# Spotify Artist & Fans-Also-Like Recovery (`gabruck97/spotify-coleta-artistas`) Actor Powerful Spotify scraper that recovers Related Artists (Fans Also Like) data, monthly listeners, and top cities. Extracts top tracks with exact play counts and biography. Ideal for music market analysis and scene mapping. Fast and reliable. - **URL**: https://apify.com/gabruck97/spotify-coleta-artistas.md - **Developed by:** [Gabriel](https://apify.com/gabruck97) (community) - **Categories:** Social media, Automation, SEO tools - **Stats:** 4 total users, 2 monthly users, 90.5% runs succeeded, NaN bookmarks - **User rating**: 5.00 out of 5 stars ## Pricing from $0.05 / 1,000 results This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage. Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have. 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 ## 🎵 Spotify Artist Intelligence & Discovery Scraper A high-performance Python scraper designed to extract deep metadata from Spotify Artist profiles. This tool utilizes **Playwright** for request interception, allowing it to bypass standard limitations and recover data that is often hidden or deprecated. --- ### 💎 The Most Affordable Scraper on the Store This project is driven by a **sustainability-first** philosophy and absolute price transparency: * **At-Cost Pricing:** My goal isn't high profit—it's to keep the tool accessible. The price is set to the absolute minimum required to cover infrastructure costs and keep the project running. * **Fueling Innovation:** The popularity of this tool directly funds the development of new features and the release of more specialized scrapers for the community. * **Community-Centric:** Found a bug or need a specific feature? **Just open an Issue.** I actively monitor the repository to implement fixes and new scrapers based on your direct feedback. --- ### 🚀 Key Advantages & Features * **[EXCLUSIVE] Related Artists Recovery:** Reclaims the "Fans Also Like" network, a feature recently limited or removed from many public Spotify interfaces. * **Exact Playcounts:** Extracts precise play counts for top tracks, providing better granularity than standard popularity scores. * **Geographic Insights:** Identifies the **Top 5 Cities** with the highest concentration of monthly listeners. * **GraphQL Interception:** Instead of slow DOM parsing, this tool intercepts internal API responses for maximum speed and 100% data integrity. * **Analysis Ready:** Delivers structured JSON output perfect for A&R, music market research, and network analysis. --- ### 📊 Extracted Data Points | Category | Data Fields | | :--- | :--- | | **Identity** | Artist Name, Verified Status, Full Biography | | **Audience** | Monthly Listeners, Total Followers | | **Geography** | Top 5 Cities (City Name & Listener Count) | | **Discography** | Top Tracks, Exact Playcounts, Duration, and Links | | **Discovery** | **Related Artists** (Full list with Names, IDs, and Links) | --- ### 📥 Input Format When running as an Apify Actor, use the following JSON input: ```json { "startUrls": [ { "url": "[https://open.spotify.com/artist/](https://open.spotify.com/artist/)..." } ] } ```` ### 📥 Output Format ````json { "name": "Artist Name", "verified": true, "listeners": 1250430, "followers": 890200, "biography": "Full artist biography text...", "cities": [ {"city": "São Paulo", "listeners": 54200}, {"city": "Mexico City", "listeners": 41300}, {"city": "London", "listeners": 35000}, {"city": "Santiago", "listeners": 38900}, {"city": "Madrid", "listeners": 31200} ], "related_artists": [ { "id": "5XN...", "name": "Similar Artist", "link": "https://open.spotify.com/artist/..." } ], "tracks": [ { "name": "Hit Track", "playcount": 25000000, "duration_sec": 195, "link": "https://open.spotify.com/track/..." } ] } # Actor input Schema ## `startUrls` (type: `array`): Insira os links dos artistas (ex: https://open.spotify.com/artist/...). ## `datasetName` (type: `string`): Se definir um nome, os dados serão guardados permanentemente e acumulados a cada execução. Se deixar vazio, será gerado um dataset temporário. ## Actor input object example ```json { "startUrls": [ { "url": "https://open.spotify.com/artist/1upZO7ZfMNrTqqrjx4blBP" } ] } ```` # 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 = { "startUrls": [ { "url": "https://open.spotify.com/artist/1upZO7ZfMNrTqqrjx4blBP" } ] }; // Run the Actor and wait for it to finish const run = await client.actor("gabruck97/spotify-coleta-artistas").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 = { "startUrls": [{ "url": "https://open.spotify.com/artist/1upZO7ZfMNrTqqrjx4blBP" }] } # Run the Actor and wait for it to finish run = client.actor("gabruck97/spotify-coleta-artistas").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 '{ "startUrls": [ { "url": "https://open.spotify.com/artist/1upZO7ZfMNrTqqrjx4blBP" } ] }' | apify call gabruck97/spotify-coleta-artistas --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=gabruck97/spotify-coleta-artistas", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Spotify Artist & Fans-Also-Like Recovery", "description": "Powerful Spotify scraper that recovers Related Artists (Fans Also Like) data, monthly listeners, and top cities. Extracts top tracks with exact play counts and biography. Ideal for music market analysis and scene mapping. Fast and reliable.", "version": "0.0", "x-build-id": "wKOZUYIJVgK03fwI6" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/gabruck97~spotify-coleta-artistas/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-gabruck97-spotify-coleta-artistas", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/gabruck97~spotify-coleta-artistas/runs": { "post": { "operationId": "runs-sync-gabruck97-spotify-coleta-artistas", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/gabruck97~spotify-coleta-artistas/run-sync": { "post": { "operationId": "run-sync-gabruck97-spotify-coleta-artistas", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "startUrls" ], "properties": { "startUrls": { "title": "URLs dos Artistas", "maxItems": 20, "type": "array", "description": "Insira os links dos artistas (ex: https://open.spotify.com/artist/...).", "items": { "type": "object", "required": [ "url" ], "properties": { "url": { "type": "string", "title": "URL of a web page", "format": "uri" } } } }, "datasetName": { "title": "Nome do Dataset (Opcional)", "type": "string", "description": "Se definir um nome, os dados serão guardados permanentemente e acumulados a cada execução. Se deixar vazio, será gerado um dataset temporário." } } }, "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 } } } } } } } } } } ```