slack-models 1.0.0

Pydantic Models for working with the Slack API

slack-models

Comprehensive Pydantic models for working with the Slack API

slack-models provides type-safe, validated data structures for Slack API integration, making it easier to build robust Slack applications with proper error handling and IDE support.

🚀 Features

• Complete Coverage: Models for all major Slack events, objects, and webhook payloads
• Type Safety: Full type annotations with Python 3.12+ modern type hints
• Validation: Automatic data validation using Pydantic 2.x
• IDE Support: Excellent autocomplete and type checking
• Event Parsing: Convenient utilities for parsing webhook payloads
• Standards Compliant: Strict adherence to official Slack API specifications

📦 Installation

pip install slack-models

Requirements:

• Python 3.12+
• pydantic >=2.11.3,<3

🔧 Quick Start

Basic Usage

from slack_models import parse_event, SlackEventCallback, MessageEvent

# Parse a webhook payload
webhook_data = {
    "type": "event_callback",
    "event": {
        "type": "message",
        "channel": "C1234567890",
        "user": "U1234567890",
        "text": "Hello, world!",
        "ts": "1234567890.123456"
    },
    "team_id": "T1234567890",
    "api_app_id": "A1234567890"
}

# Parse and validate
event = parse_event(webhook_data)
if isinstance(event, SlackEventCallback):
    if isinstance(event.event, MessageEvent):
        print(f"Message: {event.event.text}")
        print(f"Channel: {event.event.channel}")
        print(f"User: {event.event.user}")

Event Handling

from slack_models import (
    parse_event, SlackEventCallback, MessageEvent,
    ReactionAddedEvent, ChannelCreatedEvent
)

def handle_slack_event(payload: dict):
    """Handle incoming Slack events with type safety."""
    event = parse_event(payload)

    if isinstance(event, SlackEventCallback):
        if isinstance(event.event, MessageEvent):
            print(f"New message: {event.event.text}")
        elif isinstance(event.event, ReactionAddedEvent):
            print(f"Reaction added: {event.event.reaction}")
        elif isinstance(event.event, ChannelCreatedEvent):
            print(f"Channel created: {event.event.channel.name}")

Working with Models

from slack_models import User, Channel, MessageEvent

# Create and validate user data
user = User(
    id="U1234567890",
    name="john.doe",
    real_name="John Doe",
    profile={
        "email": "[e-mail]",
        "display_name": "John",
        "first_name": "John",
        "last_name": "Doe"
    }
)

# Access user information with full type safety
print(f"User: {user.name} ({user.real_name})")
print(f"Email: {user.profile.email}")

📚 Documentation

• Documentation: Comprehensive guides and API reference
• Quick Start: Get up and running quickly
• API Reference: Detailed model documentation
• Examples: Practical usage examples

🎯 Supported Events

slack-models supports all major Slack event types:

Message Events

• MessageEvent: Standard messages, bot messages, threaded messages
• AppMentionEvent: App mentions in channels
• MessageEdited: Message edit events

Reaction Events

• ReactionAddedEvent: Reaction additions
• ReactionRemovedEvent: Reaction removals

Channel Events

• ChannelCreatedEvent: New channel creation
• ChannelDeletedEvent: Channel deletion
• ChannelRenameEvent: Channel name changes

Team Events

• TeamJoinEvent: New team member joins

File Events

• FileCreatedEvent: File uploads
• FileDeletedEvent: File deletions

Webhook Types

• SlackEventCallback: Standard event callbacks
• SlackUrlVerification: URL verification challenges
• SlackAppRateLimited: Rate limiting notifications

Error Handling

from pydantic import ValidationError
from slack_models import parse_event

try:
    event = parse_event(webhook_data)
    # Process event
except ValidationError as e:
    print(f"Invalid payload: {e}")
    # Handle validation errors
except Exception as e:
    print(f"Processing error: {e}")
    # Handle other errors

🧪 Development

Setup

# Clone the repository
git clone https://github.com/gmr/slack-models.git
cd slack-models

# Create virtual environment
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

# Install development dependencies
pip install -e '.[dev]'

# Install pre-commit hooks
pre-commit install

Testing

# Run tests
pytest

# Run tests with coverage
pytest --cov=slack_models --cov-report=html

# Run linting
ruff check .

# Run type checking
mypy src/slack_models

Documentation

# Build documentation
mkdocs build

# Serve documentation locally
mkdocs serve

🤝 Contributing

Contributions are welcome! Please see our Contributing Guide for details.

Development Workflow

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Add tests for new functionality
5. Run the test suite and linting
6. Submit a pull request

📄 License

This project is licensed under the BSD-3-Clause License. See the LICENSE file for details.

🙏 Acknowledgments

• Built for Slack bot projects at AWeber
• Powered by Pydantic for data validation
• Inspired by the Slack API documentation

📞 Support

• Documentation: https://gmr.github.io/slack-models/
• Issues: https://github.com/gmr/slack-models/issues
• Source Code: https://github.com/gmr/slack-models

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Made with ❤️ by Gavin M. Roy at AWeber