# Opentable Restaurants Search Scraper (`stealth_mode/opentable-restaurants-search-scraper`) Actor
Scrape OpenTable restaurant search results effortlessly. Extract names, cuisines, availability slots, reviews, pricing, coordinates, and 30+ fields per restaurant — perfect for market research, travel apps, and food industry analysis.
- **URL**: https://apify.com/stealth\_mode/opentable-restaurants-search-scraper.md
- **Developed by:** [Stealth mode](https://apify.com/stealth_mode) (community)
- **Categories:** Automation, Developer tools, Travel
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks
- **User rating**: No ratings yet
## Pricing
from $1.50 / 1,000 results
This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage.
Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have.
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
## OpenTable Restaurant Search Scraper: Extract Paris & Global Dining Data
---
### What Is OpenTable?
OpenTable is one of the world's largest online restaurant reservation platforms, operating across major cities globally. It surfaces rich data per restaurant — availability slots, pricing tiers, cuisine types, awards, and user reviews — making it a valuable source for food industry intelligence. Manually collecting this data is impractical at scale. The **OpenTable Restaurant Search Scraper** automates extraction directly from search result pages.
---
### Overview
The **OpenTable Scraper** targets OpenTable's restaurant search URLs and returns a structured dataset for every listing on the page. Typical use cases include:
- **Travel & hospitality apps** building curated local dining guides
- **Market researchers** analyzing restaurant density, pricing, and cuisine trends by neighborhood
- **Data journalists** investigating the dining landscape in specific cities
- **Aggregator platforms** pulling live availability and offer data
---
### Input Format
The scraper accepts three configuration parameters:
```json
{
"ignore_url_failures": true,
"max_items_per_url": 200,
"urls": [
"https://www.opentable.com/s?dateTime=2026-05-28T19%3A00%3A00&covers=2&latitude=48.86182320277778&longitude=2.336352640046296&searchedLocationName=Paris&shouldUseLatLongSearch=true&metroId=3408&sortBy=web_conversion"
]
}
````
| Field | Type | Default | Description |
|---|---|---|---|
| `urls` | `array` | *(see below)* | One or more OpenTable search result URLs to scrape. Add individually or via bulk edit. |
| `max_items_per_url` | `integer` | `20` | Maximum number of restaurant records to collect per URL. Set higher (e.g., `200`) for comprehensive searches. |
| `ignore_url_failures` | `boolean` | `true` | When `true`, the scraper continues if a URL fails rather than stopping the entire run. Recommended for bulk jobs. |
#### Building a Valid Search URL
OpenTable search URLs encode several useful parameters:
| URL Parameter | Meaning |
|---|---|
| `dateTime` | Desired reservation date and time (ISO 8601) |
| `covers` | Party size |
| `latitude` / `longitude` | Geo-coordinates for location-based search |
| `searchedLocationName` | Human-readable city or area name |
| `metroId` | OpenTable's internal metro area identifier |
| `sortBy` | Result ordering (e.g., `web_conversion`, `distance`) |
> **Tip:** Build your URL directly from OpenTable's search interface, then copy it from the browser address bar.
***
### Output Format
**Sample output**
```json
{
"restaurant_id": 357597,
"name": "Nolinski",
"type": "GuestCenter",
"slot_discovery": "on",
"urls": {
"profile_link": {
"link": "https://www.opentable.com/r/nolinski-paris",
"__typename": "PageLink"
},
"__typename": "RestaurantUrls"
},
"price_band": {
"price_band_id": 2,
"currency_symbol": "€",
"name": "€30 and under",
"__typename": "PriceBand"
},
"neighborhood": {
"name": "Palais-Royal",
"__typename": "Neighborhood"
},
"statistics": {
"recent_reservation_count": 4,
"reviews": {
"all_time_text_review_count": 13,
"ratings": {
"overall": {
"rating": 4.7,
"__typename": "ReviewStatisticsRating"
},
"__typename": "ReviewStatisticsRatings"
},
"show_reviews": true,
"__typename": "ReviewStatistics"
},
"__typename": "RestaurantStatistics"
},
"primary_cuisine": {
"name": "French",
"__typename": "Cuisine"
},
"campaign_id": null,
"features": {
"subtype": null,
"bar": false,
"counter": false,
"high_top": false,
"outdoor": false,
"reservation_max_party_size": 10,
"__typename": "RestaurantFeatures"
},
"in_premium_marketplace": false,
"restaurant_availability_token": "eyJ2IjozLCJtIjoxLCJwIjowLCJzIjowLCJuIjowfQ",
"groups": [
{
"id": 332845,
"rids": null,
"off_discovery_restaurant_ids": null,
"always_off_discovery_restaurant_ids": null,
"__typename": "RestaurantGroup"
}
],
"awards": null,
"typename": "Restaurant",
"is_pinned": false,
"private_dining": {
"has_private_dining": false,
"has_enhanced_private_dining": false,
"__typename": "PrivateDining"
},
"photos": {
"gallery": {
"photos": [
{
"thumbnails": [
{
"url": "https://resizer.otstatic.com/v4/photos/76953713-2?width=640&height=360",
"__typename": "Thumbnail"
}
],
"pid": 76953713,
"__typename": "GalleryPhoto"
},
{
"thumbnails": [
{
"url": "https://resizer.otstatic.com/v4/photos/93306588-1?width=640&height=360",
"__typename": "Thumbnail"
}
],
"pid": 93306588,
"__typename": "GalleryPhoto"
},
{
"thumbnails": [
{
"url": "https://resizer.otstatic.com/v4/photos/93306584-1?width=640&height=360",
"__typename": "Thumbnail"
}
],
"pid": 93306584,
"__typename": "GalleryPhoto"
},
{
"thumbnails": [
{
"url": "https://resizer.otstatic.com/v4/photos/93306586-1?width=640&height=360",
"__typename": "Thumbnail"
}
],
"pid": 93306586,
"__typename": "GalleryPhoto"
},
{
"thumbnails": [
{
"url": "https://resizer.otstatic.com/v4/photos/93306585-1?width=640&height=360",
"__typename": "Thumbnail"
}
],
"pid": 93306585,
"__typename": "GalleryPhoto"
},
{
"thumbnails": [
{
"url": "https://resizer.otstatic.com/v4/photos/76953665-2?width=640&height=360",
"__typename": "Thumbnail"
}
],
"pid": 76953665,
"__typename": "GalleryPhoto"
}
],
"__typename": "GalleryPhotos"
},
"profile_v3": {
"url": "//resizer.otstatic.com/v3/photos/76953713-2",
"xsmall": {
"url": "//resizer.otstatic.com/v3/photos/76953713-2?width=105&height=105&webp=true",
"width": 105,
"__typename": "Thumbnail"
},
"small": {
"url": "//resizer.otstatic.com/v3/photos/76953713-2?width=160&height=160&webp=true",
"width": 160,
"__typename": "Thumbnail"
},
"legacy": {
"url": "//resizer.otstatic.com/v3/photos/76953713-2?width=208&height=208&webp=true",
"width": 208,
"__typename": "Thumbnail"
},
"medium": {
"url": "//resizer.otstatic.com/v3/photos/76953713-2?width=320&height=320&webp=true",
"width": 320,
"__typename": "Thumbnail"
},
"wide_medium": {
"url": "//resizer.otstatic.com/v3/photos/76953713-2?width=320&height=180&webp=true",
"width": 320,
"__typename": "Thumbnail"
},
"wide_mlarge": {
"url": "//resizer.otstatic.com/v3/photos/76953713-2?width=480&height=270&webp=true",
"width": 480,
"__typename": "Thumbnail"
},
"__typename": "RestaurantProfilePhotoV3"
},
"__typename": "RestaurantPhotos"
},
"just_added_details": {
"just_added": false,
"__typename": "JustAddedDetails"
},
"offers": [],
"dining_style": "Casual Elegant",
"coordinates": {
"latitude": 48.8654978,
"longitude": 2.3347863,
"__typename": "GeographicCoordinates"
},
"address": {
"line1": "16 Av. de l'Opéra",
"line2": "",
"city": "Paris",
"state": "Ile-de-France",
"post_code": "75001",
"__typename": "Address"
},
"description": "An intimate, timeless address. Corduroy banquettes, honey-coloured wood, oiled Versailles parquet flooring, Sienna yellow marble, brass, golden light... Everything comes together and brings us together, as if by magic. A softness that continues as soon as night falls in the subdued light of candles
Philip Chronopoulos celebrates the richness and finesse of French gastronomy by revisiting emblematic, comforting dishes such as pot-au-feu, poultry and macaroni gratin with morel mushrooms. The plated desserts, meanwhile, evoke memories of childhood with finesse, sublimating familiar flavours thanks to the chef's delicate expertise.
",
"top_review": {
"highlighted_text": "The food, venue and service were all excellent. It’s a little pricey but well worth it. I would definitely come back.",
"__typename": "ReviewWithHighlights"
},
"match_relevance": null,
"has_takeout": false,
"contact_information": {
"phone_number": "0142861010",
"formatted_phone_number": "01 42 86 10 10",
"__typename": "RestaurantContactInformation"
},
"delivery_partners": [],
"order_online_link": null,
"from_url": "https://www.opentable.com/s?dateTime=2026-05-28T19%3A00%3A00&covers=2&latitude=48.86182320277778&longitude=2.336352640046296&searchedLocationName=Paris&shouldUseLatLongSearch=true&originCorrelationId=ec23bce4-acb8-4be7-9e1b-b02a4dbe3f15&corrid=3403c841-8265-4547-99f0-54fa84193d81&metroId=3408&queryUnderstandingType=none&showMap=true&sortBy=web_conversion"
}
```
Each restaurant record contains 30+ fields:
#### Identity & Classification
| Field | Meaning |
|---|---|
| `Restaurant ID` | OpenTable's unique internal identifier |
| `Name` | Restaurant display name |
| `Type` | Listing type classification |
| `Typename` | GraphQL type name from OpenTable's API |
| `Primary Cuisine` | Main cuisine category (e.g., French, Italian) |
| `Dining Style` | Ambiance descriptor (e.g., Casual Elegant, Bistro) |
| `Description` | Short editorial description of the restaurant |
#### Location & Contact
| Field | Meaning |
|---|---|
| `Address` | Full street address |
| `Neighborhood` | District or area within the city |
| `Coordinates` | Latitude/longitude for mapping |
| `Contact Information` | Phone number or public contact details |
#### Pricing & Offers
| Field | Meaning |
|---|---|
| `Price Band` | Cost indicator (e.g., `$`, `$$`, `$$$`, `$$$$`) |
| `Offers` | Active promotions or special dining deals |
| `In Premium Marketplace` | Whether the restaurant pays for premium placement |
| `Campaign ID` | Associated marketing campaign identifier |
#### Availability & Booking
| Field | Meaning |
|---|---|
| `Slot Discovery` | Available reservation time slots for the queried date/party |
| `Restaurant Availability Token` | Token used to initiate a booking session |
| `URLs` | Direct links to the restaurant's OpenTable profile |
#### Reviews & Reputation
| Field | Meaning |
|---|---|
| `Statistics` | Aggregate ratings and review counts |
| `Top Review` | Excerpt from the highest-rated or featured review |
| `Awards` | Dining awards or recognition (e.g., OpenTable Diners' Choice) |
| `Match Relevance` | Score indicating how well the result matches the search query |
#### Features & Flags
| Field | Meaning |
|---|---|
| `Features` | Amenities such as outdoor seating, private events, parking |
| `Private Dining` | Whether private dining rooms are available |
| `Has Takeout` | Indicates takeout availability |
| `Delivery Partners` | Linked delivery services (e.g., Uber Eats, DoorDash) |
| `Order Online Link` | Direct link for online ordering if supported |
| `Groups` | Group booking eligibility |
| `Just Added Details` | Metadata for newly listed restaurants |
| `Is Pinned` | Whether the result is editorially pinned at the top |
| `Photos` | Image URLs associated with the listing |
***
### How to Use
1. **Run a search on OpenTable** — Set your city, date, party size, and filters. Copy the full URL from your browser.
2. **Paste into `urls`** — Add one or more search URLs to the array.
3. **Set `max_items_per_url`** — Use `200` for dense city searches; lower values for quick tests.
4. **Run the scraper** — Monitor progress in the run log.
5. **Export** — Download results as JSON, CSV, or XLSX.
**Best practices:**
- Each unique search URL (different date, location, or party size) counts as a separate item in `urls`.
- If scraping multiple cities, add one URL per city rather than running separate jobs.
- Use `ignore_url_failures: true` for any batch run to avoid interruptions from occasional timeouts.
***
### Use Cases & Business Value
- **Restaurant discovery apps:** Pre-populate curated city guides with live availability and ratings
- **Competitive analysis:** Compare pricing bands and cuisine distribution across neighborhoods
- **Event planning tools:** Find restaurants with private dining and group booking support
- **Academic research:** Study urban dining patterns, award distribution, or delivery adoption rates
***
### Conclusion
The **OpenTable Restaurant Search Scraper** turns any OpenTable search page into a rich, structured dataset in minutes. With 30+ fields spanning availability, pricing, location, reviews, and features, it provides the depth needed for serious food industry analysis or application development. Configure your search URL, set your limits, and start collecting.
# Actor input Schema
## `urls` (type: `array`):
Add the URLs of the restaurants list urls you want to scrape. You can paste URLs one by one, or use the Bulk edit section to add a prepared list.
## `ignore_url_failures` (type: `boolean`):
If true, the scraper will continue running even if some URLs fail to be scraped.
## `max_items_per_url` (type: `integer`):
The maximum number of items to scrape per URL.
## `proxy` (type: `object`):
Select proxies to be used by your scraper.
## Actor input object example
```json
{
"urls": [
"https://www.opentable.com/s?dateTime=2026-05-28T19%3A00%3A00&covers=2&latitude=48.86182320277778&longitude=2.336352640046296&searchedLocationName=Paris&shouldUseLatLongSearch=true&originCorrelationId=ec23bce4-acb8-4be7-9e1b-b02a4dbe3f15&corrid=3403c841-8265-4547-99f0-54fa84193d81&metroId=3408&queryUnderstandingType=none&showMap=true&sortBy=web_conversion"
],
"ignore_url_failures": true,
"max_items_per_url": 20,
"proxy": {
"useApifyProxy": true,
"apifyProxyGroups": [
"RESIDENTIAL"
],
"apifyProxyCountry": "US"
}
}
```
# 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 = {
"urls": [
"https://www.opentable.com/s?dateTime=2026-05-28T19%3A00%3A00&covers=2&latitude=48.86182320277778&longitude=2.336352640046296&searchedLocationName=Paris&shouldUseLatLongSearch=true&originCorrelationId=ec23bce4-acb8-4be7-9e1b-b02a4dbe3f15&corrid=3403c841-8265-4547-99f0-54fa84193d81&metroId=3408&queryUnderstandingType=none&showMap=true&sortBy=web_conversion"
],
"ignore_url_failures": true,
"max_items_per_url": 20,
"proxy": {
"useApifyProxy": true,
"apifyProxyGroups": [
"RESIDENTIAL"
],
"apifyProxyCountry": "US"
}
};
// Run the Actor and wait for it to finish
const run = await client.actor("stealth_mode/opentable-restaurants-search-scraper").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 = {
"urls": ["https://www.opentable.com/s?dateTime=2026-05-28T19%3A00%3A00&covers=2&latitude=48.86182320277778&longitude=2.336352640046296&searchedLocationName=Paris&shouldUseLatLongSearch=true&originCorrelationId=ec23bce4-acb8-4be7-9e1b-b02a4dbe3f15&corrid=3403c841-8265-4547-99f0-54fa84193d81&metroId=3408&queryUnderstandingType=none&showMap=true&sortBy=web_conversion"],
"ignore_url_failures": True,
"max_items_per_url": 20,
"proxy": {
"useApifyProxy": True,
"apifyProxyGroups": ["RESIDENTIAL"],
"apifyProxyCountry": "US",
},
}
# Run the Actor and wait for it to finish
run = client.actor("stealth_mode/opentable-restaurants-search-scraper").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 '{
"urls": [
"https://www.opentable.com/s?dateTime=2026-05-28T19%3A00%3A00&covers=2&latitude=48.86182320277778&longitude=2.336352640046296&searchedLocationName=Paris&shouldUseLatLongSearch=true&originCorrelationId=ec23bce4-acb8-4be7-9e1b-b02a4dbe3f15&corrid=3403c841-8265-4547-99f0-54fa84193d81&metroId=3408&queryUnderstandingType=none&showMap=true&sortBy=web_conversion"
],
"ignore_url_failures": true,
"max_items_per_url": 20,
"proxy": {
"useApifyProxy": true,
"apifyProxyGroups": [
"RESIDENTIAL"
],
"apifyProxyCountry": "US"
}
}' |
apify call stealth_mode/opentable-restaurants-search-scraper --silent --output-dataset
```
## MCP server setup
```json
{
"mcpServers": {
"apify": {
"command": "npx",
"args": [
"mcp-remote",
"https://mcp.apify.com/?tools=stealth_mode/opentable-restaurants-search-scraper",
"--header",
"Authorization: Bearer "
]
}
}
}
```
## OpenAPI specification
```json
{
"openapi": "3.0.1",
"info": {
"title": "Opentable Restaurants Search Scraper",
"description": "Scrape OpenTable restaurant search results effortlessly. Extract names, cuisines, availability slots, reviews, pricing, coordinates, and 30+ fields per restaurant — perfect for market research, travel apps, and food industry analysis.",
"version": "0.0",
"x-build-id": "jAceK1sL7JGdM62ZJ"
},
"servers": [
{
"url": "https://api.apify.com/v2"
}
],
"paths": {
"/acts/stealth_mode~opentable-restaurants-search-scraper/run-sync-get-dataset-items": {
"post": {
"operationId": "run-sync-get-dataset-items-stealth_mode-opentable-restaurants-search-scraper",
"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/stealth_mode~opentable-restaurants-search-scraper/runs": {
"post": {
"operationId": "runs-sync-stealth_mode-opentable-restaurants-search-scraper",
"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/stealth_mode~opentable-restaurants-search-scraper/run-sync": {
"post": {
"operationId": "run-sync-stealth_mode-opentable-restaurants-search-scraper",
"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": {
"urls": {
"title": "URLs of the restaurants list urls to scrape",
"type": "array",
"description": "Add the URLs of the restaurants list urls you want to scrape. You can paste URLs one by one, or use the Bulk edit section to add a prepared list.",
"items": {
"type": "string"
}
},
"ignore_url_failures": {
"title": "Continue running even if some URLs fail to be scraped",
"type": "boolean",
"description": "If true, the scraper will continue running even if some URLs fail to be scraped."
},
"max_items_per_url": {
"title": "Max items per URL",
"type": "integer",
"description": "The maximum number of items to scrape per URL."
},
"proxy": {
"title": "Proxy configuration",
"type": "object",
"description": "Select proxies to be used by your scraper."
}
}
},
"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
}
}
}
}
}
}
}
}
}
}
```