# Google Flights search: every itinerary for one route and date

**Use case:** 

Chicago O'Hare to Miami, one way, 30 days from the day you run it: every itinerary Google lists (the full "View more flights" list, not only the first 30), one row each with airlines, flight numbers, times with UTC offsets, duration, stops, layovers, aircraft, CO2, legroom and the price where Google gives them, and the booking link. The free summary row adds the price insight and 61-day history.

## Input

```json
{
  "origin": "ORD",
  "destination": "MIA",
  "departureDate": "+30",
  "returnDate": "",
  "legs": [],
  "searches": [],
  "searchUrls": [],
  "flexibleDays": 0,
  "adults": 1,
  "children": 0,
  "infantsInSeat": 0,
  "infantsOnLap": 0,
  "cabin": "economy",
  "maxStops": "any",
  "includeAirlines": [],
  "excludeAirlines": [],
  "maxPrice": 0,
  "maxDurationMinutes": 0,
  "departureTimeRange": "",
  "arrivalTimeRange": "",
  "sortBy": "best",
  "view": "all",
  "returnsFor": 0,
  "bookingOptionsFor": 0,
  "calendarDays": 0,
  "cheapestDays": 0,
  "market": "US",
  "language": "en",
  "currency": "USD",
  "maxItems": 0
}
```

## Output

```json
{
  "row_type": {
    "label": "Row type",
    "format": "string"
  },
  "search_id": {
    "label": "Search id",
    "format": "string"
  },
  "search_label": {
    "label": "Search",
    "format": "string"
  },
  "status": {
    "label": "Status",
    "format": "string"
  },
  "status_detail": {
    "label": "Status detail",
    "format": "string"
  },
  "scraped_at": {
    "label": "Scraped at",
    "format": "string"
  },
  "trip_type": {
    "label": "Trip type",
    "format": "string"
  },
  "origin": {
    "label": "From",
    "format": "string"
  },
  "destination": {
    "label": "To",
    "format": "string"
  },
  "departure_date": {
    "label": "Departure date",
    "format": "string"
  },
  "return_date": {
    "label": "Return date",
    "format": "string"
  },
  "legs_asked": {
    "label": "Legs asked",
    "format": "array"
  },
  "passengers": {
    "label": "Passengers",
    "format": "object"
  },
  "cabin": {
    "label": "Cabin",
    "format": "string"
  },
  "market": {
    "label": "Market",
    "format": "string"
  },
  "language": {
    "label": "Language",
    "format": "string"
  },
  "currency": {
    "label": "Currency",
    "format": "string"
  },
  "currency_served": {
    "label": "Currency served",
    "format": "string"
  },
  "view": {
    "label": "View",
    "format": "string"
  },
  "rank": {
    "label": "Rank",
    "format": "integer"
  },
  "group": {
    "label": "Group",
    "format": "string"
  },
  "leg_index": {
    "label": "Leg",
    "format": "integer"
  },
  "selected_flights": {
    "label": "Selected flights",
    "format": "array"
  },
  "price_scope": {
    "label": "Price scope",
    "format": "string"
  },
  "price": {
    "label": "Price",
    "format": "number"
  },
  "price_exact": {
    "label": "Exact fare",
    "format": "number"
  },
  "airlines": {
    "label": "Airlines",
    "format": "array"
  },
  "airline_codes": {
    "label": "Airline codes",
    "format": "array"
  },
  "flight_numbers": {
    "label": "Flights",
    "format": "array"
  },
  "departure_at": {
    "label": "Departure",
    "format": "string"
  },
  "arrival_at": {
    "label": "Arrival",
    "format": "string"
  },
  "duration_minutes": {
    "label": "Duration (min)",
    "format": "integer"
  },
  "stops": {
    "label": "Stops",
    "format": "integer"
  },
  "layovers": {
    "label": "Layovers",
    "format": "array"
  },
  "legs": {
    "label": "Legs",
    "format": "array"
  },
  "aircraft": {
    "label": "Aircraft",
    "format": "array"
  },
  "legroom": {
    "label": "Legroom",
    "format": "array"
  },
  "legroom_unit": {
    "label": "Legroom unit",
    "format": "string"
  },
  "overnight": {
    "label": "Overnight",
    "format": "boolean"
  },
  "often_delayed": {
    "label": "Often delayed",
    "format": "boolean"
  },
  "co2_kg": {
    "label": "CO2 (kg)",
    "format": "integer"
  },
  "co2_typical_kg": {
    "label": "CO2 typical (kg)",
    "format": "integer"
  },
  "co2_vs_typical_percent": {
    "label": "CO2 vs typical %",
    "format": "integer"
  },
  "checked_bags_included": {
    "label": "Checked bags included",
    "format": "integer"
  },
  "carry_on_bags_included": {
    "label": "Carry-on bags included",
    "format": "integer"
  },
  "booking_token": {
    "label": "Booking token",
    "format": "string"
  },
  "google_flights_url": {
    "label": "Google Flights link",
    "format": "string"
  },
  "itineraries_found": {
    "label": "Itineraries found",
    "format": "integer"
  },
  "price_level": {
    "label": "Price level",
    "format": "string"
  },
  "lowest_price": {
    "label": "Lowest price",
    "format": "number"
  },
  "typical_price_low": {
    "label": "Typical price (low)",
    "format": "number"
  },
  "typical_price_high": {
    "label": "Typical price (high)",
    "format": "number"
  },
  "booking_options": {
    "label": "Booking options",
    "format": "array"
  },
  "booking_options_count": {
    "label": "Booking options count",
    "format": "integer"
  },
  "best_count": {
    "label": "Best count",
    "format": "integer"
  },
  "cheapest_price": {
    "label": "Cheapest price",
    "format": "number"
  },
  "price_history": {
    "label": "Price history (Google)",
    "format": "array"
  },
  "airports": {
    "label": "Airports",
    "format": "array"
  },
  "airlines_available": {
    "label": "Airlines available",
    "format": "array"
  },
  "alliances": {
    "label": "Alliances",
    "format": "array"
  },
  "price_range_min": {
    "label": "Price range (min)",
    "format": "number"
  },
  "price_range_max": {
    "label": "Price range (max)",
    "format": "number"
  },
  "date": {
    "label": "Date",
    "format": "string"
  },
  "is_cheapest": {
    "label": "Cheapest day",
    "format": "boolean"
  },
  "trip_length_days": {
    "label": "Trip length (days)",
    "format": "integer"
  },
  "destination_rank": {
    "label": "Destination rank",
    "format": "integer"
  },
  "destination_city": {
    "label": "Destination city",
    "format": "string"
  },
  "destination_country": {
    "label": "Destination country",
    "format": "string"
  },
  "latitude": {
    "label": "Latitude",
    "format": "number"
  },
  "longitude": {
    "label": "Longitude",
    "format": "number"
  },
  "distance_text": {
    "label": "Distance",
    "format": "string"
  },
  "image_url": {
    "label": "Image",
    "format": "string"
  }
}
```

## How it works

### 1. Sign up on Apify or log in

The Google Flights Scraper & Google Flights API: Fares, Calendar Actor is ready to run with the inputs already set for "Google Flights search: every itinerary for one route and date". [Sign up or log in](https://console.apify.com/create-task-from-example/Mlfi6zf5wsucjnomu) and you'll land in Apify Console with a copy of this exact task.

### 2. Start the "Google Flights search: every itinerary for one route and date" task

The Google Flights Scraper & Google Flights API: Fares, Calendar Actor will start running based on the input automatically. You can also change all the input fields, like from (airport code), to (airport code), and more, to match your specific use case.

### 3. Receive the "Google Flights search: every itinerary for one route and date" output

Monitor the progress in real time. You will be notified as soon as your dataset is complete and ready for review. Each result includes data such as row type, search id, search, and more.

### 4. Integrate into your workflow

The final output is delivered in JSON, CSV, or Excel format, ready to be plugged into your workflow. You can also [run the "Google Flights search: every itinerary for one route and date" task via API](https://apify.com/hyperbach/google-flights-scraper.md).

## About this Actor

This example demonstrates how to use [Google Flights Scraper & Google Flights API: Fares, Calendar](https://apify.com/hyperbach/google-flights-scraper.md) with a specific input configuration. Visit the [Actor detail page](https://apify.com/hyperbach/google-flights-scraper.md) to learn more, explore other use cases, and run it yourself.


## How to integrate an Actor?

This Task's input is already configured above. Use it as-is rather than inventing a new one.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For full API examples (JavaScript, Python, CLI, MCP, OpenAPI), see this Task's Actor page: https://apify.com/hyperbach/google-flights-scraper.md

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).