pandas-stubs
Pandas type stubs. Helps you type-check your code. (by VirtusLab)
pfun
Functional, composable, asynchronous, type-safe Python. (by suned)
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| pandas-stubs | pfun | |
|---|---|---|
| 1 | 3 | |
| 118 | 146 | |
| 0.8% | - | |
| 0.0 | 6.5 | |
| 3 months ago | 5 months ago | |
| Python | Python | |
| MIT License | MIT License |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
pandas-stubs
Posts with mentions or reviews of pandas-stubs.
We have used some of these posts to build our list of alternatives
and similar projects.
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How can I fix LSP showing as ERRORS for python library sentence?
I haven't had personal experience with using pandas with pyright but check out stubs for pandas. Maybe something like this could help. https://github.com/VirtusLab/pandas-stubs
pfun
Posts with mentions or reviews of pfun.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2021-06-29.
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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?
When comparing pandas-stubs and pfun you can also consider the following projects:
returns - Make your functions return something meaningful, typed, and safe!
python-lenses - A python lens library for manipulating deeply nested immutable structures