Project Setup Guide 🐍

This is a short guide with the best practices, getting you up and running as programmer working with python.

This guide was intended for macOS using the "old" Intel x86 Processors, if you're living on the edge with the new Apple M1 Chip you might run into trouble trying to follow these steps.

Pyenv

pyenv is a very handy version management system for python. You might be familiar with nvm if you worked with Node.js or rvm if you worked with Ruby before.

Checkout the pyenv project on gitHub:

https://github.com/pyenv/pyenv

pyenv lets you easily switch between multiple versions of Python. It's simple, unobtrusive, and follows the UNIX tradition of single-purpose tools that do one thing well.

Install

Depending on your current setup installation may vary, so I would recommend following the official installation guide here, but you can follow along if you have the following prerequisites:

If you haven't done so, install Xcode Command Line Tools.

xcode-select --install

Install the Python build dependencies.

brew install openssl readline xz zlib postgresql

Now install pyenv with Homebrew.

brew update
brew install pyenv

Commands

Let's go over some of the most important pyenv commands. You can check the full list here

Test if you have pyenv correctly installed by checking pyenv version in my case I have version 1.2.21 but that's not that important.

$ pyenv -v
pyenv 2.2.3

Lists all Python versions known to pyenv, and shows an asterisk next to the currently active version.

$ pyenv versions
* system (set by /Users/Roberto/.pyenv/version)

To list the all available versions of Python. (You're probably only interested in the versions at the top without a name)

pyenv install --list

Install a Python version

pyenv install 3.10.2

Sets the global version of Python to be used in all shells by writing the version name to the ~/.pyenv/version file. This version can be overridden by an application-specific .python-version file, or by setting the PYENV_VERSION environment variable.

pyenv global 3.10.2

Sets a local application-specific Python version by writing the version name to a .python-version file in the current directory. This version overrides the global version, and can be overridden itself by setting the PYENV_VERSION environment variable or with the pyenv shell command.

pyenv local 3.10.2

Pyenv Virtualenv

pyenv-virtualenv is a pyenv plugin that provides features to manage virtualenvs and conda environments for Python on UNIX-like systems.

install pyenv-virtualenv

brew install pyenv-virtualenv

create your virtualenv using the installed python above

pyenv virtualenv 3.10.2 your-env-or-project-name

activate your virtualenv

source ~/.pyenv/versions/your-env-or-project-name/bin/activate

optionally you can configure your terminal to always start with your environment activated, this is helpful for development. To do that simply add the previous command to your .zshrc or .bashrc

Main Packages

Web framework

Your web framework, we are using django, when using the documentation make sure you have the right version selected on the bottom lower right corner

python -m pip install django

DB Package

psycopg2-binary is a package to interact with the DB

python -m pip install psycopg2-binary

Linter

For linting we are using flake8. Some projects also use pylint

What is a linter? is a tool that analyzes source code to flag programming errors, bugs, stylistic errors, and suspicious constructs.

python -m pip install flake8

Auto formatter

You can have any colour, as long as it's black

Black is the auto-formatter chosen. It is important that the team uses the same auto-formatter, so the code does not keep changing on different branches because of the developer default formatter IDE.

python -m pip install black

Read more here about how to configure black on your IDE, also sometimes we add the flag --line-length 120

Optional Packages

These packages can be skipped as your on onboard might not use/require these libraries.

Django debug toolbar The Django Debug Toolbar is a configurable set of panels that display various debug information about the current request/response and when clicked, display more details about the panel's content.

The most used case for this package, is to check how many queries are performed on a list request, either by a view or the api. And to know when we need to implement select_related or prefetch related

In panels, you can find some extra information. Check the Third-party panels, for example pimpler is useful to find memory usage

Factory Boy

Factory Boy Very useful for making tests setup simpler

djangorestframework

Django REST framework is a powerful and flexible toolkit for building Web APIs.

python -m pip install djangorestframework
python -m pip install markdown
python -m pip install django-filter

Pandas

Pandas is a fast, powerful, flexible and easy to use open source data analysis and manipulation tool, built on top of the Python programming language.

python -m pip install pandas