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Durable Task Python

Checked
azure-samples·vlatest·backend·MIT

Executes long-running Python tasks reliably within Azure Functions, handling retries and errors gracefully.

Repository

Install on your platform

Showing Claude Code. One command installs this skill into any of the agents below.

  1. 1

    Run this in your project

    terminal
    $ npx skills add azure-samples/durable-task-scheduler --skill durable-task-python -a claude-code

  2. Uses the open-source skills CLI and needs Node.js. Add -g to install it for your user instead of this project.

What we know about this skill

Publisher

azure-samples

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Install target

Live repository

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No human has reviewed this code. The checks below are a static scan of the files at one commit — nobody has run this skill or judged whether it works. A skill runs with whatever access you give your agent, so read the source before you install it.

Automated safety checks

scanned

This skill passed all 6 checks. We read its files at one commit and looked for the things that make a skill dangerous to run — not for whether it works.

  • Declares what it does: passed

    SKILL.md parses and declares a name and a description.

    SKILL.md exists, its frontmatter parses, and it declares a name and a description.

  • No undeclared network calls: passed

    Makes no network calls.

    Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.

  • No obfuscated payloads: passed

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  • No credential access: passed

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  • Pinned to a commit: passed

    Scanned azure-samples/durable-task-scheduler at c05f6ae464.

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Commit
c05f6ae464
Manifest
.github/skills/durable-task-python/SKILL.md
Scanned
3 files, 1,295 lines
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About this skill

What it does

This skill allows AI agents to orchestrate long-running, stateful workflows using the Durable Functions Python SDK. It enables chaining multiple functions together, managing their execution order and dependencies, and persisting data across function invocations. This is ideal for tasks that require complex logic and cannot be completed in a single request.

When to use it

  • Order Processing: Automate a multi-step order fulfillment process involving inventory checks, payment processing, shipping updates, and notifications.
  • Data Migration: Coordinate the migration of large datasets from one system to another, handling retries and error recovery automatically.
  • Machine Learning Pipelines: Build complex ML pipelines that involve data preprocessing, model training, evaluation, and deployment steps.
  • Long-Running Simulations: Execute simulations or analyses that take a significant amount of time, providing progress updates and managing dependencies.

Key capabilities

  • Orchestration of multiple functions
  • State persistence across function calls
  • Retry policies for reliable execution
  • External HTTP orchestration
  • Fan-out/fan-in patterns

Example prompts

  • "Start a new order processing workflow with customer ID 12345 and product SKU ABC."
  • "Check the status of workflow instance XYZ."
  • "Cancel the currently running data migration task."

Tips & gotchas

  • Requires familiarity with Azure Functions and Durable Functions concepts.
  • Workflow definitions must be deployed to an orchestrator before being invoked.