Comments (1)
Hi @hieucnguyen, great suggestion! I have used cookiecutter templates before and I have some opinionated beliefs. I think they make a lot of sense for tooling that involves setting up a collection of sorts (ie. Great Expectations) but I personally found them too rigid, especially for opinionated areas such as data science projects. Especially because people like to organize different artifacts under various nested architectures. For example, some people like to have data in a separate folder, some versioned and never explicitly written to the project dir, some as a pointer to somewhere else (feature store, etc.). So for now, I'm just focusing on what components are needed and not necessarily exactly how to organize them.
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Related Issues (19)
- test_data.py fixtures are executed multiple times HOT 1
- makefile possible error HOT 1
- black and flake8 are formatting in venv
- Conflicting directory for config.py HOT 2
- venv using python3 -m venv venv issue HOT 3
- Package version conflicts HOT 4
- mlflow error when deploying the app HOT 1
- Dockerfile issues pulling assets from S3 HOT 6
- Getting error while loading projects.json file HOT 1
- Error while working in mkdocs HOT 6
- typo in pre-commit package link HOT 1
- Unable to install dependencies on Mac M1 HOT 7
- got an unexpected keyword argument 'handler' from mkdocs serve HOT 3
- error with arguments in sns.barplot() HOT 2
- MLFlow Dashboard from Colab not showing HOT 1
- Chapter annotation - url of project.json needs to be changed HOT 1
- Can I set up all of these on Windows? HOT 1
- pip install error from guide HOT 1
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