Technology · Library
NumPy
Library · Catalog tech@1
Numerical computing for Python.
- Categories
- Matched as
- numpy
Momentum
Each signal is ranked as a percentile among the technologies that have it. A signal without enough history is not counted, and never shown as zero. How momentum works
Momentum
Collecting0 of 5 signalsNo score yet. Momentum is published only when at least 2 of the 5 signals have history. NumPy has 0, so there is no single number: each signal is shown on its own below. It is not a zero, and nothing is estimated in its place.
Snapshot OCT 24, 2026 · Scoring tech@1
- Official repository stars
- Collecting
- Star growth needs repository snapshots 30 days apart.32,900 stars now
- Member repository stars
- Collecting
- Star growth needs repository snapshots 30 days apart.0 new members in 30 days
- Package adoption
- Not published by its registries
- Its packages’ registries publish no adoption figure, so there is nothing to grow.
- Open models
- No official models
- No official model on Hugging Face, so this signal does not apply.
- News
- Collecting
- News counts once there are 3 events across the last 60 days; it has 0.0 in the last 30 days · 0 in the 30 before
Adoption by registry
The growth of NumPy’s own packages, one row per registry in that registry’s own unit. Registries count different things over different windows, so they are never added together.
No registry has two observations of NumPy’s own packages about 30 days apart yet, so there is no growth to show. Nothing is estimated in its place.
News activity
- Events · 7 days
- 0published events that mention it
- Events · 30 days
- 0published events that mention it
- Previous 30 days
- 0events in the 30 days before
Momentum history
Momentum history starts OCT 8, 2026. A chart appears once two daily snapshots carry a score; none does so far.
Repositories
Official 1
- numpy/numpy
The fundamental package for scientific computing with Python.
32.9K stars
Members 61repositories tagged with one of its aliases, most-starred first
- ahmedfgad/GeneticAlgorithmPython
Source code of PyGAD, a Python 3 library for building the genetic algorithm and training machine learning algorithms (Keras & PyTorch).
2.2K stars
- rougier/from-python-to-numpy
An open-access book on numpy vectorization techniques, Nicolas P. Rougier, 2017
2.2K stars
- ashvardanian/NumKong
SIMD-accelerated distances, dot products, matrix ops, geospatial & geometric kernels for 16 numeric types — from 6-bit floats to 64-bit complex — across x86, Arm, RISC-V, and WASM, with bindings for Python, Rust, C, C++, Swift, JS, and Go 📐
1.9K stars
- trekhleb/machine-learning-experiments
🤖 Interactive Machine Learning experiments: 🏋️models training + 🎨models demo
1.8K stars
- CPJKU/madmom
Python audio and music signal processing library
1.7K stars
- tensorly/tensorly
TensorLy: Tensor Learning in Python.
1.7K stars
- fwilliams/point-cloud-utils
An easy-to-use Python library for processing and manipulating 3D point clouds and meshes.
1.6K stars
- JuliaPy/PyCall.jl
Package to call Python functions from the Julia language
1.5K stars
- SciSharp/NumSharp
High Performance Computation for N-D Tensors in .NET, similar API to NumPy.
1.5K stars
- PyO3/rust-numpy
PyO3-based Rust bindings of the NumPy C-API
1.4K stars
- fortran-lang/stdlib
Fortran Standard Library
1.4K stars
- 3dg1luk43/ha_washdata
Home Assistant integration for smart-plug appliance monitoring: detects cycles, matches programs, estimates time remaining. Supports washing machines, dryers, dishwashers and more.
1.3K stars
Packages
“Is” packages are NumPy itself; ecosystem packages depend on them. The two are counted separately and never added together. Adoption is each registry’s own figure, with its percentile within that registry.
Is 2the technology itself, most-adopted first
- intel-numpy
NumPy is the fundamental package for array computing with Python.
Not published by PyPI - numpy
Fundamental package for array computing in Python
Not published by PyPI
Ecosystem 2,479packages that depend on it, most-adopted first
- gpflow
Gaussian process methods in TensorFlow
Not published by PyPI - gptcache
GPTCache, a powerful caching library that can be used to speed up and lower the cost of chat applications that rely on the LLM service. GPTCache works as a memcache for AIGC applications, similar to how Redis works for traditional applications.
Not published by PyPI - gptqmodel
Production ready LLM model compression/quantization toolkit with hw accelerated inference support for both cpu/gpu via HF, vLLM, and SGLang.
Not published by PyPI - grad-cam
Many Class Activation Map methods implemented in Pytorch for classification, segmentation, object detection and more
Not published by PyPI - gradio
Python library for easily interacting with trained machine learning models
Not published by PyPI - grain
Grain: A library for loading and transforming data for ML training.
Not published by PyPI - graph-retriever
Retriever combining unstructured similarity and structured document traversal.
Not published by PyPI - graphdatascience
A Python client for the Neo4j Graph Data Science (GDS) library
Not published by PyPI - graphein
Protein & Interactomic Graph Construction for Machine Learning
Not published by PyPI - graphframes
GraphFrames: DataFrame-based Graphs
Not published by PyPI - graphifyy
AI coding assistant skill (Claude Code, CodeBuddy, Codex, OpenCode, Kilo Code, Cursor, Gemini CLI, Aider, OpenClaw, Factory Droid, Trae, Hermes, Kiro, Pi, Devin CLI, Google Antigravity) - turn any folder of code, docs, papers, images, or videos into a queryable knowledge graph
Not published by PyPI - graphistry
A visual graph analytics library for extracting, transforming, displaying, and sharing big graphs with end-to-end GPU acceleration
Not published by PyPI
Latest news the 0 latest events that mention it
No published news event mentions NumPy yet.