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
- neuralforecast
Time series forecasting suite using deep learning models
Not published by PyPI - neuralgcm
Neural General Circulation Models for Weather and Climate
Not published by PyPI - neuralprophet
NeuralProphet is an easy to learn framework for interpretable time series forecasting.
Not published by PyPI - neuro-san-studio
Multi-agent orchestration studio built on the neuro-san framework.
Not published by PyPI - neuroglancer
Python integration for neuroglancer, a WebGL-based viewer for volumetric data
Not published by PyPI - neurokit2
The Python Toolbox for Neurophysiological Signal Processing.
Not published by PyPI - neuromancer
Neural Modules with Adaptive Nonlinear Constraints and Efficient Regularization
Not published by PyPI - nevergrad
A Python toolbox for performing gradient-free optimization
Not published by PyPI - new-gfpgan
GFPGAN aims at developing Practical Algorithms for Real-world Face Restoration
Not published by PyPI - newbringer-picamera2
The libcamera-based Python interface to Raspberry Pi cameras, based on the original Picamera library
Not published by PyPI - nextai-vllm
A high-throughput and memory-efficient inference and serving engine for LLMs
Not published by PyPI - nfl-data-py
python library for interacting with NFL data sourced from nflfastR
Not published by PyPI
Latest news the 0 latest events that mention it
No published news event mentions NumPy yet.