pydantic-graph
Graph and state machine library
Decision gist · record as of 2026-08-14
Yes. The package is actively maintained, has no security vulnerabilities, uses a permissive MIT license, and installs with low friction. It solves a real problem—type-safe, readable graph execution—using standard Python idioms. The recent release and high repository stars indicate active development. Install it if you need to orchestrate multi-step workflows or state machines with explicit, debuggable control flow.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.10 or later; async/await syntax required for node execution.
- Low install friction with a pure-Python wheel and 5 runtime dependencies (anyio, httpx, logfire-api, pydantic, typing-inspection).
- Active maintenance with a release 1 day old and 19277 repository stars.
License · maintenance · safety
MIT (permissive) — MIT license (permissive) means you can use this freely in commercial and private projects with minimal restrictions.
last release 2026-08-13 (1 days) · last repo commit 2026-08-14 · 19,277 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 110,997,194 downloads/mo, #320 on PyPI
Alternatives
Verify before relying
pip install pydantic-graph
from pydantic_graph import BaseNode, End, GraphBuilder, GraphRunContext
from dataclasses import dataclass
@dataclass
class MyNode(BaseNode[None, None, int]):
value: int
async def run(self, ctx: GraphRunContext) -> End[int]:
return End(self.value)
g = GraphBuilder(input_type=int, output_type=int)
result = await g.build().run(inputs=1)- Whether logfire-api is a required runtime dependency or optional for observability only.
- Performance characteristics with large graphs or long-running state machines.
- Whether the library supports synchronous execution or only async workflows.
What it is and what it does
Pydantic Graph is a type-safe graph and state machine library built on standard Python syntax. You define nodes as dataclasses with async run methods, and edges are inferred from the return type hints—when a node returns another node type, that becomes the next step; when it returns End, the graph terminates. The library prioritizes explicit, readable code over domain-specific magic, making it suitable for workflow orchestration, multi-step processes, and decision trees whether or not you're using Pydantic AI.
It depends on pydantic for validation, anyio for async coordination, httpx for HTTP operations, typing-inspection for type introspection, and logfire-api for observability. The library is actively maintained, recently released, and carries no known security vulnerabilities. It supports Python 3.10 through 3.14 and installs with low friction as a pure-Python wheel.
Use it for
- Build multi-step workflows where each step's output determines the next node to execute.
- Implement finite state machines with type-safe transitions defined by return type hints.
- Orchestrate async tasks in a directed acyclic graph with early termination via End.
- Create decision trees or approval pipelines where each node performs validation or transformation.
- Model agent-like behavior with state transitions without requiring a full AI framework.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
The package is actively maintained, has no security vulnerabilities, uses a permissive MIT license, and installs with low friction. It solves a real problem—type-safe, readable graph execution—using standard Python idioms. The recent release and high repository stars indicate active development. Install it if you need to orchestrate multi-step workflows or state machines with explicit, debuggable control flow.
Install
pydantic-graph on PyPI
Before you install
Low install friction with a pure-Python wheel and 5 runtime dependencies (anyio, httpx, logfire-api, pydantic, typing-inspection). Active maintenance with a release 1 day old and 19277 repository stars.
Requires Python 3.10 or later; async/await syntax required for node execution.
License in practice
MIT license (permissive) means you can use this freely in commercial and private projects with minimal restrictions.
Quickstart
pip install pydantic-graph
from pydantic_graph import BaseNode, End, GraphBuilder, GraphRunContext
from dataclasses import dataclass
@dataclass
class MyNode(BaseNode[None, None, int]):
value: int
async def run(self, ctx: GraphRunContext) -> End[int]:
return End(self.value)
g = GraphBuilder(input_type=int, output_type=int)
result = await g.build().run(inputs=1)Verify before relying
- Whether logfire-api is a required runtime dependency or optional for observability only.
- Performance characteristics with large graphs or long-running state machines.
- Whether the library supports synchronous execution or only async workflows.
Package facts
| License | MIT permissive |
| Python support | Supports the current Python release >=3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 5 packagesanyiohttpxlogfire-apipydantictyping-inspection |
| Maintenance | Actively maintained 1 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 110,997,194 / month, #320 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 5 - Production/StableEnvironment :: ConsoleEnvironment :: MacOS XIntended Audience :: DevelopersIntended Audience :: Information TechnologyIntended Audience :: System AdministratorsLicense :: OSI Approved :: MIT LicenseOperating System :: POSIX :: LinuxOperating System :: UnixProgramming Language :: PythonProgramming Language :: Python :: 3Programming Language :: Python :: 3 :: OnlyProgramming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.14Topic :: InternetTopic :: Software Development :: Libraries :: Python Modules |
Evidence: pydantic_graph-2.29.0-py3-none-any.whl
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See also pydantic-ai · pydantic-evals · pydantic-ai-slim · pydantic-ai-backend · python-statemachine · pydantic-ai-harness · pydantic-tes · pydantic-ai-todo · pydantic-deep · fasta2a