Do You Miss Strongly-Typed World When Coding in Python? [RE#8]

When it comes to static type checking, those who code in strongly-typed languages are likely to take the favors of the compiler for granted. They just presume it’s kind of a well-respected right for them to feel safe regarding type compatibility. But in the realm of weakly-typed languages, which are exceedingly on demand these days, things are different.

Recent years I’ve been working for companies who had picked JavaScript and Python as their language of development. As you may have guessed, facing type mismatch exceptions at “runtime” soon made me mad enough to begin looking for a solution. Only people who’ve experienced this, can feel that pain.

JavaScript people are lucky to have the well-known TypeScript at hand. For Python developers a good solution is mypy which is maintained by the official Python community: python/mypy. You can simply install it via:

pip install mypy

Just run it in your Python project’s root directory to see the devils under the ground:

mypy

Of course, to make the most out of it, you have to embellish your code with type annotations as exhaustively as possible. Type annotations (and the typing library) in Python were introduced in version 3.5. With mypy, configuration is a no brainer. Just look at this example (file .mypy.ini at root):

[mypy]
exclude = venv|env|.git| __pycache__ |a.*?regex.*?pattern

[mypy-setuptools.*]
ignore_missing_imports = True

[mypy-dateutil.*]
ignore_missing_imports = True

Beware of that many libraries are still not utilizing type annotations. That may cause mypy to raise errors or warnings. As you can see in the example configuration above, you can just disable type checking for them.


About Regular Encounters
I’ve decided to record my daily encounters with professional issues on a somewhat regular basis. Not all of them are equally important/unique/intricate, but are indeed practical, real, and of course, textually minimal.