dapr-ext-workflow
Dapr Workflow Authoring Extension for the Dapr Python SDK.
Decision gist · record as of 2026-08-14
Yes, if you are building microservices with Dapr and need workflow orchestration in Python. The package is production-stable, actively maintained, has no known vulnerabilities, and carries a permissive license. Install friction is minimal. Only consider skipping if you do not use Dapr or have no workflow orchestration requirements.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Dapr runtime to be installed and running; Python 3.10 or later is required.
- Low friction install with a single runtime dependency on dapr.
- Active maintenance with a recent release (30 days ago) and sustained development activity.
License · maintenance · safety
Apache-2.0 (permissive) — Apache-2.0 permissive license allows commercial and private use with minimal restrictions; you must include a copy of the license and state significant changes.
last release 2026-07-15 (30 days) · last repo commit 2026-08-12 · 1,015 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 184,362 downloads/mo, #10,041 on PyPI
Alternatives
Verify before relying
pip install dapr-ext-workflow
from dapr.ext.workflow import WorkflowRuntime
runtime = WorkflowRuntime()
runtime.register_workflow(my_workflow)
runtime.start()- Whether this extension is required or optional for Dapr workflow use in the Python SDK
- Specific workflow patterns or use cases this extension enables beyond base Dapr
- Performance characteristics or scalability limits for workflows defined with this extension
What it is and what it does
dapr-ext-workflow is an extension package for the Dapr Python SDK that adds workflow authoring and orchestration capabilities. It allows you to define, manage, and execute distributed workflows using Dapr's runtime, integrating with the broader Dapr ecosystem for service invocation, state management, and pub/sub messaging.
The package requires Python 3.10 or later and depends only on the dapr runtime package. It is actively maintained, with production-stable status and support for current Python versions through 3.14. The extension is positioned as part of Dapr's distributed application runtime, which handles workflow orchestration, scheduling, and execution across multiple services.
Use it for
- Define multi-step business processes that span multiple microservices using Dapr's workflow primitives
- Orchestrate long-running operations with built-in retry, timeout, and state management via Dapr
- Build event-driven workflows that coordinate service calls and handle failures automatically
- Implement saga patterns for distributed transactions across services in a Dapr-enabled environment
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you are building microservices with Dapr and need workflow orchestration in Python.
The package is production-stable, actively maintained, has no known vulnerabilities, and carries a permissive license. Install friction is minimal. Only consider skipping if you do not use Dapr or have no workflow orchestration requirements.
Install
dapr-ext-workflow on PyPI
Before you install
Low friction install with a single runtime dependency on dapr. Active maintenance with a recent release (30 days ago) and sustained development activity.
Requires Dapr runtime to be installed and running; Python 3.10 or later is required.
License in practice
Apache-2.0 permissive license allows commercial and private use with minimal restrictions; you must include a copy of the license and state significant changes.
Quickstart
pip install dapr-ext-workflow
from dapr.ext.workflow import WorkflowRuntime
runtime = WorkflowRuntime()
runtime.register_workflow(my_workflow)
runtime.start()Verify before relying
- Whether this extension is required or optional for Dapr workflow use in the Python SDK
- Specific workflow patterns or use cases this extension enables beyond base Dapr
- Performance characteristics or scalability limits for workflows defined with this extension
Package facts
| License | Apache-2.0 permissive |
| Python support | Supports the current Python release >=3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 1 packagedapr |
| Maintenance | Actively maintained 30 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 184,362 / month, #10,041 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/StableIntended Audience :: DevelopersLicense :: OSI Approved :: Apache Software LicenseOperating System :: OS IndependentProgramming Language :: PythonProgramming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.14 |
Evidence: dapr_ext_workflow-1.18.3-py3-none-any.whl
Tags
Let your AI agent find packages like this
Example. Real query, live index.
You found this page by searching. An agent finds it by wishing: SkillFed indexes 14,416 PyPI packages by what they can do, searchable in plain language.
wish › “dapr workflow authoring”
- dapr-ext-workflowExtends the Dapr Python SDK with workflow authoring capabilities,…
- dapr-ext-fastapiIntegrates Dapr distributed application runtime with FastAPI web…
- daprDapr SDK for Python provides client libraries and actor framework…
Give your agent the search over MCP, or paste the wish link into any chat.
More Distributed Computing packages
gRPC Python is an HTTP/2-based RPC framework that enables you to define and call remote procedures across network boundaries using protocol buffers for serialization.
Install it if you need RPC communication in a distributed system or are integrating with existing gRPC services.
execnet lets you spawn and communicate with Python interpreters across local processes, remote hosts, and different platforms, using a simple API for task distribution and inter-process messaging.
However, the aging maintenance status (275 days since last release) means you should verify it meets your concurrency and performance needs before committing to a…
Cloudpickle extends Python's standard pickle module to serialize lambda functions, interactively-defined functions and classes, and other constructs that the default pickle cannot handle, making it suitable for cluster computing and remote code execution.
Install it if you need to serialize lambda functions, interactively-defined code, or non-standard Python constructs for cluster computing or distributed execution.
Provides a unified, open()-compatible Python API for streaming large files from remote storage (S3, GCS, Azure, HDFS, SFTP, HTTP) and local filesystems, with transparent compression support.
Install it if you work with large files on cloud storage or remote systems and want to avoid writing boilerplate around multiple SDKs.
Portalocker provides cross-platform file locking with support for exclusive and shared locks, plus Redis-based distributed locks and process-aware PID file locking.
Install it if you need file or process coordination; the optional extras (pywin32, redis) are only required for specific lock types.
Ray is a distributed computing framework that scales Python applications from a single machine to multi-node clusters, providing abstractions for parallel tasks, stateful actors, and shared objects.
See also dapr-ext-fastapi · dapr · apache-airflow-task-sdk · prefect-gitlab · dagster-cloud · mkdocs · markdownlit · properdocs · onyx-devtools · mkdocstrings