Aviasales API in Python: flight prices via Travelpayouts

If you are building a site, bot or Mini App with flights, the simplest price source is the Travelpayouts Data API (Aviasales). Below is a Python example, typical requests and the limits we ran into while working on HotTrip.

What the Data API is and how it differs from live search

The Data API returns cached prices collected from Aviasales user searches. It is fast and free, but it is not the same as a real-time search:

• a price can be stale: according to third-party wrappers, data comes from searches of roughly the last two days;
• for rare routes and dates there may be no data;
• the final price on the purchase page may differ.

Travelpayouts has a separate API for live search with different access conditions; see the documentation. For a showcase “from X” and destination lists the Data API is usually enough.

What you need

• A Travelpayouts account and a token (issued in your dashboard).
• Your affiliate marker for links, if you want a commission.
• Python and the requests library.

Pass the token in the x-access-token header and keep it in an environment variable, not in code.

Prices by route and dates

The main method is GET https://api.travelpayouts.com/aviasales/v3/prices_for_dates.

import os
import requests

API = "https://api.travelpayouts.com/aviasales/v3/prices_for_dates"
TOKEN = os.environ["TRAVELPAYOUTS_TOKEN"]


def cheapest(origin: str, destination: str, month: str, limit: int = 10) -> list[dict]:
    """Cheapest offers. origin/destination: IATA codes, month: '2026-12'."""
    r = requests.get(
        API,
        headers={"x-access-token": TOKEN},
        params={
            "origin": origin,
            "destination": destination,
            "departure_at": month,
            "sorting": "price",
            "unique": "false",
            "currency": "rub",
            "limit": limit,
        },
        timeout=10,
    )
    r.raise_for_status()
    return r.json().get("data", [])


for offer in cheapest("MOW", "IST", "2026-12"):
    print(offer["departure_at"][:10], offer["price"], offer.get("airline"), offer.get("transfers"))

The response is a list of offers. Each usually has a price, an airline, a departure date, the number of transfers and a link field with a relative address of the Aviasales search page. Check exact fields and current parameters in the Travelpayouts documentation: they can change.

Popular destinations from a city

For a “Where to fly” block, GET /v1/city-directions?origin=MOW&currency=rub is convenient. It returns the destinations from a city in one request, which is faster than looping over routes yourself.

City and airport codes

Use IATA codes. MOW means Moscow as a whole (all airports), SVO is one airport. For input suggestions there is the autocomplete https://autocomplete.travelpayouts.com/places2?term=...&locale=en, which returns cities and airports.

Links and the affiliate marker

The link field contains a path: build the full address as https://www.aviasales.ru + link and add your affiliate marker. Then clicks are counted in your dashboard. For short links in Telegram the API has a method to create shortened affiliate links.

Pitfalls from practice

1. Cache on your side. Store responses in a database and refresh them on a schedule instead of on every user request: it is faster and saves limits.
2. Empty responses. For some routes there is no data. Show a clear message and neighbouring dates or destinations.
3. Freshness. Store the time a price was received and show it as “from”. Warn that the final price on the purchase page may differ.
4. Timeouts and errors. Set a timeout and retry on failure. Do not make a user wait for an external API.
5. Currency and language. The currency parameter controls the currency of prices; for different countries store prices per currency.

Where this is used

On top of the Data API we built a portal, a Telegram bot with flight search and price subscriptions, a Mini App and an automated channel that publishes fresh offers every two hours. Details are in the HotTrip project and in Integrations and APIs and Scraping and data.