# Apple Episodes Scraper - Low-costπŸ’²πŸŽ§πŸπŸ”΄ (`delectable_incubator/apple-episodes-scraper---low-cost`) Actor Scrape Apple Podcasts episodes by keyword πŸπŸŽ™οΈ with a powerful episode scraper Extract titles, descriptions, release dates, ratings, artwork, and more. Ideal for podcast research, content discovery, marketing insights, and building structured datasets for analysts, creators, and marketers πŸ“ŠπŸŽ§πŸš€ - **URL**: https://apify.com/delectable\_incubator/apple-episodes-scraper---low-cost.md - **Developed by:** [Prime Scrape](https://apify.com/delectable_incubator) (community) - **Categories:** Social media, Videos, Developer tools - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $0.00005 / actor start 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

Apple Episodes Scraper - PrimeScrape

--- ### Apple Episodes Scraper πŸŽ™οΈπŸ“‘πŸ The Apple Episodes Scraper is a fast, reliable, and scalable automation tool designed to extract structured podcast episode listings directly from Apple Podcasts. It transforms raw episode search results into clean, structured datasets ready for podcast analytics, content research, audience insights, and data-driven applications. --- ### Apple Episodes Scraper πŸ§ πŸŽ§πŸ“ˆ This scraper automatically extracts structured podcast episode data from Apple Podcasts based on keyword search. Ideal for podcast analysts, media researchers, content platforms, marketers, and developers. --- ### 🎯 What This Scraper Does Simply provide one or multiple keywords, and the scraper will automatically collect structured episode data. βœ… Extracts podcast episodes from Apple Podcasts βœ… Supports keyword-based search (bulk keywords supported) βœ… Handles pagination automatically βœ… Respects max items per keyword limit βœ… Extracts episode metadata & descriptions βœ… Captures release dates, genres, and ratings βœ… Structures data for analytics & integrations βœ… Ready for dashboards, datasets & pipelines --- ### πŸ“Š Data Extracted 🎧 Episode Fields | Field | Description | | --------------------- | ------------------------------------- | | πŸ†” `id` | Unique Apple episode identifier | | πŸ“ `type` | Type of item (`podcast-episodes`) | | 🎀 `artistName` | Podcast creator / publisher name | | πŸŽ™οΈ `name` | Episode title | | πŸ“ `description` | Full episode description | | ⏰ `releaseDateTime` | Episode release date & time | | πŸ“… `releaseFrequency` | Publishing frequency (if available) | | #️⃣ `trackCount` | Total episodes in show (if available) | | 🎧 `genreNames` | Episode genres/categories | | 🚫 `contentRating` | Content rating (explicit/clean) | | 🌐 `feedUrl` | RSS feed URL | | πŸ—£οΈ `languageTag` | Language of the episode | | πŸ”— `url` | Apple Podcasts episode URL | | 🌍 `websiteUrl` | External episode/show website | | πŸ–ΌοΈ `artwork_url` | Episode or show artwork | | πŸ“Ί `seasonNumbers` | Season number(s) | --- ### πŸ›  How to Use 1️⃣ Configure Input Provide one or multiple keywords: ```` { "keywords": \[ "comedy", "finance", "technology" ], "maxitems": 50 } ``` 2️⃣ Run the Actor The scraper will: β€’ Search Apple Podcasts episodes using keywords β€’ Automatically paginate results β€’ Extract episode listings β€’ Collect metadata & descriptions β€’ Structure and clean the dataset β€’ Stop when maxitems limit is reached 3️⃣ Export the Dataset Download your results in multiple formats: βœ… JSON βœ… CSV βœ… Excel βœ… XML βœ… HTML --- ### βš™οΈ Input Configuration #### πŸ“₯ Input Example ``` { "keywords": \[ "health", "business" ], "maxitems": 75 } ``` #### Input Fields | Field | Type | Description | | ---------- | ------- | ------------------------------------------------------------ | | `keywords` | array | List of keywords to search podcast episodes (bulk supported) | | `maxitems` | integer | Maximum number of episodes per keyword | --- ### πŸ“€ Output Example ``` { "id": "1000720144488", "type": "podcast-episodes", "artistName": "SiriusXM Podcasts", "name": "How to Become the Person You’ve Always Wanted to Be", "description": "Today, you’ll learn how to stop playing small...", "releaseDateTime": "2025-08-04T04:05:00Z", "releaseFrequency": "weekly", "trackCount": "85", "genreNames": \["Self-Improvement"], "contentRating": "explicit", "feedUrl": "https://example.com/feed", "languageTag": "en", "url": "https://podcasts.apple.com/us/podcast/example", "websiteUrl": "https://www.example.com", "artwork\_url": "https://is1-ssl.mzstatic.com/image/thumb/...jpg", "seasonNumbers": "5" } ```` --- ### πŸ“Š Output explanation | Field | Description | | ----------------- | ------------------------- | | `id` | Unique episode identifier | | `name` | Episode title | | `artistName` | Podcast publisher | | `releaseDateTime` | Release date/time | | `description` | Episode description | | `genreNames` | Categories/genres | | `contentRating` | Explicit or clean label | | `url` | Apple Podcasts link | | `artwork_url` | Episode artwork | | `seasonNumbers` | Season number | --- ### 🌍 Why Use This Scraper? 🎧 Episode Discovery β€” Find podcast episodes at scale πŸ“Š Market Analysis β€” Analyze content trends & topics 🧠 Content Research β€” Study podcast narratives & formats πŸ“ˆ Trend Tracking β€” Monitor new episode releases πŸ”„ Automation β€” Schedule recurring scraping πŸ€– Data Pipelines β€” Feed structured episode data into systems ⚑ Scalable β€” Built for bulk keyword extraction --- ### ⚠️ Disclaimer This tool is an independent solution and is not affiliated with or endorsed by Apple. --- ### πŸ’Έ Pricing This scraper runs on a **pay per events subscription model**. You only pay for **successful runs**. πŸ’³ **Price:** $2.89 / 1000 results --- ### Related Actors If you're interested in Podcasts or show scraping solutions, explore more tools: (Coming soon) --- ### πŸ“¬ Support ⭐⭐⭐⭐⭐ Leave a 5-star rating if you like this tool --- ### 🌍 PrimeScrape Built for scalable web data extraction & automation Contact for custom scraping solutions or enterprise requests via Apify or by email. # Actor input Schema ## `keyword` (type: `array`): One or more keywords to search for on Apple Podcasts episodes πŸ” ## `maxitems` (type: `integer`): Maximum number of episodes to scrape per keyword πŸ“Š Set how many episodes to extract ## Actor input object example ```json { "keyword": [ "comedy" ], "maxitems": 50 } ```` # Actor output Schema ## `overview` (type: `string`): No description # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "keyword": [ "comedy" ], "maxitems": 50 }; // Run the Actor and wait for it to finish const run = await client.actor("delectable_incubator/apple-episodes-scraper---low-cost").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`πŸ’Ύ Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // πŸ“š Want to learn more πŸ“–? Go to β†’ 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 = { "keyword": ["comedy"], "maxitems": 50, } # Run the Actor and wait for it to finish run = client.actor("delectable_incubator/apple-episodes-scraper---low-cost").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("πŸ’Ύ Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # πŸ“š Want to learn more πŸ“–? Go to β†’ https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "keyword": [ "comedy" ], "maxitems": 50 }' | apify call delectable_incubator/apple-episodes-scraper---low-cost --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=delectable_incubator/apple-episodes-scraper---low-cost", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Apple Episodes Scraper - Low-costπŸ’²πŸŽ§πŸπŸ”΄", "description": "Scrape Apple Podcasts episodes by keyword πŸπŸŽ™οΈ with a powerful episode scraper\n\nExtract titles, descriptions, release dates, ratings, artwork, and more. \n\nIdeal for podcast research, content discovery, marketing insights, and building structured datasets for analysts, creators, and marketers πŸ“ŠπŸŽ§πŸš€", "version": "0.0", "x-build-id": "mwa5ojyhmNx5NqCpT" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/delectable_incubator~apple-episodes-scraper---low-cost/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-delectable_incubator-apple-episodes-scraper---low-cost", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/delectable_incubator~apple-episodes-scraper---low-cost/runs": { "post": { "operationId": "runs-sync-delectable_incubator-apple-episodes-scraper---low-cost", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/delectable_incubator~apple-episodes-scraper---low-cost/run-sync": { "post": { "operationId": "run-sync-delectable_incubator-apple-episodes-scraper---low-cost", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "keyword" ], "properties": { "keyword": { "title": "Keywords to search for on Podcast Apple episodes πŸ”πŸŽ™οΈ", "type": "array", "description": "One or more keywords to search for on Apple Podcasts episodes πŸ”", "default": [ "comedy" ], "items": { "type": "string" } }, "maxitems": { "title": "Maximum number of episodes to scrape per keyword πŸ“Š Set how many episodes to extract", "type": "integer", "description": "Maximum number of episodes to scrape per keyword πŸ“Š Set how many episodes to extract", "default": 50 } } }, "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 } } } } } } } } } } ```