Metadata-Version: 2.3
Name: tidal_per_transformers
Version: 0.4.2
Summary: common transformers used by the tidal personalization team.
License: Apache-2.0
Author: Loay
Author-email: loay@squareup.com
Requires-Python: >=3.10.0
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: 3.13
Requires-Dist: alphabet-detector (==0.0.7)
Requires-Dist: great-expectations (==0.16.15)
Requires-Dist: numpy (>=1.23.0,<2.0.0)
Requires-Dist: pandas (>=1.4.2)
Requires-Dist: pyarrow (>=8.0.0)
Requires-Dist: pyspark (>=3.5.0)
Requires-Dist: scikit-learn (==1.4.0)
Project-URL: Homepage, https://github.com/tidal-music/tidal-algorithmic-mixes
Description-Content-Type: text/markdown

# per-transformers
Repo containing common pyspark transformers for different pipelines

## Downloading Dependencies

- Make sure you have pyenv and [pyenv](https://github.com/pyenv/pyenv) amd [pyenv-virtualenv](https://github.com/pyenv/pyenv-virtualenv) installed on your local environment.
- Install python 3.8.16 with pyenv `pyenv install 3.10.13`.
- Set up a new virtual env `pyenv virtualenv 3.10.13 transformers`
- Set local pyenv version `pyenv local transformers`
- Activate the virtual pyenv using `pyenv activate transformers`
- Upgrade the pip package installer `pip install --upgrade pip`
- Install poetry for package management `pip install poetry==1.7.1`
- Install dependencies from the lock file `poetry install --no-root` 

