Welcome to tif1
tif1 is a high-performance Python library designed for Formula 1 data analysis. It provides access to timing, telemetry, and weather data from the TracingInsights (2018-current).
Built as a faster alternative to fastf1, it maintains API compatibility while introducing massive performance improvements through asynchronous data loading, HTTP/2 multiplexing, and optimized data backends.
Why tif1?
Blazing Fast
4-5x faster data loading with parallel async requests and HTTP/2.
API Compatible
Same bindings as
fastf1, making migration a breeze.Flexible Backends
Choose between Pandas for compatibility or Polars for 2x faster processing.
Advanced Caching
Multi-layer caching using in-memory LRU and SQLite for persistent storage.
Key Features
- Fast: Direct CDN access via jsDelivr with SQLite caching
- Complete: Lap times, sectors, telemetry, tire compounds, weather, and more
- Historical: Data from 2018-current
- Reliable: Automatic retry logic with circuit breaker and CDN fallback
- Async: Parallel data fetching for better performance
- HTTP/2: Uses niquests for 20-30% faster network requests
- Flexible: Supports both pandas and polars backends
- Type-Safe: Comprehensive type hints for IDE support
- Jupyter-Ready: Rich HTML display in notebooks
Performance Comparison
| Operation | fastf1 | tif1 (Async) | Speedup |
|---|---|---|---|
| Load 20 Drivers Laps | ~12.0s | ~2.5s | 4.8x |
| Load 20 Drivers Telemetry | ~11.2s | ~0.4s | 28x |
| Hot Cache Load | ~1.0s | ~0.05s | 20x |
Core Architecture
tif1 uses a modern networking stack and a multi-tiered caching strategy to ensure you spend less time waiting for data and more time analyzing it.