We extract flight schedules, dynamic pricing, route networks, and seat availability from Tunisair. Delivered as clean JSON, CSV, or Parquet to S3, BigQuery, or Snowflake on your cadence.
Structured, schema-consistent data across all major object types — delivered clean, typed, and ready to query.
Complete list of extractable fields for Flight Schedules objects from tunisair.com. All fields typed and schema-versioned.
"flight_number": "TU 711", "origin": "TUN", "destination": "ORY", "departure_time": "2026-05-12T08:00:00Z", "arrival_time": "2026-05-12T10:30:00Z", "aircraft_type": "Airbus A320", "duration": "150m", "operating_carrier": "Tunisair"
| # | flight_number | origin | destination | departure_time | arrival_time | duration |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Pricing & Fares objects from tunisair.com. All fields typed and schema-versioned.
"flight_number": "TU 711", "cabin_class": "Economy", "base_price": 150.0, "taxes": 45.5, "total_price": 195.5, "currency": "EUR", "refundable": false, "baggage_included": true
| # | flight_number | cabin_class | fare_basis | base_price | taxes | total_price |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Route Network objects from tunisair.com. All fields typed and schema-versioned.
"origin_airport": "TUN", "destination_airport": "ORY", "direct_flight": true, "frequency_per_week": 14, "distance": 1475, "seasonality": "Year-round", "connection_airports": "[]"
| # | origin_airport | destination_airport | distance | direct_flight | frequency_per_week | seasonality |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Seat Availability objects from tunisair.com. All fields typed and schema-versioned.
"flight_number": "TU 711", "departure_date": "2026-05-12", "cabin_class": "Business", "available_seats": 4, "overbooked": false, "waitlist_open": false, "seat_pitch": "36 inches"
| # | flight_number | departure_date | cabin_class | available_seats | seat_map_url | overbooked |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Flight Status objects from tunisair.com. All fields typed and schema-versioned.
"flight_number": "TU 711", "date": "2026-05-12", "status": "On Time", "scheduled_departure": "08:00", "actual_departure": "08:05", "terminal_departure": "1", "gate_departure": "A12"
| # | flight_number | date | scheduled_departure | actual_departure | scheduled_arrival | actual_arrival |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our Tunisair scraper handles complex booking flows, session management, and dynamic pricing logic with JavaScript rendering and anti-bot circumvention built in.
Capture departure times, arrival times, aircraft types, and flight durations across the entire Tunisair network.
Extract base fares, taxes, and total prices for all cabin classes. Timestamped per crawl for accurate historical tracking.
Isolate base fares from airport taxes, fuel surcharges, and regulatory fees to normalise pricing data.
Extract specific fare rules, refundability, exchange conditions, and baggage allowances for Economy and Business classes.
Track included checked baggage weight, cabin baggage limits, and excess baggage fees per route and fare class.
Monitor scheduled versus actual departure times, terminal assignments, and gate changes for operational intelligence.
Scrape complex itineraries and connection times for flights routed through Tunis-Carthage International Airport.
Identify operating aircraft models and equipment changes across scheduled routes.
Run bulk schedule exports or configure continuous pipelines for real-time price monitoring.
Brief in. Clean data out.
Provide origin-destination pairs, date ranges, or flight numbers. We design the extraction schema together.
We configure Scrapy and Playwright crawlers, proxy rotation, and session management for tunisair.com.
Schema validation, null-rate checks, and price-outlier detection before full launch.
JSON, CSV, or Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Airline booking engines utilise aggressive session tracking and rate limiting. Here is how we maintain extraction stability.
Airline websites rely on stateful booking flows. We manage session cookies, token exchanges, and hidden form fields to progress through search results without triggering abandonment errors.
Pricing data often requires an active session token. Our infrastructure holds sessions open across proxy IP rotations to extract full fare breakdowns without restarting the search flow.
Airlines rate-limit aggressively. We route requests through residential proxies, matching request headers and TLS fingerprints to normalise traffic patterns and avoid IP bans.
We hash schedule and pricing data per route. Subsequent runs only push diffs, reducing compute cost and downstream processing load for your engineering team.
Every run emits structured logs to our observability stack. We alert on null-rate spikes, schema drift, and coverage drops, responding before you notice.
Online travel agencies integrate direct pricing and availability feeds to bypass expensive GDS distribution costs.
Rival airlines and travel platforms track Tunisair pricing strategies on overlapping routes to optimise their own fare structures.
Aviation analysts monitor frequency changes, seasonal route launches, and capacity adjustments across the Tunisair network.
Data teams correlate historical pricing data with booking curves to build predictive models for future fare movements.
Travel management companies monitor flight status and schedule changes to proactively rebook corporate clients during delays.
Large enterprises audit flight availability and pricing to negotiate direct corporate discount agreements.
"Tunisair pricing data shifts constantly based on load factors and booking curves, requiring persistent session management to extract accurate fares."
Airlines employ sophisticated anti-scraping measures, relying on complex session tokens and strict rate limits. DataFlirt manages the residential proxies, JavaScript rendering, and session persistence required to extract clean flight data, allowing your engineering team to focus on downstream analysis rather than maintaining fragile web scrapers.
Everything supported by our tunisair.com scraper — rendered SPA elements, auth walls, rate-limit evasion and beyond.
Open-source tooling on proven cloud infra — no vendor lock-in, full observability.
Scrapy orchestrates crawl logic and deduplication. Playwright executes JavaScript and manages session states required for complex booking engines.
We maintain pools of residential ISP proxies. Rotation happens per request with sticky sessions to maintain active flight searches without triggering bans.
Pipelines run on AWS Lambda and ECS. Airflow handles scheduling and dependency management. State is stored in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About tunisair.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available flight schedules and pricing data is generally permissible. DataFlirt extracts only public, non-authenticated information. We do not access Fidelys accounts or passenger PNR data. Clients should consult legal counsel regarding their specific usage.
We utilise residential ISP proxies and manage session states meticulously. Our crawlers replicate human browsing behaviour, balancing request concurrency to avoid triggering IP blocks while maintaining extraction throughput.
Yes. We navigate to the fare breakdown views to separate the base fare from fuel surcharges, airport taxes, and regulatory fees.
Pipelines can be configured for daily sweeps or high-frequency hourly updates on specific high-value routes to capture dynamic pricing shifts.
Yes. We can configure searches for specific multi-city routing requirements, capturing total itinerary pricing and connection details.
Our packages start at a defined list of origin-destination pairs with daily delivery. Contact us with your route list for a scoped quote.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a daily schedule dump or continuous price monitoring across thousands of routes, we scope, build, and operate the pipeline. Tell us what you need.
