We extract train schedules, seat availability, dynamic fare charts, route maps, and station metadata from IRCTC. 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 Train Schedules objects from irctc.co.in. All fields typed and schema-versioned.
"train_number": "12951", "train_name": "MUMBAI RAJDHANI", "source_station": "MMCT", "dest_station": "NDLS", "departure_time": "17:00", "arrival_time": "08:32"
| # | train_number | train_name | source_station | dest_station | departure_time | arrival_time |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Seat Availability objects from irctc.co.in. All fields typed and schema-versioned.
"train_number": "12951", "date": "2026-10-14", "class_type": "3A", "quota": "GN", "available_seats": 0, "waitlist_status": "WL45"
| # | train_number | date | class_type | quota | available_seats | waitlist_status |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Fare Data objects from irctc.co.in. All fields typed and schema-versioned.
"train_number": "12951", "class_type": "3A", "base_fare": 1850.0, "reservation_charge": 40.0, "superfast_charge": 45.0, "total_fare": 2150.0
| # | train_number | class_type | base_fare | reservation_charge | superfast_charge | gst |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Route Map objects from irctc.co.in. All fields typed and schema-versioned.
"train_number": "12951", "station_code": "ST", "station_name": "SURAT", "arrival_time": "19:43", "departure_time": "19:48", "halt_duration": "5m"
| # | train_number | station_code | station_name | arrival_time | departure_time | halt_duration |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Station Metadata objects from irctc.co.in. All fields typed and schema-versioned.
"station_code": "NDLS", "station_name": "NEW DELHI", "zone": "NR", "state": "Delhi", "number_of_platforms": 16, "latitude": 28.6415
| # | station_code | station_name | zone | state | division | latitude |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Our IRCTC scraper handles every layer of the platform: train schedules, real-time seat availability, route maps, and dynamic fare charts, with session management and anti-bot circumvention built in.
Train names, numbers, running days, source, destination, and exact timings scraped across the entire railway network.
Track available seats, RAC status, and Waitlist numbers across all classes and quotas for any given date.
Extract base fares, reservation charges, GST, and dynamic pricing multipliers applied to premium trains.
Parse complete route maps including intermediate stations, arrival times, departure times, and halt durations.
Batch query PNR numbers to track confirmation status, chart preparation, and current passenger status.
Monitor seat availability across General, Tatkal, Premium Tatkal, Ladies, and Senior Citizen quotas.
Extract station codes, full names, zones, states, and platform details to normalise your internal databases.
Track data across 1A, 2A, 3A, SL, CC, EC, and 2S classes simultaneously.
Run one-off bulk exports or configure continuous pipelines at hourly, daily, or real-time cadences.
Brief in. Clean data out.
Provide train numbers, station codes, or route pairs. We design the extraction schema together.
We configure Scrapy and Playwright crawlers, proxy rotation, session management, and CAPTCHA handling for irctc.co.in.
Schema validation, null-rate checks, and availability outlier detection before full launch.
JSON, CSV, or Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
IRCTC invests heavily in scraping detection and rate limiting. Here is how we stay resilient, and why teams choose managed infrastructure over DIY.
IRCTC deploys complex image and text CAPTCHAs during login and availability queries. We route these challenges through 2Captcha and CapSolver APIs with automated retry logic to maintain pipeline throughput.
IRCTC terminates idle sessions aggressively. Our Playwright orchestrator maintains active heartbeat requests, rotates cookies, and handles forced logouts without dropping data payloads.
Querying availability too quickly results in IP bans. We distribute requests across Indian residential proxy pools, injecting randomised delays to mimic human interaction and avoid rate limit thresholds.
The IRCTC web application relies on complex, nested DOM structures that change without notice. Our selector strategy uses structural fallbacks to ensure data extraction continues even when UI elements shift.
During peak booking windows (10:00 AM and 11:00 AM), IRCTC servers routinely throw 503 errors. Our pipelines implement exponential backoff and automatic scaling to capture data when the servers recover.
Travel agencies use schedule and availability data to construct alternative routing options for waitlisted passengers.
Aggregators combine IRCTC schedules with flight and bus data to offer multi-modal transport itineraries.
Competitor transport providers track dynamic fare surges on premium trains to optimise their own pricing algorithms.
Supply chain teams monitor train running status and schedules to coordinate last-mile delivery operations at railway stations.
Analysts correlate waitlist velocity and seat depletion rates to predict regional travel demand during festivals.
Machine learning teams use historical schedule and delay datasets to train predictive models for train punctuality.
"IRCTC is the backbone of Indian travel data, but its infrastructure is notoriously difficult to query programmatically at scale."
Most teams underestimate the investment required: reliable IRCTC scraping requires Indian residential proxies, complex CAPTCHA solving, strict session management, and handling aggressive rate limits. DataFlirt absorbs that complexity so your engineers can focus on the analysis, not the infrastructure.
Everything supported by our irctc.co.in 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 handles crawl orchestration and retry logic. Playwright handles JavaScript rendering, cookie sessions, and interaction flows required by the IRCTC portal.
We maintain pools of residential ISP proxies across Indian regions. Rotation happens per request with sticky sessions to bypass IRCTC rate limits.
Pipelines run on AWS Lambda and ECS. Airflow handles scheduling, dependency management, and SLA alerting. All state stored in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About irctc.co.in scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available train schedules and availability data is generally permissible. DataFlirt targets only public, non-authenticated route and fare data. We do not automate ticket purchasing or bypass payment gateways. Clients should review IRCTC terms of service and consult legal counsel for specific use cases.
We route image and text CAPTCHAs through automated solving APIs like 2Captcha and CapSolver. For complex interactions, we maintain fallback queues to ensure pipeline continuity.
Yes. While IRCTC servers experience severe congestion between 10:00 AM and 11:15 AM, our pipelines use exponential backoff and retry logic to capture availability data as soon as the servers respond.
Real-time streaming pipelines achieve sub-5-minute latency for seat availability signals on a defined set of train numbers and dates.
Yes. We extract base fares, reservation charges, GST, and the dynamic fare multipliers applied to premium trains like Rajdhani, Shatabdi, and Duronto.
Our smallest packages start at a defined list of 500 routes or train numbers with daily delivery. For larger network scans or real-time polling, we price based on volume and frequency. Contact us for a scoped quote.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a static database of station codes or a continuous availability feed across 10,000 routes, we scope, build, and operate the pipeline. Tell us what you need.
