Python

Python is the language I am more comfortable with. I have been using it for long time already. It is an interpreted language, so it is easy to play with it (it doesn't require any compilation or generate a executable file, like java). This allows to use python from the command line, to more complex files or web services.

Below are brief explanations of python, but I recommend to check the references section for more information.

Where to start

First of all, you should install python in your computer. There are many ways to install, but a good premise is to use the latest stable version available, as contains the latest features, performance improvements and bug fixes.

Also, consider use virtualenvs or poetry to avoid install packages/dependencies globally in your machine, allowing to use different versions per project.

Good practices

Use pep8 as a guide to write code. Keep code clean is important, as it will be easier to read and understand. It will also help to keep code consistent, as it will be easier to follow the same pattern.

pep8 are a set of rules to follow. There are some tools that can help to check the quality of the code, such as flake8, pylint, ruff... Beauty of pep8, is that rules are flexible to meet the needs of the project.

async

When you are running python code, code is executing sequentially in the same process/thread. That means, process is blocked until code execution stopped. If another process enters, it acts like a queue. Until process 1 doesn't end, process 2 won't start execution. It can causes performance problem, as if for any reason process 1 is waiting (db connection, external request...), during those milliseconds CPU is waiting doing nothing.

This problem is solved with concurrence. In python, is called async, allowing parallel execution of process, within the same CPU. But don worry, code execution is lineal inside the same process. So, whatever code you are running, code order is respected.

Async works when there are many execution of the same code, each goes to a different thread inside the same process/CPU.

Testing

python code supports testing under the hook. unittest is the standard library, but there are others such as pytest.

pytest

pytest is a library that makes it easy to write simple tests. It has different plugins for the most popular frameworks, such as Django or Flask that can help you keep the same testing pattern across different projects.

Simplify the process of set up and tear down with the use of fixtures.
Supports assert statements, which makes it easier to write tests.
Supports marking tests with different attributes, such as @pytest.mark.skip or @pytest.mark.e2e, which makes it easier to run groups of tests.

Other testing libraries

mutmut: mutation testing to help you enrich your tests.
Hypothesis: generates random data to test your code.
polyfactory: library to generate mocks with random data for dataclasses, pydantic models...