You might also cross link topics into their relevant python docs for deeper references. I know I always need to dig deeper into CSV/argparse for specific things when working with those systems.
Edit: awesome content
It is great for a cheat sheet to be on a single page. It makes ctrl+f searching useful and quick.
A cheat-sheet I really like is https://devhints.io/bash which I feel has just enough info (for me) when jumping back into bash from other work to give me proper context.
I have nothing against references or this website as a reference those are useful as well. There is a value in having a good reference which strikes a balance of being exhaustive while avoiding the trap of unreadable verbosity that specifications and standards often have.
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Here are a few things I noticed that could be improved on the Python cheatsheet page:
- The dictionary section is missing explanation of dict comprehensions. Dict comprehensions are an important and useful feature for constructing dictionaries in a concise way.
- In the section on modules, it would be good to mention virtual environments. Virtual environments are an important tool for Python dependency and package management.
- The examples in the Pandas section are useful, but more explanation or details could be provided on some of the core DataFrame operations like merging/joining, groupby, aggregations, etc.
- In the sections on concurrency and parallelism, async/await could be explained and demonstrated. Asyncio is commonly used for asynchronous programming in Python.
- The cheatsheet focuses mainly on built-in modules and functionality. It could be useful to also cover some widely used 3rd party libraries like NumPy, SciPy, Matplotlib, TensorFlow, etc.
- Sections on testing and debugging could be added - things like unittest, pytest, logging, debugging tools. Testing and debugging are key skills for Python developers.
- The cheatsheet is very text heavy. More visuals, diagrams, or tables could help make it more scannable and easier to navigate.
Overall it covers a lot of ground, but filling in some of those gaps would make it more comprehensive and useful as a reference. The content is excellent, just some ways it could be expanded on.
> The dictionary section is missing explanation of dict comprehensions. Dict comprehensions are an important and useful feature for constructing dictionaries in a concise way.
Those are in the inline section, with the other comprehensions: https://gto76.github.io/python-cheatsheet/#inline
> In the sections on concurrency and parallelism, async/await could be explained and demonstrated. Asyncio is commonly used for asynchronous programming in Python.
Those are in the coroutines section: https://gto76.github.io/python-cheatsheet/#coroutines
> The cheatsheet focuses mainly on built-in modules and functionality. It could be useful to also cover some widely used 3rd party libraries like NumPy, SciPy, Matplotlib, TensorFlow, etc.
NumPy: https://gto76.github.io/python-cheatsheet/#numpy
Matplotlib: https://gto76.github.io/python-cheatsheet/#plot
(It doesn't cover SciPy, Tensorflow. That said, I've been writing python for 23+ years, and can count on two fingers how many times I've needed either of those.)
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Some parts of the critique are correct, if not especially useful IMO. I'd say most of the parts of the critique that are correct seem to misunderstand the purpose of the cheatsheet. The best points the model generated, IMO, were the ones related to pandas and virtual environments.