Technology · Library
Pydantic
Library · Catalog tech@1
Data validation with Python type hints.
- Categories
- Matched as
- pydantic
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. Pydantic 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.28,923 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 Pydantic’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 Pydantic’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
- pydantic/pydantic
Data validation using Python type hints
28.9K stars
Members 32repositories tagged with one of its aliases, most-starred first
- langchain-ai/langchain
The agent engineering platform.
147.4K stars
- fastapi/fastapi
FastAPI framework, high performance, easy to learn, fast to code, ready for production
102.8K stars
- langchain-ai/langgraph
Build resilient agents.
42.6K stars
- pydantic/pydantic-ai
How Python does AI. Agents, realtime voice, image generation, embeddings. Every model, every interface, typed end to end.
20.4K stars
- fastapi/sqlmodel
SQL databases in Python, designed for simplicity, compatibility, and robustness.
18.4K stars
- vitalik/django-ninja
💨 Fast, Async-ready, Openapi, type hints based framework for building APIs
9.2K stars
- litestar-org/litestar
Light, flexible and extensible ASGI framework | Built to scale
8.5K stars
- mangiucugna/json_repair
Repair malformed JSON from LLMs, APIs, logs, and user input in Python.
5.1K stars
- pydantic/logfire
AI observability platform for production LLM and agent systems.
4.5K stars
- datamodel-code-generator/datamodel-code-generator
Generate Pydantic v2 models, dataclasses, TypedDict, and msgspec.Struct from OpenAPI, JSON Schema, GraphQL, Avro, Protobuf, and raw JSON/YAML/CSV.
4K stars
- mckinsey/vizro
Vizro is a low-code toolkit for building high-quality data visualization apps.
3.8K stars
- Miksus/rocketry
Modern scheduling library for Python
3.4K stars
Packages
“Is” packages are Pydantic 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
- pydantic
Data validation using Python type hints
Not published by PyPI - pydantic-core
Core functionality for Pydantic validation and serialization
Not published by PyPI
Ecosystem 1,609packages that depend on it, most-adopted first
- vbench2
Video generation benchmark
Not published by PyPI - ve-pyiceberg
Apache Iceberg is an open table format for huge analytic datasets
Not published by PyPI - vectordb-bench
VectorDBBench is not just an offering of benchmark results for mainstream vector databases and cloud services, it's your go-to tool for the ultimate performance and cost-effectiveness comparison. Designed with ease-of-use in mind, VectorDBBench is devised to help users, even non-professionals, reproduce results or test new systems, making the hunt for the optimal choice amongst a plethora of cloud services and open-source vector databases a breeze.
Not published by PyPI - Not published by PyPI
- vellum-uptrain-fork
Vellum UpTrain Fork
Not published by PyPI - vercel
Python SDK for Vercel
Not published by PyPI - vercel-sandbox
Python SDK for Vercel Sandbox
Not published by PyPI - vercel-workers
Python SDK for Vercel Workers
Not published by PyPI - vercel-workflow
Python SDK for Vercel Workflows
Not published by PyPI - verifiers
Verifiers: Environments for LLM Reinforcement Learning
Not published by PyPI - vibe-trading-ai
Natural-language finance research AI agent with backtesting
Not published by PyPI - vision-agent
Toolset for Vision Agent
Not published by PyPI
Latest news the 0 latest events that mention it
No published news event mentions Pydantic yet.