# Flipkart Email Scraper (`scrapeflow/flipkart-email-scraper`) Actor

📧 Flipkart Email Scraper (flipkart-email-scraper) extracts verified seller/company email addresses from Flipkart listings. ✅ Boost your B2B outreach, lead generation & research with fast, automated data collection. 🚀 Perfect for sales, marketing & partnerships.

- **URL**: https://apify.com/scrapeflow/flipkart-email-scraper.md
- **Developed by:** [ScrapeFlow](https://apify.com/scrapeflow) (community)
- **Categories:** Lead generation, Automation, E-commerce
- **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

### **Flipkart** Email Scraper 📱

**Flipkart** Email Scraper enables users to **extract** a wide range of **data** from **Flipkart**'s platform. This includes customer email addresses, seller **contact** information, and other relevant details that can be used for marketing or research purposes.

By utilizing this **Flipkart** email harvesting tool, businesses can access structured **data** in a user-friendly format. The scraper ensures that all **extract**ed information is accurate and up-to-date, making it a reliable choice for **data** **extract**ion tasks.

With features like automated **Flipkart** email scraping, users can collect **data** efficiently without manual intervention. This tool is ideal for **extract**ing **Flipkart** customer **emails** and other **contact** details for various business applications.

Flipkart Email Scraper is a powerful tool designed to help users extract email addresses and other contact information from Flipkart efficiently. With this automated software, businesses can streamline their data collection processes and enhance their outreach strategies.

Using the Flipkart Email Scraper, you can gather valuable contact details from Flipkart's vast marketplace. This tool is ideal for professionals looking to leverage Flipkart data for marketing, research, or business development purposes.

Flipkart data extraction tools like this scraper simplify the process of collecting customer emails and other relevant information. It eliminates manual effort and ensures accuracy in data harvesting.

### 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 |
| --- | --- |
| Customer email addresses | Extract verified email addresses of Flipkart customers for outreach purposes. |
| Seller contact information | Gather email and phone details of Flipkart sellers for business inquiries. |
| Product details | Scrape product names, descriptions, and specifications for analysis. |
| Pricing information | Extract price points and discounts for competitive research. |
| Customer reviews | Collect user reviews and ratings for sentiment analysis. |
| Categories and subcategories | Scrape product categories for better market segmentation. |
| Shipping details | Extract shipping policies and delivery options for logistics planning. |
| Seller ratings | Gather seller performance metrics for vendor evaluation. |

### Key Features of **Flipkart** Email Scraper

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

- ⭐ **Automated** **Flipkart** email scraping for efficient data collection
- ⭐ Ability to extract **Flipkart** customer emails and seller contact information
- ⭐ Supports scraping **Flipkart** for email addresses and other structured data types
- ⭐ User-friendly interface for seamless data extraction processes
- ⭐ **Customizable** filters to target specific products sellers or categories
- ⭐ Real-time data harvesting to ensure up-to-date information
- ⭐ Export data in multiple formats like CSV Excel or JSON for convenience
- ⭐ **Advanced** algorithms to ensure accuracy and minimize errors in data extraction
- ⭐ **Comprehensive** scraping capabilities for **Flipkart**s vast marketplace
- ⭐ **Secure** and compliant with legal guidelines for ethical data usage
- ⭐ Scalable solution for businesses of all sizes and industries
- ⭐ 247 customer support to assist with any technical issues or queries

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

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

1. ✅ Download and install the **Flipkart** Email Scraper software on your device
2. ✅ Launch the tool and **log in** using your credentials
3. ✅ Enter the specific search criteria or keywords for data extraction such as product categories or seller names
4. ✅ **Select** the data types you want to scrape such as customer emails or seller contact details
5. ✅ **Configure** filters to refine your search and target specific segments of **Flipkart**s marketplace
6. ✅ **Start** the scraping process by clicking the Run button within the tool interface
7. ✅ Monitor the progress of the extraction process using the real-time dashboard
8. ✅ Once completed export the extracted data in your preferred format such as CSV or JSON
9. ✅ **Review** the harvested data to ensure accuracy and completeness
10. ✅ Utilize the extracted information for your business needs such as marketing or research
11. ✅ Repeat the process as needed for different search criteria or data types
12. ✅ Contact customer support if you encounter any issues during the scraping process

### Use Cases 🎯

Marketing Campaigns
🎯 Extract **Flipkart** customer emails for targeted email marketing campaigns
🎯 Gather seller contact information for partnership opportunities

Market Research
🎯 **Analyze** product pricing and discounts for competitive insights
🎯 Scrape customer reviews for sentiment analysis and trend identification

Business Development
🎯 Harvest **Flipkart** seller emails for vendor outreach and collaboration
🎯 **Collect** product details to expand your inventory or offerings

Logistics Planning
🎯 Extract shipping details to optimize delivery strategies
🎯 **Analyze** seller ratings for reliable vendor selection

### Why choose us? 💎

Our **Flipkart** Email Scraper is designed to meet the diverse needs of businesses seeking efficient data extraction solutions. With **advanced** features like automated **Flipkart** email scraping, this tool ensures accuracy and reliability in every data harvesting task.

It is one of the **best** **Flipkart** scraping tools available, offering customizable filters and real-time data collection capabilities. Whether you need to extract **Flipkart** customer emails or gather seller contact information, our software provides a **user-friendly** interface for seamless operations.

We prioritize compliance with legal guidelines, ensuring ethical usage of extracted data. Our tool is **scalable** and suitable for businesses of all sizes, from startups to large enterprises.

With 24/7 customer support, we are committed to helping you achieve your data extraction goals effectively.

### **Flipkart** Email Scraper Scalability 📈

**Flipkart** Email Scraper is built to handle data extraction tasks of varying scales, making it suitable for businesses of all sizes. Whether you need to scrape **Flipkart** for email addresses or extract detailed product information, our tool adapts to your requirements **seamless**ly.

It supports **large-scale** data harvesting while maintaining accuracy and efficiency. The software's **advanced** algorithms ensure that even **extensive** datasets are processed quickly and reliably.

With **customizable** filters, users can target specific segments of **Flipkart**'s marketplace, optimizing the extraction process. Our scalable solution is ideal for enterprises looking to expand their operations or startups seeking to establish their presence in the market.

The **Flipkart** email harvesting tool grows with your business, providing consistent performance as your data needs evolve.

### **Flipkart** Email Scraper Legal Guidelines ⚖️

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

#### Legal & Ethical Guidelines
⚖️ **Ensure** compliance with **Flipkart**s terms of service when using the scraper
⚖️ **Do not** use extracted data for unsolicited marketing or spam activities
⚖️ **Avoid** scraping personal information that is not publicly available on **Flipkart**
⚖️ **Use** the **Flipkart** Email Scraper only for lawful business purposes
⚖️ Respect privacy laws and regulations applicable in your region
⚖️ **Obtain** consent from individuals before using their contact information for outreach
⚖️ **Do not** resell or distribute extracted data without proper authorization
⚖️ Regularly review legal updates to ensure continued compliance with data usage policies

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

### Output Format 📤

📝 Example Output (JSON)

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

### FAQ ❓

#### What is Flipkart **Email Scraper**?

Flipkart Email Scraper is a tool designed to extract email addresses and other contact information from Flipkart efficiently.

#### Can I use this tool to scrape Flipkart for email addresses?

**Yes**, the Flipkart Email Scraper is specifically designed for scraping Flipkart for email addresses and other data types.

#### Is this tool **legal** to use?

**Yes**, the tool is legal to use as long as you comply with Flipkart's terms of service and applicable privacy laws.

#### What data types can I **extract** using this scraper?

You can extract customer **emails**, seller contact information, product details, pricing data, reviews, and more.

#### Is the Flipkart email **extract**or user-friendly?

**Yes**, the tool features a **user-friendly** interface for **seamless** data extraction processes.

#### Can I **export** data in different formats?

**Yes**, you can export extracted data in formats like **CSV**, Excel, or **JSON**.

#### Does this tool support automated Flipkart email scraping?

**Yes**, the scraper automates the data extraction process for efficiency and accuracy.

#### How can I ensure compliance with **legal** guidelines?

Follow Flipkart's terms of service and privacy laws, and avoid using data for unsolicited marketing.

#### Is **customer support** available for this tool?

**Yes**, 24/7 customer support is available to assist with any technical issues or queries.

#### Can I customize filters for targeted data **extract**ion?

**Yes**, the tool allows you to configure filters to refine your search criteria.

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

**Yes**, the tool is scalable and suitable for **businesses** of all sizes.

#### What are the benefits of using this scraper?

The scraper saves time, ensures accuracy, and provides structured data for various business applications.

#### Can I scrape Flipkart customer emails for marketing purposes?

**Yes**, you can extract customer **emails** for targeted marketing campaigns, provided you comply with legal guidelines.

#### Does this tool support real-time data harvesting?

**Yes**, the scraper enables real-time data collection to ensure up-to-date information.

#### How often can I use the scraper?

You can use the scraper as often as needed, depending on your data extraction requirements.

# Actor input Schema

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

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

```

## MCP server setup

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

```

## OpenAPI specification

```json
{
    "openapi": "3.0.1",
    "info": {
        "title": "Flipkart Email Scraper",
        "description": "📧 Flipkart Email Scraper (flipkart-email-scraper) extracts verified seller/company email addresses from Flipkart listings. ✅ Boost your B2B outreach, lead generation & research with fast, automated data collection. 🚀 Perfect for sales, marketing & partnerships.",
        "version": "0.1",
        "x-build-id": "Gyia9Xnc17feFGIlm"
    },
    "servers": [
        {
            "url": "https://api.apify.com/v2"
        }
    ],
    "paths": {
        "/acts/scrapeflow~flipkart-email-scraper/run-sync-get-dataset-items": {
            "post": {
                "operationId": "run-sync-get-dataset-items-scrapeflow-flipkart-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": {
                                "$ref": "#/components/schemas/inputSchema"
                            }
                        }
                    }
                },
                "parameters": [
                    {
                        "name": "token",
                        "in": "query",
                        "required": true,
                        "schema": {
                            "type": "string"
                        },
                        "description": "Enter your Apify token here"
                    }
                ],
                "responses": {
                    "200": {
                        "description": "OK"
                    }
                }
            }
        },
        "/acts/scrapeflow~flipkart-email-scraper/runs": {
            "post": {
                "operationId": "runs-sync-scrapeflow-flipkart-email-scraper",
                "x-openai-isConsequential": false,
                "summary": "Executes an Actor and returns information about the initiated run in response.",
                "tags": [
                    "Run Actor"
                ],
                "requestBody": {
                    "required": true,
                    "content": {
                        "application/json": {
                            "schema": {
                                "$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": {
                                    "$ref": "#/components/schemas/runsResponseSchema"
                                }
                            }
                        }
                    }
                }
            }
        },
        "/acts/scrapeflow~flipkart-email-scraper/run-sync": {
            "post": {
                "operationId": "run-sync-scrapeflow-flipkart-email-scraper",
                "x-openai-isConsequential": false,
                "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.",
                "tags": [
                    "Run Actor"
                ],
                "requestBody": {
                    "required": true,
                    "content": {
                        "application/json": {
                            "schema": {
                                "$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 Flipkart (e.g., ['marketing', 'founder', 'business']). The actor will search Google for Flipkart profiles/posts containing these keywords and extract email addresses.",
                        "items": {
                            "type": "string"
                        }
                    },
                    "platform": {
                        "title": "Platform",
                        "enum": [
                            "Flipkart"
                        ],
                        "type": "string",
                        "description": "Select platform.",
                        "default": "Flipkart"
                    },
                    "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
                                    }
                                }
                            }
                        }
                    }
                }
            }
        }
    }
}
```