taskflow
Taskflow structured state management library.
Decision gist · record as of 2026-08-14
Yes, if you need declarative workflow orchestration with built-in fault tolerance and persistence. TaskFlow is production-stable (since 2013), actively maintained, has low install friction, and carries a permissive license. Its 13 runtime dependencies are manageable for most environments. Install it if you're building task-driven systems; skip it if you only need simple job queuing or one-off script execution.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.10 or later.
- Optional persistence and worker backends (sqlalchemy, kombu, kazoo) must be installed separately via extras if needed.
- Low friction installation with a pure-Python wheel.
License · maintenance · safety
Apache-2.0 (permissive) — Apache-2.0 permissive license allows commercial use, modification, and distribution with minimal restrictions; suitable for most proprietary and open-source projects.
last release 2026-05-18 (88 days)
0 known vulnerabilities (OSV.dev, 2026-08-14) · 176,421 downloads/mo, #10,242 on PyPI
Alternatives
Verify before relying
pip install taskflow
from taskflow import task, flow
class MyTask(task.Task):
def execute(self):
return "result"
my_flow = flow.Flow('my-flow').add(MyTask())
my_flow.run()- Whether the 13 runtime dependencies are all strictly necessary for basic workflow execution or if many are only needed for optional backends.
- Performance characteristics and scalability limits for large task graphs or high-frequency execution.
- Compatibility with async/await patterns or whether it is callback/synchronous-only.
What it is and what it does
TaskFlow is a structured state management library designed to orchestrate jobs, tasks, and flows in a declarative, highly available manner. It provides a framework for defining workflows as directed acyclic graphs of tasks, with built-in support for error recovery, rollback, and persistence. The library is part of the OpenStack ecosystem but is general-purpose and can be used in any Python project that needs reliable task execution.
The package ships with core execution capabilities and a pluggable architecture for optional backends: persistence layers (e.g., sqlalchemy), execution engines (e.g., worker-based via kombu), and job boards (e.g., kazoo-based). Most of these are opt-in extras; the base installation provides in-memory execution and local task scheduling. It depends on networkx for graph representation, stevedore for plugin management, and oslo libraries for serialization and utilities.
Use it for
- Build reliable ETL pipelines with automatic retry and rollback on failure.
- Orchestrate multi-step deployment or provisioning workflows in cloud infrastructure.
- Define complex job dependencies and execute them across distributed worker pools.
- Implement long-running background job queues with persistence and recovery.
- Model state transitions and task workflows in microservice architectures.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you need declarative workflow orchestration with built-in fault tolerance and persistence.
TaskFlow is production-stable (since 2013), actively maintained, has low install friction, and carries a permissive license. Its 13 runtime dependencies are manageable for most environments. Install it if you're building task-driven systems; skip it if you only need simple job queuing or one-off script execution.
Install
taskflow on PyPI
Before you install
Low friction installation with a pure-Python wheel. Actively maintained (last release 88 days ago). Requires 13 runtime dependencies including networkx, stevedore, and oslo libraries; optional extras like workers, sqlalchemy, and kazoo backends are available for specialized use cases.
Requires Python 3.10 or later. Optional persistence and worker backends (sqlalchemy, kombu, kazoo) must be installed separately via extras if needed.
License in practice
Apache-2.0 permissive license allows commercial use, modification, and distribution with minimal restrictions; suitable for most proprietary and open-source projects.
Quickstart
pip install taskflow
from taskflow import task, flow
class MyTask(task.Task):
def execute(self):
return "result"
my_flow = flow.Flow('my-flow').add(MyTask())
my_flow.run()Verify before relying
- Whether the 13 runtime dependencies are all strictly necessary for basic workflow execution or if many are only needed for optional backends.
- Performance characteristics and scalability limits for large task graphs or high-frequency execution.
- Compatibility with async/await patterns or whether it is callback/synchronous-only.
Package facts
| License | Apache-2.0 permissive |
| Python support | Supports the current Python release >=3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 13 packagespbrdebtcollectorfuturistfastenersnetworkxstevedorejsonschemaautomatonoslo.utilsoslo.serializationtenacitycachetoolspydot |
| Maintenance | Actively maintained 88 days since the last release |
| First released | |
| Downloads | 176,421 / month, #10,242 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 :: ConsoleIntended Audience :: DevelopersLicense :: OSI Approved :: Apache Software LicenseOperating System :: POSIX :: LinuxProgramming Language :: PythonProgramming Language :: Python :: 3Programming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Topic :: Software Development :: LibrariesTopic :: System :: Distributed Computing |
Evidence: taskflow-6.3.0-py3-none-any.whl
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See also craft-parts · python-mistralclient · automaton · taskcluster-taskgraph · eventsourcing · futurist · jobflow · langflow · celery · promptflow-core