durabletask
A Durable Task Client SDK for Python
Decision gist · record as of 2026-08-14
Yes, if you are building on Azure infrastructure or need durable, replay-based orchestration. The package is production-stable, actively maintained, has no known vulnerabilities, and low install friction. It is worth installing for reliable long-running workflows; if you are not using Azure or do not need replay-based fault tolerance, simpler alternatives may suffice.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.10 or later.
- Orchestrations typically require a running Azure Durable Task Scheduler or Azure Durable Functions backend to execute.
- Low friction installation with a pure Python wheel.
License · maintenance · safety
permissive license (permissive) — MIT License permits unrestricted use, modification, and distribution in both open-source and commercial projects, with only the requirement to include the license notice.
last release 2026-07-30 (15 days) · last repo commit 2026-08-13 · 38 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 387,987 downloads/mo, #7,039 on PyPI
Alternatives
Verify before relying
pip install durabletask
from durabletask import orchestrator, activity
@orchestrator
def my_orchestration(context):
result = yield context.call_activity(my_activity, input_data)
return result
@activity
def my_activity(input_data):
return process(input_data)- Whether the package supports local development/testing without Azure infrastructure
- Performance characteristics and scalability limits for large orchestrations
- Exact replay semantics and determinism guarantees for complex workflows
What it is and what it does
Durabletask is Microsoft's Python SDK for building durable orchestrations—long-running workflows that can pause, resume, and survive failures by replaying their execution history. It provides decorators and APIs to define orchestrator functions (which coordinate work) and activity functions (which perform individual tasks), allowing you to build reliable, fault-tolerant distributed systems without manually managing state or recovery logic.
The package integrates with Azure Durable Task Scheduler and Azure Durable Functions, handling the complexity of persisting execution state, retrying failed activities, and replaying orchestrations from checkpoints. It depends on grpcio and protobuf for communication, and packaging for version handling. Optional features like large payload externalization to Azure Blob Storage are available through extras.
Use it for
- Build multi-step approval workflows that survive service restarts and network failures
- Orchestrate long-running business processes (e.g., order processing, document workflows) with automatic retry and state recovery
- Coordinate parallel and sequential tasks across distributed systems with built-in fault tolerance
- Implement fan-out/fan-in patterns where one orchestration spawns many activities and waits for results
- Create audit trails and replay-based debugging for complex asynchronous workflows
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you are building on Azure infrastructure or need durable, replay-based orchestration.
The package is production-stable, actively maintained, has no known vulnerabilities, and low install friction. It is worth installing for reliable long-running workflows; if you are not using Azure or do not need replay-based fault tolerance, simpler alternatives may suffice.
Install
durabletask on PyPI
Before you install
Low friction installation with a pure Python wheel. The package is actively maintained with a recent release and no known vulnerabilities. Runtime dependencies on grpcio, protobuf, and packaging are standard and widely available.
Requires Python 3.10 or later. Orchestrations typically require a running Azure Durable Task Scheduler or Azure Durable Functions backend to execute.
License in practice
MIT License permits unrestricted use, modification, and distribution in both open-source and commercial projects, with only the requirement to include the license notice.
Quickstart
pip install durabletask
from durabletask import orchestrator, activity
@orchestrator
def my_orchestration(context):
result = yield context.call_activity(my_activity, input_data)
return result
@activity
def my_activity(input_data):
return process(input_data)Verify before relying
- Whether the package supports local development/testing without Azure infrastructure
- Performance characteristics and scalability limits for large orchestrations
- Exact replay semantics and determinism guarantees for complex workflows
Package facts
| License | permissive license permissive |
| Python support | Supports the current Python release >=3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 4 packagesgrpcioprotobufasynciopackaging |
| Maintenance | Actively maintained 15 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 387,987 / month, #7,039 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/StableLicense :: OSI Approved :: MIT LicenseProgramming Language :: Python :: 3 |
Evidence: durabletask-1.9.0-py3-none-any.whl
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See also durabletask.azuremanaged · azure-functions-durable · restate-sdk · agent-framework-durabletask · aws-durable-execution-sdk-python · absurd-sdk · dbos · temporalio · hatchet-sdk · agent-framework-azurefunctions