# Angi.com \[Only $0.8💰] Scraper (Resilient Leads & Profiles) (`memo23/angi-scraper`) Actor
\[Only $0.8💰] Extract high-quality contractor leads from Angi.com (Angie's List). Scrape business names, phone numbers, full addresses, ratings, review counts, and service categories. Just input a ZIP code or category link to instantly get structured local business data in JSON or CSV.
- **URL**: https://apify.com/memo23/angi-scraper.md
- **Developed by:** [Muhamed Didovic](https://apify.com/memo23) (community)
- **Categories:** Lead generation, Automation, Agents
- **Stats:** 3 total users, 2 monthly users, 84.6% runs succeeded, NaN bookmarks
- **User rating**: No ratings yet
## Pricing
from $0.90 / 1,000 results
This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.
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
## Angi.com Scraper (Leads & Profiles)
#### How it works
**Unlock the Full Power of Angi Home Services Data** - The most resilient scraper for extracting high-quality leads, professional profiles, and business details from Angi.com (formerly Angie's List). Whether you're conducting market research, performing competitor analysis, or building a local service database, our scraper delivers precise, structured data at scale.
*"From garage builders and plumbers to roofers and electricians, turn Angi's massive directory into your strategic advantage."*
### Why Use This Scraper?
- **Multiple Starting Points**: Start from the entire US directory, a specific state, a city, a service category, or directly input professional profile URLs.
- **Enterprise-Grade Resilience**: Implements parallel TLS fingerprint racing (`impit`) and intelligent proxy rotation to bypass aggressive Cloudflare and anti-bot blocks.
- **Deep Directory Discovery**: Automatically discovers nested states → cities → categories → professional profiles without manual pagination.
- **Structured Output**: Extract clean, verified business names, addresses, phone numbers, and service categories.
- **Export Ready**: Supports deeply nested JSON for developers or flattened CSV formats for CRM imports.
### Overview
The Angi.com Scraper is designed to seamlessly navigate Angi's Next.js infrastructure. By relying on a custom internal handler rather than standard browser automation, it maintains high throughput and bypasses limitations that block standard crawlers. The output focuses primarily on **business profile rows**, regardless of where the scrape starts.
### Supported Inputs
You can mix and match different types of Angi URLs in the `startUrls` input:
- **US Directory Root**: `https://www.angi.com/companylist/us/` (Scrapes the entire US)
- **Near Me Root**: `https://www.angi.com/nearme/`
- **State Hubs**: `https://www.angi.com/companylist/us/tx/` (Scrapes all cities in Texas)
- **City Hubs**: `https://www.angi.com/companylist/us/al/adamsville/`
- **Category Lists**: `https://www.angi.com/nearme/garage-builders/`
- **Direct Profiles**: `https://www.angi.com/companylist/us/al/cullman/access-garage-doors-of-birmingham-reviews-1.htm`
- **ZIP Codes**: Just input a 5-digit ZIP code like `90210` and the scraper will automatically resolve it to the corresponding city hub!
### Use Cases
| Audience | Example Use Case |
|---|---|
| **Sales & Lead Gen** | Build targeted contact lists of local contractors (e.g., all plumbers in Texas) with verified phone numbers. |
| **Market Researchers** | Analyze service density and categorize businesses by specific niches across different ZIP codes. |
| **Marketing Agencies** | Offer specialized marketing or SEO services to home service professionals found on Angi. |
| **Competitor Analysis** | Track local competitors, their listed services, operating hours, and service areas. |
### How It Works
```mermaid
flowchart LR
A[Start URLs] --> B{URL Type?}
B -->|Directory/Hub| C[Discover States & Cities]
B -->|Category| D[Discover Businesses]
B -->|Profile| E[Direct Extraction]
C --> D
D --> E
E --> F[Next.js JSON Payload]
F --> G[(Apify Dataset)]
style A fill:#2e86de,stroke:#000,color:#fff
style B fill:#feca57,stroke:#000,color:#000
style E fill:#10ac84,stroke:#000,color:#fff
style G fill:#ff6b6b,stroke:#000,color:#fff
````
1. **You provide URLs**: Input one or more Angi directory, category, or profile URLs.
2. **Actor categorizes inputs**: The scraper detects the URL type (hub, state, city, category, or profile).
3. **Deep fan-out**: For directory URLs, the scraper automatically navigates the hierarchy to discover individual business profiles.
4. **Data extraction**: The actor fetches the Next.js build data for each profile, extracting robust business information.
5. **Dataset export**: The extracted profiles are saved to your Apify dataset, ready for JSON or CSV download.
### Input Configuration
Here is a typical configuration. The `useInternalHandler` flag is enabled by default to ensure maximum anti-bot resilience.
```json
{
"startUrls": [
{ "url": "https://www.angi.com/nearme/garage-builders/" }
],
"maxItems": 500,
"flattenDatasetOutput": true,
"proxy": {
"useApifyProxy": true,
"apifyProxyGroups": ["RESIDENTIAL"]
}
}
```
### Output Overview
The scraper's primary dataset items are **business profile rows**.
- **Nested JSON**: Keeps objects intact (e.g., `contactInfo.address.city`).
- **Flattened (CSV-friendly)**: If you enable `flattenDatasetOutput`, nested objects are flattened into dot-separated keys (e.g., `contactInfo_address_city`), ensuring no columns are dropped in Excel.
#### Sample JSON Output
```json
{
"url": "https://www.angi.com/companylist/us/al/cullman/access-garage-doors-of-birmingham-reviews-1.htm",
"category": {
"text": "Garage Builders",
"title": "Garage Builders",
"link": "/companylist/us/al/garage-builders.htm"
},
"state": {
"text": "AL",
"title": "AL Home Services",
"href": "https://www.angi.com/companylist/us/al/"
},
"city": {
"text": "Adamsville",
"title": "Adamsville",
"link": "/companylist/us/al/adamsville/"
},
"companyProfile": {
"businessInfo": {
"businessName": "Access Garage Doors of Birmingham",
"amenities": {},
"hoursInfo": {
"hoursInfoDetail": [],
"acceptsAppointments": false
}
},
"contactInfo": {
"emails": [],
"phoneNumbers": ["205-555-0123"],
"address": {
"street1": "123 Business Way",
"city": "Cullman",
"state": "AL",
"country": "United States",
"postalCode": "35055"
}
},
"logoUrl": "https://example.com/logo.png"
}
}
```
#### Key Output Fields
##### Top-Level Group
- **`url`** (String): The direct URL to the professional's profile on Angi.
- **`category`** (Object): Details about the specific service niche.
- **`state`** (Object): Geographic state container.
- **`city`** (Object): Local city container.
##### Company Data
- **`companyProfile`** (Object): The core data container extracted from the profile page.
- **`businessInfo`** (Object): Contains the official `businessName`, `amenities`, and `hoursInfo`.
- **`contactInfo`** (Object): Contains arrays for `emails`, `phoneNumbers`, and the physical `address` object.
- **`slug`** (Object): Canonical URL and aliases.
- **`logoUrl`** (String): Full URL to the business logo.
- **`images`** (Array): Gallery of business-provided images or project photos.
*Note: For ease of use in flat exports like CSV, key profile fields are also mirrored at the top level.*
### FAQ
**Can I scrape a specific category nationwide?**
Yes! Input a nationwide category URL like `https://www.angi.com/nearme/garage-builders/`, and the scraper will automatically navigate through all states and cities for that category.
**Does it extract emails?**
The scraper extracts emails only when they are publicly available on the business profile. Many businesses do not expose their email publicly.
**What is the "flattenDatasetOutput" option?**
Angi's data is deeply nested. If you want to download a CSV for Excel or Google Sheets, enable this option. It unpacks nested objects so that every data point gets its own column.
### Support
- For issues or feature requests, please use the **Issues** section of this actor.
- If you need customization or have questions, feel free to contact the author:
- Author's website:
- Email:
### Additional Services
- **Request Customization**: Need specific filters or custom fields?
- **Dataset Purchases**: Looking for a pre-scraped dataset of all Angi pros? Reach out for pricing.
- **API Access**: High-volume API services available for enterprise integrations.
# Actor input Schema
## `startUrls` (type: `array`):
Provide Angi URLs (e.g. /companylist/us/, /nearme/, state hubs, city hubs, category listings, or direct profiles).
## `zipCodes` (type: `array`):
Enter a list of 5-digit ZIP codes (e.g. 90210). The scraper will automatically resolve them to the correct Angi city directories.
## `zipCodeCategory` (type: `string`):
If providing ZIP codes, optionally select a service category to strictly scrape that category within the ZIP code. Leave default to scrape the whole city.
## `flattenDatasetOutput` (type: `boolean`):
If **true**, deep-flatten rows: nested objects → keys like businessInfo\_businessName; arrays of objects → name\_0\_field; primitive arrays comma-joined; empty objects as '{}'. Includes the duplicate companyProfile\_\* tree. If **false** (default), keep nested JSON.
## `maxItems` (type: `integer`):
Stop the run after pushing this many rows to the dataset (each profile save or missing\_profile\_payload row). Omit or **0** for no limit.
## `maxRequestRetries` (type: `integer`):
Retries after failures before giving up.
## `proxy` (type: `object`):
Specifies proxy servers that will be used by the scraper in order to hide its origin.
For details, see Proxy configuration in README.
## Actor input object example
```json
{
"startUrls": [
{
"url": "https://www.angi.com/companylist/us/al/garage-builders.htm"
},
{
"url": "https://www.angi.com/companylist/us/al/forestdale/garage-builders.htm"
}
],
"zipCodes": [],
"zipCodeCategory": "",
"flattenDatasetOutput": false,
"maxRequestRetries": 100,
"proxy": {
"useApifyProxy": true,
"apifyProxyGroups": [
"RESIDENTIAL"
]
}
}
```
# 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 = {
"startUrls": [
{
"url": "https://www.angi.com/companylist/us/al/garage-builders.htm"
},
{
"url": "https://www.angi.com/companylist/us/al/forestdale/garage-builders.htm"
}
],
"proxy": {
"useApifyProxy": true,
"apifyProxyGroups": [
"RESIDENTIAL"
]
}
};
// Run the Actor and wait for it to finish
const run = await client.actor("memo23/angi-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 = {
"startUrls": [
{ "url": "https://www.angi.com/companylist/us/al/garage-builders.htm" },
{ "url": "https://www.angi.com/companylist/us/al/forestdale/garage-builders.htm" },
],
"proxy": {
"useApifyProxy": True,
"apifyProxyGroups": ["RESIDENTIAL"],
},
}
# Run the Actor and wait for it to finish
run = client.actor("memo23/angi-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 '{
"startUrls": [
{
"url": "https://www.angi.com/companylist/us/al/garage-builders.htm"
},
{
"url": "https://www.angi.com/companylist/us/al/forestdale/garage-builders.htm"
}
],
"proxy": {
"useApifyProxy": true,
"apifyProxyGroups": [
"RESIDENTIAL"
]
}
}' |
apify call memo23/angi-scraper --silent --output-dataset
```
## MCP server setup
```json
{
"mcpServers": {
"apify": {
"command": "npx",
"args": [
"mcp-remote",
"https://mcp.apify.com/?tools=memo23/angi-scraper",
"--header",
"Authorization: Bearer "
]
}
}
}
```
## OpenAPI specification
```json
{
"openapi": "3.0.1",
"info": {
"title": "Angi.com [Only $0.8💰] Scraper (Resilient Leads & Profiles)",
"description": "[Only $0.8💰] Extract high-quality contractor leads from Angi.com (Angie's List). Scrape business names, phone numbers, full addresses, ratings, review counts, and service categories. Just input a ZIP code or category link to instantly get structured local business data in JSON or CSV.",
"version": "0.0",
"x-build-id": "OJ4VGRf6eHyvtze8c"
},
"servers": [
{
"url": "https://api.apify.com/v2"
}
],
"paths": {
"/acts/memo23~angi-scraper/run-sync-get-dataset-items": {
"post": {
"operationId": "run-sync-get-dataset-items-memo23-angi-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$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/memo23~angi-scraper/runs": {
"post": {
"operationId": "runs-sync-memo23-angi-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/memo23~angi-scraper/run-sync": {
"post": {
"operationId": "run-sync-memo23-angi-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": {
"startUrls": {
"title": "Start URLs",
"type": "array",
"description": "Provide Angi URLs (e.g. /companylist/us/, /nearme/, state hubs, city hubs, category listings, or direct profiles).",
"items": {
"type": "object",
"required": [
"url"
],
"properties": {
"url": {
"type": "string",
"title": "URL of a web page",
"format": "uri"
}
}
}
},
"zipCodes": {
"title": "ZIP Codes",
"type": "array",
"description": "Enter a list of 5-digit ZIP codes (e.g. 90210). The scraper will automatically resolve them to the correct Angi city directories.",
"default": [],
"items": {
"type": "string"
}
},
"zipCodeCategory": {
"title": "Category for ZIP Codes (Optional)",
"enum": [
"",
"air-duct-cleaning",
"animal-removal",
"tv-antenna",
"appliance-repair",
"architects",
"asbestos-removal",
"awnings",
"remodeling-basements",
"basement-waterproofing",
"basketball-goals",
"bathtub-refinishing",
"biohazard-remediation",
"blind-cleaning",
"cabinet-makers",
"cabinet-refinishing",
"carpet-cleaning",
"carpet",
"ceiling-fans",
"central-vacuum-cleaners",
"childproofing",
"chimney-caps",
"chimney-repair",
"chimney-sweep",
"cleaning",
"closets",
"computer-repair",
"concrete-driveways",
"concrete-repair",
"countertops",
"deck-maintenance",
"decks-and-porches",
"dock-building-repair",
"pet-fencing",
"doors",
"drain-cleaning",
"drain-pipe-installation",
"drapery-cleaning",
"driveway-gates",
"driveways",
"dryer-vent-cleaning",
"drywall",
"dumpster-rental",
"earthquake-retrofit",
"egress",
"electrical",
"epoxy-flooring",
"excavating",
"fencing",
"fireplaces",
"firewood",
"buffing-and-polishing",
"floor-cleaning",
"flooring",
"foundation-repair",
"fountains",
"furniture-refinishing",
"garage-builders",
"garage-doors",
"gas-logs",
"gas-leak-repair",
"contractor",
"generator-installers",
"glass-block",
"glass-and-mirrors",
"gas-grill-repair",
"gutter-cleaning",
"gutter-repair-replacement",
"handyman-service",
"landscaping-hardscaping-and-pavers",
"hardwood-flooring",
"hauling",
"heating-oil-companies",
"holiday-decorating",
"home-automation",
"home-builders",
"energy-audit",
"home-inspection",
"kitchen-and-bath-remodeling",
"home-security-systems",
"home-staging",
"home-theater-systems",
"home-warranty-companies",
"house-cleaning",
"exterior-painting",
"hurricane-shutters",
"hvac",
"insulation",
"interior-design",
"interior-painting",
"wrought-iron",
"lawn-irrigation",
"appraisals",
"land-surveying",
"landscaping-lighting",
"appliance-sales",
"landscaping",
"lawn-and-yard-work",
"lawn-mower-repair",
"lawn-fertilization-and-treatment",
"lead-testing-and-removal",
"leaf-removal",
"leather-and-vinyl-repair",
"lighting",
"locksmiths",
"mailbox-repair",
"marble-and-granite",
"masonry",
"metal-fabrication-and-restoration",
"remodeling-modular-and-mobile-home",
"mold-testing-and-remediation",
"moving",
"concrete-leveling",
"mulch-and-topsoil",
"plant-nurseries",
"oriental-rug-cleaning",
"outdoor-kitchens",
"sunroom-and-patio-remodeling",
"patios",
"pest-control",
"home-phone-service",
"phone-repair",
"piano-moving",
"plaster-plaster-repair",
"playground-equipment",
"plumbing",
"pool-and-spa-service",
"swimming-pools",
"pressure-washing",
"home-and-garage-organization",
"radon-testing",
"real-estate-agents",
"property-appraiser",
"roof-cleaning",
"roof-ice-and-snow-removal",
"roofing",
"roto-tilling",
"satellite-tv-service",
"screen-repair",
"septic-tank",
"sewer-cleaning",
"siding",
"skylights",
"small-appliance-repair",
"snow-removal",
"solar-panels",
"concrete-stamped-decorative",
"stone-and-gravel",
"structural-engineering",
"stucco",
"ceramic-tile",
"garbage-collection",
"tree-service",
"upholstering",
"upholstery-cleaning",
"wallpapering",
"wallpaper-removal",
"water-and-smoke-damage",
"water-heaters",
"water-softeners",
"welding",
"wells-and-pumps",
"window-cleaning",
"windows",
"hurricane-film",
"window-tinting",
"window-treatments",
"woodworking"
],
"type": "string",
"description": "If providing ZIP codes, optionally select a service category to strictly scrape that category within the ZIP code. Leave default to scrape the whole city.",
"default": ""
},
"flattenDatasetOutput": {
"title": "Flatten output",
"type": "boolean",
"description": "If **true**, deep-flatten rows: nested objects → keys like businessInfo_businessName; arrays of objects → name_0_field; primitive arrays comma-joined; empty objects as '{}'. Includes the duplicate companyProfile_* tree. If **false** (default), keep nested JSON.",
"default": false
},
"maxItems": {
"title": "Max dataset items",
"minimum": 0,
"type": "integer",
"description": "Stop the run after pushing this many rows to the dataset (each profile save or missing_profile_payload row). Omit or **0** for no limit."
},
"maxRequestRetries": {
"title": "Limit retries per request",
"type": "integer",
"description": "Retries after failures before giving up.",
"default": 100
},
"proxy": {
"title": "Proxy configuration",
"type": "object",
"description": "Specifies proxy servers that will be used by the scraper in order to hide its origin.
For details, see Proxy configuration in README.",
"default": {
"useApifyProxy": true,
"apifyProxyGroups": [
"RESIDENTIAL"
]
}
}
}
},
"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
}
}
}
}
}
}
}
}
}
}
```