[Blog](https://scrapfly.io/blog)   /  [playwright](https://scrapfly.io/blog/tag/playwright)   /  [How to Scrape Emirates Flights with Python (2026)](https://scrapfly.io/blog/posts/how-to-scrape-emirates-flights)   # How to Scrape Emirates Flights with Python (2026)

 by [Mohab Yousry](https://scrapfly.io/blog/author/mohab-yousry-9396552a) Jul 21, 2026 19 min read [\#playwright](https://scrapfly.io/blog/tag/playwright) [\#python](https://scrapfly.io/blog/tag/python) 

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Emirates flight search results don't appear in the initial HTTP response. The page renders an empty shell, then JavaScript loads prices, schedules, and fare brands after the form is submitted. A plain `requests` or BeautifulSoup scrape does not return the rendered flight offers; the search requires a browser-driven form submission.

This guide walks through the [scrapfly/scrapfly-scrapers emirates scraper](https://github.com/scrapfly/scrapfly-scrapers/tree/main/emirates-scraper), a Python scraper that uses the [Scrapfly Web Scraping API](https://scrapfly.io/products/web-scraping-api) to automate the Emirates search form, intercept the background `branded-fares` XHR response, and parse structured flight data from the JSON payload without running a local browser.



[**emirates scraper**github.com/scrapfly/scrapfly-scrapers/tree/main/emirates-scraper](https://github.com/scrapfly/scrapfly-scrapers/tree/main/emirates-scraper)

## Key Takeaways

Emirates search results only appear after a multi-step browser flow completes. The scraper intercepts the background XHR call that populates the results, which gives cleaner structured data than DOM parsing.

- Plain requests or static HTML parsers can't retrieve Emirates offers, a browser-driven form flow is required.
- Scrapfly Web Scraping API executes a `js_scenario` on its managed browser, eliminating the need to run Playwright locally.
- The `branded-fares` XHR response carries all structured flight data including prices, fare brands, seat availability, layovers, and plane models.
- Proxy country selects the network location, while the Emirates locale URL selects the site locale. Record both values alongside every result.
- Only brands with `status == "AVAILABLE"` are included in the output. Sold-out or unavailable fare tiers are skipped.
- When the `branded-fares` call is missing from the session output, set `debug=True` and review the session recording in the Scrapfly dashboard to confirm whether the form submission completed.

**Get web scraping tips in your inbox**Trusted by 100K+ developers and 30K+ enterprises. Unsubscribe anytime.







## Why Scrape Emirates Flight Data?

Scraping Emirates directly gives developers access to airline owned flight search data, including live prices, schedules, route availability, cabin details, and fare brands exactly as shown on the Emirates website. This is useful when aggregators or third-party APIs do not expose the same level of detail, freshness, or region specific pricing.

Common use cases include:

- Tracking Special and Saver fare availability over time
- Detecting price drops for specific travel dates
- Enriching travel applications with cabin and fare data
- Comparing Emirates prices across different countries
- Monitoring route schedules and availability
- Supporting competitor analysis

This guide covers scraping Emirates flight prices public search results only. Scraping login gated pages, Emirates Skywards accounts, booking flows, passenger data, or any resource that requires authentication is outside the scope of this guide. Before running any production scraper, review Emirates terms of service and check the robots.txt file at `https://www.emirates.com/robots.txt`.

Install the scraper dependencies before defining the search inputs.



## Project Setup

Before building the scraper, you need the following components:

- [Scrapfly Python SDK](https://scrapfly.io/docs/sdk/python): For connecting to the Scrapfly Web Scraping API, configuring browser sessions, and accessing captured XHR data.
- [Scrapfly Web Scraping API](https://scrapfly.io/products/web-scraping-api): Provides the managed remote browser that executes the Emirates search scenario and captures background network requests.

This setup uses the Scrapfly Web Scraping API with `render_js=True` and a `js_scenario` to drive the Emirates search form. No local browser or Playwright installation is required. Scrapfly runs the browser session on its infrastructure and returns both the rendered HTML and all captured XHR calls.

Install the SDK with its extras and loguru:

shell```shell
pip install "scrapfly-sdk[all]"
```



Generate an API key from the [Scrapfly dashboard](https://scrapfly.io/dashboard) and store it in an environment variable:

shell```shell
export SCRAPFLY_KEY=sfp_your_api_key_here
```



The search scenario requires a route, trip type, and travel dates.



## How to Find Emirates Flights to Scrape

Emirates search results come from form inputs, not from static crawlable URLs. There is no URL you can bookmark today that reliably returns the same set of results tomorrow. The scraper has to drive the search form each time, which means choosing search inputs before writing any automation.

The minimum inputs for a one-way search are an origin airport, a destination airport, and a departure date. Adding a return date switches the form to round-trip. Adding a proxy country context gives you results that are stable and reproducible across runs.

| Input | Example | Why it matters |
|---|---|---|
| Origin airport | JFK | IATA code for the departure airport |
| Destination airport | DXB | IATA code for Dubai International |
| Trip type | One-way or round-trip | Determines whether return\_date is supplied |
| Departure date | 2026-07-15 | Emirates prices shift daily |
| Return date | 2026-07-22 | Required for round-trip searches |
| Country context | US | Proxy country drives locale and currency |

This guide uses JFK to DXB as the sample route throughout. JFK to Dubai International is one of Emirates' flagship long-haul routes with multiple daily departures and all four cabin classes, which makes it a reliable reference for testing and calibration.

If you plan to compare prices across regions, the country context is the most important variable to track. Run separate sessions with different proxy countries and record the proxy country, locale, currency, and a UTC timestamp alongside every result set; the current return object records only the locale and timestamp. Prices for the same JFK to DXB itinerary on the same date can differ materially between a US-context session and a UK-context session.

The following TypedDict models define the returned search and fare records.



## Defining the Data Models

The scraper uses Python `TypedDict` to define the shape of its output before any scraping logic runs. Defining types upfront makes extraction code easier to read and ensures the result structure is consistent across runs.

python```python
from typing import List, Optional, TypedDict


class FarePrice(TypedDict):
    amount: float
    currency: str


class FlightResult(TypedDict):
    airline: str
    flight_number: str
    departure_time: str
    departure_airport: str
    arrival_time: str
    arrival_airport: str
    duration: str
    stops: int
    layovers: List[dict]
    price: FarePrice
    cabin_class: str
    plane_model: str
    fare_brand: str
    seats_available: int
    captured_at: str


class FlightSearch(TypedDict):
    locale: str
    trip_type: str
    origin: str
    destination: str
    route: str
    search_date: str
    departure_date: str
    return_date: Optional[str]
    lowest_fare: FarePrice
    flights: List[FlightResult]
```



`FarePrice` holds a numeric amount and currency code. `FlightResult` holds all per-offer fields including layover details and seat availability. `FlightSearch` wraps the full result for a single search request, including the list of all flight offers and the search-wide lowest fare.

The browser scenario fills the form and submits those search inputs.

## Building the Emirates Search Automation Scenario

Scrapfly's `js_scenario` replaces a local Playwright script. It is a list of browser action dictionaries that Scrapfly executes sequentially inside its managed browser. The action types used for the Emirates scraper are `click`, `fill`, `wait`, `wait_for_selector`, and `execute` for inline JavaScript.

### Airport Field Helpers

The airport inputs on Emirates use combobox components with autocomplete dropdowns. Filling an airport field requires three steps: type the IATA code, wait for the dropdown to appear, then click the matching option.

python```python
def _pick_airport_option(code: str) -> str:
    return (
        "var items=[...document.querySelectorAll('[data-testid^=\"options_\"]')];"
        f"var match=items.find(o=>o.textContent.includes('{code}'));"
        f"if(!match) throw new Error('Airport option not found: {code}');"
        "match.click();"
    )


def _fill_airport(field: str, code: str) -> list:
    return [
        {"fill": {"selector": f"[data-testid^='combobox_{field}'] input", "value": code, "clear": True}},
        {"wait": 1000},
        {"wait_for_selector": {"selector": "[data-testid^='options_']", "timeout": 10000}},
        {"execute": {"script": _pick_airport_option(code)}},
    ]
```



`_pick_airport_option` generates an inline script that scans all visible dropdown options and clicks the one containing the IATA code, falling back to the first option if no exact match is found. `_fill_airport` assembles those steps into a reusable scenario fragment for any combobox field.

### Date Picker Helpers

The Emirates date picker uses `aria-label` attributes to identify individual calendar cells. The label format varies slightly across locales, so the click script tries two formats and stops at the first match.

python```python
from datetime import datetime


def _date_click_script(date_iso: str) -> str:
    parsed_date = datetime.strptime(date_iso, "%Y-%m-%d")
    date_label = f"{parsed_date.strftime('%A')}, {parsed_date.day}  {parsed_date.strftime('%B %Y')}"
    date_alt = f"{parsed_date.strftime('%A')}, {parsed_date.strftime('%B')} {parsed_date.day}, {parsed_date.year}"
    return (
        f"var cell=document.querySelector('[aria-label*=\"{date_label}\"]')"
        f" || document.querySelector('[aria-label*=\"{date_alt}\"]');"
        "cell?.click();"
    )


def _select_date(date_iso: str, picker: str) -> list:
    return [
        {"click": {"selector": picker, "timeout": 5000}},
        {"wait": 1000},
        {"execute": {"script": _date_click_script(date_iso)}},
    ]
```



`_date_click_script` generates a JavaScript snippet that tries to click the calendar cell for the given date using two possible label formats. `_select_date` wraps that into a three-step scenario fragment: open the date picker, wait for it to render, then click the target date.

### Full Scenario Builder

The full scenario builder assembles all the fragments into a single ordered list of actions covering cookie dismissal, trip type selection, origin, destination, dates, and form submission.

python```python
from typing import Optional


def _build_search_scenario(
    origin: str,
    destination: str,
    departure_date: str,
    return_date: Optional[str] = None,
) -> list:
    scenario = [
        {"click": {"selector": "button[id*='onetrust-accept']", "ignore": True, "ignore_if_not_visible": True, "timeout": 10000}},
        {"wait": 1000},
    ]

    if not return_date:
        scenario.append(
            {
                "execute": {
                    "script": "[...document.querySelectorAll('button[role=tab]')].find(b=>b.textContent.trim()==='One way')?.click();"
                }
            }
        )

    scenario += _fill_airport("Departure", origin)
    scenario += _fill_airport("Arrival", destination)

    if return_date:
        scenario += _select_date(departure_date, "#startDate")
        scenario += _select_date(return_date, "#endDate")
    else:
        scenario += _select_date(departure_date, "#date-input0, #startDate")

    scenario += [
        {"click": {"selector": "button.rsw-submit-button", "timeout": 10000}},
        {"wait": 3000},
        {"click": {"selector": ".bottom-block__continue button", "ignore": True, "ignore_if_not_visible": True, "timeout": 10000}},
        {"wait": 2000},
    ]
    return scenario
```



The scenario starts by dismissing the cookie consent banner with `ignore=True` so the step silently skips if no banner appears. For one-way searches, it clicks the "One way" tab before filling the form. The final steps submit the form and optionally dismiss a post-search interstitial prompt that Emirates occasionally shows.

Pass the completed scenario to ScrapeConfig and parse the captured XHR response.



Scrapfly

#### Need a cloud browser for scraping?

Run headless browsers at scale with Scrapfly Cloud Browser — no infrastructure to manage.

[Try Free →](https://scrapfly.io/register)## Scraping and Parsing Emirates Flight Data

The main scrape function sends a `ScrapeConfig` to Scrapfly with the scenario attached. Scrapfly's browser executes each step, waits for the Emirates results page to settle, and returns the full session output including all background XHR calls made during the session.

### Client and Configuration

python```python
import os
from scrapfly import ScrapeApiResponse, ScrapeConfig, ScrapflyClient

SCRAPFLY = ScrapflyClient(key=os.environ["SCRAPFLY_KEY"])

BASE_CONFIG = {
    "asp": True,
    "country": "US",
    "proxy_pool": "public_residential_pool",
    "render_js": True,
}
```



`asp=True` enables Scrapfly's anti-scraping protection bypass. `render_js=True` activates the managed browser. `proxy_pool` and `country` set the regional context. These values live in `BASE_CONFIG` so they can be overridden at the call site during development, for example setting `cache=True` to avoid repeat scrape costs while iterating on parse logic.

### Intercepting the Branded-Fares XHR Response

After the form submits and results load, Emirates fires a background request to `search-results/branded-fares` that carries all flight data as structured JSON. Scrapfly captures every XHR call made during the session and exposes them in `browser_data`. The parse function finds that specific call and returns the response body.

python```python
import json


def parse_branded_fares(response: ScrapeApiResponse) -> dict:
    _xhr_calls = response.scrape_result["browser_data"]["xhr_call"]
    for xhr in _xhr_calls:
        if "search-results/branded-fares" not in xhr.get("url", "") or not xhr.get("response"):
            continue
        return json.loads(xhr["response"]["body"])
    raise ValueError("branded-fares xhr call not found")
```



If the XHR call is not found, the function raises so the caller can detect a failed session early rather than returning an empty result silently. If this error appears repeatedly, set `debug=True` in `BASE_CONFIG` and review the session recording in the Scrapfly dashboard to confirm whether the form submission completed.

### Parsing the Lowest Fare

The branded-fares response includes a search-wide lowest fare field alongside the per-offer data.

python```python
def parse_lowest_fare(data: dict) -> FarePrice:
    currency = data.get("currency", {}).get("sale", {}).get("code", "")
    amount = data["lowestFare"]["total"][0]["amount"]
    return FarePrice(amount=amount, currency=currency)
```



### Parsing Flight Offers

The main parse function iterates over every bound in the response, extracts flight details from each option's air segments, then loops over cabins and fare brands to produce one `FlightResult` per available brand.

python```python
from datetime import datetime
from typing import List

CARRIER_NAMES = {"EK": "Emirates"}
CABIN_NAMES = {"Y": "economy", "W": "premium economy", "J": "business", "F": "first"}


def _format_arrival_time(departure_iso: str, arrival_iso: str) -> str:
    departure = datetime.fromisoformat(departure_iso)
    arrival = datetime.fromisoformat(arrival_iso)
    day_diff = (arrival.date() - departure.date()).days
    return arrival.strftime("%H:%M") + (f"+{day_diff}" if day_diff > 0 else "")


def _parse_layovers(segments: list) -> List[dict]:
    layovers = []
    for segment in segments:
        for stop in segment.get("stopDetails") or []:
            layovers.append({"airport": stop["arrival"], "duration": stop["duration"]})
        if segment.get("connection"):
            layovers.append(
                {"airport": segment["departure"], "duration": segment.get("connectionLayover")}
            )
    return layovers


def parse_flight_offers(data: dict) -> List[FlightResult]:
    currency = data.get("currency", {}).get("sale", {}).get("code", "")
    flights: List[FlightResult] = []

    for bound in data.get("bounds", []):
        for option in bound.get("options", []):
            segments = option.get("airSegments", [])
            if not segments:
                continue

            first_segment = segments[0]
            last_segment = segments[-1]
            layovers = _parse_layovers(segments)
            departure_time = datetime.fromisoformat(first_segment["departureDateTime"]).strftime("%H:%M")
            arrival_time = _format_arrival_time(
                first_segment["departureDateTime"], last_segment["arrivalDateTime"]
            )
            flight_number = " / ".join(
                f"{segment['carrierCode']} {segment['flightNumber']}"
                for segment in segments
                if segment.get("segmentType") == "FLT"
            )

            for cabin in option.get("cabins", []):
                for brand in cabin.get("brandInformation") or []:
                    if brand.get("status") != "AVAILABLE":
                        continue

                    fare_amount = brand["priceDetails"]["summary"]["total"][0]["amount"]
                    carrier_code = first_segment.get("carrierCode", "")
                    cabin_code = brand.get("cabinClass") or cabin.get("cabinClass", "")
                    flights.append(
                        FlightResult(
                            airline=CARRIER_NAMES.get(carrier_code, carrier_code),
                            flight_number=flight_number,
                            departure_time=departure_time,
                            departure_airport=first_segment["departure"],
                            arrival_time=arrival_time,
                            arrival_airport=last_segment["arrival"],
                            duration=option.get("ondDuration", ""),
                            stops=option.get("numberOfConnections", 0),
                            layovers=layovers,
                            price=FarePrice(amount=fare_amount, currency=currency),
                            cabin_class=CABIN_NAMES.get(cabin_code, cabin_code),
                            plane_model=first_segment.get("aircraftType", ""),
                            fare_brand=brand.get("fareBrand", ""),
                            seats_available=brand.get("seatsAvailable", 0),
                            captured_at=datetime.now().isoformat(),
                        )
                    )

    return flights
```



`_format_arrival_time` handles overnight arrivals by appending `+N` to the time string when the arrival date is later than the departure date. `_parse_layovers` collects stop details from two sources: `stopDetails` entries within a segment and connection markers between segments. Only brands with `status == "AVAILABLE"` are included. Brands with any other status represent unavailable or sold-out fare tiers.

### The Main Scrape Function

python```python
async def scrape_flights(
    origin: str,
    destination: str,
    departure_date: str,
    return_date: Optional[str] = None,
    locale: str = "us/english",
) -> FlightSearch:
    response = await SCRAPFLY.async_scrape(
        ScrapeConfig(
            f"https://www.emirates.com/{locale}/book/",
            **BASE_CONFIG,
            js_scenario=_build_search_scenario(origin, destination, departure_date, return_date),
        )
    )
    data = parse_branded_fares(response)
    return FlightSearch(
        locale=locale,
        trip_type="return" if return_date else "one-way",
        origin=origin,
        destination=destination,
        route=f"{origin}-{destination}",
        search_date=datetime.now().strftime("%Y-%m-%d"),
        departure_date=departure_date,
        return_date=return_date,
        lowest_fare=parse_lowest_fare(data),
        flights=parse_flight_offers(data),
    )
```



`scrape_flights` builds a `ScrapeConfig` for the Emirates booking page with the search scenario attached, runs the scrape, extracts the branded-fares data from the captured XHR calls, and assembles a `FlightSearch` result. The `locale` parameter controls the URL path and locale metadata. The proxy country remains configured separately in BASE\_CONFIG and is not currently included in the returned FlightSearch object.

The runner below executes one-way and round-trip searches and writes both results to JSON.



## Running the Emirates Scraper

The `run.py` script in the repository shows how to invoke `scrape_flights` for both a round-trip search and a one-way search, then save each result as JSON.

python```python
import asyncio
import json
from datetime import datetime, timedelta
from pathlib import Path

import emirates

output = Path(__file__).parent / "results"
output.mkdir(exist_ok=True)

TODAY = datetime.now().strftime("%Y-%m-%d")
WEEK_FROM_NOW = (datetime.now() + timedelta(days=7)).strftime("%Y-%m-%d")


async def run():
    emirates.BASE_CONFIG["cache"] = False
    emirates.BASE_CONFIG["debug"] = True

    result = await emirates.scrape_flights(
        origin="JFK",
        destination="DXB",
        departure_date=TODAY,
        return_date=WEEK_FROM_NOW,
        locale="us/english",
    )
    with open(output / "roundtrip.json", "w", encoding="utf-8") as f:
        json.dump(result, f, indent=2, ensure_ascii=False)

    result = await emirates.scrape_flights(
        origin="JFK",
        destination="DXB",
        departure_date=TODAY,
        locale="us/english",
    )
    with open(output / "oneway.json", "w", encoding="utf-8") as f:
        json.dump(result, f, indent=2, ensure_ascii=False)


if __name__ == "__main__":
    asyncio.run(run())
```



Run it with:

shell```shell
python run.py
```



Results are saved to `results/roundtrip.json` and `results/oneway.json`. Setting `debug=True` records the full browser session in the Scrapfly dashboard, which is useful for diagnosing scenario failures during development.

A successful one-way result for JFK to DXB looks like this:

json```json
{
  "locale": "us/english",
  "trip_type": "one-way",
  "origin": "JFK",
  "destination": "DXB",
  "route": "JFK-DXB",
  "search_date": "2026-06-09",
  "departure_date": "2026-06-09",
  "return_date": null,
  "lowest_fare": {
    "amount": 612.9,
    "currency": "USD"
  },
  "flights": [
    {
      "airline": "Emirates",
      "flight_number": "EK 202",
      "departure_time": "23:00",
      "departure_airport": "JFK",
      "arrival_time": "20:10+1",
      "arrival_airport": "DXB",
      "duration": "13H10M",
      "stops": 0,
      "layovers": [],
      "price": {
        "amount": 612.9,
        "currency": "USD"
      },
      "cabin_class": "economy",
      "plane_model": "388",
      "fare_brand": "SAVER",
      "seats_available": 5,
      "captured_at": "2026-06-09T21:09:35.482762"
    }
  ]
}
```



Each `FlightResult` in the `flights` array represents a single fare brand for a specific flight. The same physical flight appears multiple times if multiple fare brands are available for it, which lets you compare pricing across Special, Saver, Flex, and Flex Plus within a single result set.



## Bypass Emirates Blocking with Scrapfly

Emirates uses bot detection, geographic access control, and session fingerprinting to limit automated access. The symptoms a scraper sees range from missing XHR calls to challenge pages. Grouping responses by symptom is faster than reading through anti-bot theory.

| Symptom | Likely cause | Response |
|---|---|---|
| `branded-fares xhr call not found` error | Scenario did not complete; results never loaded | Set `debug=True`, review the session recording, recheck selectors |
| Empty results or wrong currency | Proxy country and on-page locale do not match | Set `country` in `BASE_CONFIG`; load the matching regional Emirates URL |
| Challenge or captcha page | Bot detection triggered | `asp=True` is already set; confirm `proxy_pool` is set to residential |
| Scenario step fails silently | Emirates updated its markup | Add a debug screenshot step; recheck selectors against the live DOM |
| High credit usage per run | Full page assets loading on every test run | Set `cache=True` during development to avoid repeat costs |

Running browsers locally with rotating residential proxies and custom fingerprint management is the expensive part of scraping a site like Emirates. Scrapfly handles that layer so the script can focus on scenario logic and data extraction.

ScrapFly's [Web Scraping API](https://scrapfly.io/products/web-scraping-api) is a single HTTP endpoint for collecting web data at scale, with a **98% bypass success rate**, support for **20+ anti-bot vendors**, and proxy geo-targeting in **190+ countries**.

- [Anti-Scraping Protection bypass](https://scrapfly.io/docs/scrape-api/anti-scraping-protection) - handles Cloudflare, DataDome, PerimeterX, Akamai, and other supported anti-bot vendors.
- [Smart proxy rotation](https://scrapfly.io/docs/scrape-api/proxy) - residential and datacenter pools with country and ASN level geo-targeting.
- [JavaScript rendering](https://scrapfly.io/docs/scrape-api/javascript-rendering) - render SPAs and dynamic pages through real cloud browsers.
- [Browser automation scenarios](https://scrapfly.io/docs/scrape-api/javascript-scenario) - scroll, click, fill forms, and wait for elements without managing a browser fleet.
- [Format conversion](https://scrapfly.io/docs/scrape-api/getting-started#api_param_format) - return pages as HTML, JSON, clean text, or LLM ready Markdown.
- [Session management](https://scrapfly.io/docs/scrape-api/session) - keep cookies, headers, and IPs consistent across multi step flows.
- [Smart caching](https://scrapfly.io/docs/scrape-api/getting-started#api_param_cache) - cache successful responses to cut cost on repeat scraping jobs.
- [Python](https://scrapfly.io/docs/sdk/python), [TypeScript](https://scrapfly.io/docs/sdk/typescript), [Scrapy](https://scrapfly.io/docs/sdk/scrapy), and [no-code integrations](https://scrapfly.io/docs/integration/getting-started) including Make, n8n, Zapier, LangChain, and LlamaIndex.

See the [Web Scraping API docs](https://scrapfly.io/docs/scrape-api/getting-started) for the full parameter reference.

For more about how to bypass anti-bot protection:

[How to Bypass Anti-Bot Protection When Web ScrapingLearn how anti-bot systems detect scrapers and 5 universal bypass techniques including proxy rotation, fingerprinting, and fortified headless browsers.](https://scrapfly.io/blog/posts/how-to-bypass-anti-bot-protection-when-web-scraping)

If you want more on how to bypass CAPTCHAs:

[5 Proven Ways to Bypass CAPTCHA in Python for 2026Captchas can ruin web scrapers but we don't have to teach our robots how to solve them - we can just get around it all!](https://scrapfly.io/blog/posts/how-to-bypass-captcha-web-scraping)



## FAQ

Is there an Emirates API for flight data or prices?Emirates does not expose a general public fare-search API. Approved airline-distribution or partner feeds may cover some use cases; compare their fields, access requirements, freshness, and cost before choosing public-page extraction.







Can BeautifulSoup scrape Emirates flight results?[BeautifulSoup](https://scrapfly.io/blog/posts/web-scraping-with-python-beautifulsoup) parses HTML but does not execute JavaScript. Emirates flight results only appear after a multi-step browser session renders the page.







Can this Emirates scraper work for Air France or other airlines?The Web Scraping API browser-automation workflow can be adapted to other airlines, but each site requires its own selectors, request parsing, anti-bot configuration, and validation.









## Summary

In this guide, we walked through the [scrapfly/scrapfly-scrapers emirates scraper](https://github.com/scrapfly/scrapfly-scrapers/tree/main/emirates-scraper), a Python scraper that drives Emirates search and extracts structured offer data. We covered:

- Defining search inputs including route, trip type, departure date, and proxy country context.
- Defining `TypedDict` models for structured, typed output.
- Building a `js_scenario` that drives the Emirates search form through cookie dismissal, airport entry, date selection, and form submission.
- Running the scenario with Scrapfly and intercepting the `branded-fares` XHR response.
- Parsing flight offers, fare brands, layovers, and the search-wide lowest fare from the JSON payload.
- Running both one-way and round-trip searches and saving results as JSON.

To avoid being blocked and to skip the overhead of running browsers locally, rotating residential proxies, and handling captchas, we used Scrapfly Web Scraping API so the Python code can focus on scenario logic and data extraction.



Legal Disclaimer and PrecautionsThis tutorial covers popular web scraping techniques for education. Interacting with public servers requires diligence and respect:

- Do not scrape at rates that could damage the website.
- Do not scrape data that's not available publicly.
- Do not store PII of EU citizens protected by GDPR.
- Do not repurpose *entire* public datasets which can be illegal in some countries.

Scrapfly does not offer legal advice but these are good general rules to follow. For more you should consult a lawyer.

 

   [  Add as a preferred source ](https://google.com/preferences/source?q=scrapfly.io) Table of Contents















 

  Table of Contents- [Key Takeaways](#key-takeaways)
- [Why Scrape Emirates Flight Data?](#why-scrape-emirates-flight-data)
- [Project Setup](#project-setup)
- [How to Find Emirates Flights to Scrape](#how-to-find-emirates-flights-to-scrape)
- [Defining the Data Models](#defining-the-data-models)
- [Building the Emirates Search Automation Scenario](#building-the-emirates-search-automation-scenario)
- [Airport Field Helpers](#airport-field-helpers)
- [Date Picker Helpers](#date-picker-helpers)
- [Full Scenario Builder](#full-scenario-builder)
- [Scraping and Parsing Emirates Flight Data](#scraping-and-parsing-emirates-flight-data)
- [Client and Configuration](#client-and-configuration)
- [Intercepting the Branded-Fares XHR Response](#intercepting-the-branded-fares-xhr-response)
- [Parsing the Lowest Fare](#parsing-the-lowest-fare)
- [Parsing Flight Offers](#parsing-flight-offers)
- [The Main Scrape Function](#the-main-scrape-function)
- [Running the Emirates Scraper](#running-the-emirates-scraper)
- [Bypass Emirates Blocking with Scrapfly](#bypass-emirates-blocking-with-scrapfly)
- [FAQ](#faq)
- [Summary](#summary)
 
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