We extract public running routes, elevation profiles, GPS coordinates, and trail metadata from MapMyRun. 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 Route Metadata objects from mapmyrun.com. All fields typed and schema-versioned.
"route_id": "12345890", "name": "Hyde Park Outer Loop", "city": "London", "country": "UK", "distance_km": 7.2, "climb_m": 35.4, "surface_type": "paved"
| # | route_id | name | city | country | distance_km | climb_m |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Elevation Profile objects from mapmyrun.com. All fields typed and schema-versioned.
"max_elevation_m": 45.5, "min_elevation_m": 12.0, "total_ascent_m": 35.4, "total_descent_m": 35.4, "grade_pct": 1.2, "highest_point_lat": 51.5074, "highest_point_lng": -0.1657
| # | route_id | max_elevation_m | min_elevation_m | total_ascent_m | total_descent_m | elevation_points |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Waypoints & Coordinates objects from mapmyrun.com. All fields typed and schema-versioned.
"waypoint_index": 42, "lat": 51.5074, "lng": -0.1657, "distance_from_start_km": 3.1, "point_type": "turn", "street_name": "Serpentine Road", "elevation_m": 22.1
| # | route_id | waypoint_index | lat | lng | distance_from_start_km | point_type |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Location & Tourism objects from mapmyrun.com. All fields typed and schema-versioned.
"city": "London", "neighborhood": "Hyde Park", "starting_point_poi": "Marble Arch", "ending_point_poi": "Kensington Palace", "nearby_attractions": "['The Serpentine', "Speaker's Corner"]", "scenic_rating": 4.8
| # | route_id | city | state | country | neighborhood | starting_point_poi |
|---|---|---|---|---|---|---|
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Complete list of extractable fields for Creator & Social objects from mapmyrun.com. All fields typed and schema-versioned.
"creator_username": "london_runner_99", "route_views": 48291, "route_saves": 1204, "comment_count": 14, "is_verified": false, "rating_score": 4.7
| # | route_id | creator_username | creator_level | route_views | route_saves | comment_count |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Our MapMyRun scraper extracts high-density coordinate arrays, elevation profiles, and route metadata from public trails. We handle the geospatial parsing and API interception so you get clean, queryable location data.
Extract route name, distance, total ascent, surface type, and city location for millions of public running and cycling paths.
Capture the complete array of latitude and longitude coordinates that form a route, indexed sequentially for mapping.
Extract point-by-point altitude data, calculating maximum elevation, minimum elevation, and overall grade percentage.
Filter and extract all public routes within a specific bounding box, city, or postal code for urban mobility analysis.
Track route views, save counts, and user ratings to identify the most trafficked pedestrian paths in any region.
Identify whether routes are paved, gravel, trail, or mixed surface based on user tags and metadata.
Isolate the exact starting and ending coordinates to map trailheads, park entrances, and transit proximity.
Run monthly or quarterly pipelines to capture new user-generated routes and update popularity metrics.
Extract routes from any country or region supported by the platform, completely normalised into a single format.
Brief in. Clean data out.
Provide target cities, bounding boxes, or route distance filters. We map the extraction parameters.
We configure API interceptors to capture raw coordinate arrays and elevation profiles directly from the backend.
We validate coordinate geometry, check for incomplete paths, and normalise elevation metrics.
GeoJSON, CSV, or Parquet delivered to your S3 bucket, BigQuery dataset, or PostGIS database.
Extracting routes requires parsing complex JSON arrays and intercepting dynamic map rendering APIs. Here is how we build pipelines for geospatial data.
MapMyRun renders routes visually on a map canvas. We intercept the backend XHR requests to capture the raw JSON coordinate arrays before they are drawn, ensuring zero precision loss.
Long routes like marathon courses contain tens of thousands of coordinate pairs. Our parsers handle paginated or chunked geospatial data streams without truncating the path.
Raw coordinate lists are converted into standard GeoJSON LineStrings or Well-Known Text (WKT) formats natively within the pipeline, ready for immediate spatial querying.
Extracting high-resolution elevation data triggers strict API rate limits. We distribute requests across thousands of residential IPs to maintain throughput without being blocked.
User-generated GPS data often contains anomalous jumps or zero-coordinates. We apply basic geometric validation to flag or remove broken route segments before delivery.
Travel platforms integrate popular running routes into city guides, offering tourists curated, safe paths based on local behaviour.
City planners analyse public running and cycling routes to identify high-traffic pedestrian corridors and prioritise infrastructure investments.
New fitness applications populate their initial databases with established public routes to solve the cold-start problem.
Property platforms calculate proximity to popular running trails and parks, adding active-lifestyle scores to neighbourhood profiles.
Event organisers analyse user-generated marathon and half-marathon routes to identify optimal race paths and aid station locations.
Parks departments correlate route popularity metrics with surface types to predict wear and schedule trail maintenance.
"MapMyRun holds the definitive dataset for global pedestrian movement and recreational routing, but extracting million-point coordinate arrays requires specialised pipelines."
Extracting route data goes beyond simple HTML parsing. Rendering complex GPX paths, elevation arrays, and waypoint metadata requires intercepting backend API responses and handling massive JSON payloads. DataFlirt manages the proxy rotation and coordinate parsing so your geospatial team can focus on analysis.
Everything supported by our mapmyrun.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.
Playwright loads the initial application state while Scrapy intercepts the backend XHR requests containing the raw JSON coordinate arrays, bypassing the map canvas.
We maintain pools of residential IPs to bypass rate limits on high-density API endpoints. Sticky sessions ensure complete route arrays are downloaded without interruption.
Pipelines run on AWS ECS. Airflow handles scheduling and dependency management. Geospatial validation and formatting occur in memory before delivery to your warehouse.
Data delivered to where your team already works — no new tooling required.
About mapmyrun.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available, user-generated routes is generally permissible under applicable law. DataFlirt extracts only public routes and aggregated metrics. We do not extract private workout histories, live tracking data, or circumvent authentication walls. Clients should review Terms of Service and consult legal counsel for specific use cases.
Yes. We can define a bounding box or city parameter and extract all public routes within that area, filtered by distance, climb, or surface type.
We extract the raw latitude, longitude, and elevation arrays. During the pipeline process, we can format these into standard GeoJSON LineStrings or WKT strings so they are ready for PostGIS or BigQuery.
No. We strictly extract publicly shared routes and trails. Personal workout logs, heart rate data, and live tracking are gated behind user authentication and fall outside our extraction scope.
For city-wide aggregations, we typically run monthly or quarterly refreshes to capture newly created public routes and update popularity metrics like view counts.
Our minimum engagement typically starts at extracting 10,000 routes within defined target regions. Pricing scales based on coordinate density and delivery frequency.
Yes. We provide a sample of 100 routes from a requested city, including full coordinate arrays and elevation profiles, to validate schema compatibility before contracting.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off export of city trails or a continuous feed of new public routes, we scope, build, and operate the pipeline. Tell us what you need.
