python-mastery
Toolz
| python-mastery | Toolz | |
|---|---|---|
| 7 | 23 | |
| 10,379 | 4,532 | |
| 1.5% | 0.8% | |
| 5.7 | 3.9 | |
| 3 months ago | 27 days ago | |
| Python | Python | |
| Creative Commons Attribution Share Alike 4.0 | GNU General Public License v3.0 or later |
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python-mastery
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Ask HN: Programming Courses for Experienced Coders?
I came here to mention Dave Beazley's courses and talks.
In particular, I recently prepped/ran a week-long, in-house training session of Dave's Python-Mastery[1] course at my day job. We had a group of 8 with a mix of junior and senior Software Engineers and while the juniors were generally able to follow along, it really benefited the senior SEs most. It covers the whole language in such depth and detail that you really feel like you've explored every nook and cranny by the time you're done.
[1] https://github.com/dabeaz-course/python-mastery/
(I enjoyed teaching the class so much that I've considered offering my services teaching it on a consulting basis to other orgs. If that interests anyone, feel free to reach out to the email in my profile.)
- Advanced Python Mastery
- Advanced Python Mastery – A Course by David Beazley
- is there a ruby equivalent of this?
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Ask HN: How can I get better at writing production-level Python?
Another great course is David Beazley's Advanced Python Mastery; he just put it all up on github (PDF of all slides + exercises) https://github.com/dabeaz-course/python-mastery
It's designed as a four-day workshop. Lots of material around 'mature' Python code
Toolz
- Ask HN: How can I get better at writing production-level Python?
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[DISCUSSION] What's your favorite Python library, and how has it helped you in your projects?
My favourite lib would probably be toolz, it's just so elegant and fun to use. But it's more functional approach is not always the best fit for the time, so in practice I mostly use it in research, prototyping, console and notebooks.
- REBL
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What are the best ways to learn Python and Pyspark for ML engineering?
I am not new to Python but only used it to write scripts. Should I start a Python book and then a PySpark book or go directly to PySpark? When reading the legacy code, I found there are usages like GitHub - pytoolz/toolz: A functional standard library for Python. I never heard of.
- Toolz: A Functional Standard Library For Python
- Functional python for data process
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Top python libraries/ frameworks that you suggest every one
toolz is wildly useful https://github.com/pytoolz/toolz
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Show HN: Koda, a Typesafe Functional Toolkit for Python
Maybe the toolz[0] family would cover your use cases? There is also a Cython implementation if you need better performance.
[0] https://github.com/pytoolz/toolz/
- What're the cleanest, most beautifully written projects in Github that are worth studying the code?
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Functional programming beyond itertools
You'll probably enjoy toolz.
What are some alternatives?
glom - ☄️ Python's nested data operator (and CLI), for all your declarative restructuring needs. Got data? Glom it! ☄️
funcy - A fancy and practical functional tools
fn.py - Functional programming in Python: implementation of missing features to enjoy FP
blog - David Beazley's blog.
CyToolz - Cython implementation of Toolz: High performance functional utilities
example-code-2e - Example code for Fluent Python, 2nd edition (O'Reilly 2022)
Pyrsistent - Persistent/Immutable/Functional data structures for Python
curio - Good Curio!
Coconut - Simple, elegant, Pythonic functional programming.
attrs - Python Classes Without Boilerplate
returns - Make your functions return something meaningful, typed, and safe!