Eh. I think that critique misses more than it hits.
> 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 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.
(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.
Thanks for the drill down. I should just searched the cheatsheet for each purportedly missing item. And I got a good chuckle picturing you counting “on two fingers” how many times you’ve needed SciPy or TensorFlow in 23 years!
> 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.