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https://eugeneyan.com/writing/setting-up-python-project-for-automation-and-collaboration/ #7

Open eugeneyan opened 4 years ago

eugeneyan commented 4 years ago

Migrated from json into utteranc.es

eugeneyan commented 4 years ago

Saw this on Data Elixir. Thanks for the great step-by-step!

Comment by Anonymous on 2020-07-07T20:53:35Z

eugeneyan commented 4 years ago

Thank you, I want to introduce unit-tests to my programs, this seems very nice!

Comment by Anonymous on 2020-07-08T08:04:31Z

eugeneyan commented 4 years ago

Overall good but I would prefer “tox” to “make” for the packaging, testing and release process of Python software.

Comment by Grant Jenks on 2020-07-12T17:08:14Z

eugeneyan commented 4 years ago

Yes! tox works amazing for Python automation and I would recommend it. I tend to use make as it's extendable (e.g., scala, bash, CLIs) without too much work. 🤣

Comment by Eugene Yan on 2020-07-13T02:39:34Z

pagpires commented 4 years ago

Thanks for sharing and it's very useful! Just some more that I found useful: black may be useful if linting style is not important, and pre-commit can move some basic checks to local before push. Also pipx might be helpful for some env-agnostic tooling like AWS-CLI

eugeneyan commented 4 years ago

Thanks for sharing this! pre-commit's new to me and looks very useful. (Here's the repo for those who are interested.)

gsajko commented 3 years ago

re-visiting this post, as I started new project - how should I write comments for functions? follow PEP 257? What is your apporach?

eugeneyan commented 3 years ago

I generally follow Google's styleguide here and here.

gaocegege commented 2 years ago

Awesome template!

If you are interested in making Docker a better development environment for AI/ML, I strongly suggest having a look at the project https://github.com/tensorchord/envd :tada:

envd is a machine learning development environment for data science and AI/ML engineering teams.

🐍 No Docker, only Python - Focus on writing Python code, we will take care of Docker and development environment setup.

🖨️ Built-in Jupyter/VSCode - First-class support for Jupyter and VSCode remote extension.

⏱️ Save time - Better cache management to save your time, keep the focus on the model, instead of dependencies.

☁️ Local & cloud - envd integrates seamlessly with Docker so that you can easily share, version, and publish envd environments with Docker Hub or any other OCI image registries.

🔁 Repeatable builds & reproducible results - You can reproduce the same dev environment on your laptop, public cloud VMs, or Docker containers, without any change in setup.