# Rapido Ride Scraper (`saswave/rapido-ride-scraper`) Actor The Rapido Ride Scraper is a specialized logistics and transport intelligence tool tailored for the Indian ride-hailing market. Retrieve real-time price estimation ranges for various transit categories - **URL**: https://apify.com/saswave/rapido-ride-scraper.md - **Developed by:** [SASWAVE](https://apify.com/saswave) (community) - **Categories:** Automation, Developer tools, E-commerce - **Stats:** 4 total users, 1 monthly users, 93.3% runs succeeded, 1 bookmarks - **User rating**: No ratings yet ## Pricing from $5.00 / 1,000 results 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 ### Rapido Ride Scraper The Rapido Ride Scraper is a specialized logistics and transport intelligence tool tailored for the Indian ride-hailing market. By querying Rapido's web ecosystem, this scraper retrieves real-time price estimation ranges for various transit categories—ranging from agile bike taxis to spacious multi-utility cabs—between any designated pickup and drop-off coordinates. ### FEATURE Point-to-Point Fare Quotes: Extract real-time estimation ranges for specific origin-destination pairs. Multi-Modal Breakdown: Capture structured price parameters across Rapido's expanding fleet options: bike: High-agility, lower-cost single pillion options. cab_economy: Standard budget-friendly intra-city hatchbacks and sedans. cab_premium: Higher-tier sedans focused on business and comfort. cab_xl: Multi-passenger utility vehicles (SUVs) optimized for group commutes. Geographic Normalization: Automatically resolve location names into localized territory string descriptors (e.g., Mumbai Central, Maharashtra, India). SEO Web-Route Mapping: Surface the unique underlying dynamic page configuration URLs (m.rapido.bike/unup-home/seo/...) generated by the platform. ### USE CASES Logistics Aggregation: Power third-party travel planners, route aggregators, and mobility apps with competitive live transport quotes. Commute Optimization & Analysis: Track micro-mobility vs. traditional car transit costs to isolate daily patterns across congested metro corridors. Competitive Pricing Intelligence: Monitor price fluctuations, localized base rates, and platform variations to analyze how ride-sharing options stack up in different Indian cities. Corporate Travel Budgeting: Automate predictable expense planning and mileage reimbursement tables for staff intra-city dispatch systems. ### OUTPUT ```json { "url": "https://m.rapido.bike/unup-home/seo/Mumbai, Maharashtra, India/Mumbai Central, Mumbai, Maharashtra, India?version=v3", "from": "Mumbai, Maharashtra, India", "to": "Mumbai Central, Mumbai, Maharashtra, India", "bike": "₹ 28 - ₹ 35", "cab_economy": "₹ 108 - ₹ 132", "cab_premium": "₹ 162 - ₹ 198", "cab_xl": "₹ 189 - ₹ 231" } ```` ### 🛟 SUPPORT Share your runs with the developer team and create issues on error to help us improve actor quality. You might discover edge case we didn't test yet We stay available anytime # Actor input Schema ## `from` (type: `string`): Use the same text as provided in search url ## `to` (type: `string`): Use the same text as provided in search url ## Actor input object example ```json { "from": "Mumbai, Maharashtra, India", "to": "Mumbai Central, Mumbai, Maharashtra, India" } ``` # 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 = { "from": "Mumbai, Maharashtra, India", "to": "Mumbai Central, Mumbai, Maharashtra, India" }; // Run the Actor and wait for it to finish const run = await client.actor("saswave/rapido-ride-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 = { "from": "Mumbai, Maharashtra, India", "to": "Mumbai Central, Mumbai, Maharashtra, India", } # Run the Actor and wait for it to finish run = client.actor("saswave/rapido-ride-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 '{ "from": "Mumbai, Maharashtra, India", "to": "Mumbai Central, Mumbai, Maharashtra, India" }' | apify call saswave/rapido-ride-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=saswave/rapido-ride-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Rapido Ride Scraper", "description": "The Rapido Ride Scraper is a specialized logistics and transport intelligence tool tailored for the Indian ride-hailing market. Retrieve real-time price estimation ranges for various transit categories", "version": "0.0", "x-build-id": "YZofv8GJkxVC1JkOi" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/saswave~rapido-ride-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-saswave-rapido-ride-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/saswave~rapido-ride-scraper/runs": { "post": { "operationId": "runs-sync-saswave-rapido-ride-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/saswave~rapido-ride-scraper/run-sync": { "post": { "operationId": "run-sync-saswave-rapido-ride-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "from", "to" ], "properties": { "from": { "title": "From location", "type": "string", "description": "Use the same text as provided in search url" }, "to": { "title": "To location", "type": "string", "description": "Use the same text as provided in search url" } } }, "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 } } } } } } } } } } ```