What is numpy?
NumPy is a fundamental numerical computing library providing N-dimensional arrays and comprehensive mathematical functions. It brings the speed of compiled C and Fortran code to Python with an easy-to-use Python interface.
numpy pricing
We don't have numpy's full plan breakdown yet (its pricing page resisted automated reading). Here's what we could confirm. Always check live pricing for exact numbers.
Open source (BSD license)
What numpy does
The capabilities that matter for analytics & bi software, normalised so it lines up with every alternative. “-” means we haven't confirmed it, not that it's missing.
- Self-serve dashboards
- -
- Rich visualisations
- -
- SQL editor
- -
- Semantic / metrics layer
- -
- Data modelling
- -
- Scheduled reports & alerts
- -
- Embedded analytics
- -
- Hosting
- Self-hosted only
- Warehouse-native (no extract)
- -
- Public API
- ✓
- Git-based version control
- -
Platform & deployment
Independently observed- Self-hosted
Integrations (19)
Independently observed- QuTiP
- PyQuil
- Qiskit
- PennyLane
- Pandas
- statsmodels
- Xarray
- Seaborn
- SciPy
- PyWavelets
- python-control
- HyperSpy
- Scikit-image
- OpenCV
- Mahotas
- NetworkX
- graph-tool
- igraph
- PyGSP
numpy FAQ
Common questions about numpy, answered from independent, dated evidence.
What is numpy and what does it do?
Numpy is a Python library for scientific computing that provides N-dimensional array objects and mathematical functions. It includes capabilities for linear algebra operations, Fourier transforms, and random number generation.
Source: https://numpy.org
Is numpy free to use?
Yes, numpy is completely free and open source under a liberal BSD license. No payment, subscription, or commercial licensing is required.
Source: https://numpy.org
How is numpy deployed?
Numpy is self-hosted, meaning you install and run it on your own systems as a Python package. Once installed, you can import it directly into your Python applications without external dependencies.
Source: https://numpy.org
What other libraries integrate with numpy?
Numpy integrates with a broad ecosystem of scientific Python libraries including Pandas, SciPy, Scikit-image, Xarray, NetworkX, OpenCV, Seaborn, statsmodels, and PyWavelets. This enables you to build comprehensive data analysis and scientific computing workflows.
Source: https://numpy.org
Is numpy actively maintained?
Numpy is maintained by a vibrant community of developers. As a fundamental library in Python's scientific computing ecosystem, it receives ongoing development and support.
Source: https://numpy.org
What license does numpy use?
Numpy is distributed under a liberal BSD license, which permits flexible use, modification, and distribution of the code with minimal legal restrictions.
Source: https://numpy.org
Who should use numpy?
Numpy is designed for Python developers and scientists working with numerical data and array-based computing. It serves anyone needing mathematical functions and efficient operations on N-dimensional arrays.
Source: https://numpy.org
The Vioscale score: one lens on the evidence
Not user reviews and not a paid placement: a confidence-weighted blend of the independent signals below (adoption, activity, security posture, and more), which you can sort and re-weight yourself. Vendors can correct their listing but can never move their rank, and stars are weighted low as a vanity metric. It is one way to read the evidence for numpy, not the verdict.
| Signal | Score | Weight | Contribution | Evidence |
|---|---|---|---|---|
| Github Activity | 63 | 0.10 | 6.6 | ✓ |
| Capabilities | 29 | 0.19 | 5.4 | ✓ |
| Release Cadence | 89 | 0.06 | 5.2 | ✓ |
| Integrations | 37 | 0.10 | 3.9 | ✓ |
| Github Stars | 85 | 0.03 | 2.5 | ✓ |
| Security Posture | 0 | 0.07 | 0.0 | - |
| Package Downloads | 0 | 0.15 | 0.0 | - |
| Stackoverflow Activity | 0 | 0.07 | 0.0 | - |
Computed . Re-weight it by intent, or see the full method.
All data & sourcesshow ↓
Every value we hold, with its source, retrieval date, and confidence. This is the evidence behind the score: don't trust it, verify it.
Activity
| Attribute | Value | Evidence |
|---|---|---|
| Commits last 30d | 100 | mediumsource · 2026-07-31 · 65% |
Adoption
| Attribute | Value | Evidence |
|---|---|---|
| Github stars | 32,464 | highsource · 2026-07-31 · 90% |
Content
| Attribute | Value | Evidence |
|---|---|---|
| Faq | [{"answer":"Numpy is a Python library for scientific computing that provides N-dimensional array objects and mathematical functions. It includes capabilities for linear algebra operations, Fourier transforms, and random number generation.","source":"https://numpy.org","question":"What is numpy and what does it do?","confidence":0.95},{"answer":"Yes, numpy is completely free and open source under a liberal BSD license. No payment, subscription, or commercial licensing is required.","source":"https://numpy.org","question":"Is numpy free to use?","confidence":0.95},{"answer":"Numpy is self-hosted, meaning you install and run it on your own systems as a Python package. Once installed, you can import it directly into your Python applications without external dependencies.","source":"https://numpy.org","question":"How is numpy deployed?","confidence":0.85},{"answer":"Numpy integrates with a broad ecosystem of scientific Python libraries including Pandas, SciPy, Scikit-image, Xarray, NetworkX, OpenCV, Seaborn, statsmodels, and PyWavelets. This enables you to build comprehensive data analysis and scientific computing workflows.","source":"https://numpy.org","question":"What other libraries integrate with numpy?","confidence":0.9},{"answer":"Numpy is maintained by a vibrant community of developers. As a fundamental library in Python's scientific computing ecosystem, it receives ongoing development and support.","source":"https://numpy.org","question":"Is numpy actively maintained?","confidence":0.9},{"answer":"Numpy is distributed under a liberal BSD license, which permits flexible use, modification, and distribution of the code with minimal legal restrictions.","source":"https://numpy.org","question":"What license does numpy use?","confidence":0.95},{"answer":"Numpy is designed for Python developers and scientists working with numerical data and array-based computing. It serves anyone needing mathematical functions and efficient operations on N-dimensional arrays.","source":"https://numpy.org","question":"Who should use numpy?","confidence":0.85}] | highsource · 2026-07-31 · 91% |
Features
| Attribute | Value | Evidence |
|---|---|---|
| Capabilities | {"hosting":"self","api_access":true} | mediumsource · 2026-08-05 · 60% |
Integrations
| Attribute | Value | Evidence |
|---|---|---|
| Count | 19 | mediumsource · 2026-08-05 · 60% |
Language
| Attribute | Value | Evidence |
|---|---|---|
| Primary | Python | highsource · 2026-07-31 · 90% |
Pricing
Release
| Attribute | Value | Evidence |
|---|---|---|
| Cadence days | 19 | mediumsource · 2026-07-31 · 70% |
Reliability
| Attribute | Value | Evidence |
|---|---|---|
| Status page | Yes | mediumsource · 2026-08-05 · 60% |