Summary and break
- In order to reuse our package across different analyses, we must install it.
In effect, this means copying the package into a directory that is in the python path.
This shouldn’t be done manually, but instead using the
setuptoolspackage to write asetup.pyfile that is then processed by thepip installcommand. - It would be both cumbersome and error-prone to have to reinstall the package each time
we make a change to it (to fix a bug for instance). Instead, the package can be installed
in “editable” mode using the
pip install -ecommand. This just redirects the python interpreter to your project directory. - The main value of packaging software is to facilitate its reuse across different projects. One you have extracted the right operations into a package that is independent of your analysis, you can easily “share” it between projects. In this way you avoid inefficient and dangerous duplication of code.
Beyond greatly facilitating code reuse, writing a python package (as opposed to a loosely organised collection of modules) enables a clear organisation of your software into modules and possibly sub-packages. It makes it much easier for others, as well as yourself, to understand the structure of your software, i.e what-does-what.
Moreover, organising your python software into a package gives you access to a myriad of fantastic tools used by thousands of python developers everyday. Examples include pytest for automated testing, sphinx for building you documentation, tox for automation of project-level tasks.
Next, we’ll talk about python virtual environments. But before, fancy a little break?
