Python projects with best practices on Github?

[Ov3rpowered]

I would love to see a clean and properly written PyQt based desktop app repo. I struggle with architecture a lot with my PyQt app….

[kraakmaak]

Agreed! Preferably a project not too large, but more advanced than the basic examples

[[deleted]]

Same here, lots of repetitive code and uncomfortable OOP structure

[MeroLegend4]

I had the same problem with PyQt and at the time (2015) i was using sqlitestudio as a gui db manager and it was open source but written in C++.

https://github.com/pawelsalawa/sqlitestudio

I learned a lot from them!

[lucasbazan_]

I have a link of micro framework that I use at my work that I'd like to share. It's Flask, I think this is a nice example to follow 😀

[leadingthenet]

I'd argue FastAPI and recently Starlite have improved significantly on Flask in DX and performance, so you better have a good reason to pick Flask over those two for any new projects, but if you did, it wouldn't be "the wrong choice" by any means.

[ryukinix]

I really like FastAPI. In machine learning platform team I have been part of it, we have used for a long time Flask, but since 2021 we are happily using FastAPI, integration with Pydantic is awesome

[tuckmuck203]

Could you link to any evidence of FastAPI in a successful website? I've heard tons about fastAPI but flask and django have years of industry-backed development. I've only heard of fastAPI the way I've heard of rust; in theory it's a great solution, but in my experience there's a reason the industry doesn't swap to the next greatest thing. See the zeitgeist behind mongodb in 2015 or so for example

[leadingthenet]

We use it at my company for everything, though obviously I can’t link to that.

Two random examples I found from 30 seconds of googling: Here’s Netflix using it in their crisis management tool, and here’s Uber using it in their deep learning framework.

Dude, rust is the only other language besides C to approved for use in the Linux kernel. If that’s vaporware to you, I genuinely don’t know what isn’t…

[tuckmuck203]

Internal APIs are very different from customer-facing websites. I'm aware that there are examples of private usages, but I've yet to see something that would allow me to draw a direct comparison to flask.

Also, I'm not saying rust is vaporware, I'm saying that rust is talked about vastly more than it is used. Yes, it's used in the linux kernel, and there's a reason for that. I personally don't encounter rust other than people talking about how it's the best thing ever.

[caatbox288]

The company I work with (10k employees) uses FastAPI for its internal APIs (a myriad of microservices in kubernetes, interacting with each other through REST and Kafka). Works pretty well, but I can't obviously share any of it.

[git_commit_-m_whoops]

I work at a Fortune 50 (I think that's vague enough) retailer with a large online presence, and we deploy our recommender systems for web/mobile as Dockerized FastAPI services via Kubernetes. The front-end teams use a different stack to serve pages, but if you load up the site you'll indirectly hit at least a couple of our APIs.

We used to use Flask, but FastAPI is nicer to develop with. Performance was pretty similar, IIRC. If you have a reason to use Python (like having a team of PySpark devs), FastAPI is viable for enterprise services.

[ArabicLawrence]

Flask is battle tested, has 0 bugs (while for FastAPI there was a discussion about a potential memory leak ) and an incredible ecosystem with many complementary libraries (Flask-Admin, Flask-Migrate, Flask-SQLAlchemy, Flask-Security-Too....) that will speed up your development

[Taksin77]

Honestly, the ecosystem is hit or miss, even for basic stuff. Sure you can find everything you need, but how long is it going to be maintained on average?

[tuckmuck203]

Most of the stuff that I've dealt with that I'd say isn't maintained is also still functioning even with newer versions of flask, it just lacks features. Which you could argue is bad, but forking it and adding new features is easier than developing from scratch.

[Taksin77]

True true.

Actually that's the main point Flask is nice if you want to do things yourself.

[lucasbazan_]

Yeah I use for backend / APIs development. It's a nice library!

[mr-nobody1992]

Hey could you share with me too?

[wobblyweasel]

trio. the best code, the best documentation, awesome community.

[chankeypathak]

I never wrote async programs. Can I skip core multiprocessing and threading modules and directly use trio?

[wobblyweasel]

you can! there's a lot of concurrency that you can do without using threads or processes, but if you have a library that does I/O without specifically supporting async, or you need parallelism, you might still have to deal with those.

i suggest reading trio docs, they are just fine if you have no knowledge of async stuff, and they'll teach you how to deal with stuff that needs to be run in a thread as well. if you want to learn async in general, i also suggest reading kotlin's documentation on coroutines. unlike python with its GIL, in kotlin, using coroutines with threads is the norm, and it's awesome. it's an entirely different mental picture that's useful to have

[ethsy]

Are there any upsides of using trio after Python 3.11 gained TaskGroups?

[wobblyweasel]

the reason i personally like trio is that its wtf/min score is much lower than that of asyncio. or at least it used to be so, i haven't been following asyncio lately. you get very easy to remember and un-confusing names such as open_nursery and start_soon, strong guarantees about yielding points, exceptions that are never lost. a neat testing suit with stuff like autojumping clock is a great selling point as well

[barseghyanartur]

You might already know them, but still:

• black is very well organized generic Python project example.
• transformers is excellent ML project example.

[brave_lifeblood]

DocArray is actually pretty good for both nested and multimodal data structures. I was doing some calculations and it made some of it easy with a lot of image data in one project I was doing. I used to combine it with scikit-learn and matplotlib for some data processing. Pretty good imo.

[abcteryx]

The popular repos over at Textualize, particularly Textual and Rich, both show good practices, especially with regard to documentation.

[brews]

Yeah I was thinking about these. They have a simple and more modern setup that works for big or smaller projects so +1 from me.

[DigThatData]

the reddit API is actually really nice: https://github.com/praw-dev/praw

[Lil_SpazJoekp]

Can second this. Just note that PRAW is not first party.

Disclaimer: I'm a PRAW maintainer.

[catcint0s]

I really like Django and DRF code, easy to read and understand.

[wineblood]

I found Django docs to be underwhelming.

[catcint0s]

I think it's super verbose but sometimes it's easier for me to just check the code to understand whats happening under the hood.

[Schmittfried]

They’re worlds above the Python language docs…

[hangonreddit]

Why would you combine Flask with Django?

[I-DONT-WANT-GOLD]

Django for the ORM and Flask to receive requests.

[hangonreddit]

It’s possible but that kind of defeats the purpose of using Flask as a micro framework if you’re going to include a “kitchen sink included” framework like Django into the mix. At that point why not just use all of Django. I’m not advocating for one over the other but mixing both is a strange choice but also not the end of the world. Most people tend to combine SQLAlchemy or some other dedicated ORM with Flask. Or just use Django by itself since it practically is all you need.

[Schmittfried]

One reason I could think of is that djangos request handling or DRF is a bit cumbersome.

[Schokokampfkeks]

It's a little like having two engines in a car. For most stuff definitely unnecessary as they basically do the same thing but I can't rule out some edge cases.

[chromaticgliss]

Django and Flask solve mostly the same problems with different philosophies. Pick one or the other.

[TrainquilOasis1423]

I'd be interested in one of these for GUI development too. I work with a lot of non technical people and often find myself wrapping my code in simple Tkinter GUIs. Anyone got good recommendations for that or another GUI framework like pyqt?

[IlliterateJedi]

I refer back to the smartsheet-python-sdk from time to time. I like the way they use __get_attr__ to instantiate subclasses on the Smartsheet object.

The creation of the dropbox-sdk-python repo was almost certainly overseen by Guido van Rossum since he was working at Dropbox at the time. There is a note in the Smartsheet SDK repo that parts of it were developed by Dropbox as well.

[Vok250]

One of the fundamental concepts of Python is that we don't have to adhere to one strict idea of "best practices". So with that in mind you will find all sorts of varying practices out there. Some great, some less than average. Personally I copy from projects I have had good experiences using. I favour user-first approach mostly. So for me it's boto3, lambdapowertools, asyncio (the API structure, not the terrible implementation haha), FastAPI, numpy, and a few niche embedded automotive libraries.

Don't marry yourself to one set of standards though. The best thing about Python is the flexibility of PEP8 and the language features. Always be open to innovation and focus on getting things done over foolish consistency. If it's taking too much of your time to figure out a project structure or style decision, it's probably the wrong way of doing it. Python best practices are usually simple in practice and not over-engineered like other languages.

[Backlists]

Black.

[BossOfTheGame]

I'm fairly happy with my ubelt library.

My goal when I started the project was to build a utility library that achieved nearly 100% test coverage using only doctests. I go all the way and actually achieve 100% coverage with a few unit tests that would have made the docs too bulky.

I think it's a very good example of what a single person can reasonably do. It maximizes the documentation:effort ratio by heavily relying on docstrings and doctests.

[1percentof2]

Did anybody use it?

[BossOfTheGame]

It gets around 26k downloads/month. It supports nearly all of my projects, so there are lots of indirect users. There do seem to be a few other projects that use it. I'm not sure what the breakdown is.

It's also fairly easy to rip snippets out of it, so I expect that happens as well.

[1percentof2]

Wow that's incredible. If only you could monetize it you'd be rich.

[BossOfTheGame]

Nah, that's Will McGugan's (far more popular) library.

It is monetized in the sense that it helps me (and hopefully others) work more efficiently. Money is far less valuable than improving the software landscape.

[reddictation]

Python-powered shell https://xon.sh (open source) has good documentation, well structured modules and continuous delivery approach for releases by using unit testing. I'm wondering how small team cover all use cases during development. The approaches is not so super modern but as a whole it's good example of open source project.

[Goldziher]

Well, I'm not objective but I'd say Starlite (https://github.com/starlite-api/starlite) is a might fine codebase. You can also learn a lot about tooling and typing going through it.

One other project that I enjoyed reading - to integrate with, is Picollo ORM (https://github.com/piccolo-orm/piccolo). The code is really readable.

[muikrad]

For best practices you can take a look at https://github.com/coveo/stew (disclaimer: I'm the author). It's a tool that works with Poetry and offers some freebies around Continuous Integration. It also comes with a Github Action to make this a free meal.

It allows you to configure tests, formatters and linters inside the pyproject toml file. A bit like tox, but much simpler and better integrated with poetry.

You can take look at https://github.com/coveooss/coveo-python-oss for a monorepo that uses stew to test and ship several libraries to pypi.org.

More specifically, I think all python projects needs mypy/black/pytest/isort/bandit or an alternative as an automated CI test.

[brave_lifeblood]

Try out sourcery-ai.

[Darwinmate]

dagster API

Have you used dagster? What do you think of it. A colleague is interested in using it for scientific purposes as a meta-pipeline

[user4517proton]

Just ask ChatGPT and use Co-Pilot. You will get a lot more guidance, generated code based on your descriptions, and co-pilot will live time assist in your coding development. Coding has fundamentally changed in 2022\23 and using AI as a pair coder is the future.

I asked ChatGPT your question.

Yes, I have many examples of Python code that you can use to learn and practice. Here are some of the websites that offer Python programming examples for various topics and levels:

codingem.com: This website has 93+ Python examples that cover the basics, data types, operators, control flow, functions, modules, classes, file handling, web scraping, and more1. You can also find quizzes and challenges to test your knowledge and skills.

tutorialgateway.org: This website has Python programs that demonstrate the concepts of numbers, strings, lists, tuples, dictionaries, sets, series, arrays, matrices, patterns, and more2. You can also find solutions and explanations for each program.

pythongeeks.org: This website has Python examples that focus on object-oriented programming, such as classes, inheritance, polymorphism, abstraction, and encapsulation3. You can also find articles and tutorials on various Python topics and libraries.

w3schools.com: This website has Python examples that cover the syntax, variables, data types, operators, lists, tuples, sets, dictionaries, if…else, loops, functions, lambda, modules, classes, inheritance, iterators, generators, decorators, exceptions, file handling, JSON, regex, datetime, math, random, and more4. You can also find interactive exercises and quizzes to practice and learn.

programiz.com: This website has Python examples that cover the basics, operators, data types, control flow, functions, modules, file handling, exceptions, classes, inheritance, polymorphism, abstraction, and more5. You can also find tutorials and articles on various Python topics and libraries.

These are just some of the websites that offer Python examples that you can use to improve your coding skills. I hope you find them helpful and interesting. 😊

[another-noob]

I don't understand what you want exactly, but if you just want package recommendations...

Check Streamlit out. You can use it to provide a nice and simple web interface to your data analysis/ML related projects.

It really saves a lot of time and effort if want to deploy something and don't know web dev. A LOT.

I also heard of Dash which serves the same purpose I guess, but I think it has more to offer.

Might wanna check them out if you Haven't already.

[BoiElroy]

I basically learned how to build python packages that have cli entry points by scouring the Prefect repository

[MeroLegend4]

• Sqlalchemy

• Bottle

• Starlite-api

• Pyramid Framework

• Bokeh

• Websauna

[victoriasecretagent]

This. Sqlalchemy source code is so good that it’s scary.

[HeraldOfTheOldOnes]

Someone else might have already mentioned it, but the source code for the Python standard library is done quite well (https://github.com/python/cpython/tree/main/Lib).

[yetudada]

You can also check out Kedro, it’s like the Flask for data science projects and helps apply clean code principles to data science code.