Top 4 Python ipynb Projects

mlcourse.ai

85 9,390 3.4 Python

Open Machine Learning Course

Project mention: Open Machine Learning Course | news.ycombinator.com | 2023-10-22

euporie

20 1,449 9.7 Python

Jupyter notebooks in the terminal

Project mention: I'm building a new web browser | /r/Python | 2023-05-23

Currently it's part of euporie-notebook, but I'm planning on splitting it out and publishing the web-browser as an independent project.

InfluxDB

www.influxdata.com sponsored

Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
pygraphblas

7 338 0.0 Python

GraphBLAS for Python

Project mention: Large Photonic Processor Solves Graph Problems | news.ycombinator.com | 2023-05-10

This is interesting to me because it's advancing the work on the notion of quantum graph problem solving.
I'm sure we've all heard how quantum computers can be used in the future to decrypt information from today. There's a lot of research out there on how QC may be able to efficiently factor large semiprimes and bust our existing cryptographic algorithms, but to me this is the more mundane side of QC.
The exciting side to me is that many graph problems, particularly whole graph problems like connectivity and shortest paths have a potential quantum advantage. This is particularly advantageous for sparse and hypersparse graphs that have billions of nodes but relatively low node degree. Language Models, chemical assay databases, proteomics, causal inference, and fraud detection are just a few problems that involve huge sparse graphs that could get a huge boost from quantum.
And to show my own bias here [1], I think the future of graph algorithms, including quantum, is expressing them in Linear Algebraic form with the GraphBLAS API. Using the GraphBLAS, you can write your algorithm in a mathematical form using the multiplication of adjacency matrices that is then synthesized to some optimal form for a given architecture.
The same code you write can then be run on a variety of backends, currently CPUs and CUDA using SuiteSparse's new JIT, but soon FPGAs and yes, quantum computers. Parallelism will become so broad and conceptually divergent that you won't even be able to conceive of an efficient hand written single function for all possible platforms.
[1] https://github.com/Graphegon/pygraphblas

1filellm

5 214 8.9 Python

Specify a github or local repo, github pull request, arXiv or Sci-Hub paper, Youtube transcript or documentation URL on the web and scrape into a text file and clipboard for easier LLM ingestion

Project mention: The lifecycle of a code AI completion | news.ycombinator.com | 2024-04-07

I created a cli tool that copies a GitHub or local repo into a text file for llm ingestion. It only pulls the filetypes you specify.
https://github.com/jimmc414/1filellm

NOTE: The open source projects on this list are ordered by number of github stars. The number of mentions indicates repo mentiontions in the last 12 Months or since we started tracking (Dec 2020).