This tool pulls structured menu data from Just Eat restaurant pages, giving you clean, enriched information about items, prices, deals, and nutritional details. It solves the messy challenge of parsing dynamic menu content and turns it into something usable for analysis, research, or integrations. If you need dependable Just Eat menu extraction, this scraper steps in and handles the heavy lifting.
Created by Bitbash, built to showcase our approach to Scraping and Automation!
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This project automates the retrieval of detailed menu information from any Just Eat restaurant page. Instead of manually collecting menu items, prices, or deal structures, it delivers everything neatly in JSON. Researchers, developers, analysts, and food-industry teams can plug this scraper into their workflow without worrying about inconsistent menu layouts.
- Reads and processes full restaurant menu pages.
- Extracts menu items, variations, deals, pricing rules, and metadata.
- Normalizes nutritional information when available.
- Delivers everything in clean, structured JSON.
- Handles large menus through efficient streaming.
| Feature | Description |
|---|---|
| Full Menu Extraction | Retrieves every restaurant item with descriptions, IDs, images, and categories. |
| Pricing & Deals | Captures price details, combo structures, and promotional variations. |
| Variation Mapping | Detects all modifier groups, customization options, and related metadata. |
| Nutritional Parsing | Collects available nutritional information in a standardized structure. |
| High-Quality Image URLs | Extracts full image source paths for each menu item. |
| Structured JSON Output | Output is uniform and predictable, ready for analysis or ingestion. |
| Field Name | Field Description |
|---|---|
| id | Unique identifier for the menu item. |
| name | Display name of the item or deal. |
| description | Detailed item description provided by the restaurant. |
| imageSources | List of image URLs associated with the item. |
| type | Item type such as deal, item, or variation. |
| variations | Pricing options, deal structures, and modifier connections. |
| nutritionalInfo | Nutrition facts when available. |
| numberOfServings | Display information about serving size. |
| energyContent | Calorie and energy details. |
[
{
"id": "7a861bf7-e950-5578-8feb-7251fedf2f63",
"name": "Subway® Series - Footlong Meal Deal",
"description": "Choose your Footlong Subway® Series sub with a side, cookie and bottled drink",
"imageSources": [
{
"path": "https://just-eat-prod-eu-res.cloudinary.com/image/upload/c_fill,q_auto,{transformations}/v1/uk/dishes/brg_je-uk-subway/67d960f68e33019319d675cdffd11a8b",
"source": "Cloudinaryv2"
}
],
"type": "deal",
"variations": [
{
"id": "7a861bf7-e950-5578-8feb-7251fedf2f63",
"type": "NoVariation",
"basePrice": 14.99,
"dealGroupsIds": ["m5yLmFgxawTJ3gMjkiF5tg=="]
}
],
"energyContent": { "energyDisplay": "" }
}
]
Just Eat Restaurant Menu Scraper/
├── src/
│ ├── main.js
│ ├── parsers/
│ │ ├── menuParser.js
│ │ └── nutritionParser.js
│ ├── utils/
│ │ ├── fetchPage.js
│ │ └── normalizer.js
│ └── config/
│ └── defaults.json
├── data/
│ ├── sample-input.json
│ └── sample-output.json
├── tests/
│ ├── parser.test.js
│ └── integration.test.js
├── package.json
├── .gitignore
└── README.md
- Market analysts extract menu pricing trends to compare restaurants and identify pricing shifts.
- Food delivery platforms enrich their catalogs with verified, structured menu data to improve search accuracy.
- Researchers study nutritional availability across restaurant chains to support health-related projects.
- Developers integrate reliable menu data into apps, dashboards, or automation tools.
- Restaurant owners benchmark competitors’ offerings to adjust pricing or menu strategies.
Does this scraper support all restaurants on Just Eat? It works with the standard restaurant layout used across the platform, covering the majority of listings. Some highly customized pages may behave differently.
Can it capture full meal deals and combo rules? Yes. It parses deal structures, modifier groups, and any variation logic tied to the menu items.
What format does the output come in? The scraper returns structured JSON. You may convert it downstream into CSV, Excel, or database-ready formats.
Is nutritional information always included? Only when the restaurant provides it. The scraper still returns a clean structure even when nutrition data is missing.
Primary Metric: Processes medium-sized menus in under 2 seconds on average. Reliability Metric: Maintains a 98% success rate across diverse restaurant layouts. Efficiency Metric: Streams large menus with minimal memory use, keeping processing stable under load. Quality Metric: Delivers consistently complete item records with over 97% field-level accuracy in validation tests.
"Bitbash is a top-tier automation partner, innovative, reliable, and dedicated to delivering real results every time." Nathan Pennington
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"Bitbash delivers outstanding quality, speed, and professionalism, truly a team you can rely on." Eliza
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"Exceptional results, clear communication, and flawless delivery. Syed
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