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
- data-designer-engine
Generation engine for DataDesigner synthetic data generation
Not published by PyPI - Not published by PyPI
- databricks-agents
Mosaic AI Agent Framework SDK
Not published by PyPI - databricks-ai-bridge
Official Python library for Databricks AI support
Not published by PyPI - databricks-genai-inference
Interact with the Databricks Foundation Model API from python
Not published by PyPI - databricks-labs-dqx
Data Quality eXtended (DQX) is a Python library for data quality checks and data quality monitoring
Not published by PyPI - databricks-langchain
Support for Databricks AI support in LangChain
Not published by PyPI - databricks-openai
Support for Databricks AI support with OpenAI
Not published by PyPI - datachain
Wrangle unstructured AI data at scale
Not published by PyPI - datacontract-cli
The datacontract CLI is an open source command-line tool for working with Data Contracts. It uses data contract YAML files to lint the data contract, connect to data sources and execute schema and quality tests, detect breaking changes, and export to different formats. The tool is written in Python. It can be used as a standalone CLI tool, in a CI/CD pipeline, or directly as a Python library.
Not published by PyPI - datacontract-specification
The Pydantic Model of the Data Contract Specification
Not published by PyPI - datacurve-pier
A framework for running coding agents in sandboxed environments and keeping full trajectories for analysis.
Not published by PyPI
Latest news the 0 latest events that mention it
No published news event mentions Pydantic yet.