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
- numba/numba
NumPy aware dynamic Python compiler using LLVM
11.2K stars
- Yorko/mlcourse.ai
Open Machine Learning Course
10.7K stars
- arogozhnikov/einops
Flexible and powerful tensor operations for readable and reliable code (for pytorch, jax, TF and others)
9.6K stars
- iamseancheney/python_for_data_analysis_2nd_chinese_version
《利用Python进行数据分析·第2版》
9K stars
- ijl/orjson
Fast, correct Python JSON library supporting dataclasses, datetimes, and numpy
8.2K stars
- lanpa/tensorboardX
tensorboard for pytorch (and chainer, mxnet, numpy, ...)
8K stars
- HIPS/autograd
Efficiently computes derivatives of NumPy code.
7.5K stars
- chainer/chainer
A flexible framework of neural networks for deep learning
5.9K stars
- biolab/orange3
🍊 :bar_chart: :bulb: Orange: Interactive data analysis
5.7K stars
- bukosabino/ta
Technical Analysis Library using Pandas and Numpy
5.2K stars
- dusty-nv/jetson-containers
Machine Learning Containers for NVIDIA Jetson and JetPack-L4T
4.9K stars
- MegEngine/MegEngine
MegEngine 是一个快速、可拓展、易于使用且支持自动求导的深度学习框架
4.8K 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
- beique
Ricequant Algorithm Trading System
Not published by PyPI - benchpots
A Python Toolbox for Benchmarking Machine Learning on Partially-Observed Time Series
Not published by PyPI - bentoml
BentoML: The easiest way to serve AI apps and models
Not published by PyPI - bermuda
Spatial algorithms for napari project, compiled for performance
Not published by PyPI - bert-demo
Google AI 2018 BERT pytorch implementation
Not published by PyPI - bert-score
PyTorch implementation of BERT score
Not published by PyPI - bert4torch
an elegant bert4torch
Not published by PyPI - bertopic
BERTopic performs topic Modeling with state-of-the-art transformer models.
Not published by PyPI - betacal
Beta calibration
Not published by PyPI - better-optimize
A drop-in replacement for scipy optimize functions with quality of life improvements
Not published by PyPI - bfcl-eval
Berkeley Function Calling Leaderboard (BFCL)
Not published by PyPI - bigframes
BigQuery DataFrames -- scalable analytics and machine learning with BigQuery
Not published by PyPI
Latest news the 0 latest events that mention it
No published news event mentions NumPy yet.