# EcoBici CDMX Trip Data Scraper (`jungle_synthesizer/ecobici-cdmx-trip-data-scraper`) Actor Scrapes historical trip CSVs (back to 2010) and live GBFS station feeds from EcoBici — CDMX's Lyft-operated bike-share with 480+ stations and 10M+ trips per year. - **URL**: https://apify.com/jungle\_synthesizer/ecobici-cdmx-trip-data-scraper.md - **Developed by:** [BowTiedRaccoon](https://apify.com/jungle_synthesizer) (community) - **Categories:** Travel - **Stats:** 2 total users, 1 monthly users, 71.4% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing Pay per event This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## EcoBici CDMX Trip Data Scraper Extract historical trip records and live station data from [EcoBici](https://www.ecobici.cdmx.gob.mx/datos-abiertos/) — Mexico City's Lyft-operated public bike-share network with 480+ stations and over 10 million trips per year. ### What this actor does - **Downloads and stream-parses historical monthly trip CSVs** going back to 2010 (97 MB+ per monthly file) - **Fetches live GBFS station data** — station names, coordinates, dock capacity, and real-time service status - **Enriches trip records** with origin and destination station details (lat/lng, capacity, operational status) - Respects memory constraints via streaming CSV parsing — files are never buffered in full ### Input | Field | Type | Default | Description | |-------|------|---------|-------------| | `mode` | string | `both` | What to fetch: `trips` (historical CSVs), `stations` (live GBFS), or `both` | | `yearFrom` | integer | current year | Earliest year to include in historical trip data | | `yearTo` | integer | current year | Latest year to include in historical trip data | | `maxItems` | integer | unlimited | Cap on total output records | ### Output Each record contains: | Field | Description | |-------|-------------| | `trip_id` | Row-level identifier (`YYYY-MM-`) | | `bike_id` | Bike identifier from the source CSV | | `user_gender` | Rider gender (M/F) | | `user_age` | Rider age in years | | `origin_station_id` | Numeric station ID (origin) | | `destination_station_id` | Numeric station ID (destination) | | `origin_station_name` | Station name from GBFS | | `destination_station_name` | Station name from GBFS | | `origin_lat` / `origin_lng` | Station coordinates | | `destination_lat` / `destination_lng` | Station coordinates | | `depart_at` | Departure datetime (ISO 8601) | | `arrive_at` | Arrival datetime (ISO 8601) | | `duration_seconds` | Trip duration in seconds | | `trip_type` | `docked` (standard docked bike) | | `month` | Source month (`YYYY-MM`) | | `year` | Source year | | `source_csv_url` | URL of the CSV file | | `station_capacity` | Total dock slots at origin station | | `station_status` | `IN_SERVICE` or `NOT_IN_SERVICE` | | `source_url` | EcoBici open data page URL | | `scraped_at` | ISO 8601 scrape timestamp | ### Use cases - Urban mobility research and transportation policy analysis - Last-mile connectivity studies (Roma, Condesa, Polanco, Centro Historico) - Station-level demand forecasting and rebalancing optimization - Academic research on bike-share systems in Latin America - Housing density and real estate proximity signals ### Notes - Monthly CSV files for recent years are approximately 97 MB each. Runs that request multiple years will take proportionally longer. - Station enrichment relies on the live GBFS feed at the time of each run. Decommissioned stations may not appear in the GBFS but will still appear in historical CSVs. - The actor uses streaming CSV parsing with no in-memory buffering — memory usage stays well below 1 GB even for large historical downloads. # Actor input Schema ## `sp_intended_usage` (type: `string`): Please describe how you plan to use the data extracted by this crawler. ## `sp_improvement_suggestions` (type: `string`): Provide any feedback or suggestions for improvements. ## `sp_contact` (type: `string`): Provide your email address so we can get in touch with you. ## `maxItems` (type: `integer`): Maximum number of trip records to scrape. Leave blank for all records. ## `mode` (type: `string`): What data to fetch: 'trips' (historical CSV data), 'stations' (live GBFS station feed), or 'both' (default). ## `yearFrom` (type: `integer`): Earliest year to include in historical trip data (e.g. 2023). Defaults to current year only. ## `yearTo` (type: `integer`): Latest year to include in historical trip data. Defaults to current year. ## Actor input object example ```json { "sp_intended_usage": "Describe your intended use...", "sp_improvement_suggestions": "Share your suggestions here...", "sp_contact": "Share your email here...", "maxItems": 10, "mode": "both", "yearFrom": 2026, "yearTo": 2026 } ```` # Actor output Schema ## `results` (type: `string`): No description # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "sp_intended_usage": "Describe your intended use...", "sp_improvement_suggestions": "Share your suggestions here...", "sp_contact": "Share your email here...", "maxItems": 10, "mode": "both", "yearFrom": 2026, "yearTo": 2026 }; // Run the Actor and wait for it to finish const run = await client.actor("jungle_synthesizer/ecobici-cdmx-trip-data-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "sp_intended_usage": "Describe your intended use...", "sp_improvement_suggestions": "Share your suggestions here...", "sp_contact": "Share your email here...", "maxItems": 10, "mode": "both", "yearFrom": 2026, "yearTo": 2026, } # Run the Actor and wait for it to finish run = client.actor("jungle_synthesizer/ecobici-cdmx-trip-data-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "sp_intended_usage": "Describe your intended use...", "sp_improvement_suggestions": "Share your suggestions here...", "sp_contact": "Share your email here...", "maxItems": 10, "mode": "both", "yearFrom": 2026, "yearTo": 2026 }' | apify call jungle_synthesizer/ecobici-cdmx-trip-data-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=jungle_synthesizer/ecobici-cdmx-trip-data-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "EcoBici CDMX Trip Data Scraper", "description": "Scrapes historical trip CSVs (back to 2010) and live GBFS station feeds from EcoBici — CDMX's Lyft-operated bike-share with 480+ stations and 10M+ trips per year.", "version": "0.1", "x-build-id": "TxrSK7ADm7fckLe2e" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/jungle_synthesizer~ecobici-cdmx-trip-data-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-jungle_synthesizer-ecobici-cdmx-trip-data-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/jungle_synthesizer~ecobici-cdmx-trip-data-scraper/runs": { "post": { "operationId": "runs-sync-jungle_synthesizer-ecobici-cdmx-trip-data-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/jungle_synthesizer~ecobici-cdmx-trip-data-scraper/run-sync": { "post": { "operationId": "run-sync-jungle_synthesizer-ecobici-cdmx-trip-data-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "required": [ "mode" ], "properties": { "sp_intended_usage": { "title": "What is the intended usage of this data?", "minLength": 1, "type": "string", "description": "Please describe how you plan to use the data extracted by this crawler." }, "sp_improvement_suggestions": { "title": "How can we improve this crawler for you?", "minLength": 1, "type": "string", "description": "Provide any feedback or suggestions for improvements." }, "sp_contact": { "title": "Contact Email", "minLength": 1, "type": "string", "description": "Provide your email address so we can get in touch with you." }, "maxItems": { "title": "Max Items", "type": "integer", "description": "Maximum number of trip records to scrape. Leave blank for all records." }, "mode": { "title": "Mode", "enum": [ "both", "trips", "stations" ], "type": "string", "description": "What data to fetch: 'trips' (historical CSV data), 'stations' (live GBFS station feed), or 'both' (default)." }, "yearFrom": { "title": "Year From", "type": "integer", "description": "Earliest year to include in historical trip data (e.g. 2023). Defaults to current year only." }, "yearTo": { "title": "Year To", "type": "integer", "description": "Latest year to include in historical trip data. Defaults to current year." } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```