✈️ faster-flights
Fast, strongly-typed Google Flights scraping for Python.
Documentation • Issues • PyPI
pip install faster-flights
Quick start
from fast_flights import FlightQuery, Passengers, ShoppingOptions, create_query, get_flights
query = create_query(
flights=[
FlightQuery(
date="2026-03-31",
from_airport="TPE",
to_airport="NRT",
),
],
trip="one-way",
seat="economy", # economy / premium-economy / business / first
passengers=Passengers(adults=1),
language="en-US",
currency="USD",
)
results = get_flights(
query,
shopping=ShoppingOptions(
ranking_mode="best",
result_sort="top_flights",
),
)
for flight in results[:3]:
print(f"{flight.airlines} - ${flight.price}")
print(flight.rank, flight.group_key)
print(results.metadata.shopping.cheapest_price)
Current public API
The supported top-level API is the set exported from fast_flights:
FlightQueryPassengerscreate_query()andcreate_filter()(create_filteris a compatibility alias)SearchSessionShoppingOptionsbuild_booking_tfs()/build_booking_url()get_flights()select_flight()get_return_flights()get_flights_multicity()get_flights_multicity_chained()get_selected_flight_page()PlaywrightBrowserProvider(experimental)fetch_flights_html()
Use IATA airport codes like "TPE", "NRT", or "JFK" in FlightQuery. The repository does not currently export a public airport search helper.
Google shopping ranking and sorting
Use ShoppingOptions when you want the same server-side ranking and ordering that Google Flights uses in its shopping RPC:
from fast_flights import ShoppingOptions, get_flights
results = get_flights(
query,
shopping=ShoppingOptions(
ranking_mode="cheapest",
result_sort="price",
),
)
Supported values:
ranking_mode:best,cheapestresult_sort:top_flights,price,departure_time,arrival_time,duration,emissions
When shopping is provided:
get_flights()andget_return_flights()use the shopping RPC instead of HTML parsing- result order matches Google’s RPC order
results.metadata.shoppingincludes ranking metadata such asranking_mode,result_sort,cheapest_price,ranking_token,source, and Google group boundaries- each
Flightsitem carries additiverank,group_key, andgroup_titlemetadata
Round-trip searches
Round-trip search is a two-step flow:
- Query outbound options with
get_flights() - Select one outbound option and fetch return options with
get_return_flights()
from fast_flights import (
FlightQuery,
Passengers,
create_query,
get_flights,
get_return_flights,
select_flight,
)
query = create_query(
flights=[
FlightQuery(date="2026-03-31", from_airport="TPE", to_airport="NRT"),
FlightQuery(date="2026-04-05", from_airport="NRT", to_airport="TPE"),
],
trip="round-trip",
seat="business",
passengers=Passengers(adults=1),
language="en-US",
currency="USD",
)
outbound = get_flights(query)
return_query = select_flight(query, outbound[0])
returning = get_return_flights(return_query)
Each outbound result carries a hidden select_token. select_flight() wraps that token into a ReturnQuery.
get_return_flights() first tries Google's selected-flight HTML and verifies that the returned itinerary direction matches the requested return leg. If Google still serves the wrong payload there, the library rebuilds the browser-style selected tfs state from the chosen outbound segments and fetches the bundled return page again.
Only if both HTML paths fail does the library fall back to an independent one-way query for the requested return leg. In that last-resort mode, the returned Flights.price values are per-leg one-way prices rather than Google's selected round-trip total.
Session workflow
Use SearchSession when you want one API for chained search state, current search links, the final booking link, and optional Google shopping ranking:
from fast_flights import FlightQuery, Passengers, SearchSession, ShoppingOptions, create_query
query = create_query(
flights=[
FlightQuery(date="2026-03-31", from_airport="TPE", to_airport="NRT"),
FlightQuery(date="2026-04-05", from_airport="NRT", to_airport="TPE"),
],
trip="round-trip",
seat="economy",
passengers=Passengers(adults=1),
language="en-US",
currency="USD",
)
session = SearchSession(
query,
mode="rpc-first",
shopping=ShoppingOptions(ranking_mode="best", result_sort="top_flights"),
)
outbound = session.results()
session = session.select(outbound[0])
returning = session.results()
session = session.select(returning[0])
print(session.current_search_tfs) # selected-page / search-state tfs
print(session.final_booking_tfs) # final booking itinerary tfs
print(session.booking_url()) # https://www.google.com/travel/flights/booking?...
build_booking_tfs() and build_booking_url() expose the same final booking-state builder directly if you already have selected_legs.
Experimental browser parity
If later-leg results do not match what Google shows in a real browser, you can let SearchSession fall back to a browser-captured shopping response:
from fast_flights import (
FlightQuery,
Passengers,
PlaywrightBrowserProvider,
SearchSession,
create_query,
)
query = create_query(
flights=[
FlightQuery(date="2026-03-31", from_airport="TPE", to_airport="LHR"),
FlightQuery(date="2026-04-14", from_airport="LHR", to_airport="TPE"),
],
trip="round-trip",
seat="economy",
passengers=Passengers(adults=1),
language="en-GB",
currency="GBP",
)
session = SearchSession(
query,
mode="rpc-first",
browser_fallback=True,
browser_provider=PlaywrightBrowserProvider(),
)
This path is experimental and only applies to later legs. The normal order stays:
rpc-first: shopping RPC -> selected/bundled HTML -> browser capture -> directional fallbackssr-first: selected/bundled HTML -> shopping RPC -> browser capture -> directional fallback
The browser provider captures the real GetShoppingResults response and feeds that response into the existing parser. It does not replay the request body in v1.
Multi-city searches
There are three supported multi-city workflows.
1. Total trip price + directional per-leg options
Use get_flights_multicity_chained() when you want Google's bundled multi-city pricing plus correctly directed parsed options for each leg.
from fast_flights import FlightQuery, get_flights_multicity_chained
legs = [
FlightQuery(date="2026-03-31", from_airport="TPE", to_airport="NRT"),
FlightQuery(date="2026-04-05", from_airport="NRT", to_airport="HKG"),
FlightQuery(date="2026-04-10", from_airport="HKG", to_airport="TPE"),
]
result = get_flights_multicity_chained(
legs,
seat="economy",
language="en-US",
currency="USD",
)
print(result[0].total_price)
print(result[1].flights[0].flights[-1].to_airport.code) # per-leg directional results
total_price is Google's bundled multi-city price from the RPC response. The per-leg flights lists are populated with independent one-way searches for each leg so the parsed routes always match the requested leg direction. That means later-leg Flights.price values are per-leg one-way prices, not re-priced bundled totals.
2. Per-leg flight details
Use get_flights_multicity() when you want each leg as an independent one-way search.
from fast_flights import FlightQuery, Passengers, get_flights_multicity
legs = get_flights_multicity(
flights=[
FlightQuery(date="2026-03-31", from_airport="TPE", to_airport="NRT"),
FlightQuery(date="2026-04-05", from_airport="NRT", to_airport="HKG"),
FlightQuery(date="2026-04-10", from_airport="HKG", to_airport="TPE"),
],
seat="economy",
passengers=Passengers(adults=1),
language="en-US",
currency="USD",
)
This returns per-leg one-way pricing, not Google's bundled total trip price.
3. Hybrid workflow
Use get_flights(create_query(..., trip="multi-city")) for Google's bundled first-leg options, then get_flights_multicity() for detailed options on legs 2+.
from fast_flights import (
FlightQuery,
Passengers,
create_query,
get_flights,
get_flights_multicity,
)
legs = [
FlightQuery(date="2026-03-31", from_airport="TPE", to_airport="NRT"),
FlightQuery(date="2026-04-05", from_airport="NRT", to_airport="HKG"),
FlightQuery(date="2026-04-10", from_airport="HKG", to_airport="TPE"),
]
query = create_query(
flights=legs,
trip="multi-city",
seat="economy",
passengers=Passengers(adults=1),
language="en-US",
currency="USD",
)
leg1 = get_flights(query)
remaining = get_flights_multicity(
flights=legs[1:],
seat="economy",
passengers=Passengers(adults=1),
language="en-US",
currency="USD",
)
4. Direct Google Flights selected page
Use get_selected_flight_page() when a user picks an option and you want the direct Google Flights page for that selection.
from fast_flights import get_selected_flight_page
selected = get_selected_flight_page(query, leg1[0])
print(selected.url)
print(selected.f_sid)
print(selected.bl)
print(selected.data_service_requests["ds:1"].rpc_id)
For multi-city searches, this gives you the real Google Flights selected page plus the client-side data-service requests embedded in that page. Google still does not expose later-leg bundled options as parsed Flights objects through this library's public API.
The round-trip return-flight API is not the supported way to fetch legs 2+ for multi-city itineraries. Google's HTML response for that path does not provide the required data.
Integrations and proxies
Fetching customization is split between integration= for HTML fetches and browser_provider= for experimental browser-assisted parity in SearchSession.
Bright Data
from fast_flights import get_flights
from fast_flights.integrations import BrightData
integration = BrightData(api_key="...")
results = get_flights(query, integration=integration)
Custom integrations
Subclass fast_flights.integrations.base.Integration and implement fetch_html(q) -> str.
from fast_flights.integrations.base import Integration
class MyIntegration(Integration):
def fetch_html(self, q):
return "...html..."
Browser providers
Browser providers are separate from integrations. They do not replace fetch_html(). They only provide an optional network-capture fallback for chained SearchSession searches.
from fast_flights import PlaywrightBrowserProvider, SearchSession
session = SearchSession(
query,
browser_fallback=True,
browser_provider=PlaywrightBrowserProvider(),
)
Proxy support
results = get_flights(query, proxy="http://user:pass@proxy:8080")
get_flights_multicity() also forwards integration= and proxy= to each per-leg one-way search. RPC-based multi-city flows (get_flights(...trip="multi-city") and get_flights_multicity_chained()) support proxy= but not integration overrides.
Documentation
Contributing
Contributing is welcomed. A few notes though:
- please no ai slop. i am not reading all that.
- one change at a time. what your title says is what you've changed.
- no new dependencies unless it's related to the core parsing.
- really, i cant finish reading all of them, i have other projects and life to do. really sorry
Metadata
Release files for faster-flights 3.8.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| faster_flights-3.8.0.tar.gz | 32.7 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| faster_flights-3.8.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 68.5 kB
Release files / faster_flights-3.8.0.tar.gz
| Download URL | faster_flights-3.8.0.tar.gz |
|---|---|
| Size | 32.7 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
7b353d40ca891c8fbb5f3bf548c367dde66da2f8b62d0be47bfa8cbf7526cd51
|
|
BLAKE2b-256 checksum How to use checksums |
2d24d57dbea86e931c6093e9b0141c9cf701add7cd179a52a1524b6b199149d8
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/6.1.0 CPython/3.13.12
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Jul 9, 2026.
Transparency logRelease files / faster_flights-3.8.0-py3-none-any.whl
| Download URL | faster_flights-3.8.0-py3-none-any.whl |
|---|---|
| Size | 35.7 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
72476fbaf0906ae517d1545b27bcc0953c4f3484bafab13e334a8ac6a5b651ff
|
|
BLAKE2b-256 checksum How to use checksums |
2730a8ed37e1e04842d84f5d8a26b77a1da224662517c466efac5f75554da1a0
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/6.1.0 CPython/3.13.12
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Jul 9, 2026.
Transparency log