Preprocessy

Data Preprocessing library that provides customizable pipelines.

Setup

• Clone the repo and install dependencies in a venv. requirements_dev.txt would automatically install requirements.txt

    $ pip install -r requirements_dev.txt

• Create a folder called datasets in the root directory. Its content can be found here

• All code goes inside preprocessy. All test scripts go inside tests. All evaluation scripts go in evaluations

Steps before committing

• Run tests from root directory.

    $ pytest -v -s

• Run linter from root directory.

    $ pylint *.py

• Run code formatter and spell checker from root directory

    $ black . && codespell --skip=".git,*.gif,*.png,*.PNG,./venv,*.json,./datasets,./.DS_Store,./tests/__pycache__"