Type annotations for specifying, validating, and serializing arrays with arbitrary backends in Pydantic (and beyond)
⚡ Executive Summary & Quick Facts
Authoritative Sourcenumpydantic is numpydantic is an open-source project written in Python: Type annotations for specifying, validating, and serializing arrays with arbitrary backends in Pydantic (and beyond)..
“According to real-time open source telemetry recorded on GitHubRepo.cloud (as of November 2026), p2p-ld/numpydantic has accumulated 150 GitHub stars and 7 forks. It is written in Python, licensed under MIT, and ranks #21,921 globally. It is actively maintained with the latest commit recorded on Oct 27, 2026.”
| Repository | p2p-ld/numpydantic ↗ |
|---|---|
| Primary Category | arrays |
| Language & Stack | Python |
| Software License | MIT |
| Community Traction | ★ 150 stars · ⑂ 7 forks · #21,921 globally |
| Maintenance | ● Active (Last commit: Oct 27, 2026) · 23 open issues |
| Target Audience | Developers and engineering teams building with Python, seeking reliable, tested, and actively maintained tooling for production workloads. |
🛡️ Repository Maintenance & Health Audit (2026)
Health Score: 88/100 · Grade AYes, numpydantic is actively maintained. Continuous telemetry recorded the last code commit on Oct 27, 2026 (16 days ago). Supported by 150 stars and 7 community forks, this repository holds a calculated health index of 88/100, reflecting regular maintenance (16 days ago) and healthy issue cadence.
Star History
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+10
STARS · LAST 30 DAYS
1
PER DAY
#2,895
MOST-STARRED Python
| Window | 7 days | 30 days | 90 days |
|---|---|---|---|
| Stars gained | +0 | +10 | +90 |
| Per day | 1 | 1 | 1 |
| Forks gained | +0 | +3 | +10 |
numpydantic gained 10 stars in the last 30 days, about 1 a day, and now has 150. It is about 3 years old and has averaged roughly 50 stars a year. It ranks #2,895 among Python repositories and #21,921 across all languages on GitHubRepo.
Trending Record
12
DAYS ON TRENDING
#17438
BEST RANK
Oct 28, 2026
FIRST APPEARANCE
Active
STATUS TODAY
numpydantic has maintained a continuous presence across global trending indexes, peaking at #17438. Below is the 30-day activity profile:
💡 Overview
numpydantic is an open-source project written in Python: Type annotations for specifying, validating, and serializing arrays with arbitrary backends in Pydantic (and beyond).
Engineered for speed, consistency, and developer ease, it solves common hurdles in arrays, dask, data-modeling. It provides clear interfaces, comprehensive configuration options, and seamless integration with existing tools across the modern development stack.
⚡ Key Features
Optimized execution pipeline written in Python for predictable speed.
Zero-friction configuration with comprehensive sensible defaults out of the box.
Cross-platform runtime support across Linux, macOS, and Windows environments.
Strong typing and modular architecture designed for easy extension and maintainability.
Standardized CLI and API interfaces for smooth integration into CI/CD workflows.
Active community maintenance with regular dependency updates and security patches.
📥 Installation
$ pip install numpydantic⚙ System Requirements
Platforms
- • macOS
- • Linux
- • Windows
Runtime & Dependencies
Python >= 3.9, pip, virtualenv
Architecture
x86_64, ARM64 (Apple Silicon & Graviton)
🧠 How It Works
numpydantic coordinates its core functionality through a modular Python pipeline. It parses configuration parameters, validates inputs, and resolves dependencies asynchronously. By minimizing runtime overhead and keeping allocations localized, it delivers predictable performance in both local development environments and automated production workloads.
🎯 Production Use Cases
Production System Integration
Embed numpydantic into Python backend services to handle core application logic.
CI/CD Automated Pipelines
Run automated validation, builds, and integration suites during deployments.
Developer Tooling & Workflows
Accelerate developer onboarding with pre-configured project utilities.
Open Source Extension
Fork and customize internal modules under the repository's open MIT license.
🚀 Getting Started
Install numpydantic using your package manager: `pip install numpydantic`
Initialize your project workspace or configuration file for numpydantic.
Import numpydantic into your codebase or invoke it directly from your terminal.
Execute your test suite or run `numpydantic --help` to verify successful setup.
👍 Strengths
⚠️ Considerations
⇄ Alternatives & Direct Competitors
👥 Who Should Use This
Developers and engineering teams building with Python, seeking reliable, tested, and actively maintained tooling for production workloads.
🏆 Nearby in the Rankings
p2p-ld/numpydantic is currently ranked #21,921 by stars across every repository tracked on GitHubRepo. These are adjacent projects:
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|---|---|---|---|---|
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| #21,921 | p2p-ld/numpydantic This Project | Python | ★ 150 | |
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Frequently Asked Questions
What does numpydantic do? +
Type annotations for specifying, validating, and serializing arrays with arbitrary backends in Pydantic (and beyond)
Is numpydantic actively maintained in 2026? +
Yes, numpydantic is actively maintained. The latest code push was recorded on Oct 27, 2026 (16 days ago). It holds a calculated Maintenance Health Score of 88/100 (A rating) with 150 stars and 23 open issues.
What language is numpydantic written in? +
The primary language is Python. Topics include: arrays, dask, data-modeling, hdf5, numpy.
How many stars does numpydantic have? +
numpydantic has 150 stars and 7 forks on GitHub.
How does numpydantic rank among GitHub repositories? +
With 150 stars, p2p-ld/numpydantic is ranked #21,921 globally across all repositories tracked on GitHubRepo and #2,895 among Python projects.
What license is numpydantic distributed under? +
The repository reports a MIT license. Always verify the repository LICENSE file for legal terms.
