# Luma Email Scraper (`solid-scraper/luma-email-scraper`) Actor

📧 Luma Email Scraper automatically extracts verified emails from Luma profiles with smart filters for accurate lead lists. Perfect for sales, recruiting, and marketing teams—faster outreach, less manual work. 🚀

- **URL**: https://apify.com/solid-scraper/luma-email-scraper.md
- **Developed by:** [SolidScraper](https://apify.com/solid-scraper) (community)
- **Categories:** Lead generation, Automation, Agents
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 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

### Luma Email Scraper 📬

**Luma Email Scraper** is an Apify actor that helps you extract email addresses related to **Luma** profiles using your selected **keywords** and **custom email-domain filters**. Whether you're a marketer, lead researcher, or data analyst, this **Luma email scraper** makes it easier to build outreach lists by collecting contact emails surfaced from publicly available data tied to your topic. It’s designed for “**email scraper for Luma**” and “**Luma lead scraper**” workflows—so you can scale contact discovery and save hours of manual work.

---

### Why choose Luma Email Scraper?

| Feature | Benefit |
| --- | --- |
| ✅ **Keyword-based Luma email discovery** | Finds emails associated with Luma bios/posts related to your keywords |
| ✅ **Custom email-domain targeting** | Filters results using your `customDomains` (e.g., `@gmail.com`) for better-fit leads |
| ✅ **Two scraping engines** | Switch between `legacy` and `cost-effective` to match speed vs reliability needs |
| ✅ **Reliability with retries & fallbacks** | Includes retries and fallbacks for resilience when results are limited |
| ✅ **Structured dataset output** | Outputs a consistent row format with `network`, `keyword`, `title`, `url`, and `email` |
| ✅ **Scale controls** | Use `maxEmails` to stop when you reach your desired volume (helps control time and cost) |

---

### Key features

- 🔎 **Targeted email extraction**: Extracts email addresses that match your specified email-domain filters from publicly available Luma-related content
- 🧠 **Keyword-driven lead generation**: Uses your `keywords` to surface relevant contacts for your “email scraper for Luma” use case
- 🎯 **Domain filtering (precision)**: Use `customDomains` to focus on emails from domains you care about (like `@gmail.com`)
- 🛡️ **Resilient scraping behavior**: Built-in retry logic and fallback handling to keep runs effective when results are inconsistent
- ⚙️ **Engine flexibility**: Choose between `cost-effective` (faster/cheaper approach using residential proxies) and `legacy` (more traditional, reliability-focused approach)
- 💾 **Real-time saving to dataset**: Each discovered email row is pushed to the dataset as soon as it’s found
- ⏱️ **Practical scale controls**: Stops automatically once `maxEmails` is reached, so you can run bulk email scraping tool workflows without uncontrolled runtimes

---

### Input

Provide input via an `input.json` file. Example structure:

```json
{
  "keywords": ["dj event"],
  "location": "",
  "platform": "Luma",
  "customDomains": ["@gmail.com"],
  "maxEmails": 20,
  "engine": "legacy",
  "proxyConfiguration": {}
}
````

#### Input Fields

| Field | Required | Description |
| --- | --- | --- |
| `keywords` | ✅ Yes | A list of keywords to search for (these drive which Luma bios/posts are considered for email extraction). |
| `location` | ❌ No | Location to filter results. Leave empty (`""`) for no location filtering. |
| `platform` | ❌ No | Select platform. This actor supports `Luma` (default: `Luma`). |
| `customDomains` | ❌ No | List of custom email domains used to filter extracted emails (default includes `@gmail.com`). |
| `maxEmails` | ❌ No | Maximum number of emails to collect. The scraper stops once this limit is reached. Default is `20`. |
| `engine` | ❌ No | Choose scraping engine: `cost-effective` (cost effective using residential proxies) or `legacy` (more traditional approach). Default is `legacy`. |
| `proxyConfiguration` | ❌ No | Proxy configuration for this Actor (configured via Apify proxy settings). |

***

### Output

The actor saves discovered leads as rows in a JSON dataset. Each pushed row represents one email contact tied to a keyword result.

```json
[
  {
    "network": "Luma.com",
    "keyword": "dj event",
    "title": "No title",
    "description": "No data",
    "url": "No URL",
    "email": "example@gmail.com"
  }
]
```

#### Output Fields

| Field | Type | Description |
| --- | --- | --- |
| `network` | string | Source label for the extracted results (set to `Luma.com`). |
| `keyword` | string | The keyword that led to this result. |
| `title` | string | Title associated with the result item. |
| `description` | string | Description/snippet text where the email was found. |
| `url` | string | URL associated with the result item. |
| `email` | string | The extracted email address that matches your domain filters. |

> Export tip: Apify lets you export dataset results to formats like JSON/CSV from the dataset page, which is handy for CRM import or spreadsheet analysis.

***

### How to use Luma Email Scraper (via Apify Console)

1. **Open Apify Console**\
   Log in at https://console.apify.com and open the **Actors** section.

2. **Find the actor**\
   Search for **Luma Email Scraper** and open the actor details page.

3. **Go to the INPUT tab and configure your run**\
   Fill in `keywords` (required). Add `customDomains` if you want tighter targeting (for example, only emails like `@gmail.com`).

4. **Set engine and limits**\
   Choose `engine` (`legacy` or `cost-effective`) and optionally set `maxEmails` to control how many emails you want per run.

5. **(Optional) Configure proxies**\
   If you’re running large searches or need more resilience, configure `proxyConfiguration` using the Apify proxy settings.

6. **Click Run**\
   Start the actor and monitor progress in the logs. You’ll see messages when pages are fetched successfully and when emails are pushed to the dataset.

7. **Open the OUTPUT dataset**\
   Once the run finishes, open the dataset to view and export the collected `network`, `keyword`, `title`, `description`, `url`, and `email` rows.

No coding required—get relevant Luma contact emails in minutes with **Luma Email Scraper**. 🚀

***

### Advanced features & SEO optimization

- 🧩 **Engineered for Luma email extraction**: Optimized for “**Luma email scraper**” workflows like automated email discovery and lead generation email scraper pipelines.
- 🔄 **Rate-limit friendly resilience**: Includes retries and fallbacks when results are limited or inconsistent, helping improve outcomes for automatic email scraping runs.
- 🎛️ **Input normalization & filtering**: Uses your `keywords` plus your `customDomains` to focus extraction on emails from the domains that matter to your campaign.
- 📝 **Progress-aware runs**: Maintains persistent progress (cursor and seen emails) so long runs don’t lose work when interrupted.
- 📊 **Bulk-ready dataset rows**: Each email is immediately pushed as a structured record—ideal for B2B email scraper analysis and downstream automation.

***

### Best use cases

- 📈 **B2B lead generation teams**: Quickly assemble contact emails for outreach campaigns based on event and audience keywords.
- 🧪 **Market researchers**: Build datasets of Luma contact emails to compare niches, topics, and community segments.
- 🎯 **Email marketing analysts**: Validate list quality by exporting consistent `keyword`-linked email results for segmentation.
- 🧰 **CRM and outreach operations**: Use the structured dataset rows to automate enrichment and keep lead sources traceable by `url` and `keyword`.
- 🔎 **Growth marketers**: Run bulk email scraping tool tasks to expand prospect lists around specific themes.
- 💻 **Developer and data workflows**: Treat **Luma Email Scraper** as a data source that outputs clean JSON rows for ETL pipelines.
- 🌐 **Contact data enrichment**: Combine keyword context (`keyword`, `title`, `description`) with `email` to improve matching in downstream systems.

***

### Technical specifications

- **Supported Input Formats**
  - ✅ `keywords` as an array of strings
  - ✅ `location` as a string (optional)
  - ✅ `platform` as `Luma` (default)
  - ✅ `customDomains` as an array of strings (optional)
  - ✅ `maxEmails` as an integer between `1` and `10000`
  - ✅ `proxyConfiguration` as an object configured via Apify proxy editor

- **Proxy Support**
  - ✅ Built-in proxy configuration via `proxyConfiguration`
  - ✅ `engine` supports `cost-effective` and `legacy` behaviors for different reliability/speed needs

- **Retry Mechanism**
  - ✅ Includes retries and fallbacks for improved resilience when fetching or parsing results

- **Dataset Structure**
  - ✅ JSON dataset rows with:
    - `network`, `keyword`, `title`, `description`, `url`, `email`

- **Rate Limits & Performance**
  - ✅ Uses `maxEmails` to stop once you reach the target count
  - ✅ Large searches or high email limits may increase runtime (default guidance in the actor input notes)

- **Limitations**
  - ❌ Results depend on what’s available in publicly accessible sources tied to the provided keywords and filters
  - ❌ Reaching `maxEmails` is not guaranteed if fewer matching emails are found

***

### FAQ

#### What does the Luma Email Scraper output?

✅ It outputs a dataset of JSON rows where each row includes `network`, `keyword`, `title`, `description`, `url`, and the extracted `email`.

#### Which inputs are required to start?

✅ You must provide `keywords`. Other fields like `customDomains`, `location`, `maxEmails`, and `engine` are optional.

#### Can I restrict results to specific email domains?

✅ Yes. Use `customDomains` to filter extracted emails by domain (for example, `@gmail.com`).

#### How do I increase results when the email count is low?

✅ Try re-running with broader keywords and more related terms, and/or add more domains to `customDomains` to match a wider set of publicly available contacts.

#### Does this scraper require coding or an API key?

❌ No coding is required to run it in Apify Console. You only provide input fields through the built-in form or an `input.json` file.

#### Can I control how many emails I collect?

✅ Yes. Set `maxEmails`. The actor stops when the limit is reached (up to the schema max of `10000`).

#### What’s the difference between `legacy` and `cost-effective` engines?

✅ `engine` lets you choose between `legacy` and `cost-effective` behaviors. The input description explains that `cost-effective` is designed to be faster/cheaper using residential proxies, while `legacy` is positioned as more reliable but slower and more expensive.

#### Is this legal and compliant to use for lead generation?

✅ The actor works with **publicly accessible sources**. You’re responsible for complying with applicable laws and relevant platform policies, including GDPR/CCPA and spam regulations.

***

### Support & feature requests

If you’re using **Luma Email Scraper** and want to share feedback or ask for improvements, we’re happy to help.

- 💡 **Feature Requests**: Examples include CSV export enhancements, additional filtering options, or CRM-friendly formats tailored to your workflow.
- 📧 **Contact**: Send a message to <dataforleads@gmail.com>.

Your feedback helps shape what we build next for **Luma Email Scraper**. 🙌

***

### Closing CTA / Final thoughts

*If you need an SEO-optimized Luma lead scraper that turns keywords into structured email results, **Luma Email Scraper** is built for you.*\
Run it with the right keywords and domain filters—and scale your contact discovery confidently. 🚀

***

### Disclaimer

This tool only accesses **publicly accessible sources**. It does not access private profiles, authenticated data, or password-protected content.

You are responsible for ensuring your use complies with applicable laws and regulations (including GDPR/CCPA), as well as spam regulations and relevant platform terms of service. For data removal requests, contact <dataforleads@gmail.com>.

Please use **Luma Email Scraper** responsibly, ethically, and for legitimate purposes only.

# Actor input Schema

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

A list of keywords to search for.

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

Location to filter search results.

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

Select platform.

## `customDomains` (type: `array`):

List of custom email domains

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

Maximum number of emails to collect. The scraper will stop once this limit is reached. Setting a higher limit allows for more potential results but doesn't guarantee reaching that number. This helps save costs by controlling scraping time.

## `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`):

Configure proxies for this Actor.

## Actor input object example

```json
{
  "keywords": [
    "dj event"
  ],
  "location": "",
  "platform": "Luma",
  "customDomains": [
    "@gmail.com"
  ],
  "maxEmails": 20,
  "engine": "legacy"
}
```

# 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": [
        "dj event"
    ],
    "location": "",
    "customDomains": [
        "@gmail.com"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("solid-scraper/luma-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": ["dj event"],
    "location": "",
    "customDomains": ["@gmail.com"],
}

# Run the Actor and wait for it to finish
run = client.actor("solid-scraper/luma-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": [
    "dj event"
  ],
  "location": "",
  "customDomains": [
    "@gmail.com"
  ]
}' |
apify call solid-scraper/luma-email-scraper --silent --output-dataset

```

## MCP server setup

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

```

## OpenAPI specification

```json
{
    "openapi": "3.0.1",
    "info": {
        "title": "Luma Email Scraper",
        "description": "📧 Luma Email Scraper automatically extracts verified emails from Luma profiles with smart filters for accurate lead lists. Perfect for sales, recruiting, and marketing teams—faster outreach, less manual work. 🚀",
        "version": "0.0",
        "x-build-id": "y0iNSwPPQdtd4yttT"
    },
    "servers": [
        {
            "url": "https://api.apify.com/v2"
        }
    ],
    "paths": {
        "/acts/solid-scraper~luma-email-scraper/run-sync-get-dataset-items": {
            "post": {
                "operationId": "run-sync-get-dataset-items-solid-scraper-luma-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": {
                                "$ref": "#/components/schemas/inputSchema"
                            }
                        }
                    }
                },
                "parameters": [
                    {
                        "name": "token",
                        "in": "query",
                        "required": true,
                        "schema": {
                            "type": "string"
                        },
                        "description": "Enter your Apify token here"
                    }
                ],
                "responses": {
                    "200": {
                        "description": "OK"
                    }
                }
            }
        },
        "/acts/solid-scraper~luma-email-scraper/runs": {
            "post": {
                "operationId": "runs-sync-solid-scraper-luma-email-scraper",
                "x-openai-isConsequential": false,
                "summary": "Executes an Actor and returns information about the initiated run in response.",
                "tags": [
                    "Run Actor"
                ],
                "requestBody": {
                    "required": true,
                    "content": {
                        "application/json": {
                            "schema": {
                                "$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": {
                                    "$ref": "#/components/schemas/runsResponseSchema"
                                }
                            }
                        }
                    }
                }
            }
        },
        "/acts/solid-scraper~luma-email-scraper/run-sync": {
            "post": {
                "operationId": "run-sync-solid-scraper-luma-email-scraper",
                "x-openai-isConsequential": false,
                "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.",
                "tags": [
                    "Run Actor"
                ],
                "requestBody": {
                    "required": true,
                    "content": {
                        "application/json": {
                            "schema": {
                                "$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": "A list of keywords to search for.",
                        "default": [
                            "dj event"
                        ],
                        "items": {
                            "type": "string"
                        }
                    },
                    "location": {
                        "title": "Location",
                        "type": "string",
                        "description": "Location to filter search results.",
                        "default": ""
                    },
                    "platform": {
                        "title": "Platform",
                        "enum": [
                            "Luma"
                        ],
                        "type": "string",
                        "description": "Select platform.",
                        "default": "Luma"
                    },
                    "customDomains": {
                        "title": "Custom Email Domains",
                        "type": "array",
                        "description": "List of custom email domains",
                        "default": [
                            "@gmail.com"
                        ],
                        "items": {
                            "type": "string"
                        }
                    },
                    "maxEmails": {
                        "title": "Max Emails",
                        "minimum": 1,
                        "maximum": 10000,
                        "type": "integer",
                        "description": "Maximum number of emails to collect. The scraper will stop once this limit is reached. Setting a higher limit allows for more potential results but doesn't guarantee reaching that number. This helps save costs by controlling scraping time.",
                        "default": 20
                    },
                    "engine": {
                        "title": "Engine",
                        "enum": [
                            "cost-effective",
                            "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": "Configure proxies for this Actor."
                    }
                }
            },
            "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
                                    }
                                }
                            }
                        }
                    }
                }
            }
        }
    }
}
```