# Realtor Email Scraper (`scraperx/realtor-email-scraper`) Actor

🏠 Realtor Email Scraper finds verified realtor email addresses fast by extracting contact details from public listings. ⚡ Boost outreach for sales, partnerships & lead gen. 🚀 Quick, efficient, and built for targeted real estate marketing.

- **URL**: https://apify.com/scraperx/realtor-email-scraper.md
- **Developed by:** [ScraperX](https://apify.com/scraperx) (community)
- **Categories:** Automation, Lead generation, Real estate
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $3.99 / 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.

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

### **Realtor** Email Scraper 📱

The **Realtor** Email Scraper allows users to **extract** a wide range of **data** from real estate platforms. It is designed to collect detailed **contact** information, including email addresses, names, and phone numbers of real estate professionals.

This tool also gathers additional **data** such as agency names, property details, and location information. By using the **Realtor** Email Scraper, users can build comprehensive **data**bases for marketing and networking purposes.

The **extract**ed **data** is presented in a structured format, making it easy to analyze and utilize. Whether you are looking to connect with real estate agents or generate leads, this tool provides the information you need efficiently and accurately.

Realtor Email Scraper is a powerful tool designed to help users extract contact information from real estate platforms efficiently. It enables businesses and individuals to gather valuable data for marketing, networking, or research purposes.

With the Realtor Email Scraper, you can access and compile email addresses and other key details of real estate professionals. This tool is ideal for building targeted email lists and generating leads in the real estate industry.

The Realtor Email Scraper simplifies the process of collecting contact information, saving time and effort for users. It is designed to provide accurate and up-to-date data for real estate agents and professionals.

### Support and feedback

- **Bug reports**: Open a ticket in the repository Issues section
- **Custom features**: Contact our enterprise support team
  *Email: dev.scraperengine@gmail.com *
### Extractable Data Table 📊
| Data Type | Description |
| --- | --- |
| Email addresses | Extract the email addresses of real estate agents and professionals. |
| Full names | Retrieve the names of real estate agents and property professionals. |
| Phone numbers | Collect phone numbers for direct communication with agents. |
| Agency names | Identify the agencies or companies associated with the agents. |
| Property details | Extract information about listed properties, including descriptions and prices. |
| Location information | Gather location data for agents, agencies, and properties. |
| Social media profiles | Find links to social media profiles of real estate professionals. |
| Website URLs | Retrieve URLs of agency or personal websites for additional insights. |

### Key Features of **Realtor** Email Scraper

Here are the **standout features** that make the **Realtor** Email Scraper a **top-tier tool** for **marketers**, **agencies**, and **researchers**:

- ⭐ **Automated** extraction of real estate agent email addresses for efficient data collection
- ⭐ Ability to gather detailed contact information including phone numbers and names
- ⭐ Supports extraction of agency names and associated property details for comprehensive insights
- ⭐ Structured output format for easy analysis and integration into marketing tools
- ⭐ **Customizable** scraping options to target specific regions or property types
- ⭐ **High** accuracy and up-to-date data to ensure reliable information for outreach campaigns
- ⭐ User-friendly interface for seamless operation without technical expertise
- ⭐ **Fast** processing speeds to save time and enhance productivity
- ⭐ **Secure** data handling to protect user privacy and comply with regulations
- ⭐ Compatibility with various real estate platforms for versatile data collection

### How to use **Realtor** Email Scraper 🚀

Follow this **simple, step-by-step guide** to start extracting **Realtor** emails today:

1. ✅ **Sign up** or **log in** to the **Realtor** Email Scraper platform
2. ✅ **Select** the target real estate platform or website for data extraction
3. ✅ Define the scraping parameters such as location property type or agent criteria
4. ✅ **Start** the scraping process and monitor progress through the dashboard
5. ✅ **Review** the extracted data and ensure accuracy before exporting
6. ✅ **Export** the data in your preferred format such as CSV or Excel
7. ✅ **Integrate** the exported data into your marketing or CRM tools
8. ✅ Use the data to create targeted email campaigns or build a real estate database
9. ✅ Repeat the process as needed to keep your data updated and relevant
10. ✅ Contact support if you encounter any issues during the scraping process

### Use Cases 🎯

Lead Generation for Real Estate Agencies
🎯 Build targeted email lists of real estate agents for outreach campaigns
🎯 Generate leads by collecting contact information from **Realtor** platforms

Market Research and Analysis
🎯 Gather data on property listings and agent activities for market insights
🎯 **Analyze** trends and patterns in real estate using extracted information

Networking with Real Estate Professionals
🎯 Connect with real estate agents and agencies for collaboration opportunities
🎯 **Find** contact details of property agents to expand your professional network

Creating Real Estate Email Databases
🎯 Compile comprehensive email lists for marketing and communication purposes
🎯 Organize data efficiently for future reference and outreach

### Why choose us? 💎

**Realtor** Email Scraper is the ultimate solution for extracting contact information from real estate platforms. Our tool is designed to provide accurate and **reliable** data, ensuring users can build targeted email lists effortlessly.

With **advanced** features and customizable options, the **Realtor** Email Scraper caters to diverse needs in the real estate industry. Whether you are looking to generate leads, conduct market research, or connect with professionals, our tool delivers high-quality results.

We prioritize user satisfaction by offering a **user-friendly** interface and fast processing speeds. Our commitment to data security ensures that your information is handled responsibly and complies with legal guidelines.

Choose **Realtor** Email Scraper to streamline your data collection process and achieve your business goals efficiently.

### **Realtor** Email Scraper Scalability 📈

**Realtor** Email Scraper is built to handle data extraction tasks of varying scales, making it suitable for businesses of all sizes. Whether you need to collect information on a few agents or thousands of professionals, our tool can accommodate your requirements.

The scalable design ensures consistent performance even for **large-scale** scraping projects. Users can customize parameters to focus on specific regions, property types, or agent categories.

With fast processing speeds and structured outputs, the **Realtor** Email Scraper simplifies data management and integration. Our solution adapts to your growing needs, providing reliable results as your business expands.

Experience the scalability of **Realtor** Email Scraper and take your real estate data collection to the next level.

### **Realtor** Email Scraper Legal Guidelines ⚖️

**Yes**—scraping **Realtor** is **legal** as long as you follow **ethical** and **compliant** practices. The **Realtor** Email Scraper extracts only **publicly available** information from **public** **Realtor** profiles, making it **safe** and **compliant** for **research**, **marketing**, and **analysis**.

#### Legal & Ethical Guidelines
⚖️ **Ensure** compliance with local and international data privacy laws when using the **Realtor** Email Scraper
⚖️ **Obtain** consent from individuals before using their contact information for marketing purposes
⚖️ **Avoid** scraping platforms that explicitly prohibit data extraction in their terms of service
⚖️ **Use** the extracted data responsibly and refrain from spamming or unethical practices
⚖️ Regularly review legal regulations to ensure your data collection activities remain compliant
⚖️ **Do not** sell or distribute extracted data without proper authorization or consent

### Input Parameters 🧩
📦 Example Input (JSON)
```json
{
  "keywords": ["Realtor Email Scraper"],
  "country": "Global",
  "maxEmailNumbers": 20,
  "platform": "Realtor",
  "engine": "legacy"
}
````

### Input Table

| Data Type | Description |
| --- | --- |
| keywords | Keywords to find relevant profiles |
| country | Country setting (Global) |
| maxEmailNumbers | Maximum emails to collect (default 20) |
| platform | Platform to scrape (Realtor) |
| engine | Engine type (legacy) |
| proxyConfiguration | Optional proxy settings |

### Output Format 📤

📝 Example Output (JSON)

```json
[
  {
    "network": "Realtor",
    "keyword": "Realtor Email Scraper",
    "title": "Google's Single-Benefit Marketing Strategy for Chrome ...",
    "description": "✓For years, once we created a Gmail account, we couldn't change the username (the part before @ gmail.com ). ... Grand Rapids Marketing Co. Read more",
    "url": "https://www.linkedin.com/posts/phill-agnew_heres-how-google-marketed-chrome-browser-activity-7404878510214914048-dLxI",
    "email": "before@gmail.com"
  }
]
```

### Output Table

| Data Type | Description |
| --- | --- |
| network | Identifies Realtor as the source |
| keyword | Keyword that triggered the result (Realtor Email Scraper) |
| title | Profile title or username |
| description | Public bio snippet with contact info |
| url | Direct Realtor profile link |
| email | Extracted email address |

### FAQ ❓

#### What is Realtor **Email Scraper**?

Realtor Email Scraper is a tool designed to extract contact information from real estate platforms for marketing and networking purposes.

#### What data can I **extract** using this tool?

You can extract email addresses, names, phone numbers, agency names, property details, and more.

#### Is the **extract**ed data accurate?

**Yes**, the tool is designed to provide accurate and up-to-date information from real estate platforms.

#### Can I customize the scraping parameters?

**Yes**, you can define specific criteria such as location, property type, or agent details.

#### Is the tool easy to use?

**Yes**, the Realtor Email Scraper features a **user-friendly** interface for **seamless** operation.

#### How is the data **export**ed?

The extracted data can be exported in various formats, including **CSV** and Excel.

#### Does the tool comply with data privacy laws?

**Yes**, users are encouraged to follow legal guidelines and ensure **compliance** with data privacy regulations.

#### Can I use this tool for **lead generation**?

**Yes**, the Realtor Email Scraper is ideal for building targeted email lists and generating leads.

#### Is the tool scalable for large projects?

**Yes**, it is designed to handle data extraction tasks of varying scales efficiently.

#### What platforms does the tool support?

The Realtor Email Scraper is compatible with various real estate platforms for versatile data collection.

#### How often should I update my data?

Regular updates are recommended to ensure your database remains accurate and relevant.

#### Is technical expertise required to use the tool?

**No**, the tool is designed for users of all skill levels, with a simple and intuitive interface.

#### What should I do if I encounter issues?

Contact support for assistance with any technical or operational problems.

#### Can I integrate the data into my **CRM**?

**Yes**, the exported data can be easily integrated into marketing or CRM tools.

#### Is the tool **secure**?

**Yes**, Realtor Email Scraper prioritizes data security and ensures responsible handling of information.

# Actor input Schema

## `keywords` (type: `array`):

List of keywords to search for on Realtor (e.g., \['marketing', 'founder', 'business']). The actor will search Google for Realtor profiles/posts containing these keywords and extract email addresses.

## `platform` (type: `string`):

Select platform.

## `location` (type: `string`):

Optional: Add location to search query (e.g., 'London', 'New York'). Leave empty to search globally.

## `emailDomains` (type: `array`):

Optional: Filter results to only include emails from specific domains (e.g., \['@gmail.com', '@outlook.com']). Leave empty to collect all email domains.

## `maxEmails` (type: `integer`):

Maximum number of emails to collect per keyword (default: 20).

## `engine` (type: `string`):

Choose scraping engine. 🚀 Cost Effective (New): Uses residential proxies with async requests for faster, cheaper scraping. 🔧 Legacy: Uses GOOGLE\_SERP proxy with traditional selectors - more reliable but slower and more expensive.

## `proxyConfiguration` (type: `object`):

Choose which proxies to use. By default, no proxy is used. If Google rejects or blocks the request, the actor will automatically fallback to datacenter proxy, then residential proxy with 3 retries.

## Actor input object example

```json
{
  "keywords": [
    "marketing"
  ],
  "platform": "Realtor",
  "location": "",
  "emailDomains": [
    "@gmail.com"
  ],
  "maxEmails": 20,
  "engine": "legacy",
  "proxyConfiguration": {
    "useApifyProxy": false
  }
}
```

# 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 '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "keywords": [
        "marketing"
    ],
    "emailDomains": [
        "@gmail.com"
    ],
    "proxyConfiguration": {
        "useApifyProxy": false
    }
};

// Run the Actor and wait for it to finish
const run = await client.actor("scraperx/realtor-email-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 '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {
    "keywords": ["marketing"],
    "emailDomains": ["@gmail.com"],
    "proxyConfiguration": { "useApifyProxy": False },
}

# Run the Actor and wait for it to finish
run = client.actor("scraperx/realtor-email-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 '{
  "keywords": [
    "marketing"
  ],
  "emailDomains": [
    "@gmail.com"
  ],
  "proxyConfiguration": {
    "useApifyProxy": false
  }
}' |
apify call scraperx/realtor-email-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "command": "npx",
            "args": [
                "mcp-remote",
                "https://mcp.apify.com/?tools=scraperx/realtor-email-scraper",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

```

## OpenAPI specification

```json
{
    "openapi": "3.0.1",
    "info": {
        "title": "Realtor Email Scraper",
        "description": "🏠 Realtor Email Scraper finds verified realtor email addresses fast by extracting contact details from public listings. ⚡ Boost outreach for sales, partnerships & lead gen. 🚀 Quick, efficient, and built for targeted real estate marketing.",
        "version": "0.1",
        "x-build-id": "n0zgSdgO9kBSQ31qE"
    },
    "servers": [
        {
            "url": "https://api.apify.com/v2"
        }
    ],
    "paths": {
        "/acts/scraperx~realtor-email-scraper/run-sync-get-dataset-items": {
            "post": {
                "operationId": "run-sync-get-dataset-items-scraperx-realtor-email-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": {
                                "$ref": "#/components/schemas/inputSchema"
                            }
                        }
                    }
                },
                "parameters": [
                    {
                        "name": "token",
                        "in": "query",
                        "required": true,
                        "schema": {
                            "type": "string"
                        },
                        "description": "Enter your Apify token here"
                    }
                ],
                "responses": {
                    "200": {
                        "description": "OK"
                    }
                }
            }
        },
        "/acts/scraperx~realtor-email-scraper/runs": {
            "post": {
                "operationId": "runs-sync-scraperx-realtor-email-scraper",
                "x-openai-isConsequential": false,
                "summary": "Executes an Actor and returns information about the initiated run in response.",
                "tags": [
                    "Run Actor"
                ],
                "requestBody": {
                    "required": true,
                    "content": {
                        "application/json": {
                            "schema": {
                                "$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": {
                                    "$ref": "#/components/schemas/runsResponseSchema"
                                }
                            }
                        }
                    }
                }
            }
        },
        "/acts/scraperx~realtor-email-scraper/run-sync": {
            "post": {
                "operationId": "run-sync-scraperx-realtor-email-scraper",
                "x-openai-isConsequential": false,
                "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.",
                "tags": [
                    "Run Actor"
                ],
                "requestBody": {
                    "required": true,
                    "content": {
                        "application/json": {
                            "schema": {
                                "$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",
                "required": [
                    "keywords"
                ],
                "properties": {
                    "keywords": {
                        "title": "Keywords",
                        "type": "array",
                        "description": "List of keywords to search for on Realtor (e.g., ['marketing', 'founder', 'business']). The actor will search Google for Realtor profiles/posts containing these keywords and extract email addresses.",
                        "items": {
                            "type": "string"
                        }
                    },
                    "platform": {
                        "title": "Platform",
                        "enum": [
                            "Realtor"
                        ],
                        "type": "string",
                        "description": "Select platform.",
                        "default": "Realtor"
                    },
                    "location": {
                        "title": "Location Filter",
                        "type": "string",
                        "description": "Optional: Add location to search query (e.g., 'London', 'New York'). Leave empty to search globally.",
                        "default": ""
                    },
                    "emailDomains": {
                        "title": "Email Domains Filter",
                        "type": "array",
                        "description": "Optional: Filter results to only include emails from specific domains (e.g., ['@gmail.com', '@outlook.com']). Leave empty to collect all email domains.",
                        "items": {
                            "type": "string"
                        }
                    },
                    "maxEmails": {
                        "title": "Maximum Emails per Keyword",
                        "minimum": 1,
                        "maximum": 5000,
                        "type": "integer",
                        "description": "Maximum number of emails to collect per keyword (default: 20).",
                        "default": 20
                    },
                    "engine": {
                        "title": "Engine",
                        "enum": [
                            "legacy"
                        ],
                        "type": "string",
                        "description": "Choose scraping engine. 🚀 Cost Effective (New): Uses residential proxies with async requests for faster, cheaper scraping. 🔧 Legacy: Uses GOOGLE_SERP proxy with traditional selectors - more reliable but slower and more expensive.",
                        "default": "legacy"
                    },
                    "proxyConfiguration": {
                        "title": "Proxy Configuration",
                        "type": "object",
                        "description": "Choose which proxies to use. By default, no proxy is used. If Google rejects or blocks the request, the actor will automatically fallback to datacenter proxy, then residential proxy with 3 retries."
                    }
                }
            },
            "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
                                    }
                                }
                            }
                        }
                    }
                }
            }
        }
    }
}
```