ImageShack Scraper is a fast and reliable tool for extracting rich image data from ImageShack’s public pages. It helps developers, analysts, and content teams collect structured image metadata for research, discovery, and content-driven workflows with minimal effort.
Created by Bitbash, built to showcase our approach to Scraping and Automation!
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This project retrieves detailed information about images published on ImageShack, including featured, discovered, user, and individual image pages. It solves the problem of accessing structured image data where no simple public API is available and is designed for users who need clean, reusable datasets.
It is ideal for developers, data teams, and researchers working on media analysis, trend discovery, or content aggregation.
- Collects image details from featured, discover, user, and image pages
- Extracts identifiers, URLs, tags, usernames, and timestamps
- Optionally expands datasets with related images
- Supports controlled limits for large listings
- Designed for stable, high-throughput data collection
| Feature | Description |
|---|---|
| Featured Images Extraction | Retrieve images highlighted on ImageShack for curated content analysis. |
| Discover Page Scraping | Collect the latest images from the discover feed in near real time. |
| Detailed Image Metadata | Extract IDs, image URLs, usernames, tags, upload time, and avatars. |
| Related Images Support | Optionally include related images linked to each primary image. |
| Flexible URL Inputs | Works with lists, user profiles, and individual image pages. |
| Field Name | Field Description |
|---|---|
| type | Type of item, typically image. |
| url | Public ImageShack page URL. |
| imageId | Unique identifier of the image. |
| imageUrl | Primary image URL. |
| imageUrlAlt | Alternative or scaled image URL. |
| imageName | Image title or name if available. |
| userAvatar | URL of the uploader’s avatar image. |
| tags | List of tags associated with the image. |
| uploadedAt | Image upload date and time. |
| relatedImages | List of related images when enabled. |
[
{
"type": "image",
"url": "https://imageshack.com/i/f0e2aa72j",
"imageId": "f0e2aa72j",
"imageUrl": "http://imageshack.com/scaled/medium/540/e2aa72.jpg",
"imageUrlAlt": "https://imagizer.imageshack.com/a/img540/1851/e2aa72.jpg",
"imageName": ".",
"userAvatar": "https://imagizer.imageshack.com/v2/56x56q70/c/843/0f7u.jpg",
"tags": [
"bike",
"game",
"jump",
"photography",
"sport",
"sports"
],
"uploadedAt": "2014-07-16 11:18",
"relatedImages": []
}
]
ImageShack Scraper/
├── src/
│ ├── main.js
│ ├── crawler/
│ │ ├── image_parser.js
│ │ └── related_images.js
│ ├── utils/
│ │ ├── helpers.js
│ │ └── validators.js
│ └── config/
│ └── settings.example.json
├── data/
│ ├── input.sample.json
│ └── output.sample.json
├── package.json
└── README.md
- Data analysts use it to collect large image datasets, so they can analyze visual trends and tag distributions.
- Content researchers use it to monitor featured and discover images, so they can stay updated on popular visuals.
- Developers use it to build media-driven applications, so they can integrate structured image metadata easily.
- Marketing teams use it to study image themes and tags, so they can align campaigns with trending visuals.
Can I limit how many images are collected? Yes, you can define a maximum item limit to control dataset size when working with large pages or feeds.
Does it support user profile pages? Yes, user profile URLs are supported and will return images associated with that user.
Can related images increase runtime? Including related images increases the number of requests and data volume, which can proportionally affect runtime and resource usage.
What happens if invalid input is provided? The process stops early and reports a clear error message explaining what needs to be corrected.
Primary Metric: Processes roughly 100 images per minute under stable conditions.
Reliability Metric: Maintains a high success rate when provided with valid URLs and configuration.
Efficiency Metric: Optimized requests keep resource usage low while maintaining high throughput.
Quality Metric: Image records are consistently complete with accurate metadata and tag coverage.
