Skip to main content

A Python library for building task-based workflows with scheduling, webhooks, artifact management, and observability

Project description

Task Framework

A Python library for building and executing task-based workflows with built-in support for scheduling, webhooks, artifact management, and observability.

Features

  • Multi-Task Server: Deploy multiple task definitions to a single server, each with isolated execution environments
  • Thread Execution: Run tasks synchronously or asynchronously with full state management
  • Artifact Management: Track inputs and outputs with support for JSON, text, and file artifacts
  • File Storage: Pluggable file storage interface with local filesystem and pre-signed URL support
  • Scheduling: Cron-based scheduling with APScheduler integration
  • Webhooks: Event-driven notifications with automatic retry and delivery tracking
  • Observability: Built-in Prometheus metrics and structured logging
  • OpenAPI 3.1.0: Auto-generated API documentation at /docs

Installation

pip install task-framework

Or with uv:

uv add task-framework

Quick Start

Multi-Task Server

The Task Framework runs as a server that can host multiple task definitions. Each task is packaged as a zip file with its code and metadata.

Start a task server:

# Start server with auto-discovery from task_definitions/ directory
task-framework serve --host 0.0.0.0 --port 3000

# Or for development, load a task from source
task-framework serve --dev-task /path/to/my-task/

Deploy a task via API:

curl -X POST http://localhost:3000/admin/tasks \
  -H "X-API-Key: your-admin-key" \
  -F "file=@my-task-1.0.0.zip"

Task Zip Structure:

my-task-1.0.0.zip/
  task_metadata.json    # Task metadata and schemas
  task.py              # Task implementation
  pyproject.toml       # Dependencies (optional)

Example Task Function:

async def my_task(context):
    # Get input artifacts
    inputs = await context.get_input_artifacts()
    
    # Process inputs
    result = {"message": "Task completed", "input_count": len(inputs)}
    
    # Publish output
    from task_framework.models.artifact import Artifact
    await context.publish_output_artifacts([
        Artifact(kind="json", value=result, media_type="application/json")
    ])

## API Usage

### Create a Thread (Execute Task)

```bash
curl -X POST http://localhost:3000/threads \
  -H "X-API-Key: your-api-key" \
  -H "X-User-Id: user123" \
  -H "X-App-Id: app456" \
  -H "Content-Type: application/json" \
  -d '{
    "mode": "sync",
    "inputs": [{"kind": "json", "value": {"data": "test"}}]
  }'

In multi-task mode, add ?task_id=my-task&version=1.0.0 query parameters.

List Threads

curl http://localhost:3000/threads \
  -H "X-API-Key: your-api-key" \
  -H "X-User-Id: user123" \
  -H "X-App-Id: app456"

Health Check

curl http://localhost:3000/health

Task Package Format

A task package is a zip file containing:

my-task-1.0.0.zip/
  task_metadata.json    # Task metadata
  task.py              # Task implementation
  pyproject.toml       # Dependencies

Example task_metadata.json:

{
  "name": "my-task",
  "version": "1.0.0",
  "description": "My task description",
  "entry_point": "task:my_task_function",
  "input_schemas": [
    {"kind": "json", "media_type": "application/json", "required": true}
  ],
  "output_schemas": [
    {"kind": "json", "media_type": "application/json"}
  ]
}

Documentation

  • API Documentation: Start the server and visit /docs for interactive Swagger UI
  • User Guide: See docs/user/ for getting started guides
  • Architecture: See docs/architecture/ for system design documentation
  • Feature Documentation: See docs/features/ for detailed feature documentation

Authentication

The framework uses API key authentication via the X-API-Key header:

  • Regular API Keys: Require user_id and app_id metadata for access control
  • Admin API Keys: Full access to all endpoints including /admin/* routes

Public endpoints (no authentication required):

  • GET /health - Health check
  • GET /metrics - Prometheus metrics
  • GET /task/metadata - Task metadata discovery

Requirements

  • Python 3.13+
  • FastAPI
  • Pydantic 2.x
  • uvicorn

License

MIT License - see LICENSE file for details.

Contributing

Contributions are welcome! Please see the development documentation in docs/developer/ for setup instructions.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

task_framework_py-0.0.7b0.tar.gz (333.1 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

task_framework_py-0.0.7b0-py3-none-any.whl (440.5 kB view details)

Uploaded Python 3

File details

Details for the file task_framework_py-0.0.7b0.tar.gz.

File metadata

  • Download URL: task_framework_py-0.0.7b0.tar.gz
  • Upload date:
  • Size: 333.1 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.13.3

File hashes

Hashes for task_framework_py-0.0.7b0.tar.gz
Algorithm Hash digest
SHA256 1125c9b08955b065a441ae8a95c2cb98ccc52657977135d5270756c8fa60e5b5
MD5 bca72da280cbaa37f082bea788409446
BLAKE2b-256 8362d73c2957cf6d975beff1555dfb73701a588dbb957988989dc38a1826f292

See more details on using hashes here.

File details

Details for the file task_framework_py-0.0.7b0-py3-none-any.whl.

File metadata

File hashes

Hashes for task_framework_py-0.0.7b0-py3-none-any.whl
Algorithm Hash digest
SHA256 ae3f0f3c0ca03d58c889b349a750e3754372534a08f2e3111f351d19596fa81a
MD5 840d6833030d72a3be195254f2e4fb31
BLAKE2b-256 e1c090e7a651b490e722cdb030a3ca109f6eaa9613f2f8caa661c8613ce56d69

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page