# Patreon Posts Parser Spider (`getdataforme/patreon-posts-parser-spider`) Actor Extract and analyze Patreon posts with ease. This Apify Actor scrapes detailed data like titles, engagement metrics, and media links from multiple creators. Perfect for researchers, marketers, and developers seeking insights without manual effort.... - **URL**: https://apify.com/getdataforme/patreon-posts-parser-spider.md - **Developed by:** [GetDataForMe](https://apify.com/getdataforme) (community) - **Categories:** Automation, Lead generation, Agents - **Stats:** 13 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $9.00 / 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 ### Description Extract and analyze Patreon posts with ease. This Apify Actor scrapes detailed data like titles, engagement metrics, and media links from multiple creators. Perfect for researchers, marketers, and developers seeking insights without manual effort.... --- ## Patreon Posts Parser Spider ### Introduction The Patreon Posts Parser Spider is a powerful Apify Actor designed to extract and parse posts from Patreon creators' pages efficiently. It scrapes detailed information about posts, including metadata, engagement metrics, and media links, enabling users to gather valuable insights from Patreon content. This tool is ideal for researchers, marketers, and developers who need structured data from Patreon without manual effort. ### Features - **Comprehensive Data Extraction**: Captures key post details such as IDs, types, titles, comment and like counts, publication dates, and URLs. - **High Reliability**: Built with robust error handling to ensure consistent data retrieval from Patreon's dynamic pages. - **Flexible Input**: Accepts multiple usernames for batch processing, allowing extraction from several creators in a single run. - **Structured Output**: Delivers clean JSON data with share images and metadata, ready for analysis or integration. - **Performance Optimized**: Utilizes efficient scraping techniques to minimize runtime and resource usage. - **No Authentication Required**: Operates without needing Patreon login credentials, simplifying usage. - **Apify Integration**: Seamlessly runs on the Apify platform with built-in monitoring and export options. ### Input Parameters | Parameter | Type | Required | Description | Example | |-----------|--------|----------|-------------|---------| | Usernames | array | No | List of Patreon usernames to scrape posts from. Each username should be a string without the '@' symbol. | ["3blue1brown", "anothercreator"] | ### Example Usage #### Input Configuration ```json { "Usernames": ["3blue1brown"] } ```` #### Output Example ```json [ { "campaign_id": "580365", "post_id": "7107742", "post_type": "text_only", "title": null, "comment_count": 19, "like_count": 29, "is_paid": false, "created_at": "2016-10-28T18:38:21.000+00:00", "published_at": "2016-10-28T18:38:49.000+00:00", "url": "https://www.patreon.com/posts/7107742", "share_images": { "landscape": { "url": "https://c7.patreon.com/https%3A%2F%2Fwww.patreon.com%2F%2Fcard-teaser-image%2Fpost%2F7107742%2Flandscape%3Fc=7778105931127776273/selector/%23post-teaser%2C.png" }, "portrait": { "url": "https://c7.patreon.com/https%3A%2F%2Fwww.patreon.com%2F%2Fcard-teaser-image%2Fpost%2F7107742%2Fportrait%3Fc=7778105931127776273/selector/%23post-teaser%2C.png" } }, "actor_id": "CrNwiMCytBdqaJVFb", "run_id": "wb53xttpPokrpSKpR" }, { "campaign_id": "580365", "post_id": "7108625", "post_type": "text_only", "title": "Animation from upcoming video", "comment_count": 8, "like_count": 12, "is_paid": false, "created_at": "2016-10-28T20:42:02.000+00:00", "published_at": "2016-10-28T20:48:01.000+00:00", "url": "https://www.patreon.com/posts/animation-from-7108625", "share_images": { "landscape": { "url": "https://c7.patreon.com/https%3A%2F%2Fwww.patreon.com%2F%2Fcard-teaser-image%2Fpost%2F7108625%2Flandscape%3Fc=-2022120548151437515/selector/%23post-teaser%2C.png" }, "portrait": { "url": "https://c7.patreon.com/https%3A%2F%2Fwww.patreon.com%2F%2Fcard-teaser-image%2Fpost%2F7108625%2Fportrait%3Fc=-2022120548151437515/selector/%23post-teaser%2C.png" } }, "actor_id": "CrNwiMCytBdqaJVFb", "run_id": "wb53xttpPokrpSKpR" }, { "campaign_id": "580365", "post_id": "7114165", "post_type": "text_only", "title": "Wow. Just, wow.", "comment_count": 21, "like_count": 37, "is_paid": false, "created_at": "2016-10-29T16:50:03.000+00:00", "published_at": "2016-10-29T17:00:08.000+00:00", "url": "https://www.patreon.com/posts/wow-just-wow-7114165", "share_images": { "landscape": { "url": "https://c7.patreon.com/https%3A%2F%2Fwww.patreon.com%2F%2Fcard-teaser-image%2Fpost%2F7108625%2Flandscape%3Fc=501350337707861191/selector/%23post-teaser%2C.png" }, "portrait": { "url": "https://c7.patreon.com/https%3A%2F%2Fwww.patreon.com%2F%2Fcard-teaser-image%2Fpost%2F7114165%2Fportrait%3Fc=501350337707861191/selector/%23post-teaser%2C.png" } }, "actor_id": "CrNwiMCytBdqaJVFb", "run_id": "wb53xttpPokrpSKpR" } ] ``` ### Use Cases - **Market Research**: Analyze engagement trends on Patreon to understand creator popularity and content performance. - **Competitive Intelligence**: Monitor rival creators' posts to identify successful strategies and themes. - **Content Aggregation**: Build databases of Patreon content for newsletters or archives. - **Academic Research**: Study creator-audience interactions through post metadata and metrics. - **Business Automation**: Automate data collection for reports on digital content monetization. - **Trend Analysis**: Track posting frequency and types to predict creator activity. ### Installation and Usage 1. Search for "Patreon Posts Parser Spider" in the Apify Store 2. Click "Try for free" or "Run" 3. Configure input parameters 4. Click "Start" to begin extraction 5. Monitor progress in the log 6. Export results in your preferred format (JSON, CSV, Excel) ### Output Format The Actor outputs an array of JSON objects, each representing a post. Key fields include `campaign_id`, `post_id`, `post_type` (e.g., "text\_only"), `title`, `comment_count`, `like_count`, `is_paid`, `created_at`, `published_at`, `url`, and `share_images` with landscape and portrait URLs. Additional fields like `actor_id` and `run_id` are included for tracking. ### Support For custom/simplified outputs or bug reports, please contact: - Email: support@getdataforme.com - Subject line: "custom support" - Contact form: https://getdataforme.com/contact/ We're here to help you get the most out of this Actor! *** # Actor input Schema ## `Usernames` (type: `array`): The usernames for the spider. ## `itemLimit` (type: `integer`): Specifies the maximum number of items to process. ## Actor input object example ```json { "Usernames": [ "3blue1brown" ], "itemLimit": 10 } ``` # Actor output Schema ## `results` (type: `string`): Scraped data items from dataset # 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 = { "itemLimit": 10 }; // Run the Actor and wait for it to finish const run = await client.actor("getdataforme/patreon-posts-parser-spider").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 = { "itemLimit": 10 } # Run the Actor and wait for it to finish run = client.actor("getdataforme/patreon-posts-parser-spider").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 '{ "itemLimit": 10 }' | apify call getdataforme/patreon-posts-parser-spider --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=getdataforme/patreon-posts-parser-spider", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Patreon Posts Parser Spider", "description": "Extract and analyze Patreon posts with ease. This Apify Actor scrapes detailed data like titles, engagement metrics, and media links from multiple creators. Perfect for researchers, marketers, and developers seeking insights without manual effort....", "version": "0.0", "x-build-id": "fTEhpShfftHChRil8" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/getdataforme~patreon-posts-parser-spider/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-getdataforme-patreon-posts-parser-spider", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/getdataforme~patreon-posts-parser-spider/runs": { "post": { "operationId": "runs-sync-getdataforme-patreon-posts-parser-spider", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/getdataforme~patreon-posts-parser-spider/run-sync": { "post": { "operationId": "run-sync-getdataforme-patreon-posts-parser-spider", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "properties": { "Usernames": { "title": "Usernames", "type": "array", "description": "The usernames for the spider.", "default": [ "3blue1brown" ], "items": { "type": "string" } }, "itemLimit": { "title": "Item Limit", "type": "integer", "description": "Specifies the maximum number of items to process.", "default": 10 } } }, "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 } } } } } } } } } } ```