# Doordash Email Scraper (`scraper-engine/doordash-email-scraper`) Actor

DoorDash Email Scraper extracts publicly available restaurant email addresses from DoorDash listings. Build targeted contact lists by city or cuisine. Ideal for suppliers, marketers, and agencies running restaurant outreach campaigns.

- **URL**: https://apify.com/scraper-engine/doordash-email-scraper.md
- **Developed by:** [Scraper Engine](https://apify.com/scraper-engine) (community)
- **Categories:** Lead generation, Automation, Developer tools
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

$19.99/month + usage

To use this Actor, you pay a monthly rental fee to the developer. The rent is subtracted from your prepaid usage every month after the free trial period.You also pay for the Apify platform usage, which gets cheaper the higher Apify subscription plan you have.

Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#rental-actors

## 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

### **Social Media** Email Scraper 📱

The Doordash Email Scraper allows you to **extract** a wide range of valuable **data** from Doordash user profiles. This includes email addresses, user names, and other relevant **contact** information that can be utilized for marketing and outreach purposes.

The tool is designed to ensure **data** accuracy and relevance, helping you build a reliable Doordash email **data**base. With its advanced scraping technology, you can **extract** **data** efficiently and organize it for easy access.

Whether you're targeting specific users or collecting **data** for broader analysis, this tool provides the flexibility you need. It is suitable for businesses of all sizes, offering scalable solutions for email scraping and **data** management.

Doordash Email Scraper is a powerful tool designed to help businesses and developers extract email addresses and other contact information from Doordash user profiles. This tool is ideal for those looking to streamline their marketing efforts or build targeted email lists efficiently.

With the Doordash Email Scraper, you can automate the process of gathering customer emails, saving time and resources. It provides a reliable way to access and organize contact information without manual data entry.

This Doordash data extraction tool is designed to be user-friendly and highly customizable, catering to various business needs. It ensures accurate and up-to-date information, making it a valuable asset for any data-driven strategy.

### 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 verified email addresses from Doordash user profiles. |
| User Names | Retrieve the names associated with Doordash accounts. |
| Contact Information | Collect additional contact details available on Doordash profiles. |
| Account Metadata | Gather metadata such as account creation date or activity status. |
| Profile Links | Extract links to user profiles for further analysis. |
| Location Data | Retrieve location-based information where available. |
| Business Details | Collect information related to Doordash business accounts. |
| Custom Tags | Extract user-defined tags or labels associated with profiles. |

### Key Features of **Social Media** Email Scraper

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

- ⭐ **Automated** email scraping for Doordash user profiles
- ⭐ **Accurate** and up-to-date data extraction capabilities
- ⭐ **Customizable** scraping parameters to target specific data
- ⭐ User-friendly interface for seamless operation
- ⭐ **Advanced** filtering options for refined data collection
- ⭐ Compliance with legal and ethical data scraping standards
- ⭐ Scalable solutions for businesses of all sizes
- ⭐ **Secure** and reliable data handling processes
- ⭐ Supports bulk email extraction for large-scale operations
- ⭐ Detailed reporting and export options for data management

### How to use **Social Media** Email Scraper 🚀

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

1. ✅ **Sign up** or **log in** to access the Doordash Email Scraper tool
2. ✅ Navigate to the dashboard and select the scraping parameters
3. ✅ Enter the target URLs or keywords for Doordash profiles
4. ✅ Customize filters to refine the data extraction process
5. ✅ **Start** the scraping process and monitor progress in real-time
6. ✅ **Review** the extracted data on the dashboard for accuracy
7. ✅ **Export** the data in your preferred format such as CSV or JSON
8. ✅ **Integrate** the data into your CRM or email marketing platform

### Use Cases 🎯

Marketing Campaigns
🎯 Build targeted email lists for promotional campaigns
🎯 Enhance customer outreach with accurate contact information

Business Development
🎯 **Identify** potential partners or clients on Doordash
🎯 Gather contact details for lead generation and networking

Data Analysis
🎯 **Analyze** user demographics and behavior on Doordash
🎯 Extract data for market research and trend analysis

Customer Support
🎯 Retrieve contact information to address customer inquiries
🎯 Build a comprehensive database for customer relationship management

### Why choose us? 💎

Choosing our Doordash Email Scraper ensures you gain access to a **reliable** and efficient tool for data extraction. Our software is designed with **advanced** scraping capabilities, ensuring accurate and up-to-date information.

We prioritize user experience, offering a **user-friendly** interface and customizable features to meet diverse needs. Our tool complies with all legal and ethical guidelines, providing peace of mind for businesses and developers.

Whether you're building a Doordash email database or automating your email list generation, our tool delivers exceptional performance. We also offer robust customer support to assist you at every step of the process.

By choosing us, you can save time, reduce manual effort, and focus on leveraging data for your business growth. Our **scalable** solutions cater to businesses of all sizes, ensuring that you can adapt the tool to your specific requirements.

Trust our Doordash data extraction tool to deliver **reliable** results and enhance your data-driven strategies.

### **Social Media** Email Scraper Scalability 📈

The Doordash Email Scraper is designed to handle projects of any size, making it a scalable solution for businesses and developers. Whether you're a small business owner or a large enterprise, our tool adapts to your data extraction needs.

It supports bulk email scraping, allowing you to gather large volumes of data **efficient**ly. With **advanced** filtering options, you can target specific profiles or data points, ensuring relevance and accuracy.

Our software is built to handle high-demand operations without compromising performance. As your business grows, the Doordash Email Scraper grows with you, offering flexible solutions for data management.

Its robust infrastructure ensures **seamless** operation, even during **large-scale** scraping tasks. Trust our tool to deliver consistent results, regardless of the scope of your project.

### **Social Media** Email Scraper Legal Guidelines ⚖️

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

#### Legal & Ethical Guidelines
⚖️ **Ensure** compliance with Doordashs terms of service before using the scraper
⚖️ **Do not** use the tool for unauthorized or malicious purposes
⚖️ **Obtain** user consent where required before extracting personal data
⚖️ **Avoid** scraping sensitive or confidential information from profiles
⚖️ **Use** the tool only for legitimate business or research purposes
⚖️ **Do not** resell or distribute extracted data without proper authorization
⚖️ Follow all applicable data protection and privacy laws in your region
⚖️ Regularly review updates to Doordashs policies to ensure compliance

### Input Parameters 🧩
📦 Example Input (JSON)
```json
{
  "keywords": ["Doordash Email Scraper"],
  "country": "Global",
  "maxEmailNumbers": 20,
  "platform": "Social Media",
  "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 (Social Media) |
| engine | Engine type (legacy) |
| proxyConfiguration | Optional proxy settings |

### Output Format 📤

📝 Example Output (JSON)

```json
[
  {
    "network": "Social Media",
    "keyword": "Doordash 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 Social Media as the source |
| keyword | Keyword that triggered the result (Doordash Email Scraper) |
| title | Profile title or username |
| description | Public bio snippet with contact info |
| url | Direct Social Media profile link |
| email | Extracted email address |

### FAQ ❓

#### What is the Doordash **Email Scraper**?

The Doordash Email Scraper is a tool designed to extract email addresses and other contact information from Doordash user profiles.

#### Is the Doordash **Email Scraper** **legal** to use?

**Yes**, it is legal to use as long as you comply with Doordash's terms of service and applicable data protection laws.

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

You can extract email addresses, user names, contact information, profile links, and more.

#### Can I customize the scraping parameters?

**Yes**, the tool allows you to customize filters and parameters for targeted data extraction.

#### Is the tool suitable for **large-scale** data scraping?

**Yes**, the Doordash Email Scraper is scalable and supports bulk email extraction.

#### How do I **export** the **extract**ed data?

You can export the data in various formats such as **CSV** or **JSON** for easy integration.

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

**Yes**, it is designed to comply with data protection and privacy laws when used responsibly.

#### What are the system requirements for using this tool?

The tool is web-based and requires a stable internet connection and a modern browser.

#### Can I scrape sensitive information with this tool?

**No**, the tool is not intended for scraping sensitive or confidential information.

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

**Yes**, we offer robust customer support to assist you with any issues or questions.

#### How often is the data updated?

The tool ensures that the extracted data is accurate and up-to-date at the time of scraping.

#### Can I use this tool for personal projects?

**Yes**, the tool can be used for personal or business projects, provided it complies with legal guidelines.

#### What happens if Doordash updates its platform?

Our team regularly updates the scraper to ensure compatibility with Doordash's platform changes.

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

The tool supports scalable operations, and limits depend on your subscription plan.

#### Can I automate the scraping process?

**Yes**, the tool allows for automation to streamline data extraction tasks.

# Actor input Schema

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

List of keywords to search for on Doordash (e.g., \['marketing', 'founder', 'business']). The actor will search Google for Doordash 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": "Doordash",
  "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("scraper-engine/doordash-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("scraper-engine/doordash-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 scraper-engine/doordash-email-scraper --silent --output-dataset

```

## MCP server setup

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

```

## OpenAPI specification

```json
{
    "openapi": "3.0.1",
    "info": {
        "title": "Doordash Email Scraper",
        "description": "DoorDash Email Scraper extracts publicly available restaurant email addresses from DoorDash listings. Build targeted contact lists by city or cuisine. Ideal for suppliers, marketers, and agencies running restaurant outreach campaigns.",
        "version": "0.1",
        "x-build-id": "v1PA6j1ARblh0V9ig"
    },
    "servers": [
        {
            "url": "https://api.apify.com/v2"
        }
    ],
    "paths": {
        "/acts/scraper-engine~doordash-email-scraper/run-sync-get-dataset-items": {
            "post": {
                "operationId": "run-sync-get-dataset-items-scraper-engine-doordash-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": {
                                "$ref": "#/components/schemas/inputSchema"
                            }
                        }
                    }
                },
                "parameters": [
                    {
                        "name": "token",
                        "in": "query",
                        "required": true,
                        "schema": {
                            "type": "string"
                        },
                        "description": "Enter your Apify token here"
                    }
                ],
                "responses": {
                    "200": {
                        "description": "OK"
                    }
                }
            }
        },
        "/acts/scraper-engine~doordash-email-scraper/runs": {
            "post": {
                "operationId": "runs-sync-scraper-engine-doordash-email-scraper",
                "x-openai-isConsequential": false,
                "summary": "Executes an Actor and returns information about the initiated run in response.",
                "tags": [
                    "Run Actor"
                ],
                "requestBody": {
                    "required": true,
                    "content": {
                        "application/json": {
                            "schema": {
                                "$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": {
                                    "$ref": "#/components/schemas/runsResponseSchema"
                                }
                            }
                        }
                    }
                }
            }
        },
        "/acts/scraper-engine~doordash-email-scraper/run-sync": {
            "post": {
                "operationId": "run-sync-scraper-engine-doordash-email-scraper",
                "x-openai-isConsequential": false,
                "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.",
                "tags": [
                    "Run Actor"
                ],
                "requestBody": {
                    "required": true,
                    "content": {
                        "application/json": {
                            "schema": {
                                "$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 Doordash (e.g., ['marketing', 'founder', 'business']). The actor will search Google for Doordash profiles/posts containing these keywords and extract email addresses.",
                        "items": {
                            "type": "string"
                        }
                    },
                    "platform": {
                        "title": "Platform",
                        "enum": [
                            "Doordash"
                        ],
                        "type": "string",
                        "description": "Select platform.",
                        "default": "Doordash"
                    },
                    "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
                                    }
                                }
                            }
                        }
                    }
                }
            }
        }
    }
}
```