Metadata-Version: 2.1
Name: tidal_per_transformers
Version: 0.0.6
Summary: common transformers used by the tidal personalization team.
License: Apache License V 2.0
Author: Loay
Author-email: loay@squareup.com
Requires-Python: >=3.8.0
Classifier: License :: Other/Proprietary License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Requires-Dist: alphabet-detector (==0.0.7)
Requires-Dist: boto3 (==1.24.59)
Requires-Dist: great-expectations (==0.16.15)
Requires-Dist: numpy (>=1.16.4)
Requires-Dist: pandas (>=1.4.2)
Requires-Dist: pyarrow (==7.0.0)
Requires-Dist: pyspark (>=3.3.0)
Requires-Dist: s3fs (==2022.11.0)
Requires-Dist: scikit-learn (==1.1.1)
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 3.8.16`.
- Set up a new virtual env `pyenv virtualenv 3.8.16 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==1.5.1`
- Install dependencies from the lock file `poetry install --no-root` 

