Python Cheatsheet

Discoverability, a document like this makes it much easier to find features and tools you were unaware of. The Python documentation is awesome, but it doesn't provide a 30k ft overview of the language and standard library, especially when the standard lib is so comprehensive.

Re: Python Cheatsheet

#5

Post by majkinetor » Thu, Jul 20, 2023, 9:53 PM UTC

I like pages like this. Exactly the level of detail I need when I want to use python once in a while. Thanks.

Re: Python Cheatsheet

#6

Post by Given_47 » Thu, Jul 20, 2023, 10:07 PM UTC

samwillis wrote: post #4

zabzonk wrote: post #3

who exactly is this aimed at? why would they not use the python on-line documentation?

Discoverability, a document like this makes it much easier to find features and tools you were unaware of. The Python documentation is awesome, but it doesn't provide a 30k ft overview of the language and standard library, especially when the standard lib is so comprehensive.

Exactly. Analogous to curling cheat.sh or simply using the tldr pages as opposed to sifting thru the entirety of a man page for a quick command

Re: Python Cheatsheet

#7

Post by mey » Thu, Jul 20, 2023, 10:10 PM UTC

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

Re: Python Cheatsheet

#8

Post by analog31 » Thu, Jul 20, 2023, 10:19 PM UTC

zabzonk wrote: post #3

who exactly is this aimed at? why would they not use the python on-line documentation?

"Unofficial" documentation can serve needs that are neglected by the official docs, even if only by offering a different point of view. I can't speak to Python specifically, but to make an analogy, a microcontroller that I'm working with right now is documented by a 3500 page manual that requires a fair amount of expertise just to know what to look for. But a seasoned embedded dev might be just fine with that, and annoyed by anything simpler. On the other hand, I can make headway by using the Arduino API and boatloads of online documentation in the form of blogs, tutorials, StackOverflow, etc.

Likewise, nobody knows how to write technical documentation that's readable by everybody.

In the case of Python, the official docs are typically the last place where I'd look for stuff, given the quality of documents such as this cheat sheet. There's still a need for authoritative "developer" documentation, but not for me.

The diversity of Python developers, from hobbyists to pro's, justifies a similar diversity of documentation.

Re: Python Cheatsheet

#9

Post by dazzaji » Thu, Jul 20, 2023, 10:20 PM UTC

mey wrote: post #7

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

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.

Re: Python Cheatsheet

#10

Post by hoistbypetard » Thu, Jul 20, 2023, 10:34 PM UTC

dazzaji wrote: post #9

mey wrote: post #7

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

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…

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

> 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.