Technology · Library

NumPy

Library · Catalog tech@1

Numerical computing for Python.

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 signals

No 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.

    Official repositoryPython

    32.9K stars

Members 61repositories tagged with one of its aliases, most-starred first

  • pytorch/pytorch

    Tensors and Dynamic neural networks in Python with strong GPU acceleration

    Tagged numpyPython

    103.6K stars

  • lutzroeder/netron

    Visualizer for neural network, deep learning and machine learning models

    Tagged numpyJavaScript

    33.5K stars

  • donnemartin/data-science-ipython-notebooks

    Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.

    Tagged numpyPython

    29.4K stars

  • huggingface/datasets

    🤗 The largest hub of ready-to-use datasets for AI models with fast, easy-to-use and efficient data manipulation tools

    Tagged numpyPython

    22K stars

  • bbfamily/abu

    阿布量化交易系统(股票,期权,期货,比特币,机器学习) 基于python的开源量化交易,量化投资架构

    Tagged numpyPython

    18.8K stars

  • exaloop/codon

    A high-performance, zero-overhead, extensible Python compiler with built-in NumPy support

    Tagged numpyPython

    16.8K stars

  • kailashahirwar/cheatsheets-ai

    Essential Cheat Sheets for deep learning and machine learning researchers https://medium.com/@kailashahirwar/essential-cheat-sheets-for-machine-learning-and-deep-learning-researchers-efb6a8ebd2e5

    Tagged numpy

    15.4K stars

  • dask/dask

    Parallel computing with task scheduling

    Tagged numpyPython

    13.9K stars

  • tangyudi/Ai-Learn

    人工智能学习路线图,整理近200个实战案例与项目,免费提供配套教材,零基础入门,就业实战!包括:Python,数学,机器学习,数据分析,深度学习,计算机视觉,自然语言处理,PyTorch tensorflow machine-learning,deep-learning data-analysis data-mining mathematics data-science artificial-intelligence python tensorflow tensorflow2 caffe keras pytorch algorithm numpy pandas matplotlib seaborn nlp cv等热门领域

    Tagged numpy

    13.4K stars

  • MorvanZhou/tutorials

    机器学习相关教程

    Tagged numpyPython

    13.1K stars

  • cupy/cupy

    NumPy & SciPy for GPU

    Tagged numpyPython

    12.4K stars

  • rougier/scientific-visualization-book

    An open access book on scientific visualization using python and matplotlib

    Tagged numpyPython

    11.6K 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.

    Published from numpy/numpyPyPI

    Not published by PyPI
  • numpy

    Fundamental package for array computing in Python

    Listed in the catalogPyPI

    Not published by PyPI

Ecosystem 2,479packages that depend on it, most-adopted first

  • anarcii

    A language model suite for numbering antigen receptor sequences.

    Depends on numpyPyPI

    Not published by PyPI
  • anastruct

    Finite element analysis of 2D structures

    Depends on numpyPyPI

    Not published by PyPI
  • andrew-test-weave

    A toolkit for building composable interactive data driven applications.

    Depends on numpyPyPI

    Not published by PyPI
  • androidviewclient

    AndroidViewClient is a 100% pure python library and tools

    Depends on numpyPyPI

    Not published by PyPI
  • angelslim

    A toolkit for compress llm model.

    Depends on numpyPyPI

    Not published by PyPI
  • angelslim-fork

    A toolkit for compress llm model.

    Depends on numpyPyPI

    Not published by PyPI
  • anndata

    Annotated data.

    Depends on numpyPyPI

    Not published by PyPI
  • ansys-dpf-core

    Data Processing Framework - Python Core

    Depends on numpyPyPI

    Not published by PyPI
  • ansys-fluent-core

    PyFluent provides Pythonic access to Ansys Fluent.

    Depends on numpyPyPI

    Not published by PyPI
  • antimeridian

    Correct GeoJSON geometries that cross the 180th meridian

    Depends on numpyPyPI

    Not published by PyPI
  • antropy

    AntroPy: entropy and complexity of time-series in Python

    Depends on numpyPyPI

    Not published by PyPI
  • anyjev

    AnyJev: Jev-style typed decisions with probabilities from open LLMs: a training-free readout of any model, and the self-distilled Tacit models. Not affiliated with TypeSafe AI.

    Depends on numpyPyPI

    Not published by PyPI

Latest news the 0 latest events that mention it

No published news event mentions NumPy yet.