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
- SALib/SALib
Sensitivity Analysis Library in Python. Contains Sobol, Morris, FAST, and other methods.
1K 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
- nlm-ingestor
Parsers and ingestors for different file types and formats
Not published by PyPI - nlopt
Library for nonlinear optimization, wrapping many algorithms for global and local, constrained or unconstrained, optimization
Not published by PyPI - nlpaug
Natural language processing augmentation library for deep neural networks
Not published by PyPI - nmslib
Non-Metric Space Library (NMSLIB)
Not published by PyPI - nmslib-metabrainz
Non-Metric Space Library (NMSLIB)
Not published by PyPI - nnaudio
A fast GPU audio processing toolbox with 1D convolutional neural network
Not published by PyPI - nncf
Neural Networks Compression Framework
Not published by PyPI - nndeploy
An Easy-to-Use and High-Performance AI deployment framework
Not published by PyPI - nnunetv2
nnU-Net is a framework for out-of-the box image segmentation.
Not published by PyPI - nnunetv2-neuropoly
NeuroPoly fork of nnU-Net
Not published by PyPI - nnunetv2ml
nnU-Net is a framework for out-of-the box image segmentation.
Not published by PyPI - node2vec
Implementation of the node2vec algorithm
Not published by PyPI
Latest news the 0 latest events that mention it
No published news event mentions NumPy yet.