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That is a lot of data for a single page IMO. You already have a TOC, several library sections might be pages unto themselves. You might also cross link topics

by mey 3y ago

That is a lot of data for a single page IMO. You already have a TOC, several library sections might be pages unto themselves. 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

dazzaji 3y ago
This comment got me thinking “What do you notice that is incorrect or important but missing from this page?” I discovered two things: 1) I’m too shallow in Python to identify any such issues and 2) while GPT-4 and Sage struggled with that precise question, in about 3 seconds I got what appears to be a really useful critique from Claude 2 100k. I’ll share that in case anybody is interested: ___ 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.
- hoistbypetard 3y ago
  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. Those are in the inline section, with the other comprehensions: https://gto76.github.io/python-cheatsheet/#inline 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 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 https://gto76.github.io/python-cheatsheet/#numpy Matplotlib: https://gto76.github.io/python-cheatsheet/#plot 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.) ---- 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.
  - dazzaji 3y ago
    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!
n3t 3y ago
> That is a lot of data for a single page IMO. It is great for a cheat sheet to be on a single page. It makes ctrl+f searching useful and quick.
- mey 3y ago
  At what point does something move from being a cheat-sheet to being a reference manual/training document? I don't have a hard definition other than the "you know it when you see it" and this cross that threshold for me. A cheat-sheet I really like is https://devhints.io/bash 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.
  - Karliss 3y ago
    For me the threshold is in the name: a cheat sheet must fit on 1-2 sheets of paper that you can stick to a wall or keep on desk without forming a pile. If it doesn't fit on paper it isn't a cheat sheet it is a reference. You can roughly apply the same guideline even digital format a chat sheet must fit 1-2 screens without scrolling. 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.

by mey 3y ago

dazzaji 3y ago

This comment got me thinking “What do you notice that is incorrect or important but missing from this page?” I discovered two things: 1) I’m too shallow in Python to identify any such issues and 2) while GPT-4 and Sage struggled with that precise question, in about 3 seconds I got what appears to be a really useful critique from Claude 2 100k. I’ll share that in case anybody is interested: ___ 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.

hoistbypetard 3y ago
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. Those are in the inline section, with the other comprehensions: https://gto76.github.io/python-cheatsheet/#inline 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 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 https://gto76.github.io/python-cheatsheet/#numpy Matplotlib: https://gto76.github.io/python-cheatsheet/#plot 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.) ---- 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.
- dazzaji 3y ago
  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!

n3t 3y ago

> That is a lot of data for a single page IMO. It is great for a cheat sheet to be on a single page. It makes ctrl+f searching useful and quick.

mey 3y ago
At what point does something move from being a cheat-sheet to being a reference manual/training document? I don't have a hard definition other than the "you know it when you see it" and this cross that threshold for me. A cheat-sheet I really like is https://devhints.io/bash 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.
- Karliss 3y ago
  For me the threshold is in the name: a cheat sheet must fit on 1-2 sheets of paper that you can stick to a wall or keep on desk without forming a pile. If it doesn't fit on paper it isn't a cheat sheet it is a reference. You can roughly apply the same guideline even digital format a chat sheet must fit 1-2 screens without scrolling. 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.