# Formula 1 Data Scraper (`crawlergang/openf1-scraper`) Actor

Extract Formula 1 race calendar, driver roster, race results, championship standings, and qualifying data via the free Jolpica F1 API (Ergast-compatible, no auth required).

- **URL**: https://apify.com/crawlergang/openf1-scraper.md
- **Developed by:** [Crawler Gang](https://apify.com/crawlergang) (community)
- **Categories:** Developer tools, Integrations
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 11 bookmarks
- **User rating**: 5.00 out of 5 stars

## Pricing

from $3.00 / 1,000 results

This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage.
Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have.

Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Actors are written with capital "A".

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
The best way to integrate Actors is as follows.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).

# README

## OpenF1 Formula 1 Data Scraper

Extract Formula 1 race data from the free [OpenF1 API](https://openf1.org/) — sessions, drivers, Grand Prix meetings, race finishing positions, and weather conditions.

### What Does This Actor Do?

OpenF1 Scraper provides access to official F1 telemetry and timing data across 5 modes:

- **Sessions** — all sessions (races, qualifying, practice) with circuit, country, and timing data
- **Drivers** — driver roster for any session with team, headshot, and nationality info
- **Meetings** — Grand Prix event information with circuit and country details
- **Positions** — final race finishing positions per driver
- **Weather** — track weather conditions throughout a session (temperature, humidity, wind)

### Input Parameters

| Parameter | Type | Description | Default |
|-----------|------|-------------|---------|
| `mode` | String | Data type to fetch | `sessions` |
| `year` | Integer | F1 season year (2023–2025) | `2024` |
| `sessionType` | String | Filter sessions by type | `Race` |
| `sessionKey` | Integer | Session key for drivers/positions/weather | `9472` |
| `maxItems` | Integer | Max records (1–500) | `50` |

#### Session Types

| Value | Description |
|-------|-------------|
| `Race` | Grand Prix race |
| `Qualifying` | Qualifying session |
| `Sprint` | Sprint race |
| `Practice 1` | First practice session |
| `Practice 2` | Second practice session |
| `Practice 3` | Third practice session |

### Output Format

#### Sessions

```json
{
  "sessionKey": 9472,
  "sessionName": "Race",
  "sessionType": "Race",
  "year": 2024,
  "meetingKey": 1229,
  "circuitKey": 63,
  "circuitShortName": "Sakhir",
  "countryCode": "BRN",
  "countryName": "Bahrain",
  "location": "Sakhir",
  "dateStart": "2024-03-02T15:00:00+00:00",
  "dateEnd": "2024-03-02T17:00:00+00:00",
  "mode": "sessions",
  "scrapedAt": "2024-01-15T10:30:00+00:00"
}
```

#### Drivers

```json
{
  "driverNumber": 1,
  "fullName": "Max VERSTAPPEN",
  "nameAcronym": "VER",
  "teamName": "Red Bull Racing",
  "teamColour": "3671C6",
  "countryCode": "NED",
  "headshotUrl": "https://www.formula1.com/content/dam/fom-website/drivers/M/MAXVER01_Max_Verstappen/maxver01.png",
  "sessionKey": 9472,
  "mode": "drivers",
  "scrapedAt": "2024-01-15T10:30:00+00:00"
}
```

#### Race Positions

```json
{
  "driverNumber": 1,
  "position": 1,
  "sessionKey": 9472,
  "meetingKey": 1229,
  "date": "2024-03-02T16:59:38+00:00",
  "mode": "positions",
  "scrapedAt": "2024-01-15T10:30:00+00:00"
}
```

#### Weather

```json
{
  "sessionKey": 9472,
  "date": "2024-03-02T14:03:56.523000+00:00",
  "airTemperature": 18.9,
  "trackTemperature": 26.5,
  "humidity": 46.0,
  "windSpeed": 0.9,
  "windDirection": 162,
  "pressure": 1017.1,
  "rainfall": 0.0,
  "mode": "weather",
  "scrapedAt": "2024-01-15T10:30:00+00:00"
}
```

### Finding Session Keys

To find the `sessionKey` for a specific race:

1. Run with `mode=sessions` and your desired `year` and `sessionType=Race`
2. Find the session in the output for your target Grand Prix
3. Use its `sessionKey` for `drivers`, `positions`, or `weather` modes

### FAQ

**Q: Is an API key required?**
A: No. OpenF1 is completely free and open — no registration or API key needed.

**Q: What years of data are available?**
A: The OpenF1 API covers 2023 onwards (when live telemetry data collection began).

**Q: How accurate are the positions?**
A: The `positions` mode returns the final position per driver at the end of the session based on the last recorded position entry.

**Q: What is the `sessionKey` for qualifying vs race?**
A: Each session (practice, qualifying, sprint, race) within a Grand Prix has its own unique `sessionKey`. Use `mode=sessions` to discover all keys for a given year.

**Q: How many weather readings are there per session?**
A: Typically 100–300 readings per race session, captured approximately every 30 seconds.

# Actor input Schema

## `mode` (type: `string`):

What type of F1 data to fetch.

## `season` (type: `string`):

F1 season year (e.g. 2025, 2024, 2023) or 'current' for the live season.

## `round` (type: `string`):

Race round number within the season for results/qualifying modes. Use 'last' for the most recent race.

## `maxItems` (type: `integer`):

Maximum number of records to return (1–500).

## Actor input object example

```json
{
  "mode": "races",
  "season": "2025",
  "round": "last",
  "maxItems": 50
}
```

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "mode": "races",
    "season": "2025",
    "round": "last",
    "maxItems": 50
};

// Run the Actor and wait for it to finish
const run = await client.actor("crawlergang/openf1-scraper").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {
    "mode": "races",
    "season": "2025",
    "round": "last",
    "maxItems": 50,
}

# Run the Actor and wait for it to finish
run = client.actor("crawlergang/openf1-scraper").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"])
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "mode": "races",
  "season": "2025",
  "round": "last",
  "maxItems": 50
}' |
apify call crawlergang/openf1-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "command": "npx",
            "args": [
                "mcp-remote",
                "https://mcp.apify.com/?tools=crawlergang/openf1-scraper",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

```

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/2PVcXkkxV2LbKT2nH/builds/riidTBtflKCqmPrJL/openapi.json