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-0.0.1b0.tar.gz (311.2 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-0.0.1b0-py3-none-any.whl (410.9 kB view details)

Uploaded Python 3

File details

Details for the file task_framework_py-0.0.1b0.tar.gz.

File metadata

  • Download URL: task_framework_py-0.0.1b0.tar.gz
  • Upload date:
  • Size: 311.2 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-0.0.1b0.tar.gz
Algorithm Hash digest
SHA256 ddd1d415cec0db1ae9c7de03cdc75fb32fd1390fc48b582538b698f15b1c5c55
MD5 cb1fde20c6a3226f344155d1ebd3d867
BLAKE2b-256 785fd43250b971e68832a768132e857ba02a0e78ffedf2d300905ba1108384c6

See more details on using hashes here.

File details

Details for the file task_framework_py-0.0.1b0-py3-none-any.whl.

File metadata

File hashes

Hashes for task_framework_py-0.0.1b0-py3-none-any.whl
Algorithm Hash digest
SHA256 9e563fd25ca242551277d7b7319f5750783d8238e93e65d873bc56e9b0708efe
MD5 b1dfb1052f6ff92e4de10b14f53ab19c
BLAKE2b-256 b6be287139c4ee633f48c30d775f8aea8508d831eb6c0d8b039ef9b7d0696d6c

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