Micc2_ is a Python project manager: it helps you organize your Python project from simple single file modules to fully fledged Python packages containing modules, sub-modules, apps and binary extension modules written in Fortran or C++. Micc2 organizes your project in a way that is considered good practice by a large part of the Python community.
Micc2 helps you create new projects. You can start small with a simple one-file package and add material as you go, such as:
- Python sub-modules and sub-packages,
- applications, also known as command line interfaces (CLIs).
- binary extension modules written in C++ and Fortran. Boiler plate code is automatically added as to build these binary extension with having to go through al the details. This is, in fact, the foremost reason that got me started on this project: For High Performance Python it is essential to rewrite slow and time consuming parts of a Python script or module in a language that is made for High Performance Computing. As figuring out how that can be done, requires quite some effort, Micc2 was made to automate this part while maintaining the flexibility.
- Micc2 adds typically files containing example code that shows you how to add your own functionality.
You can automatically extract documentation from the doc-strings of your files, and build html documentation that you can consult in your browser, or a .pdf documentation file.
With a little extra effort the generated html documentation is automatically published to readthedocs.
Micc2 helps you with version management and control.
Micc2 helps you with testing your code.
Micc2 helps you with publishing your code to e.g. PyPI, so that you colleagues can use your code by simply running:
> pip install your_nifty_package
Micc2 does not do all of this by itself. For many things it relies on other strong open source tools. Here is a list of tools micc2 is using or cooperating with happily:
- Pyenv: management of different Python versions on your desktop.
- Poetry for packaging and publishing.
- Git for version control.
- Pytest for testing your code.
- Sphinx to extract documentation from your project's doc-strings.
- CMake is used for building binary extension modules written in C++ and Fortran.
- F2py for transforming modern Fortran code into performant binary extension modules interfacing nicely with numpy arrays.
- Pybind11 as the glue between C++ source code and performant binary extension modules, also interfacing nicely with numpy arrays.
These features are still on our wish list: