# Twitter Email Scraper (`scrapapi/twitter-email-scraper`) Actor

- **URL**: https://apify.com/scrapapi/twitter-email-scraper.md
- **Developed by:** [ScrapAPI](https://apify.com/scrapapi) (community)
- **Categories:** Automation, Lead generation, Social media
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks
- **User rating**: No ratings yet

## Pricing

from $2.99 / 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

### **Twitter** Email Scraper 📱

The **Twitter** Email Scraper allows users to **extract** various types of **data** from **Twitter** profiles. This includes publicly available email addresses, usernames, and other relevant **contact** details.

By automating the **data** collection process, the tool ensures accuracy and saves significant time for users. It is designed to retrieve only information that is publicly accessible, adhering to ethical and legal standards.

In addition to email addresses, the scraper can also gather profile bios, follower counts, and location **data**. These **data** points are essential for businesses and researchers looking to analyze or connect with **Twitter** users.

The tool is customizable, enabling users to filter and **extract** **data** based on specific keywords or criteria. This makes it a versatile solution for a wide range of use cases, from lead generation to academic research.

Twitter Email Scraper is a powerful tool designed to extract email addresses from Twitter profiles efficiently and accurately. It simplifies the process of gathering contact information for businesses, researchers, and marketers.

With the increasing need for targeted outreach, scraping emails from Twitter has become an essential task for many professionals. This tool automates the process, saving time and effort while ensuring data accuracy.

Our Twitter email extraction tool is built to comply with ethical guidelines and provide reliable results. It is ideal for businesses looking to connect with potential leads or enhance their marketing strategies.

### 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 publicly available email addresses from Twitter profiles. |
| Usernames | Retrieve Twitter usernames for identification and outreach. |
| Profile bios | Collect bio descriptions from user profiles for analysis. |
| Follower counts | Gather follower statistics to assess user influence. |
| Location data | Extract location information if publicly shared by users. |
| Profile URLs | Save direct links to user profiles for quick access. |
| Profile images | Download profile pictures for visual identification. |
| Tweets and hashtags | Scrape recent tweets and associated hashtags for content analysis. |

### Key Features of **Twitter** Email Scraper

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

- ⭐ **Automated** email extraction from **Twitter** profiles for maximum efficiency
- ⭐ **Customizable** filters to target specific keywords or user demographics
- ⭐ Ability to scrape additional data such as bios follower counts and locations
- ⭐ **High** accuracy and reliability in data collection processes
- ⭐ User-friendly interface for both beginners and advanced users
- ⭐ Compliance with ethical and legal standards for data scraping
- ⭐ **Fast** processing speeds to handle large volumes of data efficiently
- ⭐ Export options for saving data in various formats like CSV or JSON
- ⭐ **Secure** and private data handling to protect user information
- ⭐ **Regular** updates to ensure compatibility with **Twitter**s platform changes
- ⭐ Detailed logs and reports for tracking scraping activities
- ⭐ 247 customer support to assist with any issues or questions

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

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

1. ✅ **Sign up** or **log in** to access the **Twitter** Email Scraper tool
2. ✅ **Input** your desired keywords or filters for targeted data scraping
3. ✅ Set the parameters for the type of data you want to extract such as emails or bios
4. ✅ **Start** the scraping process by clicking the Run button
5. ✅ Monitor the progress of the scraper through the real-time dashboard
6. ✅ Once the scraping is complete review the extracted data in the results section
7. ✅ **Export** the data to your preferred format such as CSV or JSON for further use
8. ✅ Repeat the process with different keywords or settings for additional data

### Use Cases 🎯

Lead Generation
🎯 Extract email addresses of potential clients or partners from **Twitter** profiles
🎯 **Use** the data to create targeted email marketing campaigns

Market Research
🎯 **Analyze** user bios and tweets to understand audience interests and trends
🎯 Gather location data to identify regional preferences and behaviors

Recruitment
🎯 **Find** and contact potential candidates through their publicly available emails
🎯 **Analyze** follower counts and bios to identify influencers in specific fields

Academic Research
🎯 **Collect** data for studies on social media behavior and user demographics
🎯 **Analyze** hashtags and tweets to understand public discourse on specific topics

### Why choose us? 💎

Our **Twitter** Email Scraper is designed to provide unmatched efficiency and accuracy in data extraction. We prioritize user convenience by offering a simple interface and customizable features.

With our tool, you can extract emails and other data from **Twitter** profiles quickly and securely. We understand the importance of compliance, which is why our scraper adheres to all legal and ethical guidelines.

Whether you are a marketer, recruiter, or researcher, our tool is tailored to meet your specific needs. The scraper is **regular**ly updated to ensure compatibility with **Twitter**'s platform changes.

Additionally, we offer 24/7 customer support to assist you with any challenges or questions. Our focus on reliability and user satisfaction makes us the **best** **Twitter** email scraper available.

Choose us for a seamless and effective data scraping experience.

### **Twitter** Email Scraper Scalability 📈

The **Twitter** Email Scraper is built to handle projects of all sizes, from small-scale extractions to **large-scale** data collection. Its robust architecture ensures fast and **efficient** processing, even with high volumes of data.

Users can customize their scraping parameters to focus on specific keywords or demographics. This flexibility makes the tool suitable for various industries and use cases.

Whether you need to extract a few hundred emails or millions of data points, our scraper can scale to meet your requirements. The tool also supports batch processing, enabling users to run multiple scraping tasks simultaneously.

With its **advanced** optimization, the scraper minimizes resource consumption while maximizing output. This makes it an ideal solution for businesses and researchers looking for a scalable **Twitter** data scraping tool.

### **Twitter** Email Scraper Legal Guidelines ⚖️

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

#### Legal & Ethical Guidelines
⚖️ **Ensure** that you only scrape publicly available data from **Twitter** profiles
⚖️ **Do not** use the scraper to collect sensitive or private information without consent
⚖️ Comply with **Twitter**s terms of service and data usage policies
⚖️ **Avoid** using the tool for spamming or unethical marketing practices
⚖️ Respect user privacy and do not share extracted data without permission
⚖️ **Use** the scraper only for legitimate and lawful purposes
⚖️ **Ensure** that your usage of the tool adheres to local and international data protection laws
⚖️ Regularly review and update your scraping practices to maintain compliance

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

### Output Format 📤

📝 Example Output (JSON)

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

### FAQ ❓

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

The Twitter Email Scraper is a tool designed to extract **publicly available** email addresses and other data from Twitter profiles.

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

**Yes**, as long as you comply with Twitter's terms of service and only collect publicly accessible data.

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

You can extract email addresses, usernames, bios, follower counts, location data, profile URLs, and more.

#### How do I use the Twitter **Email Scraper**?

Simply input your keywords, set your parameters, and start the scraping process through the tool's interface.

#### Can I **export** the **extract**ed data?

**Yes**, the tool allows you to export data in formats like **CSV** or **JSON** for further use.

#### Is the scraper compatible with all Twitter accounts?

The scraper can access data from public Twitter profiles but cannot retrieve information from private accounts.

#### How accurate is the data **extract**ion?

The tool is designed to provide high accuracy by focusing on **publicly available** information.

#### Can I use the scraper for bulk data **extract**ion?

**Yes**, the scraper supports batch processing for large-scale data collection.

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

**Yes**, we offer 24/7 customer support to assist with any issues or questions.

#### Does the scraper comply with data protection laws?

**Yes**, the tool is designed to comply with local and international data protection regulations.

#### Can I customize the scraping parameters?

**Yes**, you can use filters to target specific keywords, demographics, or data types.

#### How often is the tool updated?

The scraper is regularly updated to ensure compatibility with Twitter's platform changes.

#### Is the tool beginner-friendly?

**Yes**, the Twitter Email Scraper features a **user-friendly** interface suitable for all experience levels.

#### What industries can benefit from this tool?

Industries such as marketing, recruitment, and academic research can benefit from using this tool.

#### Can I scrape tweets and hashtags?

**Yes**, the tool allows you to collect tweets and associated hashtags for content analysis.

# Actor input Schema

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

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

```

## MCP server setup

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

```

## OpenAPI specification

```json
{
    "openapi": "3.0.1",
    "info": {
        "title": "Twitter Email Scraper",
        "version": "0.1",
        "x-build-id": "MiNjwqh5IOl1QGbHa"
    },
    "servers": [
        {
            "url": "https://api.apify.com/v2"
        }
    ],
    "paths": {
        "/acts/scrapapi~twitter-email-scraper/run-sync-get-dataset-items": {
            "post": {
                "operationId": "run-sync-get-dataset-items-scrapapi-twitter-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": {
                                "$ref": "#/components/schemas/inputSchema"
                            }
                        }
                    }
                },
                "parameters": [
                    {
                        "name": "token",
                        "in": "query",
                        "required": true,
                        "schema": {
                            "type": "string"
                        },
                        "description": "Enter your Apify token here"
                    }
                ],
                "responses": {
                    "200": {
                        "description": "OK"
                    }
                }
            }
        },
        "/acts/scrapapi~twitter-email-scraper/runs": {
            "post": {
                "operationId": "runs-sync-scrapapi-twitter-email-scraper",
                "x-openai-isConsequential": false,
                "summary": "Executes an Actor and returns information about the initiated run in response.",
                "tags": [
                    "Run Actor"
                ],
                "requestBody": {
                    "required": true,
                    "content": {
                        "application/json": {
                            "schema": {
                                "$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": {
                                    "$ref": "#/components/schemas/runsResponseSchema"
                                }
                            }
                        }
                    }
                }
            }
        },
        "/acts/scrapapi~twitter-email-scraper/run-sync": {
            "post": {
                "operationId": "run-sync-scrapapi-twitter-email-scraper",
                "x-openai-isConsequential": false,
                "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.",
                "tags": [
                    "Run Actor"
                ],
                "requestBody": {
                    "required": true,
                    "content": {
                        "application/json": {
                            "schema": {
                                "$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 Twitter (e.g., ['marketing', 'founder', 'business']). The actor will search Google for Twitter profiles/posts containing these keywords and extract email addresses.",
                        "items": {
                            "type": "string"
                        }
                    },
                    "platform": {
                        "title": "Platform",
                        "enum": [
                            "Twitter"
                        ],
                        "type": "string",
                        "description": "Select platform.",
                        "default": "Twitter"
                    },
                    "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
                                    }
                                }
                            }
                        }
                    }
                }
            }
        }
    }
}
```