returns
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returns | effect | |
---|---|---|
20 | 25 | |
3,221 | 3,801 | |
3.8% | 14.2% | |
9.1 | 9.9 | |
9 days ago | 6 days ago | |
Python | TypeScript | |
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.
effect
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A better way to handle errors in JavaScript
Just use a library that already contains this and more functional programming idioms, like fp-ts or its successor, Effect [0]. It is a little more complex to learn but much more robust that simply implementing your own Result and other types.
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Building React Components Using Unions in TypeScript
effect-ts
- Alternatives to scala FP
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Functions vs. Procedures: Keep them separate.
But could we manage to achieve the same (avoid the same side-effect pollution), but entirely without handling it through the type system? Could we even manage to do it in JavaScript/TypeScript? Even without Haskell-ist wizardry like effect-ts?
- Javascript futures and Result monads belong together
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What DI framework are you using?
I inject services with https://github.com/Effect-TS/effect and Layers
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Introduction
I have chosen fp-ts since it is the tool I am the most familiar with but there are others out there, for example effect-ts.
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State of Scala.js frameworks
FYI there's a ZIO "port" for Typescript (https://github.com/Effect-TS/core) so if you want, you can still write pure FP code in frontend too. I haven't tried it yet though, I myself am a backend engineer and only play with frontend stuff for personal projects, when I've got some time.
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The case for TS+
// file: IO.ts export class IO { constructor(readonly io: () => A) {} } export const succeed = (a: A) => new IO(() => a); export const succeedWith = (a: () => A) => new IO(a); export function map(f: (a: A) => B): (self: IO) => IO { return (self: IO) => new IO(() => f(self.io())); } export function flatMap(f: (a: A) => IO): (self: IO) => IO { return (self) => new IO(() => f(self.io()).io()); } export function zip(b: IO): (self: IO) => IO<[A, B]> { return (self) => new IO(() => [self.io(), b.io()]); } export function run(self: IO) { return self.io(); } // file: Function.ts // omitted definition of pipe, long https://github.com/Effect-TS/core/blob/master/packages/system/src/Function/pipe.ts // file: USE.ts import * as IO from "./IO"; import { pipe } from "./Function"; export const program = pipe( IO.succeed(0), IO.map((n) => n + 1), IO.flatMap((r) => IO.succeedWith(() => { console.log(`result: ${r}`); }) ) ); IO.run(program);
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GraphQL error handling to the max with Typescript, codegen and fp-ts
In order to make our throwing and unsafe APIs into safe data fetching functions, we'll use data types and techniques from the Functional Programming paradigm. In particular, we'll use the fp-ts library (but you can choose the FP library of your choice, e.g. purify, effect, monio, and others).
What are some alternatives?
fp-ts - Functional programming in TypeScript
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.