returns
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returns | pfun | |
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20 | 3 | |
3,226 | 146 | |
3.9% | - | |
9.1 | 6.5 | |
1 day ago | 4 months ago | |
Python | Python | |
BSD 2-clause "Simplified" License | MIT License |
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returns
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This Week in Python (February 23, 2024)
returns – Make your functions return something meaningful, typed, and safe
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Unleash the Power of Python Monads: A Design Pattern for Elegant Code!
returns from the DRY python group appears to offer similar functionality.
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Rust's Option and Result. In Python.
Not to diminish this at all, but https://github.com/dry-python/returns also exists. The scope is wider, but the look and feel of the types feels very similar.
- Functional python for data process
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Faif/Python-patterns: A collection of design patterns/idioms in Python
https://github.com/dry-python/returns#maybe-container
You can decide for yourself what is more readable: all these lambdas or the `None and f()` code.
One of the repos that I found interesting recently is https://github.com/dry-python/returns
- Show HN: Koda, a Typesafe Functional Toolkit for Python
- A simple Rust-like Result type for Python
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What can you do in Haskell that you can't do in Python(for example)?
Functional semantics are available in Python, but IMO not that great. List, dict, and generator comprehensions allow you to perform most operations that you would use in a functional first programming language and there are third party libraries like toolz and funcy that implement some of the more advanced operations. The main issue I've found with using Python as a functional language is it doesn't support fluent syntax. With Scala you can do a relatively complex map/filter/reduce operation with syntactic ease list_of_ints.map(x => x*x).filter(x => x%2 ==0).reduce(x,y => x+y) With Python it's just clunky and less readable b/c of support of list comprehension syntax over fluent syntax. sum([x**2 for x in list_of_ints if x % 2 == 0]) A codebase with 5000 lines of the Scala style code will be much readable and maintainable than with the Python style code.
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Make tests a part of your app
dry-python/returns is a library with primitives that make typed functional programming in Python easier.
pfun
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good examples of functional-like python code that one can study?
Another examples: pfun - stuff you'd find in FP language, but in Python (like using monads for effects)
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Effectful Programming in Machine Learning pipeline
I am a long-time Coconut user, so functional ideas are relatively easy to play with. But I recently discovered pfun which has a lovely system for Effectful programming.
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How To Make Functional Programming in Python Go Fast
In pfun 0.12.0 the interpreter for the effect system was completely re-written as a Python C extension. Lets do some benchmarking to see how big a difference this actually makes in terms of performance. We'll use the performance of the the Scala library ZIO as a baseline, as the pfun effect system draws most of its inspiration from there. ZIO has a fairly extensive benchmarking suite. The most obvious benchmark for testing raw interpreter speed, without any parallelism, is called deepLeftBind (bind is the canonical name for the and_then operation, also called flatMap in Scala):
What are some alternatives?
Toolz - A functional standard library for Python.
CyToolz - Cython implementation of Toolz: High performance functional utilities
Deal - 🤝 Design by contract for Python. Write bug-free code. Add a few decorators, get static analysis and tests for free.
Coconut - Simple, elegant, Pythonic functional programming.
fn.py - Functional programming in Python: implementation of missing features to enjoy FP
funcy - A fancy and practical functional tools
effect - effect isolation in Python, to facilitate more purely functional code
classes - Smart, pythonic, ad-hoc, typed polymorphism for Python
Pyrsistent - Persistent/Immutable/Functional data structures for Python
pandas-stubs - Pandas type stubs. Helps you type-check your code.
python-lenses - A python lens library for manipulating deeply nested immutable structures
fp-ts - Functional programming in TypeScript