Uber Eats Scraper — Menu & Location Data
Pricing
from $2.72 / 1,000 uber eats scraper — menu & location data
Uber Eats Scraper — Menu & Location Data
Extract Uber Eats menus, item prices, categories, and location data. Features URL-list and query inputs, structured Dataset output, HTTP-first transport, automatic browser escalation, and mandatory Apify RESIDENTIAL proxy routing.
Pricing
from $2.72 / 1,000 uber eats scraper — menu & location data
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Developer
Vitalii Bondarev
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1
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2 days ago
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Extract Uber Eats menus, item prices, categories, and location data. Features URL-list and query inputs, structured Dataset output, HTTP-first transport, automatic browser escalation, and mandatory Apify RESIDENTIAL proxy routing.
What it does
Uber Eats Scraper — Menu & Location Data is a data-collection tool for the travel and ecommerce category. The inputs let you set the scope and preferences for a run, while the results provide organized records that are easier to review and use.
Input
Provide the values that define the scope and preferences for the run. Review each option before starting so the resulting dataset matches the information you want to analyze or reuse.
| Name | Type | Description | Default |
|---|---|---|---|
| maxItems | integer | Maximum number of records to save to the Dataset. | 100 |
| proxyConfiguration | object | Apify proxy configuration. Residential proxies are enabled by default. | {"useApifyProxy":true,"apifyProxyGroups":["RESIDENTIAL"]} |
| query | string | Best-effort restaurant discovery query. Uber may return no stores when a delivery location is unavailable. | — |
| urls | array | Public Uber store page URLs to scrape. Explicit URLs continue even when query discovery returns no stores. | https://www.ubereats.com/store/zuckers-bagels-fidis/YK9UYIbxTd2Gappp2N4pgQ |
Output
A successful run produces a dataset of structured items collected according to your inputs. You can review the records, use them in analysis, or pass them to another part of your workflow. The exact fields depend on the source data and the options selected for the run.
Usage
- Open the actor page.
- Keep the prefilled US store URL for a working default run, or replace it with one or more concrete Uber Eats store URLs.
- Run the actor and wait for the collection to finish.
- Download the results from the dataset and use the records in your preferred workflow.
Search is optional and best-effort. When both urls and query are supplied, a search page with no discovered stores is logged and saved as diagnostic evidence, while the explicit store URLs are still scraped.
Menu extraction reads Uber's embedded Schema.org JSON-LD (Restaurant → hasMenu → MenuSection → MenuItem) and keeps the existing Dataset shape: restaurant plus menu_item with title, description, price, image URL, and fallback item ID.
Pricing
Pricing is pay-per-event, so you pay only for results.
