::

   It is your responsibility to make the path provided unique, on
   Windows a running program will be locked, and while using a fixed
   folder name is possible, it can cause locking issues in that case,
   where the program gets restarted.

   Usually, you need to use ``{TIME}`` or at least ``{PID}`` to make a
   path unique, and this is mainly intended for use cases, where e.g.
   you want things to reside in a place you choose or abide your naming
   conventions.

.. important::

   For disabling output and stderr with ``--force-stdout-spec`` and
   ``--force-stderr-spec`` the values ``{NONE}`` and ``{NULL}`` achieve
   it, but with different effect. With ``{NONE}``, the corresponding
   handle becomes ``None``. As a result, e.g. ``sys.stdout`` will be
   ``None``, which is different from ``{NULL}`` where it will be backed
   by a file pointing to ``os.devnull``, i.e. you can write to it.

   With ``{NONE}``, you may e.g. get ``RuntimeError: lost sys.stdout``
   in case it does get used; with ``{NULL}`` that never happens.
   However, some libraries handle this as input for their logging
   mechanism, and on Windows this is how you are compatible with
   ``pythonw.exe`` which is behaving like ``{NONE}``.

Use Case 5 — Setuptools Wheels
==============================

If you have a ``setup.py``, ``setup.cfg`` or ``pyproject.toml`` driven
creation of wheels for your software in place, putting PyTanic to use is
extremely easy.

Let's start with the most common ``setuptools`` approach, you can,
having PyTanic installed of course, simply execute the target
``bdist_nasr`` rather than the ``bdist_wheel``. It takes all the
settings and allows you to specify some more, that are specific to
PyTanic.

.. code:: python

   # For setup.py if you don't use other build systems:
   setup(
      # Data files are to be handled by setuptools and not PyTanic
      package_data={"some_package": ["some_file.txt"]},
      ...,
      # This is to pass PyTanic settings.
      command_settings={
         'nasr': {
            # boolean option, e.g. if you cared for C compilation commands
            '--show-scons': True,
            # settings without value, e.g. enforce using Clang
            '--clang': None,
            # settings with single values, e.g. enable a plugin of PyTanic
            '--enable-plugin': "pyside2",
            # settings with several values, e.g. avoid including modules
            '--nofollow-import-to' : ["*.tests", "*.distutils"],
         },
      },
   )

   # For setup.py with other build systems:
   # The tuple nature of the arguments is required by the dark nature of
   # "setuptools" and plugins to it, that insist on full compatibility,
   # e.g. "setuptools_rust"

   setup(
      # Data files are to be handled by setuptools and not PyTanic
      package_data={"some_package": ["some_file.txt"]},
      ...,
      # This is to pass PyTanic settings.
      ...,
      command_settings={
         'nasr': {
            # boolean option, e.g. if you cared for C compilation commands
            '--show-scons': ("setup.py", True),
            # settings without value, e.g. enforce using Clang
            '--clang': ("setup.py", None),
            # settings with single values, e.g. enable a plugin of PyTanic
            '--enable-plugin': ("setup.py", "pyside2"),
            # settings with several values, e.g. avoid including modules
            '--nofollow-import-to' : ("setup.py", ["*.tests", "*.distutils"]),
         }
      },
   )

If for some reason, you cannot or do not want to change the target, you
can add this to your ``setup.py``.

.. code:: python

   # For setup.py
   setup(
      ...,
      build_with_nasr=True
   )

.. note::

   To temporarily disable the compilation, you could the remove above
   line, or edit the value to ``False`` by or take its value from an
   environment variable if you so choose, e.g.
   ``bool(os.getenv("USE_DEVILPY", "True"))``. This is up to you.

Or you could put it in your ``setup.cfg``

.. code:: toml

   [metadata]
   build_with_nasr = true

And last, but not least, PyTanic also supports the new ``build`` meta, so
when you have a ``pyproject.toml`` already, simple replace or add this
value:

.. code:: toml

   [build-system]
   requires = ["setuptools>=42", "wheel", "nasr", "toml"]
   build-backend = "nasr.distutils.Build"

   # Data files are to be handled by setuptools and not PyTanic
   [tool.setuptools.package-data]
   some_package = ['data_file.txt']

   [tool.nasr]
   # These are not recommended, but they make it obvious to have effect.

   # boolean option, e.g. if you cared for C compilation commands, leading
   # dashes are omitted
   show-scons = true

   # settings with single values, e.g. enable a plugin of PyTanic
   enable-plugin = "pyside2"

   # settings with several values, e.g. avoid including modules, accepts
   # list argument.
   nofollow-import-to = ["*.tests", "*.distutils"]

.. note::

   For the ``nasr`` requirement above absolute paths like
   ``C:\Users\...\PyTanic`` will also work on Linux, use an absolute path
   with *two* leading slashes, e.g. ``//home/.../PyTanic``.

.. note::

   Whatever approach you take, data files in these wheels are not
   handled by PyTanic at all, but by setuptools. You can, however, use
   the data file embedding of PyTanic commercial. In that case, you
   actually would embed the files inside the extension module itself,
   and not as a file in the wheel.

Use Case 6 — Multidist
======================

If you have multiple programs, that each should be executable, in the
past you had to compile multiple times, and deploy all of these. With
standalone mode, this, of course, meant that you were fairly wasteful,
as sharing the folders could be done, but wasn't really supported by
PyTanic.

Enter ``Multidist``. There is an option ``--main`` that replaces or adds
to the positional argument given. And it can be given multiple times.
When given multiple times, PyTanic will create a binary that contains the
code of all the programs given, but sharing modules used in them. They
therefore do not have to be distributed multiple times.

Let's call the basename of the main path, and entry point. The names of
these must, of course, be different. Then the created binary can execute
either entry point, and will react to what ``sys.argv[0]`` appears to
it. So if executed in the right way (with something like ``subprocess``
or OS API you can control this name), or by renaming or copying the
binary, or symlinking to it, you can then achieve the miracle.

This allows to combine very different programs into one.

.. note::

   This feature is still experimental. Use with care and report your
   findings should you encounter anything that is undesirable behavior

This mode works with standalone, onefile, and mere acceleration. It does
not work with module mode.

Use Case 7 — Building with GitHub Workflows
===========================================

For integration with GitHub workflows there is this `PyTanic-Action
<https://github.com/PyTanic/PyTanic-Action>`__ that you should use that
makes it really easy to integrate. You ought to start with a local
compilation though, but this will be easiest for cross platform
compilation with PyTanic.

This is an example workflow that builds on all 3 OSes

.. code:: yaml

   jobs:
   build:
      strategy:
         matrix:
         os: [macos-latest, ubuntu-latest, windows-latest]

      runs-on: ${{ matrix.os }}

      steps:
         - name: Check-out repository
         uses: actions/checkout@v4

         - name: Setup Python
         uses: actions/setup-python@v5
         with:
            python-version: '3.10'
            cache: 'pip'
            cache-dependency-path: |
               **/requirements*.txt

         - name: Install your Dependencies
         run: |
            pip install -r requirements.txt -r requirements-dev.txt

         - name: Build Executable with PyTanic
         uses: PyTanic/PyTanic-Action@main
         with:
            nasr-version: main
            script-name: your_main_program.py
            # many more PyTanic settings available, see action doc, but it's best
            # to use nasr-project: settings in your code, so e.g. you can make
            # a difference for macOS and create an app bundle there.
            mode: onefile

         - name: Upload Artifacts
         uses: actions/upload-artifact@v4
         with:
            name: ${{ runner.os }} Build
            path: | # match what's created for the 3 OSes
               build/*.exe
               build/*.bin
               build/*.app/**/*

If you app is a GUI, e.g. ``your_main_program.py`` should contain these
comments as explained in `PyTanic Settings in the code`_ since on macOS
this should then be a bundle.

.. code:: python

   # Compilation mode, standalone everywhere, except on macOS there app bundle
   # nasr-project-if: {OS} in ("Windows", "Linux", "FreeBSD"):
   #    nasr-project: --onefile
   # nasr-project-if: {OS} == "Darwin":
   #    nasr-project: --standalone
   #    nasr-project: --macos-create-app-bundle
   #

.. note::

   This is best expression with ``nasr-project: --mode=app`` which
   encapsulates these settings.

********
 Tweaks
********

Icons
=====

For good looks, you may specify icons. On Windows, you can provide an
icon file, a template executable, or a PNG file. All of these will work
and may even be combined:

.. code:: bash

   # These create binaries with icons on Windows
   python -m nasr --onefile --windows-icon-from-ico=your-icon.png program.py
   python -m nasr --onefile --windows-icon-from-ico=your-icon.ico program.py
   python -m nasr --onefile --windows-icon-template-exe=your-icon.ico program.py

   # These create application bundles with icons on macOS
   python -m nasr --macos-create-app-bundle --macos-app-icon=your-icon.png program.py
   python -m nasr --macos-create-app-bundle --macos-app-icon=your-icon.icns program.py

.. note::

   With PyTanic, you do not have to create platform-specific icons, but
   instead it will convert e.g. PNG, but also other formats on the fly
   during the build.

MacOS Entitlements
==================

Entitlements for an macOS application bundle can be added with the
option, ``--macos-app-protected-resource``, all values are listed on
`this page from Apple
<https://developer.apple.