Pyrsistent
NumPy
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Pyrsistent | NumPy | |
---|---|---|
6 | 272 | |
1,977 | 26,290 | |
- | 1.6% | |
7.2 | 10.0 | |
3 months ago | 7 days ago | |
Python | Python | |
MIT License | GNU General Public License v3.0 or later |
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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.
Pyrsistent
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Text Parsing: Now You Have Three Problems (David Beazley)
There are python libraries that implement Clojure style functional data types. Have you tried pyrsistent - https://github.com/tobgu/pyrsistent
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What are some amazing, great python external modules, libraries to explore?
Hissp is really interesting. Read through the docs and you'll understand Python more deeply. It works well with Toolz and Pyrsistent.
- When you discover deepcopy in python
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What is the proper way to create a new copy for list, dictionary, tuples, and array
This is normal for some functional languages, since by definition they should prohibit assignment and hence mutation. But you can also achieve a similar (not the same) effect in python, using libraries like pyrsistent (https://github.com/tobgu/pyrsistent/)
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Hello, HPy
It still is, and Cython is great for accelerating critical Python code.
A C extension is far preferable when you want to code in C, either to write a new data type[1], or write a Python frontend to a C library[2] that is too complex to be well supported by simple FFI.
I think people use Cython more internally when they value the maintainability of "mostly Python" over the fact that it's slower than what native C would get them.
[1]: https://github.com/tobgu/pyrsistent
[2]: https://github.com/libgit2/pygit2
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Toolz: A functional standard library for Python
There's Pyrsistent[1], which provides persistent data structures.
[1] https://github.com/tobgu/pyrsistent
NumPy
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Dot vs Matrix vs Element-wise multiplication in PyTorch
In NumPy with @, dot() or matmul():
- NumPy 2.0.0 Beta1
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Element-wise vs Matrix vs Dot multiplication
In NumPy with * or multiply(). ` or multiply()` can multiply 0D or more D arrays by element-wise multiplication.
- JSON dans les projets data science : Trucs & Astuces
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JSON in data science projects: tips & tricks
Data science projects often use numpy. However, numpy objects are not JSON-serializable and therefore require conversion to standard python objects in order to be saved:
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Introducing Flama for Robust Machine Learning APIs
numpy: A library for scientific computing in Python
- help with installing numpy, please
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A Comprehensive Guide to NumPy Arrays
Python has become a preferred language for data analysis due to its simplicity and robust library ecosystem. Among these, NumPy stands out with its efficient handling of numerical data. Let’s say you’re working with numbers for large data sets—something Python’s native data structures may find challenging. That’s where NumPy arrays come into play, making numerical computations seamless and speedy.
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Why do all the popular projects use relative imports in __init__ files if PEP 8 recommends absolute?
I was looking at all the big projects like numpy, pytorch, flask, etc.
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NumPy 2.0 development status & announcements: major C-API and Python API cleanup
I wish the NumPy devs would more thoroughly consider adding full fluent API support, e.g. x.sqrt().ceil(). [Issue #24081]
What are some alternatives?
Toolz - A functional standard library for Python.
SymPy - A computer algebra system written in pure Python
fn.py - Functional programming in Python: implementation of missing features to enjoy FP
Pandas - Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
funcy - A fancy and practical functional tools
blaze - NumPy and Pandas interface to Big Data
Coconut - Simple, elegant, Pythonic functional programming.
SciPy - SciPy library main repository
CyToolz - Cython implementation of Toolz: High performance functional utilities
Numba - NumPy aware dynamic Python compiler using LLVM
Deal - 🤝 Design by contract for Python. Write bug-free code. Add a few decorators, get static analysis and tests for free.
Nim - Nim is a statically typed compiled systems programming language. It combines successful concepts from mature languages like Python, Ada and Modula. Its design focuses on efficiency, expressiveness, and elegance (in that order of priority).