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FastF1 organizes Formula 1 data around the concepts of Events (race weekends) and Sessions (individual practice, qualifying, or race sessions). This page covers how to access and work with these fundamental objects.

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Overview

The typical workflow for loading F1 data starts with identifying an event and session: 
import fastf1

# Get a specific session
session = fastf1.get_session(2021, 'Bahrain', 'Q')
session.load()

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Getting a Session

The primary entry point is get_session(), which returns a Session object based on year, event, and session identifier.

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Function: get_session()

fastf1.get_session(
    year: int,
    gp: str | int,
    identifier: int | str | None = None,
    *,
    backend: Literal['fastf1', 'f1timing', 'ergast'] | None = None,
    exact_match: bool = False
) -> Session
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year
int
required
Championship year (e.g., 2021, 2023)
​
gp
str | int
required
Event name as a string or round number as an integer. String matching uses fuzzy search by default.Examples: 'bahrain', 'Silverstone', 1 (first round)
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identifier
int | str | None
Session identifier - can be:
  • Session name: 'Race', 'Qualifying', 'Practice 1'
  • Abbreviation: 'R', 'Q', 'FP1', 'FP2', 'FP3', 'S' (Sprint), 'SQ' (Sprint Qualifying)
  • Session number: 1, 2, 3, 4, 5
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backend
Literal['fastf1', 'f1timing', 'ergast'] | None
Data source backend:
  • 'fastf1': FastF1’s own backend (default, 2018-present)
  • 'f1timing': F1 live timing API (2018-present)
  • 'ergast': Ergast database (1950-present, limited features)
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exact_match
bool
default:"False"
If True, requires exact event name match instead of fuzzy search

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Usage Examples

# Get the second free practice of the first race of 2021
session = fastf1.get_session(2021, 1, 'FP2')
get_session() returns a Session object but does not load any data yet. You must call session.load() to fetch timing, telemetry, and other session-specific data.

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Getting an Event

You can also access the event object directly using get_event().

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Function: get_event()

fastf1.get_event(
    year: int,
    gp: int | str,
    *,
    backend: Literal['fastf1', 'f1timing', 'ergast'] | None = None,
    exact_match: bool = False
) -> Event
Returns an Event object representing a complete race weekend.
​
year
int
required
Championship year
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gp
int | str
required
Event name (string) or round number (integer)

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Event Class

The Event class represents a single race weekend and provides methods to access individual sessions. 
import fastf1

# Get the event
event = fastf1.get_event(2021, 'Bahrain')

# Access event information
print(event.EventName)          # 'Bahrain Grand Prix'
print(event.Country)            # 'Bahrain'
print(event.Location)           # 'Sakhir'
print(event.RoundNumber)        # 1
print(event.EventFormat)        # 'conventional' or 'sprint'

# Get specific sessions from the event
race = event.get_race()
quali = event.get_qualifying()
fp1 = event.get_practice(1)

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Event Methods

Returns a Session object for the specified session.
session = event.get_session('Q')
session = event.get_session(5)  # Session 5 (usually Race)
Returns the race session.
race = event.get_race()
Returns the qualifying session.
quali = event.get_qualifying()
Returns the sprint session (if applicable).
sprint = event.get_sprint()
Returns the specified practice session.
fp1 = event.get_practice(1)
fp2 = event.get_practice(2)
fp3 = event.get_practice(3)
Returns True if this is a testing event.
if event.is_testing():
    print("This is a testing event")

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Event Schedules

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Getting the Event Schedule

fastf1.get_event_schedule(
    year: int,
    *,
    include_testing: bool = True,
    backend: Literal['fastf1', 'f1timing', 'ergast'] | None = None
) -> EventSchedule
Returns an EventSchedule object containing all events for a season. 
import fastf1

# Get all events for 2023
schedule = fastf1.get_event_schedule(2023)

# Access the schedule as a DataFrame
for index, event in schedule.iterrows():
    print(f"{event.RoundNumber}: {event.EventName} - {event.Country}")

# Get a specific event from the schedule
bahrain = schedule.get_event_by_round(1)
monaco = schedule.get_event_by_name('Monaco')

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EventSchedule Class

The EventSchedule class extends pandas DataFrame and provides additional methods:
Get an event by its round number.
first_race = schedule.get_event_by_round(1)
Get an event by name using fuzzy matching.
# Fuzzy matching
monza = schedule.get_event_by_name('monza')

# Exact matching
british = schedule.get_event_by_name('British Grand Prix', exact_match=True)
Returns a boolean Series indicating which events are testing events.
testing_events = schedule[schedule.is_testing()]

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Available Event Data

Each event in the schedule contains:
  • RoundNumber - Round number in the championship
  • Country - Country where the event takes place
  • Location - Specific location/circuit
  • EventName - Short name of the event
  • OfficialEventName - Official full name
  • EventDate - Date of the event (usually race day)
  • EventFormat - Format type: 'conventional', 'sprint', 'sprint_shootout', 'sprint_qualifying', or 'testing'
  • Session1 through Session5 - Names of each session
  • Session1Date through Session5Date - Local timestamps for each session
  • Session1DateUtc through Session5DateUtc - UTC timestamps for each session
  • F1ApiSupport - Whether F1 API data is available

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Testing Sessions

Pre-season testing sessions require special functions: 
# Get a testing event
test_event = fastf1.get_testing_event(2023, test_number=1)

# Get a specific testing session
test_session = fastf1.get_testing_session(2023, test_number=1, session_number=1)
test_session.load()

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Session Object

Once you have a Session object, you can access its properties: 
session = fastf1.get_session(2023, 'Monaco', 'Q')

# Session information (available before loading)
print(session.name)              # 'Qualifying'
print(session.date)              # pandas.Timestamp of session date
print(session.event.EventName)   # 'Monaco Grand Prix'
print(session.f1_api_support)    # True/False
Most session data is only available after calling session.load(). See the Loading Data page for details.

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