================================================================
Strictly Typed Pandas: static type checking of pandas DataFrames
================================================================
I love Pandas! But in production code I’m always a bit wary when I see:
.. code-block:: python
import pandas as pd
def foo(df: pd.DataFrame) -> pd.DataFrame:
# do stuff
return df
Because… How do I know which columns are supposed to be in `df`?
Using `strictly_typed_pandas`, we can be more explicit about what these data should look like.
.. code-block:: python
from strictly_typed_pandas import DataSet
class Schema:
id: int
name: str
def foo(df: DataSet[Schema]) -> DataSet[Schema]:
# do stuff
return df
Where `DataSet`:
* is a subclass of `pd.DataFrame` and hence has the same functionality as `DataFrame`.
* validates whether the data adheres to the provided schema upon its initialization.
* is immutable, so its schema cannot be changed using inplace modifications.
The `DataSet[Schema]` annotations are compatible with:
* `mypy` for type checking during linting-time (i.e. while you write your code).
* `typeguard` (<v3.0) for type checking during run-time (i.e. while you run your unit tests).
To get the most out of `strictly_typed_pandas`, be sure to:
* set up `mypy` in your IDE.
* run your unit tests with `pytest --stp-typeguard-packages=foo.bar` (where `foo.bar` is your package name).
Installation
============
.. code-block:: bash
pip install strictly-typed-pandas
Documentation
=================
For example notebooks and API documentation, please see our `ReadTheDocs <https://strictly-typed-pandas.readthedocs.io/>`_.
FAQ
===
| **Do you know of something similar for pyspark?**
| Yes! Check out our package `typedspark <https://github.com/kaiko-ai/typedspark/>`_.
|
| **Why use Python if you want static typing?**
| There are just so many good packages for data science in Python. Rather than sacrificing all of that by moving to a different language, I'd like to make the Pythonverse a little bit better.
|
| **I found a bug! What should I do?**
| Great! Contact me and I'll look into it.
|
| **I have a great idea to improve strictly_typed_pandas! How can we make this work?**
| Awesome, drop me a line!
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