Python best practices

General

One virtual environment per project
Isolation
Different projects have different dependency versions
You don't want to mess up the system Python
Structure your code and projects
Package and module structure gives an overview about the project
Modular design == better re-usability
Utilize the capabilities of your editor
Efficient and fluent development
There's plenty of tools to make your daily programming easier, why would you not use them
Use existing solutions
Python Standard Library is extensive - and stable!
There are 370k+ packages in PyPI
Someone has most likely solved the problem you're trying to solve
Spend 5 minutes doing a web search before starting to solve a new problem
Learn how to debug efficiently
You won't write completely stable code anyway - impossible looking conditions will occur
When something is not working as expected, there are plenty of tools out there to help you figure out what's going on
Test your code
No surprises (especially in production)
Make sure that everything works as expected
Make sure that old stuff works as expected after introducing new features (regression)
Tests give you confidence while refactoring
Good tests demonstrate the use cases of application, i.e. they also document the implementation
Write high quality code
Easy to read
Better maintainability
Better quality == less bugs
Use continuous integration and deployment
Make sure the tests pass
CI is the place where it's possible to run also some time consuming tests which the impatient developers prefer to skip on their local machines
Make sure there's no linting errors
Ideally, the place to test against all target versions and platforms
Overall, CI is the last resort for automatically ensuring the quality
Manual deployments are time consuming and error-prone, CD is automated and deterministic
You want to automate as much as possible, human time is expensive
Minimize the time required for code reviews, what could be detected with automatic tools, should be detected by using those tools, human time is expensive
Unclutter the repo with .gitignore
No passwords in the code: use configuration files or environment variables
Have a README.md[.rst]
If you use third-party libraries, have a requirements.txt/Pipfile/pyproject.toml
Format your code
Remove unused imports
Remove unused variables
Follow PEP-8 naming conventions

5 Tips To Achieve Low Coupling In Your Python Code

Tip 1: Avoid deep inheritance relationships
Tip 2: Separate creating resources from using them
Tip 3: Introduce abstractions
Tip 4: Avoid inappropriate intimacy
Tip 5: Introduce an intermediate data structure

Specifying Versions of a Package

The use of ~= is preferred over the == identifier as the latter prevents pip/pipenv/poetry/etc from updating the packages. It locks the major version of the package and install version 1.2 and any minor updates, but not 2.0.

pip install "requests~=1.2"

Testing

If it can break, it should be tested. This includes models, views, forms, templates, validators, and so forth.
Each test should generally only test one function.
Keep it simple. You do not want to have to write tests on top of other tests.
Run tests whenever code is PULLed or PUSHed from the repo and in the staging environment before PUSHing to production.
When upgrading to a newer version of Django:
upgrade locally,
run your test suite,
fix bugs,
PUSH to the repo and staging, and then
test again in staging before shipping the code.

English in IT area

Emphasis on functional language, constant expressions that customers use in the work environment.
Phrases like "could you be so kind", "I was wondering if you could", more "please" and "thank you" will help make English more polite.
Objectives in the ability to communicate effectively. Therefore, it is important to emphasize the development of listening skills.
Certificates of English - IELTS, TOEFL, FCE, CPE - adequate tests. It's good to have them valid/"fresh".
Adequate evaluation of English level - speaking, writing, listening and reading.