anaconda-issues
NumPy
anaconda-issues | NumPy | |
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10 | 272 | |
641 | 26,413 | |
0.0% | 1.1% | |
6.6 | 10.0 | |
3 months ago | 5 days ago | |
Python | ||
- | GNU General Public License v3.0 or later |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
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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.
anaconda-issues
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ssl certifiates are broken
Google search of the issue also turned up this thread: https://github.com/ContinuumIO/anaconda-issues/issues/72
- Model 8bit Optimization Through WSL
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Why is Anaconda running so slow in my terminal?
I found this post on github that describes the same issue I'm facing but the solutions didn't help.
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Python 3 Types in the Wild
A scientist typically wouldn't write web backend, a sysadmin doesn't do a lot of statistical stuff, etc.
A small startup might do well to make their MVP in Python, but as the code grows the implicit costs (of using Python) do too.
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In re: Rust, sorry I wasn't clear above. I don't mean that Rust is a glue language, I mean that people write e.g. grep replacements in it and things like that. Python does systems programming by being glue, Rust does it by being, well, Rust. It makes sense to me that Rust libs would get Python wrappers, but it also seems to me that that adds to my argument: Python is good for small glue, but crunchy things (like grep) should be written in e.g. Rust or Go or something.
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One other things about Python is that the packaging & distribution "story" is ridiculous now. The people in charge of that call themselves the Python Packaging Authority (which name, given what they're doing, reminds me of Brazil the movie) and they seem to me to be running amok, cargo-culting the crap out of what should be a pretty simple and straightforward problem. I could go on but I feel a rant brewing, so I'll cut it off there.
It's not just the PyPA folks that are having problems packaging and distributing Python. The Conda folks ship Tkinter in a broken state for five years now: https://github.com/ContinuumIO/anaconda-issues/issues/6833 That's the default GUI system that ships with the Python Standard Library.
Compare and contrast with Rust's Cargo, or Nim's Nimble, or Erlang's Rebar, etc.
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tkinter font is pixelated
If so, you can check this solution. I've encountered this same issue when using Anaconda or Conda. https://github.com/ContinuumIO/anaconda-issues/issues/6833
- Astrophysicist wants to learn Python
- I know everyone hates Waves, but I seriously hate IK Multimedia even more. Anyone else?
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cannot connect to Centos 8 server from windows 10 PC using xrdp, macOS ok
https://github.com/ContinuumIO/anaconda-issues/issues/1206#issuecomment-258672013
- Windows 10 5.0.1 install gets stuck at "Anaconda3\pkgs\.install.py" · Issue #7587 · ContinuumIO/anaconda-issues
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?
Projects - :page_with_curl: A list of practical projects that anyone can solve in any programming language.
SymPy - A computer algebra system written in pure Python
text-generation-webui - A Gradio web UI for Large Language Models. Supports transformers, GPTQ, AWQ, EXL2, llama.cpp (GGUF), Llama models.
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
pytube-dl - this python application can be used to download youtube videos , thumbnails and descriptions.
blaze - NumPy and Pandas interface to Big Data
cligen - Nim library to infer/generate command-line-interfaces / option / argument parsing; Docs at
SciPy - SciPy library main repository
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).
Numba - NumPy aware dynamic Python compiler using LLVM
astropy - Astronomy and astrophysics core library