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Python client library for RaceResult Web API

Project description

RaceResult Python Web API Library

A Python client library for the RaceResult Web API that mirrors the functionality of the Go library.

Features

  • Pythonic API design with dataclasses
  • Session management with automatic cleanup
  • Event and participant operations
  • Raw timing data retrieval
  • Easy-to-use endpoint classes
  • Type hints for better IDE support

Installation

pip install -e .
# or for development:
pip install -r requirements.txt

Quick Start

Environment Setup

Create a .env file with your credentials:

RACERESULT_API_KEY=your_api_key_here
RACERESULT_USERNAME=your_username
RACERESULT_PASSWORD=your_password

Basic Usage

from rr_webapi import API
import os

# Create API client
api = API("events.raceresult.com", use_https=True)

# Login with API key
api.public().login(api_key=os.getenv("RACERESULT_API_KEY"))

try:
    # Get your events
    events = api.public().event_list()
    print(f"You have {len(events)} events")
    
    # Open an event
    if events:
        event_api = api.event_api(events[0].id)
        
        # Get participants
        participants = event_api.data.list([
            "ID", "BIB", "FIRSTNAME", "LASTNAME", "CONTEST.NAME"
        ])
        print(f"Event has {len(participants)} participants")
        
        # Get raw data for a participant
        if participants:
            raw_data = event_api.rawdata.get_by_pid(participants[0][0])  # ID is first field
            print(f"Participant has {len(raw_data)} raw data entries")

finally:
    # Always logout
    api.public().logout()

API Structure

Main Components

  • API: Main client with session management
  • Public: Authentication and account operations
  • EventAPI: Event-specific operations

Event API Endpoints

  • data: Participant data retrieval and filtering
  • participants: Participant management (CRUD)
  • contests: Contest/category management
  • rawdata: Raw timing data access

Authentication

API Key Authentication

api.public().login(api_key="your_api_key")

Username/Password Authentication

api.public().login(username="username", password="password")

Bulk Operations

Adding Multiple Participants at Once

# Prepare multiple participants
participants = []
for i in range(1001, 1006):
    participant = {
        "Bib": i,
        "FirstName": "Test",
        "LastName": str(i),
        "Sex": "m",
        "DateOfBirth": "1990-01-01",
        "Contest": contest_id
    }
    participants.append(participant)

# Save all participants in bulk
event_api.participants().save(participants, no_history=False)

Manual Raw Data Entry

# Add a manual timing entry
event_api.rawdata().add_manual(
    timing_point="Finish",
    identifier_name="bib",  # or "pid"  
    identifier_value=1001,
    time=3600.5,  # Time in decimal seconds
    add_t0=False
)

Data Models

The library uses dataclasses for structured data:

@dataclass
class EventListItem:
    id: str
    name: str
    date: str
    participants: int
    # ... other fields

Examples

See the ../../examples/python/ directory for complete examples:

  • basic_usage.py: Authentication and basic operations
  • participant_and_rawdata.py: Advanced participant and timing data operations
  • bulk_participant_save.py: Bulk saving multiple participants at once

Development

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

# Install dependencies
pip install -r requirements.txt

# Run tests
python -m pytest tests/

Requirements

  • Python 3.7+
  • requests
  • python-dateutil
  • python-dotenv

Package Structure

rr_webapi/
├── __init__.py          # Main API class
├── api.py              # Core HTTP client
├── public.py           # Public API endpoints
├── eventapi.py         # Event API wrapper
├── general.py          # General utilities
└── endpoints/          # Endpoint implementations
    ├── data.py
    ├── contests.py
    ├── participants.py
    └── rawdata.py

License

This library follows the same license as the original Go library.

Contributing

  1. Follow the existing code patterns
  2. Add tests for new functionality
  3. Update documentation
  4. Ensure examples work with changes

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