Patreon Extractor Scraper

A powerful all-in-one tool for extracting creator data, campaigns, posts, products, collections, chats, and comments from Patreon using flexible query inputs. This scraper simplifies collecting structured Patreon data at scale and provides full control over what sections to crawl using intuitive query commands. Designed for analysts, creators, researchers, and developers who need reliable, structured Patreon insights quickly and efficiently.

     

Created by Bitbash, built to showcase our approach to Scraping and Automation!
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Introduction

This project delivers a complete Patreon data extraction solution capable of scraping creators, campaigns, posts, comments, products, collections, chats, user info, and more. It solves the challenge of manually navigating Patreon’s dynamic structure by offering a universal query system capable of identifying and fetching multiple data types seamlessly.

Why This Patreon Extractor Matters

• Extracts rich, structured Patreon data across creators, posts, and collections.
• Supports keywords, URLs, IDs, and Patreon Query Language (PQL) inputs.
• Allows authenticated sessions for accessing subscriber-only content.
• Handles batch queries in a single run for efficient data gathering.
• Provides predictable, consistent output ideal for analytics pipelines.

Features

Feature	Description
Multi-Query Support	Accepts keywords, URLs, IDs, or @campaign shortcuts in a single batch request.
Comprehensive Data Extraction	Scrapes creators, posts, comments, collections, chats, products, tags, and user info.
Patreon Query Language (PQL)	Offers precise control using commands like posts:, @campaign/posts, product:, etc.
Public & Authenticated Modes	Supports session_id cookie for accessing subscriber-only content.
Smart URL Interpretation	Converts flexible input formats into structured scraping rules.
High-Performance Extraction	Optimized request handling for fast, stable scraping at scale.

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What Data This Scraper Extracts

Field Name	Field Description
id	Unique identifier of a post, creator, product, or collection.
title	Title of a post or content piece.
teaser_text	Preview text or shortened description.
published_at	Timestamp of publication.
user	Creator/user information and profile details.
images	Associated media such as photos or thumbnails.
audio / media	Audio or media metadata including filenames and IDs.
access_rules	Tier and access information for gated content.
comment_count	Total number of comments on a post.
like_count	Engagement metrics including likes and reactions.
url	Direct link to the post or creator page.
post_type	Type of post (audio, video, image, poll, article, etc.).
view_count	Number of views recorded for the post.
insights_last_updated_at	Timestamp for analytics refresh.
metadata	Additional structured data per content type.

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Example Output

{
  "id": "72996515",
  "title": "Hillsong: A MegaChurch Exposed. Ep 1: Welcome Home",
  "post_type": "audio_file",
  "comment_count": 56,
  "like_count": 188,
  "view_count": 467,
  "published_at": "2022-10-07T10:08:07.000+00:00",
  "url": "https://www.patreon.com/posts/hillsong-exposed-72996515",
  "audio": {
    "file_name": "AdFree-DraftV1-20221007-TCO-Hillsong1.mp3",
    "id": "171203911",
    "type": "media"
  },
  "access_rules": [
    {
      "access_rule_type": "tier",
      "id": "7909551",
      "post_count": 603
    }
  ]
}

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Directory Structure Tree

Patreon Extractor 🎯 ⭐5.0/
├── src/
│   ├── runner.py
│   ├── extractors/
│   │   ├── campaign_parser.py
│   │   ├── post_parser.py
│   │   ├── product_parser.py
│   │   ├── collection_parser.py
│   │   └── user_parser.py
│   ├── outputs/
│   │   └── exporters.py
│   └── config/
│       └── settings.example.json
├── data/
│   ├── inputs.sample.json
│   └── sample_output.json
├── requirements.txt
└── README.md

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Use Cases

• Market researchers analyze creator growth, engagement, and product performance to forecast trends.
• Content creators monitor competitor campaigns to optimize their own pricing, tiers, and content output.
• Data analysts aggregate Patreon insights for dashboards, ML models, or audience behavior studies.
• Membership platforms benchmark creator success metrics for product development and strategy.
• Journalists & researchers investigate creator ecosystems, fan behavior, and cultural impact patterns.

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FAQs

Q1: Can this scraper access subscriber-only content? Yes, but only if you include your own valid session_id cookie from Patreon. You must already be a paid subscriber to the creator whose protected content you access.

Q2: What types of input formats does the scraper support? It accepts URLs, keywords, campaign names, IDs, @shortcuts, and advanced PQL queries such as posts:, @Campaign/posts, product:, user:, and more.

Q3: Is batch scraping supported? Yes. The query parameter accepts arrays of values, allowing large-scale multi-request operations in a single run.

Q4: Why use QUERY instead of URL? QUERY offers more flexible intent-based scraping, supports non-URL inputs, and allows more precise targeting of sections like posts, chats, collections, tags, and products.

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Performance Benchmarks and Results

Primary Metric: Processes an average of 40–60 queries per minute, depending on content depth and media volume.

Reliability Metric: Maintains a 98% success rate across large datasets with automatic retries and stability tuning.

Efficiency Metric: Optimized extraction pipeline handles multi-section campaigns with minimal redundant requests, reducing overhead by ~35%.

Quality Metric: Consistently delivers over 95% field completeness across supported data types (campaigns, posts, products, comments, and collections).

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