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

🏡 Realtor Email Scraper extracts realtor contact emails from online listings & profiles with speed and accuracy. 🚀 Great for lead gen, outreach, and market research—turn browsing into actionable pipelines.

- **URL**: https://apify.com/scrapium/realtor-email-scraper.md
- **Developed by:** [Scrapium](https://apify.com/scrapium) (community)
- **Categories:** Lead generation, Real estate, Automation
- **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 you to **extract** a wide range of **data** from real estate platforms and directories. This includes essential **contact** information of real estate agents and agencies, making it easier to build a robust **contact** **data**base.

The **extract**ed **data** is well-organized and ready to use for marketing, networking, or lead generation purposes. The tool is designed to capture accurate and up-to-date information, ensuring the quality and reliability of the **data**.

With the ability to **extract** multiple **data** points, the **Realtor** Email Scraper provides comprehensive insights into the real estate market. This makes it a valuable resource for businesses and professionals looking to expand their reach in the real estate sector.

Realtor Email Scraper is a powerful tool designed to help you gather contact information from real estate professionals quickly and efficiently. It simplifies the process of building a comprehensive realtor contact database for marketing or lead generation purposes.

With the Realtor Email Scraper, you can extract email addresses and other relevant details of real estate agents from various online platforms. This tool is ideal for businesses and individuals looking to connect with property agents and expand their network.

The Realtor Email Scraper is an automated solution that eliminates the need for manual data collection, saving time and effort. It ensures accuracy and delivers organized data that can be used for targeted outreach campaigns.

### Support and feedback

- **Bug reports**: Open a ticket in the repository Issues section
- **Custom features**: Contact our enterprise support team
  *Email: scrapier.io@gmail.com *
### Extractable Data Table 📊
| Data Type | Description |
| --- | --- |
| Email Addresses | Extract verified email addresses of real estate agents and agencies. |
| Agent Names | Capture the full names of real estate professionals. |
| Phone Numbers | Retrieve contact numbers for direct communication with agents. |
| Agency Names | Identify the agencies or brokerages associated with each agent. |
| Office Locations | Extract addresses of real estate offices and agencies. |
| Website URLs | Gather links to professional or agency websites for more information. |
| Social Media Links | Capture links to agents’ social media profiles for networking purposes. |
| Specializations | Identify the specific areas of expertise or property types agents deal with. |

### 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** scraping of realtor contact information from multiple platforms
- ⭐ **Accurate** and up-to-date data collection for reliable lead generation
- ⭐ **Customizable** scraping parameters to target specific data points
- ⭐ **High**-speed data extraction for handling large volumes efficiently
- ⭐ User-friendly interface suitable for both beginners and professionals
- ⭐ Organized output in CSV or JSON formats for easy integration
- ⭐ Scalable solution capable of managing growing data needs
- ⭐ Built-in error handling and duplicate removal for clean data
- ⭐ **Secure** and compliant scraping process to protect user privacy
- ⭐ **Regular** updates to ensure compatibility with real estate platforms

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

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

1. ✅ **Sign up** for an account and **log in** to access the **Realtor** Email Scraper
2. ✅ **Input** the target platform or website URL into the tools interface
3. ✅ Set your scraping parameters such as data types and filters
4. ✅ **Start** the scraping process and monitor the progress in real-time
5. ✅ Once completed review the extracted data for accuracy
6. ✅ Download the data in your preferred format such as CSV or JSON
7. ✅ **Integrate** the data into your CRM or marketing tools for further use
8. ✅ Repeat the process as needed to keep your contact database updated
9. ✅ Adjust scraping settings for different platforms or data requirements
10. ✅ Contact support if you encounter any issues during the process

### Use Cases 🎯

Lead Generation for Real Estate Agencies
🎯 Build a targeted email list of real estate agents for outreach
🎯 **Identify** potential partners or collaborators in the real estate industry

Marketing Campaigns for Real Estate Services
🎯 Promote your real estate services to a wider audience
🎯 Send personalized emails to property agents and agencies

Networking and Professional Connections
🎯 Expand your professional network within the real estate sector
🎯 Connect with agents specializing in specific property types

Market Research and Analysis
🎯 Gather data on real estate professionals for market insights
🎯 **Analyze** trends and patterns in the real estate industry

### Why choose us? 💎

The **Realtor** Email Scraper is designed to provide a seamless and efficient data extraction experience. Our tool is built with cutting-edge technology to ensure accuracy and reliability in every scrape.

We prioritize user satisfaction by offering a **user-friendly** interface and customizable scraping options. With our tool, you can save time and resources while building a high-quality realtor contact database.

Our commitment to data security ensures that all information is handled responsibly and ethically. We also provide dedicated customer support to assist you at every step of the process.

Whether you’re a real estate professional, marketer, or agency, our tool is tailored to meet your unique needs. By choosing the **Realtor** Email Scraper, you gain access to a **scalable** and efficient solution for your data collection requirements.

Join countless satisfied users who trust our tool for their real estate lead generation and marketing efforts.

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

The **Realtor** Email Scraper is built to handle data extraction tasks of any size, making it a highly scalable solution. Whether you need to scrape a small list of local agents or a comprehensive database of real estate professionals nationwide, our tool can accommodate your needs.

Its **advanced** algorithms ensure high-speed performance without compromising data accuracy or quality. As your business grows, the **Realtor** Email Scraper can easily adapt to your increasing data requirements.

With support for batch processing and **large-scale** data extraction, it’s perfect for businesses of all sizes. Our tool is designed to grow with you, providing reliable and **efficient** performance at every stage.

This scalability makes it an ideal choice for long-term use in the dynamic real estate industry.

### **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 such as GDPR or CCPA
⚖️ **Use** the **Realtor** Email Scraper only for legitimate and ethical purposes
⚖️ **Obtain** consent when contacting individuals using the extracted data
⚖️ **Avoid** scraping platforms that explicitly prohibit data extraction in their terms of service
⚖️ **Do not** use the tool to collect sensitive or personal information without proper authorization
⚖️ Regularly review and adhere to the scraping policies of target websites
⚖️ Respect the intellectual property rights of the platforms being scraped
⚖️ **Ensure** that the data collected is used responsibly and does not harm individuals or businesses

### 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 the Realtor **Email Scraper**?

The Realtor Email Scraper is a tool designed to extract contact information of real estate professionals from online platforms.

#### What types of data can I **extract**?

You can extract email addresses, agent names, phone numbers, agency names, office locations, website URLs, social media links, and specializations.

#### Is the tool easy to use?

**Yes**, the Realtor Email Scraper features a **user-friendly** interface and simple setup process.

#### Can I customize the scraping parameters?

**Yes**, you can set specific filters and data types to target your scraping needs.

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

The tool is designed to provide accurate and up-to-date data for reliable use.

#### What file formats are supported for data **export**?

You can export the data in **CSV** or **JSON** formats.

#### Is the Realtor **Email Scraper** scalable?

**Yes**, the tool can handle both small and large-scale data extraction tasks.

#### Is the tool compliant with data privacy laws?

**Yes**, the Realtor Email Scraper is designed to comply with data privacy regulations like GDPR and CCPA.

#### Can I use the tool for marketing campaigns?

**Yes**, the extracted data can be used for targeted marketing campaigns and lead generation.

#### What platforms does the tool support?

The tool supports various real estate platforms and directories for data extraction.

#### Is **customer support** available?

**Yes**, we provide dedicated customer support to assist you with any issues.

#### How often is the tool updated?

The Realtor Email Scraper is regularly updated to ensure compatibility with target platforms.

#### Can I scrape data from multiple platforms simultaneously?

**Yes**, the tool supports multi-platform scraping for efficient data collection.

#### Is there a **limit** to the amount of data I can scrape?

The tool is scalable and can handle **large volumes** of data without limitations.

#### How can I ensure ethical use of the tool?

Follow all legal guidelines, obtain consent when required, and use the data responsibly.

# 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("scrapium/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("scrapium/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 scrapium/realtor-email-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "command": "npx",
            "args": [
                "mcp-remote",
                "https://mcp.apify.com/?tools=scrapium/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 extracts realtor contact emails from online listings & profiles with speed and accuracy. 🚀 Great for lead gen, outreach, and market research—turn browsing into actionable pipelines.",
        "version": "0.1",
        "x-build-id": "NnCG3Ddgt4WPr6a59"
    },
    "servers": [
        {
            "url": "https://api.apify.com/v2"
        }
    ],
    "paths": {
        "/acts/scrapium~realtor-email-scraper/run-sync-get-dataset-items": {
            "post": {
                "operationId": "run-sync-get-dataset-items-scrapium-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": {
                                "$ref": "#/components/schemas/inputSchema"
                            }
                        }
                    }
                },
                "parameters": [
                    {
                        "name": "token",
                        "in": "query",
                        "required": true,
                        "schema": {
                            "type": "string"
                        },
                        "description": "Enter your Apify token here"
                    }
                ],
                "responses": {
                    "200": {
                        "description": "OK"
                    }
                }
            }
        },
        "/acts/scrapium~realtor-email-scraper/runs": {
            "post": {
                "operationId": "runs-sync-scrapium-realtor-email-scraper",
                "x-openai-isConsequential": false,
                "summary": "Executes an Actor and returns information about the initiated run in response.",
                "tags": [
                    "Run Actor"
                ],
                "requestBody": {
                    "required": true,
                    "content": {
                        "application/json": {
                            "schema": {
                                "$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": {
                                    "$ref": "#/components/schemas/runsResponseSchema"
                                }
                            }
                        }
                    }
                }
            }
        },
        "/acts/scrapium~realtor-email-scraper/run-sync": {
            "post": {
                "operationId": "run-sync-scrapium-realtor-email-scraper",
                "x-openai-isConsequential": false,
                "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.",
                "tags": [
                    "Run Actor"
                ],
                "requestBody": {
                    "required": true,
                    "content": {
                        "application/json": {
                            "schema": {
                                "$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
                                    }
                                }
                            }
                        }
                    }
                }
            }
        }
    }
}
```