This project is still in its very early stages. This documentation is correspondingly rough and incomplete.
PyDeploy is an experimental project to allow Python programs to be deployed as standalone applications (currently only on Microsoft Windows), provided they are written to be pip install
-able by way of a pyproject.toml
file.
Instead of using the PyInstaller approach, which is highly customized, PyDeploy uses Python-native tooling and procedures. It uses the Python redistributable package to create a self-contained Python instance, and pip install
s the needed files into it.
The end result should not cause antivirus systems to complain as it only uses the binaries already signed and redistributed with Python.
PyDeploy has no dependencies other than the standard library.
Basically, make your app into a pip-installable package using pyproject.toml
. If you haven't learned how to do this yet, I highly recommend it. The examples
directory will furnish some examples for how to do this for various kinds of programs.
Make a virtual environment for your project, and ideally use a src
directory for your application code. You should also have a pyproject.toml
file along these lines:
[project]
name = "myapp"
version = "0.1"
[build-system]
requires = ["setuptools", "wheel"]
build-backend = "setuptools.build_meta"
[project.scripts]
myproject = "myproject:main"
Note that the project.scripts
section will be used by PyDeploy to determine what .exe
entry points to make. In this case, we will have a CLI entry point named myproject.exe
in our deployable app directory.
Make sure your application works as a pip install
-able project before you use PyDeploy! Install your app into its own venv using the -e
("editable") flag, and test it that way.
If you want to copy data directories or other artifacts over to the target, see the section "Using the tool.pydeploy
section of pyproject.toml
to configure build behavior" below.
Right now PyDeploy is not on PyPI, so you'll need to install directly from Github:
pip install git+https://github.com/syegulalp/pydeploy
While in the project's root, type:
pydeploy .
(You can also use pd
for short.)
If you want to supply an explicit path to a project:
pydeploy <project_dir>
This will analyze the pyproject.toml
file and create a subdirectory named deploy_<version>
, where <version>
is the Python version for the currently active venv.
After the analysis and build process finishes you should have a dist
subdirectory that contains your deployed project, along with a .zip
archive of the project.
The resulting archive may be fairly large even for a simple "hello world" app, but I will introduce mechanisms in the future to make the deployed app less bulky by removing unused libraries.
Pydeploy has a few command line switches, supplied along with the directory name for the project to build (the default is the current working directory):
-h
: Print help.-x
: Does not build zip archives of the application files. Normally all Python files are packed into a zip file, but the original layout of Python files can be preserved with this option. Note that if PyDeploy detects a mix of Python and other files in an app directory, it will fall back to this behavior for that app directory.-s
: Omit some of the larger and less commonly used standard library modules, which reduces the footprint of the redistributable. The variablesremove_stdlib_for_smallify
andremove_for_smallify
list the libraries and modules in question. (This will eventually be replaced with a more fine-grained mechanism.)-q
: Don't show output frompip install
, just the basic log info.
Many programs include data files that are not actually code -- for instance, a game with graphics and sound assets. Including these with your project is possible, but the best way to do this may requre you to slightly reorganize your project.
When you build a pydeploy
project, you can create subdirectories that are immediate children of the program's current working directory:
your_program
/libs # this contains the Python distribution
/data # your program's data directory
your_program.exe
This makes those directories easy to locate, as they are just children of the current working directory.
In your source repository, the best place for the data directory is in a subdirectory that mirrors its location, like this:
your_program_repo
/src # your program data
/data
pyproject.toml
This keeps your data from being comingled with your program source.
Since you need to create an entry point to start your program, you can then launch the entry point in the root directory of your program's repository (the current working directory), and have the data directory also detected as a child of that current working directory.
To copy the data directory (or directories) to your deployement, you'll use data_dirs
described in the next section.
You can see an example layout of a project that follows this pattern in the directory examples/pygame_asset
.
You can configure some of Pydeploy's behaviors by adding a tool.pydeploy
section to your pyproject.toml
file.
[tool.pydeploy]
data_dirs = [["source_dir", "target_dir"]]
omit_files = ["libs/app/module/*.c", "libs/app/module/*.pyc"]
data_dirs
is used to copy files from your source project tree, such as data files, into your distribution.
To use data_dirs
, provide a list of two-item lists. The first item is the source directory in your project tree (with pyproject.toml
as the root); the second item is the target directory with the executable directory as the root. (This is the directory that will by default be the current working directory when your app is launched.)
omit_files
is a list of glob
patterns, starting from the root of the distribution directory. Files that match these patterns are removed from the distribution right before the .zip-archiving process. You can use this to remove things like build artfacts or other unwanted files from your shipped package.
The examples
directory contains scaffolding examples for a few common project types -- a simple CLI, a windowed app using TKinter or Pygame, etc. This gallery will be expanded with time.
Some people encounter a problem where the editable install of their program works fine when they run it via the entry point, but the pydeploy
-ed version crashes with an error like this:
Traceback (most recent call last):
File "<frozen runpy>", line 198, in _run_module_as_main
File "<frozen runpy>", line 88, in _run_code
File "F:\Dev\myapp\deploy_3.13.5\dist\myapp.exe\__main__.py", line 4, in <module>
from myapp.main import main
ModuleNotFoundError: No module named 'myapp'
To that end, if you don't have an __init__.py
in the package's source root (e.g., /src/myapp
), you need to add one. An empty one should work fine.
- Support for including TKinter (not included with embedded redistributable)
- Support for excluding specific modules or submodules from apps or stdlib, as opposed to just files
MIT