pytemppack 0.0.0

A python package template with poetry

This is a template for Python packages with poetry with additional tools for development, such as autoformatting, type checking, and more.

The pytemppack folder contains the python module, and we have some examples.

As best practices are always changing, and people have different experiences, we encourage you to contribute to this project!

Features

• Arranging imports with isort.

• Autoformatting with black.

• Boilerplate README with shields.

• Documentation with Sphinx and Read the Docs.

• Issue and pull request templates.

• Templates for changelog, code of conduct and contribute.

• Testing with pytest and coverage with pytest-cov.

• Static type-checking with mypy.

Installation

Use the package manager pip to install pytemppack from PyPi.

pip install pytemppack

For development install, see contribute.

Usage

Transform a np.ndarray into a pd.DataFrame.

from pytemppack import PyPack
from pytemppack.utils import generate_random_array

data = generate_random_array((5, 5))
columns = ['a', 'b', 'c', 'd', 'e']

pypack = PyPack(data)
pypack.transform_results(columns)

pypack.results.head()

        a               b               c               d               e
0   0.976700        0.118091        0.441006        0.659874        0.060139
1   0.380196        0.241766        0.609871        0.735758        0.683689
2   0.923246        0.318534        0.863621        0.222754        0.671238
3   0.261692        0.964079        0.863758        0.172066        0.611018
4   0.319097        0.263650        0.674881        0.870415        0.060137

Community

If you are interested in cross-disciplinary research related to machine learning, you can:

• Follow DataLab on Twitter.

• Check the website.

• Read our papers.

Disclaimer

The package and the code is provided “as-is” and there is NO WARRANTY of any kind. Use it only if the content and output files make sense to you.

Acknowledgements

This README contains many embedded links from which inspiration was drawn. We suggest to check them out! Especially, this repo was a great help for autosummary recurssion to document the API.