more-itertools
nimpy
Our great sponsors
more-itertools | nimpy | |
---|---|---|
9 | 38 | |
3,423 | 1,413 | |
1.6% | - | |
9.1 | 5.8 | |
10 days ago | 3 months ago | |
Python | Nim | |
MIT License | MIT License |
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.
more-itertools
-
I want to learn reading other people code
I'd bet that reading through more-itertools would be a good exercise.
-
Why iter() & next()
check out the code examples in itertools and the source code of more-itertools if you want to see cases where next and iter get used by themselves.
-
Quick way to split and zip a list?
from itertools import islice # Copied from the more-itertools library (MIT license) # https://github.com/more-itertools/more-itertools def batched(iterable, n): "Batch data into lists of length n. The last batch may be shorter." # batched('ABCDEFG', 3) --> ABC DEF G if n < 1: raise ValueError('n must be at least one') it = iter(iterable) while (batch := list(islice(it, n))): yield batch
- more-itertools: More routines for operating on iterables, beyond itertools
-
How do I loop this?
more_itertools.chunked
-
Is there a better way to write this code?
I've had a tab open to more-itertools on github for weeks; maybe I should go read it...
-
Help loading data in batches
The popular more-itertools library implements (among many others) a chunked method which yields lists of size n from an iterator. There is also the ichunked method which yields iterators of size n instead of lists.
-
How to find missing number in groups(lists)
There's a function called consecutive_groups in the more-itertools library that will do this for you efficiently.
-
I am a proficient Python coder whose learning has plateaued. Any really useful libraries I should look into learning? Taking recommendations.
Here are some that might answer your question: - algorithms is a library which contains many of the most useful algorithms for sorting, searching, working with trees, math algorithms like factorials, prime finders and many more - data classes to save you the trouble of writing everytime special methods in a class like init, repr, set, get - box allows the use of dot on dictionaries to access the keys - more-itertools for more routines to operate on iterables than those itertools provide.
nimpy
-
Mojo is now available on Mac
I mean honestly, the closest language to Mojo really is Nim. In the latest Lex Fridman interview [0] when he talks about his ideas behind Mojo it pretty much sounds like he's describing Nim. Ok fair, he wants Mojo to be a full superset of Python, but honestly with nimpy [1] our Python interop is about as seamless as it can really be (without being a superset, which Mojo clearly is not yet). Even the syntax of Mojo looks a damn lot like Nim imo. Anyway, I guess he has the ability to raise enough funds to hire enough people to write his own language within ~2 years so as not have to follow random peoples whim about where to take the language. So I guess I can't blame him. But as someone who's pretty invested in the Nim community it's quite a shame to see such a hyped language receive so much attention by people who should really check out Nim. ¯\_(ツ)_/¯
[0]: https://youtu.be/pdJQ8iVTwj8?si=LfPSNDq8UKKIsJd3
[1]: https://github.com/yglukhov/nimpy
-
Show HN: Pip Imports in Deno
You can also do this in Nim, which basically means you can write any program you could in Python with libraries in Nim. https://github.com/yglukhov/nimpy
-
Nim v2.0 Released
Ones that have not been mentioned so far:
nlvm is an unofficial LLVM backend: https://github.com/arnetheduck/nlvm
npeg lets you write PEGs inline in almost normal PEG notation: https://github.com/zevv/npeg
futhark provides for much more automatic C interop: https://github.com/PMunch/futhark
nimpy allows calling Python code from Nim and vice versa: https://github.com/yglukhov/nimpy
questionable provides a lot of syntax sugar surrounding Option/Result types: https://github.com/codex-storage/questionable
ratel is a framework for embedded programming: https://github.com/PMunch/ratel
cps allows arbitrary procedure rewriting to continuation passing style: https://github.com/nim-works/cps
chronos is an alternative async/await backend: https://github.com/status-im/nim-chronos
zero-functional fixes some inefficiencies when chaining list operations: https://github.com/zero-functional/zero-functional
owlkettle is a declarative macro-oriented library for GTK: https://github.com/can-lehmann/owlkettle
A longer list can be found at https://github.com/ringabout/awesome-nim.
-
Prospects of utilising Nim in scientific computation?
I use Python daily for its massive momentum for scientific stuff, but I also use Nim for everything else. Nim compiles to C, and making Python native modules with Nim is easy with Nimpy.
- Can't run compiled nim code in Python
-
Returning to Nim from Python and Rust
If are a data scientist and come from python take a look at nimpy, a great way to just import python libraries and use them! https://github.com/yglukhov/nimpy Numpy, pandas, pytorch all usable in Nim.
Nim is the ultimate glue language, use libraries from anything: python, c, js, objc.
-
Python's “Disappointing” Superpowers
I've come to really enjoy programming in Nim. Note that Nim is very different language despite sharing a similar syntax. However, I feel it keeps a lot of the "feel" of Python 2 days of being a fairly simple neat language but that lets you do things at compile time (like compile time duck typing).
There's a good Python -> Nim bridge: https://github.com/yglukhov/nimpy
-
Dunder methods in nimpy
See this nimpy issue about it: https://github.com/yglukhov/nimpy/issues/43
-
What language to move to from python to speed up algo?
It has pretty good integration with python, either for having your main code in python and writing small hot functions as nim and importing via nimporter or using python libraries in nim via nimpy.
-
ABI compatibility in Python: How hard could it be?
Related: Nimpy[0] provides an easy way to write Python extensions in Nim, which manages the ABI side very well.
Python 2 is now gone, but until it was, Nimpy was an easy way to write Python extension modules that only needed to be compiled once, and would work with any of your installed Python 2 and Python 3. Magic.
[0] https://github.com/yglukhov/nimpy
What are some alternatives?
TheAlgorithms - All Algorithms implemented in Python
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).
python-patterns - A collection of design patterns/idioms in Python
Box - Python dictionaries with advanced dot notation access
sortedcontainers - Python Sorted Container Types: Sorted List, Sorted Dict, and Sorted Set
nimporter - Compile Nim Extensions for Python On Import!
algorithms
scinim - The core types and functions of the SciNim ecosystem
PyPattyrn - A simple library for implementing common design patterns.
nimpylib - Some python standard library functions ported to Nim
python-ds - No non-sense and no BS repo for how data structure code should be in Python - simple and elegant.
Datamancer - A dataframe library with a dplyr like API