NAV
shell python r javascript

Introduction

OpenF1 is a free and open-source API that provides real-time and historical Formula 1 data.

The API offers a wealth of information, including lap timings, car telemetry, radio communications, and more. Whether you're looking to create interactive dashboards, dive deep into race analysis, or even develop connected objects that light up every time your favorite driver takes the lead, OpenF1 makes it all possible.

Data can be accessed in either JSON or CSV formats, making it user-friendly for both developers and non-developers alike. For a quick start, you can access the API through your web browser. A sample URL is provided for each method for easy reference.

API methods

Car data

Some data about each car, at a sample rate of about 3.7 Hz.

curl "https://api.openf1.org/v1/car_data?driver_number=55&session_key=9159&speed>=315"

from urllib.request import urlopen
import json

response = urlopen('https://api.openf1.org/v1/car_data?driver_number=55&session_key=9159&speed>=315')
data = json.loads(response.read().decode('utf-8'))
print(data)

# If you want, you can import the results in a DataFrame (you need to install the `pandas` package first)
# import pandas as pd
# df = pd.DataFrame(data)

# If needed, install libraries
# install.packages('httr')
# install.packages('jsonlite')

library(httr)
library(jsonlite)

response <- GET('https://api.openf1.org/v1/car_data?driver_number=55&session_key=9159&speed>=315')
parsed_data <- fromJSON(content(response, 'text'))
print(parsed_data)

# If you want, you can import the results in a DataFrame
# df <- do.call(rbind, lapply(parsed_data, data.frame, stringsAsFactors = FALSE))
# df <- as.data.frame(t(as.matrix(df)))

fetch('https://api.openf1.org/v1/car_data?driver_number=55&session_key=9159&speed>=315')
  .then(response => response.json())
  .then(jsonContent => console.log(jsonContent));

Output:

[
  {
    "brake": 0,
    "date": "2023-09-15T13:08:19.923000+00:00",
    "driver_number": 55,
    "drs": 12,
    "meeting_key": 1219,
    "n_gear": 8,
    "rpm": 11141,
    "session_key": 9159,
    "speed": 315,
    "throttle": 99
  },
  {
    "brake": 100,
    "date": "2023-09-15T13:35:41.808000+00:00",
    "driver_number": 55,
    "drs": 8,
    "meeting_key": 1219,
    "n_gear": 8,
    "rpm": 11023,
    "session_key": 9159,
    "speed": 315,
    "throttle": 57
  }
]

HTTP Request

GET https://api.openf1.org/v1/car_data

Sample URL

https://api.openf1.org/v1/car_data?driver_number=55&session_key=9159&speed>=315

Attributes

Name Description
brake Whether the brake pedal is pressed (100) or not (0).
date The UTC date and time, in ISO 8601 format.
driver_number The unique number assigned to an F1 driver (cf. Wikipedia).
drs The Drag Reduction System (DRS) status (see mapping table below).
meeting_key The unique identifier for the meeting. Use latest to identify the latest or current meeting.
n_gear Current gear selection, ranging from 1 to 8. 0 indicates neutral or no gear engaged.
rpm Revolutions per minute of the engine.
session_key The unique identifier for the session. Use latest to identify the latest or current session.
speed Velocity of the car in km/h.
throttle Percentage of maximum engine power being used.



Below is a table that correlates DRS values to its supposed interpretation (from FastF1).

DRS value Interpretation
0 DRS off
1 DRS off
2 ?
3 ?
8 Detected, eligible once in activation zone
9 ?
10 DRS on
12 DRS on
14 DRS on

Drivers

Provides information about drivers for each session.

curl "https://api.openf1.org/v1/drivers?driver_number=1&session_key=9158"

from urllib.request import urlopen
import json

response = urlopen('https://api.openf1.org/v1/drivers?driver_number=1&session_key=9158')
data = json.loads(response.read().decode('utf-8'))
print(data)

# If you want, you can import the results in a DataFrame (you need to install the `pandas` package first)
# import pandas as pd
# df = pd.DataFrame(data)

# If needed, install libraries
# install.packages('httr')
# install.packages('jsonlite')

library(httr)
library(jsonlite)

response <- GET('https://api.openf1.org/v1/drivers?driver_number=1&session_key=9158')
parsed_data <- fromJSON(content(response, 'text'))
print(parsed_data)

# If you want, you can import the results in a DataFrame
# df <- do.call(rbind, lapply(parsed_data, data.frame, stringsAsFactors = FALSE))
# df <- as.data.frame(t(as.matrix(df)))

fetch('https://api.openf1.org/v1/drivers?driver_number=1&session_key=9158')
  .then(response => response.json())
  .then(jsonContent => console.log(jsonContent));

Output:

[
  {
    "broadcast_name": "M VERSTAPPEN",
    "country_code": "NED",
    "driver_number": 1,
    "first_name": "Max",
    "full_name": "Max VERSTAPPEN",
    "headshot_url": "https://www.formula1.com/content/dam/fom-website/drivers/M/MAXVER01_Max_Verstappen/maxver01.png.transform/1col/image.png",
    "last_name": "Verstappen",
    "meeting_key": 1219,
    "name_acronym": "VER",
    "session_key": 9158,
    "team_colour": "3671C6",
    "team_name": "Red Bull Racing"
  }
]

HTTP Request

GET https://api.openf1.org/v1/drivers

Sample URL

https://api.openf1.org/v1/drivers?driver_number=1&session_key=9158

Attributes

Name Description
broadcast_name The driver's name, as displayed on TV.
country_code A code that uniquely identifies the country.
driver_number The unique number assigned to an F1 driver (cf. Wikipedia).
first_name The driver's first name.
full_name The driver's full name.
headshot_url URL of the driver's face photo.
last_name The driver's last name.
meeting_key The unique identifier for the meeting. Use latest to identify the latest or current meeting.
name_acronym Three-letter acronym of the driver's name.
session_key The unique identifier for the session. Use latest to identify the latest or current session.
team_colour The hexadecimal color value (RRGGBB) of the driver's team.
team_name Name of the driver's team.

Intervals

Fetches real-time interval data between drivers and their gap to the race leader.
Available during races only, with updates approximately every 4 seconds.

curl "https://api.openf1.org/v1/intervals?session_key=9165&interval<0.005"

from urllib.request import urlopen
import json

response = urlopen('https://api.openf1.org/v1/intervals?session_key=9165&interval<0.005')
data = json.loads(response.read().decode('utf-8'))
print(data)

# If you want, you can import the results in a DataFrame (you need to install the `pandas` package first)
# import pandas as pd
# df = pd.DataFrame(data)

# If needed, install libraries
# install.packages('httr')
# install.packages('jsonlite')

library(httr)
library(jsonlite)

response <- GET('https://api.openf1.org/v1/intervals?session_key=9165&interval<0.005')
parsed_data <- fromJSON(content(response, 'text'))
print(parsed_data)

# If you want, you can import the results in a DataFrame
# df <- do.call(rbind, lapply(parsed_data, data.frame, stringsAsFactors = FALSE))
# df <- as.data.frame(t(as.matrix(df)))

fetch('https://api.openf1.org/v1/intervals?session_key=9165&interval<0.005')
  .then(response => response.json())
  .then(jsonContent => console.log(jsonContent));

Output:

[
  {
    "date": "2023-09-17T13:31:02.395000+00:00",
    "driver_number": 1,
    "gap_to_leader": 41.019,
    "interval": 0.003,
    "meeting_key": 1219,
    "session_key": 9165
  }
]

HTTP Request

GET https://api.openf1.org/v1/intervals

Sample URL

https://api.openf1.org/v1/intervals?session_key=9165&interval<0.005

Attributes

Name Description
date The UTC date and time, in ISO 8601 format.
driver_number The unique number assigned to an F1 driver (cf. Wikipedia).
gap_to_leader The time gap to the race leader in seconds, +1 LAP if lapped, or null for the race leader.
interval The time gap to the car ahead in seconds, +1 LAP if lapped, or null for the race leader.
meeting_key The unique identifier for the meeting. Use latest to identify the latest or current meeting.
session_key The unique identifier for the session. Use latest to identify the latest or current session.

Laps

Provides detailed information about individual laps.

curl "https://api.openf1.org/v1/laps?session_key=9161&driver_number=63&lap_number=8"

from urllib.request import urlopen
import json

response = urlopen('https://api.openf1.org/v1/laps?session_key=9161&driver_number=63&lap_number=8')
data = json.loads(response.read().decode('utf-8'))
print(data)

# If you want, you can import the results in a DataFrame (you need to install the `pandas` package first)
# import pandas as pd
# df = pd.DataFrame(data)

# If needed, install libraries
# install.packages('httr')
# install.packages('jsonlite')

library(httr)
library(jsonlite)

response <- GET('https://api.openf1.org/v1/laps?session_key=9161&driver_number=63&lap_number=8')
parsed_data <- fromJSON(content(response, 'text'))
print(parsed_data)

# If you want, you can import the results in a DataFrame
# df <- do.call(rbind, lapply(parsed_data, data.frame, stringsAsFactors = FALSE))
# df <- as.data.frame(t(as.matrix(df)))

fetch('https://api.openf1.org/v1/laps?session_key=9161&driver_number=63&lap_number=8')
  .then(response => response.json())
  .then(jsonContent => console.log(jsonContent));

Output:

[
  {
    "date_start": "2023-09-16T13:59:07.606000+00:00",
    "driver_number": 63,
    "duration_sector_1": 26.966,
    "duration_sector_2": 38.657,
    "duration_sector_3": 26.12,
    "i1_speed": 307,
    "i2_speed": 277,
    "is_pit_out_lap": false,
    "lap_duration": 91.743,
    "lap_number": 8,
    "meeting_key": 1219,
    "segments_sector_1": [
      2049,
      2049,
      2049,
      2051,
      2049,
      2051,
      2049,
      2049
    ],
    "segments_sector_2": [
      2049,
      2049,
      2049,
      2049,
      2049,
      2049,
      2049,
      2049
    ],
    "segments_sector_3": [
      2048,
      2048,
      2048,
      2048,
      2048,
      2064,
      2064,
      2064
    ],
    "session_key": 9161,
    "st_speed": 298
  }
]

HTTP Request

GET https://api.openf1.org/v1/laps

Sample URL

https://api.openf1.org/v1/laps?session_key=9161&driver_number=63&lap_number=8

Attributes

Name Description
date_start The UTC starting date and time, in ISO 8601 format.
driver_number The unique number assigned to an F1 driver (cf. Wikipedia).
duration_sector_1 The time taken, in seconds, to complete the first sector of the lap.
duration_sector_2 The time taken, in seconds, to complete the second sector of the lap.
duration_sector_3 The time taken, in seconds, to complete the third sector of the lap.
i1_speed The speed of the car, in km/h, at the first intermediate point on the track.
i2_speed The speed of the car, in km/h, at the second intermediate point on the track.
is_pit_out_lap A boolean value indicating whether the lap is an "out lap" from the pit (true if it is, false otherwise).
lap_duration The total time taken, in seconds, to complete the entire lap.
lap_number The sequential number of the lap within the session (starts at 1).
meeting_key The unique identifier for the meeting. Use latest to identify the latest or current meeting.
segments_sector_1 A list of values representing the "mini-sectors" within the first sector (see mapping table below).
segments_sector_2 A list of values representing the "mini-sectors" within the second sector (see mapping table below).
segments_sector_3 A list of values representing the "mini-sectors" within the third sector (see mapping table below).
session_key The unique identifier for the session. Use latest to identify the latest or current session.
st_speed The speed of the car, in km/h, at the speed trap, which is a specific point on the track where the highest speeds are usually recorded.



Below is a table that correlates segment values to their meaning.

Value Color
0 not available
2048 yellow sector
2049 green sector
2050 ?
2051 purple sector
2052 ?
2064 pitlane
2068 ?

Segments are not available during races. Also, The segment values may not always align perfectly with the colors shown on TV, for unknown reasons.

Location

The approximate location of the cars on the circuit, at a sample rate of about 3.7 Hz.
Useful for gauging their progress along the track, but lacks details about lateral placement — i.e. whether the car is on the left or right side of the track. The origin point (0, 0, 0) appears to be arbitrary and not tied to any specific location on the track.

curl "https://api.openf1.org/v1/location?session_key=9161&driver_number=81&date>2023-09-16T13:03:35.200&date<2023-09-16T13:03:35.800"

from urllib.request import urlopen
import json

response = urlopen('https://api.openf1.org/v1/location?session_key=9161&driver_number=81&date>2023-09-16T13:03:35.200&date<2023-09-16T13:03:35.800')
data = json.loads(response.read().decode('utf-8'))
print(data)

# If you want, you can import the results in a DataFrame (you need to install the `pandas` package first)
# import pandas as pd
# df = pd.DataFrame(data)

# If needed, install libraries
# install.packages('httr')
# install.packages('jsonlite')

library(httr)
library(jsonlite)

response <- GET('https://api.openf1.org/v1/location?session_key=9161&driver_number=81&date>2023-09-16T13:03:35.200&date<2023-09-16T13:03:35.800')
parsed_data <- fromJSON(content(response, 'text'))
print(parsed_data)

# If you want, you can import the results in a DataFrame
# df <- do.call(rbind, lapply(parsed_data, data.frame, stringsAsFactors = FALSE))
# df <- as.data.frame(t(as.matrix(df)))

fetch('https://api.openf1.org/v1/location?session_key=9161&driver_number=81&date>2023-09-16T13:03:35.200&date<2023-09-16T13:03:35.800')
  .then(response => response.json())
  .then(jsonContent => console.log(jsonContent));

Output:

[
  {
    "date": "2023-09-16T13:03:35.292000+00:00",
    "driver_number": 81,
    "meeting_key": 1219,
    "session_key": 9161,
    "x": 567,
    "y": 3195,
    "z": 187
  },
  {
    "date": "2023-09-16T13:03:35.752000+00:00",
    "driver_number": 81,
    "meeting_key": 1219,
    "session_key": 9161,
    "x": 489,
    "y": 3403,
    "z": 186
  }
]

HTTP Request

GET https://api.openf1.org/v1/location

Sample URL

https://api.openf1.org/v1/location?session_key=9161&driver_number=81&date>2023-09-16T13:03:35.200&date<2023-09-16T13:03:35.800

Attributes

Name Description
date The UTC date and time, in ISO 8601 format.
driver_number The unique number assigned to an F1 driver (cf. Wikipedia).
meeting_key The unique identifier for the meeting. Use latest to identify the latest or current meeting.
session_key The unique identifier for the session. Use latest to identify the latest or current session.
x The 'x' value in a 3D Cartesian coordinate system representing the current approximate location of the car on the track.
y The 'y' value in a 3D Cartesian coordinate system representing the current approximate location of the car on the track.
z The 'z' value in a 3D Cartesian coordinate system representing the current approximate location of the car on the track.

Meetings

Provides information about meetings.
A meeting refers to a Grand Prix or testing weekend and usually includes multiple sessions (practice, qualifying, race, ...).

curl "https://api.openf1.org/v1/meetings?year=2023&country_name=Singapore"

from urllib.request import urlopen
import json

response = urlopen('https://api.openf1.org/v1/meetings?year=2023&country_name=Singapore')
data = json.loads(response.read().decode('utf-8'))
print(data)

# If you want, you can import the results in a DataFrame (you need to install the `pandas` package first)
# import pandas as pd
# df = pd.DataFrame(data)

# If needed, install libraries
# install.packages('httr')
# install.packages('jsonlite')

library(httr)
library(jsonlite)

response <- GET('https://api.openf1.org/v1/meetings?year=2023&country_name=Singapore')
parsed_data <- fromJSON(content(response, 'text'))
print(parsed_data)

# If you want, you can import the results in a DataFrame
# df <- do.call(rbind, lapply(parsed_data, data.frame, stringsAsFactors = FALSE))
# df <- as.data.frame(t(as.matrix(df)))

fetch('https://api.openf1.org/v1/meetings?year=2023&country_name=Singapore')
  .then(response => response.json())
  .then(jsonContent => console.log(jsonContent));

Output:

[
  {
    "circuit_key": 61,
    "circuit_short_name": "Singapore",
    "country_code": "SGP",
    "country_key": 157,
    "country_name": "Singapore",
    "date_start": "2023-09-15T09:30:00+00:00",
    "gmt_offset": "08:00:00",
    "location": "Marina Bay",
    "meeting_key": 1219,
    "meeting_name": "Singapore Grand Prix",
    "meeting_official_name": "FORMULA 1 SINGAPORE AIRLINES SINGAPORE GRAND PRIX 2023",
    "year": 2023
  }
]

HTTP Request

GET https://api.openf1.org/v1/meetings

Sample URL

https://api.openf1.org/v1/meetings?year=2023&country_name=Singapore

Attributes

Name Description
circuit_key The unique identifier for the circuit where the event takes place.
circuit_short_name The short or common name of the circuit where the event takes place.
country_code A code that uniquely identifies the country.
country_key The unique identifier for the country where the event takes place.
country_name The full name of the country where the event takes place.
date_start The UTC starting date and time, in ISO 8601 format.
gmt_offset The difference in hours and minutes between local time at the location of the event and Greenwich Mean Time (GMT).
location The city or geographical location where the event takes place.
meeting_key The unique identifier for the meeting. Use latest to identify the latest or current meeting.
meeting_name The name of the meeting.
meeting_official_name The official name of the meeting.
year The year the event takes place.

Pit

Provides information about cars going through the pit lane.

curl "https://api.openf1.org/v1/pit?session_key=9158&pit_duration<31"

from urllib.request import urlopen
import json

response = urlopen('https://api.openf1.org/v1/pit?session_key=9158&pit_duration<31')
data = json.loads(response.read().decode('utf-8'))
print(data)

# If you want, you can import the results in a DataFrame (you need to install the `pandas` package first)
# import pandas as pd
# df = pd.DataFrame(data)

# If needed, install libraries
# install.packages('httr')
# install.packages('jsonlite')

library(httr)
library(jsonlite)

response <- GET('https://api.openf1.org/v1/pit?session_key=9158&pit_duration<31')
parsed_data <- fromJSON(content(response, 'text'))
print(parsed_data)

# If you want, you can import the results in a DataFrame
# df <- do.call(rbind, lapply(parsed_data, data.frame, stringsAsFactors = FALSE))
# df <- as.data.frame(t(as.matrix(df)))

fetch('https://api.openf1.org/v1/pit?session_key=9158&pit_duration<31')
  .then(response => response.json())
  .then(jsonContent => console.log(jsonContent));

Output:

[
  {
    "date": "2023-09-15T09:38:23.038000+00:00",
    "driver_number": 63,
    "lap_number": 5,
    "meeting_key": 1219,
    "pit_duration": 24.5,
    "session_key": 9158
  },
  {
    "date": "2023-09-15T10:05:01.229000+00:00",
    "driver_number": 81,
    "lap_number": 13,
    "meeting_key": 1219,
    "pit_duration": 30.8,
    "session_key": 9158
  }
]

HTTP Request

GET https://api.openf1.org/v1/pit

Sample URL

https://api.openf1.org/v1/pit?session_key=9158&pit_duration<31

Attributes

Name Description
date The UTC date and time, in ISO 8601 format.
driver_number The unique number assigned to an F1 driver (cf. Wikipedia).
lap_number The sequential number of the lap within the session (starts at 1).
meeting_key The unique identifier for the meeting. Use latest to identify the latest or current meeting.
pit_duration The time spent in the pit, from entering to leaving the pit lane, in seconds.
session_key The unique identifier for the session. Use latest to identify the latest or current session.

Position

Provides driver positions throughout a session, including initial placement and subsequent changes.

curl "https://api.openf1.org/v1/position?meeting_key=1217&driver_number=40&position<=3"

from urllib.request import urlopen
import json

response = urlopen('https://api.openf1.org/v1/position?meeting_key=1217&driver_number=40&position<=3')
data = json.loads(response.read().decode('utf-8'))
print(data)

# If you want, you can import the results in a DataFrame (you need to install the `pandas` package first)
# import pandas as pd
# df = pd.DataFrame(data)

# If needed, install libraries
# install.packages('httr')
# install.packages('jsonlite')

library(httr)
library(jsonlite)

response <- GET('https://api.openf1.org/v1/position?meeting_key=1217&driver_number=40&position<=3')
parsed_data <- fromJSON(content(response, 'text'))
print(parsed_data)

# If you want, you can import the results in a DataFrame
# df <- do.call(rbind, lapply(parsed_data, data.frame, stringsAsFactors = FALSE))
# df <- as.data.frame(t(as.matrix(df)))

fetch('https://api.openf1.org/v1/position?meeting_key=1217&driver_number=40&position<=3')
  .then(response => response.json())
  .then(jsonContent => console.log(jsonContent));

Output:

[
  {
    "date": "2023-08-26T09:30:47.199000+00:00",
    "driver_number": 40,
    "meeting_key": 1217,
    "position": 2,
    "session_key": 9144
  },
  {
    "date": "2023-08-26T09:35:51.477000+00:00",
    "driver_number": 40,
    "meeting_key": 1217,
    "position": 3,
    "session_key": 9144
  }
]

HTTP Request

GET https://api.openf1.org/v1/position

Sample URL

https://api.openf1.org/v1/position?meeting_key=1217&driver_number=40&position<=3

Attributes

Name Description
date The UTC date and time, in ISO 8601 format.
driver_number The unique number assigned to an F1 driver (cf. Wikipedia).
meeting_key The unique identifier for the meeting. Use latest to identify the latest or current meeting.
position Position of the driver (starts at 1).
session_key The unique identifier for the session. Use latest to identify the latest or current session.

Race control

Provides information about race control (racing incidents, flags, safety car, ...).

curl "https://api.openf1.org/v1/race_control?flag=BLACK AND WHITE&driver_number=1&date>=2023-01-01&date<2023-09-01"

from urllib.request import urlopen
import json

response = urlopen('https://api.openf1.org/v1/race_control?flag=BLACK AND WHITE&driver_number=1&date>=2023-01-01&date<2023-09-01')
data = json.loads(response.read().decode('utf-8'))
print(data)

# If you want, you can import the results in a DataFrame (you need to install the `pandas` package first)
# import pandas as pd
# df = pd.DataFrame(data)

# If needed, install libraries
# install.packages('httr')
# install.packages('jsonlite')

library(httr)
library(jsonlite)

response <- GET('https://api.openf1.org/v1/race_control?flag=BLACK AND WHITE&driver_number=1&date>=2023-01-01&date<2023-09-01')
parsed_data <- fromJSON(content(response, 'text'))
print(parsed_data)

# If you want, you can import the results in a DataFrame
# df <- do.call(rbind, lapply(parsed_data, data.frame, stringsAsFactors = FALSE))
# df <- as.data.frame(t(as.matrix(df)))

fetch('https://api.openf1.org/v1/race_control?flag=BLACK AND WHITE&driver_number=1&date>=2023-01-01&date<2023-09-01')
  .then(response => response.json())
  .then(jsonContent => console.log(jsonContent));

Output:

[
  {
    "category": "Flag",
    "date": "2023-06-04T14:21:01+00:00",
    "driver_number": 1,
    "flag": "BLACK AND WHITE",
    "lap_number": 59,
    "meeting_key": 1211,
    "message": "BLACK AND WHITE FLAG FOR CAR 1 (VER) - TRACK LIMITS",
    "scope": "Driver",
    "sector": null,
    "session_key": 9102
  }
]

HTTP Request

GET https://api.openf1.org/v1/race_control

Sample URL

https://api.openf1.org/v1/race_control?flag=BLACK AND WHITE&driver_number=1&date>=2023-01-01&date<2023-09-01

Attributes

Name Description
category The category of the event (CarEvent, Drs, Flag, SafetyCar, ...).
date The UTC date and time, in ISO 8601 format.
driver_number The unique number assigned to an F1 driver (cf. Wikipedia).
flag Type of flag displayed (GREEN, YELLOW, DOUBLE YELLOW, CHEQUERED, ...).
lap_number The sequential number of the lap within the session (starts at 1).
meeting_key The unique identifier for the meeting. Use latest to identify the latest or current meeting.
message Description of the event or action.
scope The scope of the event (Track, Driver, Sector, ...).
sector Segment ("mini-sector") of the track where the event occurred? (starts at 1).
session_key The unique identifier for the session. Use latest to identify the latest or current session.

Sessions

Provides information about sessions.
A session refers to a distinct period of track activity during a Grand Prix or testing weekend (practice, qualifying, sprint, race, ...).

curl "https://api.openf1.org/v1/sessions?country_name=Belgium&session_name=Sprint&year=2023"

from urllib.request import urlopen
import json

response = urlopen('https://api.openf1.org/v1/sessions?country_name=Belgium&session_name=Sprint&year=2023')
data = json.loads(response.read().decode('utf-8'))
print(data)

# If you want, you can import the results in a DataFrame (you need to install the `pandas` package first)
# import pandas as pd
# df = pd.DataFrame(data)

# If needed, install libraries
# install.packages('httr')
# install.packages('jsonlite')

library(httr)
library(jsonlite)

response <- GET('https://api.openf1.org/v1/sessions?country_name=Belgium&session_name=Sprint&year=2023')
parsed_data <- fromJSON(content(response, 'text'))
print(parsed_data)

# If you want, you can import the results in a DataFrame
# df <- do.call(rbind, lapply(parsed_data, data.frame, stringsAsFactors = FALSE))
# df <- as.data.frame(t(as.matrix(df)))

fetch('https://api.openf1.org/v1/sessions?country_name=Belgium&session_name=Sprint&year=2023')
  .then(response => response.json())
  .then(jsonContent => console.log(jsonContent));

Output:

[
  {
    "circuit_key": 7,
    "circuit_short_name": "Spa-Francorchamps",
    "country_code": "BEL",
    "country_key": 16,
    "country_name": "Belgium",
    "date_end": "2023-07-29T15:35:00+00:00",
    "date_start": "2023-07-29T15:05:00+00:00",
    "gmt_offset": "02:00:00",
    "location": "Spa-Francorchamps",
    "meeting_key": 1216,
    "session_key": 9140,
    "session_name": "Sprint",
    "session_type": "Race",
    "year": 2023
  }
]

HTTP Request

GET https://api.openf1.org/v1/sessions

Sample URL

https://api.openf1.org/v1/sessions?country_name=Belgium&session_name=Sprint&year=2023

Attributes

Name Description
circuit_key The unique identifier for the circuit where the event takes place.
circuit_short_name The short or common name of the circuit where the event takes place.
country_code A code that uniquely identifies the country.
country_key The unique identifier for the country where the event takes place.
country_name The full name of the country where the event takes place.
date_end The UTC ending date and time, in ISO 8601 format.
date_start The UTC starting date and time, in ISO 8601 format.
gmt_offset The difference in hours and minutes between local time at the location of the event and Greenwich Mean Time (GMT).
location The city or geographical location where the event takes place.
meeting_key The unique identifier for the meeting. Use latest to identify the latest or current meeting.
session_key The unique identifier for the session. Use latest to identify the latest or current session.
session_name The name of the session (Practice 1, Qualifying, Race, ...).
session_type The type of the session (Practice, Qualifying, Race, ...).
year The year the event takes place.

Stints

Provides information about individual stints.
A stint refers to a period of continuous driving by a driver during a session.

curl "https://api.openf1.org/v1/stints?session_key=9165&tyre_age_at_start>=3"

from urllib.request import urlopen
import json

response = urlopen('https://api.openf1.org/v1/stints?session_key=9165&tyre_age_at_start>=3')
data = json.loads(response.read().decode('utf-8'))
print(data)

# If you want, you can import the results in a DataFrame (you need to install the `pandas` package first)
# import pandas as pd
# df = pd.DataFrame(data)

# If needed, install libraries
# install.packages('httr')
# install.packages('jsonlite')

library(httr)
library(jsonlite)

response <- GET('https://api.openf1.org/v1/stints?session_key=9165&tyre_age_at_start>=3')
parsed_data <- fromJSON(content(response, 'text'))
print(parsed_data)

# If you want, you can import the results in a DataFrame
# df <- do.call(rbind, lapply(parsed_data, data.frame, stringsAsFactors = FALSE))
# df <- as.data.frame(t(as.matrix(df)))

fetch('https://api.openf1.org/v1/stints?session_key=9165&tyre_age_at_start>=3')
  .then(response => response.json())
  .then(jsonContent => console.log(jsonContent));

Output:

[
  {
    "compound": "SOFT",
    "driver_number": 16,
    "lap_end": 20,
    "lap_start": 1,
    "meeting_key": 1219,
    "session_key": 9165,
    "stint_number": 1,
    "tyre_age_at_start": 3
  },
  {
    "compound": "SOFT",
    "driver_number": 20,
    "lap_end": 62,
    "lap_start": 44,
    "meeting_key": 1219,
    "session_key": 9165,
    "stint_number": 3,
    "tyre_age_at_start": 3
  }
]

HTTP Request

GET https://api.openf1.org/v1/stints

Sample URL

https://api.openf1.org/v1/stints?session_key=9165&tyre_age_at_start>=3

Attributes

Name Description
compound The specific compound of tyre used during the stint (SOFT, MEDIUM, HARD, ...).
driver_number The unique number assigned to an F1 driver (cf. Wikipedia).
lap_end Number of the last completed lap in this stint.
lap_start Number of the initial lap in this stint (starts at 1).
meeting_key The unique identifier for the meeting. Use latest to identify the latest or current meeting.
session_key The unique identifier for the session. Use latest to identify the latest or current session.
stint_number The sequential number of the stint within the session (starts at 1).
tyre_age_at_start The age of the tyres at the start of the stint, in laps completed.

Team radio

Provides a collection of radio exchanges between Formula 1 drivers and their respective teams during sessions.
Please note that only a limited selection of communications are included, not the complete record of radio interactions.

curl "https://api.openf1.org/v1/team_radio?session_key=9158&driver_number=11"

from urllib.request import urlopen
import json

response = urlopen('https://api.openf1.org/v1/team_radio?session_key=9158&driver_number=11')
data = json.loads(response.read().decode('utf-8'))
print(data)

# If you want, you can import the results in a DataFrame (you need to install the `pandas` package first)
# import pandas as pd
# df = pd.DataFrame(data)

# If needed, install libraries
# install.packages('httr')
# install.packages('jsonlite')

library(httr)
library(jsonlite)

response <- GET('https://api.openf1.org/v1/team_radio?session_key=9158&driver_number=11')
parsed_data <- fromJSON(content(response, 'text'))
print(parsed_data)

# If you want, you can import the results in a DataFrame
# df <- do.call(rbind, lapply(parsed_data, data.frame, stringsAsFactors = FALSE))
# df <- as.data.frame(t(as.matrix(df)))

fetch('https://api.openf1.org/v1/team_radio?session_key=9158&driver_number=11')
  .then(response => response.json())
  .then(jsonContent => console.log(jsonContent));

Output:

[
  {
    "date": "2023-09-15T09:40:43.005000",
    "driver_number": 11,
    "meeting_key": 1219,
    "recording_url": "https://livetiming.formula1.com/static/2023/2023-09-17_Singapore_Grand_Prix/2023-09-15_Practice_1/TeamRadio/SERPER01_11_20230915_104008.mp3",
    "session_key": 9158
  },
  {
    "date": "2023-09-15T10:32:47.325000",
    "driver_number": 11,
    "meeting_key": 1219,
    "recording_url": "https://livetiming.formula1.com/static/2023/2023-09-17_Singapore_Grand_Prix/2023-09-15_Practice_1/TeamRadio/SERPER01_11_20230915_113201.mp3",
    "session_key": 9158
  }
]

HTTP Request

GET https://api.openf1.org/v1/team_radio

Sample URL

https://api.openf1.org/v1/team_radio?session_key=9158&driver_number=11

Attributes

Name Description
date The UTC date and time, in ISO 8601 format.
driver_number The unique number assigned to an F1 driver (cf. Wikipedia).
meeting_key The unique identifier for the meeting. Use latest to identify the latest or current meeting.
recording_url URL of the radio recording.
session_key The unique identifier for the session. Use latest to identify the latest or current session.

Weather

The weather over the track, updated every minute.

curl "https://api.openf1.org/v1/weather?meeting_key=1208&wind_direction>=130&track_temperature>=52"

from urllib.request import urlopen
import json

response = urlopen('https://api.openf1.org/v1/weather?meeting_key=1208&wind_direction>=130&track_temperature>=52')
data = json.loads(response.read().decode('utf-8'))
print(data)

# If you want, you can import the results in a DataFrame (you need to install the `pandas` package first)
# import pandas as pd
# df = pd.DataFrame(data)

# If needed, install libraries
# install.packages('httr')
# install.packages('jsonlite')

library(httr)
library(jsonlite)

response <- GET('https://api.openf1.org/v1/weather?meeting_key=1208&wind_direction>=130&track_temperature>=52')
parsed_data <- fromJSON(content(response, 'text'))
print(parsed_data)

# If you want, you can import the results in a DataFrame
# df <- do.call(rbind, lapply(parsed_data, data.frame, stringsAsFactors = FALSE))
# df <- as.data.frame(t(as.matrix(df)))

fetch('https://api.openf1.org/v1/weather?meeting_key=1208&wind_direction>=130&track_temperature>=52')
  .then(response => response.json())
  .then(jsonContent => console.log(jsonContent));

Output:

[
  {
    "air_temperature": 27.8,
    "date": "2023-05-07T18:42:25.233000+00:00",
    "humidity": 58,
    "meeting_key": 1208,
    "pressure": 1018.7,
    "rainfall": 0,
    "session_key": 9078,
    "track_temperature": 52.5,
    "wind_direction": 136,
    "wind_speed": 2.4
  }
]

HTTP Request

GET https://api.openf1.org/v1/weather

Sample URL

https://api.openf1.org/v1/weather?meeting_key=1208&wind_direction>=130&track_temperature>=52

Attributes

Name Description
air_temperature Air temperature (°C).
date The UTC date and time, in ISO 8601 format.
humidity Relative humidity (%).
meeting_key The unique identifier for the meeting. Use latest to identify the latest or current meeting.
pressure Air pressure (mbar).
rainfall Whether there is rainfall.
session_key The unique identifier for the session. Use latest to identify the latest or current session.
track_temperature Track temperature (°C).
wind_direction Wind direction (°), from 0° to 359°.
wind_speed Wind speed (m/s).

Data filtering

Refine your query by including parameters directly in the URL.
Results can be filtered by any attribute, except arrays.

Example
To fetch pit-out laps for driver number 55 (Carlos Sainz) that last at least 2 minutes, use: https://api.openf1.org/v1/laps?session_key=9222&driver_number=55&is_pit_out_lap=true&lap_duration>=120

Time-Based Filtering

You can narrow down your results using time ranges.

Example
To get all sessions in September 2023, use: https://api.openf1.org/v1/sessions?date_start>=2023-09-01&date_end<=2023-09-30

The API supports a wide range of date formats (those compatible with Python's dateutil.parser.parse method). Examples include:

CSV Format

To receive your query results in CSV format instead of the default JSON, simply append the query parameter csv=true to your URL. This feature is particularly handy to import the data into spreadsheet software like Microsoft Excel.

Example
To get all sessions for the year 2023 in CSV format, use the following URL: https://api.openf1.org/v1/sessions?year=2023&csv=true

System architecture

Our architecture is serverless, optimized for resilience, cost-efficiency and scalability.

architecture schema

Ingestor

The data ingestor runs every 5 minutes to check for new real-time data. During live sessions, at least two instances are active at any time to ensure reliable data recording. The ingestor also performs basic data normalization for efficient database indexing.

Database

We use a MongoDB database with indexes for each collection, enabling faster query responses.

Query API

The Query API serves as the intermediary between the user and the database. It processes user queries, fetches the relevant data from the database, and returns it in the requested format.

FAQ

Can I access past data during an ongoing session?

Yes, real-time storage allows for instant access to past and current session data.

What's the delay between live events and API updates?

The API typically updates about 3 seconds after a live event. However, this time could be extended due to factors like serverless cold starts, which occur when the service is scaling up.
As a point of reference, F1 TV typically has a 6-second delay.

Is there a query timeout?

Queries are limited to a 1-minute timeout. If your request takes too long, consider breaking it down into smaller queries and then combining the results.

Community and Support

For community-driven questions or feedback, we encourage you to participate in our Github Discussions. If you encounter any bugs or issues, please report them by creating a new issue on our Github repository. We're always open to contributions that enhance the project!

For specialized inquiries, feel free to reach out to me directly. However, for general support questions, please use the Github Discussions platform to ensure that the entire community can benefit from the answers.

Additionally, I offer freelance data science and data engineering services. Whether your project is in the realm of motorsports or spans other domains, you can count on me for high-quality, efficient coding solutions. If you're interested in collaborating, please contact me here.

Roadmap

We welcome your ideas and suggestions for OpenF1's future. Please share them on our Github Discussions page.

Usage Guidelines

The OpenF1 API is an open-source service designed to be easily accessible, requiring no authentication and imposing no rate limits. We kindly ask that you use the service responsibly to conserve computational resources. If you find the API useful, please consider donating to support the long-term sustainability of the project.

The creators of OpenF1 disclaim any liability for losses or damages incurred through the use of this API. We cannot guarantee the API's continuous availability or the accuracy of its data.

Acknowledgments

Special thanks to Philipp Schaefer (theOehrly) for his contributions to the FastF1 Python package, which has greatly inspired OpenF1. The SignalR data recorder used in OpenF1 is also sourced from the FastF1 package.

shell python r javascript