# Tour de France Rankings & Stages Scraper (`jungle_synthesizer/letour-fr-tour-de-france-rankings-stages-scraper`) Actor Scrapes official Tour de France jersey rankings (GC, points, mountains, youth, team) and stage metadata (start/finish cities, distance, elevation, type) from letour.fr. Covers all 21 stages — ideal for fantasy cycling, sports analytics, and content pipelines during the July race window. - **URL**: https://apify.com/jungle\_synthesizer/letour-fr-tour-de-france-rankings-stages-scraper.md - **Developed by:** [BowTiedRaccoon](https://apify.com/jungle_synthesizer) (community) - **Categories:** Sports, AI - **Stats:** 7 total users, 1 monthly users, 100.0% runs succeeded, 0 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 ## Tour de France Rankings & Stages Scraper Scrapes official Tour de France jersey rankings (GC, points, mountains, youth, and team) plus stage metadata (start/finish cities, distance, elevation, stage type) directly from [letour.fr](https://www.letour.fr). Covers all 21 stages — updated daily during the July race window. ### What does it do? Each run retrieves: - **Stage metadata** — start/finish cities, total distance, elevation gain, and stage classification (Flat, Hilly, Mountain, Individual Time Trial, Team Time Trial) - **Jersey rankings** for each stage across up to 7 classification types: General (GC yellow), Points (green), Mountains (polka-dot), Youth (white), Team, Combative, and Lanterne Rouge - **Rider details** — position, bib number, name, country (ISO 3-letter code), team name, accumulated time, time gap to leader, and points Data is sourced from the official site's AJAX ranking endpoints, which return server-rendered HTML for every completed stage. ### Why use this instead of scraping ProCyclingStats? [ProCyclingStats](https://www.procyclingstats.com) is the de facto third-party cycling data source but it is protected by Cloudflare (verified 403 in pre-flight testing). `letour.fr` serves the same official rankings from clean, datacenter-friendly HTML with no bot protection — no residential proxy required. ### Input | Field | Type | Default | Description | |-------|------|---------|-------------| | `year` | integer | 2026 | Tour de France year to scrape | | `stageNumbers` | array of integers | all 21 stages | Filter to specific stages, e.g. `[1, 2, 21]` | | `rankingTypes` | array of strings | all types | Which jersey rankings to scrape: `general`, `points`, `mountains`, `youth`, `team`, `combative`, `lanterne_rouge` | | `maxItems` | integer | 0 (unlimited) | Hard cap on total records saved | ### Output dataset fields | Field | Type | Description | |-------|------|-------------| | `year` | integer | Tour de France year | | `stage_number` | integer | Stage number (1–21) | | `stage_type` | string | Flat / Hilly / Mountain / Individual Time Trial / Team Time Trial | | `start_city` | string | Stage start city | | `finish_city` | string | Stage finish city | | `distance_km` | number | Stage distance in km | | `elevation_gain_m` | integer | Total elevation gain in metres | | `ranking_type` | string | general / points / mountains / youth / team / combative / lanterne_rouge | | `position` | integer | Rider position in the ranking | | `bib` | integer | Rider bib number | | `rider_name` | string | Rider abbreviated name (e.g. "T. POGACAR") | | `rider_country` | string | Country code (ISO 3166-1 alpha-3, e.g. "SLO") | | `team_name` | string | Full team name | | `team_code` | string | Team 3-letter code (where available) | | `finish_time` | string | Accumulated race time for general/youth/team rankings | | `time_gap` | string | Time gap to race leader | | `points` | integer | Points total for green/mountains rankings | | `source` | string | Source URL of the ranking data | ### Sample output (Stage 21 GC, 2025) ```json { "year": 2026, "stage_number": 21, "stage_type": "Flat", "start_city": "Thoiry", "finish_city": "Paris Champs-Élysées", "distance_km": 133, "elevation_gain_m": 1000, "ranking_type": "general", "position": 1, "bib": 1, "rider_name": "T. POGACAR", "rider_country": "SLO", "team_name": "UAE TEAM EMIRATES XRG", "team_code": null, "finish_time": "76h 00' 32''", "time_gap": null, "points": null, "source": "https://www.letour.fr/en/ajax/ranking/21/itg/2b9.../subtab" } ```` ### Usage tips - **During the race window (July 4–26, 2026)**: Run daily to capture updated standings after each stage finishes. Stage 1–20 rankings update that evening; Stage 21 (Paris) closes the tour. - **Historical data**: Stage results from the 2025 Tour are accessible at the same URL paths. - **Future stages**: Ranking tabs are only populated for completed stages. Running the scraper on a future stage returns 0 results for that stage — no error is thrown. - **Scaling**: For a full run (21 stages × 5 jersey types = ~105 ranking tables × ~160 riders = ~16,800 rows), a single run completes in under 3 minutes at the default concurrency of 5. ### Technical notes The actor uses a 4-level hierarchical crawl: 1. `/en/overall-route` → discovers all stage links 2. `/en/stage-N` → extracts stage metadata (city names from page title, distance/type/elevation from `stageHeader__infos` blocks) 3. `/en/rankings/stage-N` → discovers AJAX subtab URLs (hash-keyed, rotated per year) 4. `/en/ajax/ranking/N///subtab` → parses rider rows from the rankings table HTML # 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. ## `year` (type: `integer`): Tour de France year to scrape (defaults to current/upcoming) ## `stageNumbers` (type: `array`): Specific stage numbers to scrape (1-21). Leave empty to scrape all stages. ## `rankingTypes` (type: `array`): Jersey ranking types to scrape: general (GC), points (green), mountains (polka-dot), youth (white), team. Leave empty for all. ## `maxItems` (type: `integer`): Maximum number of records to scrape ## 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...", "year": 2026, "stageNumbers": [ 1, 2 ], "rankingTypes": [ "general", "points", "mountains", "youth", "team" ], "maxItems": 100 } ``` # 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...", "year": 2026, "stageNumbers": [ 1, 2 ], "rankingTypes": [ "general", "points", "mountains", "youth", "team" ], "maxItems": 100 }; // Run the Actor and wait for it to finish const run = await client.actor("jungle_synthesizer/letour-fr-tour-de-france-rankings-stages-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...", "year": 2026, "stageNumbers": [ 1, 2, ], "rankingTypes": [ "general", "points", "mountains", "youth", "team", ], "maxItems": 100, } # Run the Actor and wait for it to finish run = client.actor("jungle_synthesizer/letour-fr-tour-de-france-rankings-stages-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...", "year": 2026, "stageNumbers": [ 1, 2 ], "rankingTypes": [ "general", "points", "mountains", "youth", "team" ], "maxItems": 100 }' | apify call jungle_synthesizer/letour-fr-tour-de-france-rankings-stages-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=jungle_synthesizer/letour-fr-tour-de-france-rankings-stages-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Tour de France Rankings & Stages Scraper", "description": "Scrapes official Tour de France jersey rankings (GC, points, mountains, youth, team) and stage metadata (start/finish cities, distance, elevation, type) from letour.fr. Covers all 21 stages — ideal for fantasy cycling, sports analytics, and content pipelines during the July race window.", "version": "0.1", "x-build-id": "vXd0fbQfc2apNd1tO" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/jungle_synthesizer~letour-fr-tour-de-france-rankings-stages-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-jungle_synthesizer-letour-fr-tour-de-france-rankings-stages-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~letour-fr-tour-de-france-rankings-stages-scraper/runs": { "post": { "operationId": "runs-sync-jungle_synthesizer-letour-fr-tour-de-france-rankings-stages-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~letour-fr-tour-de-france-rankings-stages-scraper/run-sync": { "post": { "operationId": "run-sync-jungle_synthesizer-letour-fr-tour-de-france-rankings-stages-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": [ "maxItems" ], "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." }, "year": { "title": "Year", "type": "integer", "description": "Tour de France year to scrape (defaults to current/upcoming)", "default": 2026 }, "stageNumbers": { "title": "Stage Numbers", "type": "array", "description": "Specific stage numbers to scrape (1-21). Leave empty to scrape all stages.", "items": { "type": "integer" } }, "rankingTypes": { "title": "Ranking Types", "type": "array", "description": "Jersey ranking types to scrape: general (GC), points (green), mountains (polka-dot), youth (white), team. Leave empty for all.", "items": { "type": "string" } }, "maxItems": { "title": "Max Items", "type": "integer", "description": "Maximum number of records to scrape", "default": 0 } } }, "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 } } } } } } } } } } ```