# Reddit Scraper | All in one (`scrapeforge/reddit-scraper`) Actor

Scrape Reddit posts, comments, subreddits, and user profiles. Extract engagement metrics, media, nested comment threads, and 35+ data fields. Filter by date, score, NSFW, and media.

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

## Pricing

from $0.50 / 1,000 results

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.

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

## Reddit Scraper 🤖

Scrape **Reddit posts, comments, subreddits, search results, and user profiles** — fast, at scale, and **without a Reddit API key or login**. Extract engagement metrics, media URLs, nested comment threads, and 35+ structured fields from any public Reddit content.

Perfect for market research, brand monitoring, sentiment analysis, trend tracking, lead generation, and feeding LLMs/RAG pipelines with real Reddit discussions.

### Why this scraper

- 🔑 **No API key, no Reddit account** — just run it.
- ⚡ **Fast & concurrent** — processes posts in parallel; a lightweight *metadata-only* mode for cheap, high-speed monitoring.
- 🔎 **Deep search coverage** — returns **several times more results per query** than a basic search.
- 💬 **Full comment threads** — nested replies, optionally flattened into one row per comment.
- 🧱 **35+ structured fields** per post, ready for analysis or the API/MCP.
- 💸 **Transparent, low cost** — pay only for what you scrape.

### What you can scrape

| Source | How |
|--------|-----|
| **Subreddit** posts | `subreddits: ["technology"]` |
| **Search** across Reddit | `searchTerms: ["machine learning"]` |
| **User** posts & comments | `usernames: ["spez"]` |
| **Any Reddit URL** | `startUrls` — posts, subreddits, users, or search URLs |

### Two modes: tune speed vs. depth

| | **Full mode** (default) | **Fast mode** |
|---|---|---|
| Set | `fetchPostDetails: true` | `fetchPostDetails: false` |
| Gets | title, body text, **upvote ratio**, media, all fields | post metadata only (title, score, author, dates, flags, media) — no body/ratio |
| Speed / cost | one extra request per post | metadata only → **much faster & cheaper** |
| Best for | full analysis | high-volume monitoring, dashboards |

> Comments are a separate switch — turn on **`scrapeComments`** to extract them (each comment is a billed result and its own row). See the Comments section below.

### Input

#### Scraping sources (use one or combine)

| Field | Type | Description |
|-------|------|-------------|
| `subreddits` | string[] | Subreddit names (without `r/` prefix) |
| `searchTerms` | string[] | Keywords to search across Reddit |
| `usernames` | string[] | Reddit usernames (without `u/` prefix) |
| `startUrls` | URL[] | Direct Reddit URLs (posts, subreddits, users, search) |

#### Scope, sorting & coverage

| Field | Type | Default | Description |
|-------|------|---------|-------------|
| `maxItems` | integer | 100 | Max posts per source (1–10,000) |
| `sort` | string | `hot` | `hot`, `new`, `top`, `rising`, `relevance`, `comments` |
| `timeFilter` | string | `all` | Time range for `top`/search: `hour`, `day`, `week`, `month`, `year`, `all` |
| `maximizeCoverage` | boolean | `true` | For **searches**, gather results more thoroughly and de-duplicate → many more posts per query |

#### Comments

| Field | Type | Default | Description |
|-------|------|---------|-------------|
| `scrapeComments` | boolean | false | **Turn ON to extract comments.** Each comment is a **billed result** and its **own row** (linked to its post). OFF = comments are never fetched (no cost) |
| `maxComments` | integer | 100 | Max comments per post (only when `scrapeComments` is ON) |
| `commentDepth` | integer | 3 | Max depth of nested replies, 1–20 (only when `scrapeComments` is ON) |

#### Filters

| Field | Type | Default | Description |
|-------|------|---------|-------------|
| `startDate` | string | — | Only posts after this date (`YYYY-MM-DD`) |
| `endDate` | string | — | Only posts before this date (`YYYY-MM-DD`) |
| `minScore` | integer | — | Minimum post score |
| `includeNSFW` | boolean | false | Include NSFW posts |
| `mediaOnly` | boolean | false | Only posts with images, videos, or galleries |

#### Performance & advanced

| Field | Type | Default | Description |
|-------|------|---------|-------------|
| `fetchPostDetails` | boolean | true | Fetch full post detail (body, upvote ratio, comments). Turn **off** for fast, cheap metadata-only runs |
| `maxConcurrency` | integer | 5 | How many posts to process in parallel (1–20) |
| `customMapFunction` | string | — | JavaScript to transform each result. Receives `post`, must return an object |

### Output

Each post is one dataset item with 35+ fields:

```json
{
  "id": "1abc123",
  "title": "Post title",
  "text": "Post body text",
  "url": "https://www.reddit.com/r/technology/comments/1abc123/...",
  "author": "username",
  "authorFullname": "t2_abc",
  "subreddit": "technology",
  "score": 15432,
  "upvoteRatio": 0.95,
  "numComments": 892,
  "postType": "image",
  "createdAt": "2026-04-15T10:30:00.000Z",
  "domain": "i.redd.it",
  "isNSFW": false,
  "hasMedia": true,
  "media": [{ "type": "image", "url": "https://i.redd.it/...jpeg" }],
  "linkFlair": "Discussion",
  "comments": [
    { "author": "commenter", "body": "Comment text", "score": 523, "depth": 0, "isOP": false, "replies": [] }
  ]
}
````

**Field groups:** core (`id`, `title`, `text`, `author`, `subreddit`, `permalink`, `createdAt`, `postType`, `domain`, `linkUrl`) · engagement (`score`, `upvoteRatio`, `numComments`, `numCrossposts`, `totalAwards`) · media (`thumbnail`, `media[]`, `hasMedia`, `hasVideo`, `hasImage`, `isGallery`) · flags (`isNSFW`, `isSpoiler`, `isStickied`, `isLocked`, `isArchived`, `isSelf`) · flair (`linkFlair`, `authorFlair`) · metadata (`subredditSubscribers`, `sourceType`, `sourceQuery`, `scrapedAt`).

With `scrapeComments: true`, each comment becomes its own **billed row** (`itemType: "comment"`) carrying `body`, `author`, `score`, `depth`, `isOP`, plus `postId`/`postTitle`/`subreddit` to link it back to its post — ideal for exporting a flat comment list.

### Examples

**Top posts from a subreddit (last week):**

```json
{ "subreddits": ["technology"], "maxItems": 50, "sort": "top", "timeFilter": "week" }
```

**Search Reddit, maximum coverage:**

```json
{ "searchTerms": ["benq monitor"], "maxItems": 300, "sort": "relevance", "maximizeCoverage": true }
```

**A post with its comments (each comment a billed row):**

```json
{ "startUrls": ["https://www.reddit.com/r/AskReddit/comments/1abc123/title/"], "scrapeComments": true, "maxComments": 100 }
```

**Posts + comments as a flat list:**

```json
{ "subreddits": ["buildapc"], "maxItems": 50, "scrapeComments": true, "maxComments": 100 }
```

**Fast, cheap monitoring (metadata only):**

```json
{ "subreddits": ["worldnews"], "maxItems": 500, "fetchPostDetails": false, "sort": "new" }
```

### Tips on speed & cost

- **Don't need body text?** Set `fetchPostDetails: false` — dramatically faster and cheaper (no per-post fetch).
- **Need comments?** Turn on `scrapeComments` — each comment is a billed row. Set `maxComments` sensibly (e.g. `50–200`); cost scales with how many comments you pull.
- **Want more results from a search?** Keep `maximizeCoverage: true` and raise `maxItems`.
- Raise `maxConcurrency` (e.g. 8–10) for more speed, or lower it to be gentler.

### Limitations

- Scrapes **public** content only. Private or quarantined subreddits return an error.
- `upvoteRatio` and post **body text** require `fetchPostDetails: true`; **comments** require `scrapeComments: true`.
- Very large comment threads may not return every single nested reply.
- `subredditSubscribers` and award counts are best-effort and may be `0` when not exposed.

### Disclaimer

This actor accesses publicly available data from Reddit and is provided for research and educational purposes. By using it you agree to comply with [Reddit's User Agreement](https://www.redditinc.com/policies/user-agreement) and all applicable laws. You are solely responsible for how the collected data is used. Always respect rate limits and the privacy of Reddit users.

# Actor input Schema

## `startUrls` (type: `array`):

Reddit URLs to scrape: subreddit URLs (r/python), post URLs, user profiles (u/username), or search URLs.

## `searchTerms` (type: `array`):

Keywords to search across Reddit.

## `subreddits` (type: `array`):

Subreddit names to scrape posts from (without r/ prefix).

## `usernames` (type: `array`):

Reddit usernames to scrape posts/comments from (without u/ prefix).

## `maxItems` (type: `integer`):

Maximum number of posts to extract per source.

## `scrapeComments` (type: `boolean`):

Turn ON to extract comments. ⚠️ Each comment is counted as a result (it adds to cost) and appears as its own row in the dataset, linked to its post. Turn OFF and comments are never fetched (no cost, no rows).

## `maxComments` (type: `integer`):

Maximum comments to extract per post. Only applies when 'Scrape comments' is ON.

## `commentDepth` (type: `integer`):

Maximum depth of nested replies to follow. Only applies when 'Scrape comments' is ON.

## `fetchPostDetails` (type: `boolean`):

Extract full post detail — body text and upvote ratio. More complete data, but slower (one extra request per post). Turn OFF for fast, low-cost runs that return post metadata only (title, score, author, dates, media, flags).

## `maxConcurrency` (type: `integer`):

How many posts to process in parallel. Higher = faster; lower = gentler.

## `maximizeCoverage` (type: `boolean`):

For search terms, gather results more thoroughly and de-duplicate them to return more posts per query. Only affects searchTerms.

## `sort` (type: `string`):

Sort order for subreddit posts and search results.

## `timeFilter` (type: `string`):

Time range filter (for 'top' and search sorting).

## `startDate` (type: `string`):

Only include posts after this date (YYYY-MM-DD).

## `endDate` (type: `string`):

Only include posts before this date (YYYY-MM-DD).

## `minScore` (type: `integer`):

Only include posts with at least this score.

## `includeNSFW` (type: `boolean`):

Include NSFW (Not Safe For Work) posts.

## `mediaOnly` (type: `boolean`):

Only include posts that contain media (images, videos, galleries).

## `customMapFunction` (type: `string`):

JavaScript function to transform each post object. Receives 'post' as argument, must return an object.

## Actor input object example

```json
{
  "subreddits": [
    "programming"
  ],
  "maxItems": 100,
  "scrapeComments": false,
  "maxComments": 100,
  "commentDepth": 3,
  "fetchPostDetails": true,
  "maxConcurrency": 5,
  "maximizeCoverage": true,
  "sort": "hot",
  "timeFilter": "all",
  "includeNSFW": false,
  "mediaOnly": false
}
```

# Actor output Schema

## `results` (type: `string`):

All scraped items (posts, and comments when enabled) in the default dataset.

## `overview` (type: `string`):

Default dataset rendered with the Overview view (key post fields).

## `comments` (type: `string`):

Flat comment rows — meaningful when 'Comments as Separate Items' is enabled.

# 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 = {
    "subreddits": [
        "programming"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("scrapeforge/reddit-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 = { "subreddits": ["programming"] }

# Run the Actor and wait for it to finish
run = client.actor("scrapeforge/reddit-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 '{
  "subreddits": [
    "programming"
  ]
}' |
apify call scrapeforge/reddit-scraper --silent --output-dataset

```

## MCP server setup

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

```

## OpenAPI specification

```json
{
    "openapi": "3.0.1",
    "info": {
        "title": "Reddit Scraper | All in one",
        "description": "Scrape Reddit posts, comments, subreddits, and user profiles. Extract engagement metrics, media, nested comment threads, and 35+ data fields. Filter by date, score, NSFW, and media.",
        "version": "1.0",
        "x-build-id": "28gzm5on3yzkSX6Hp"
    },
    "servers": [
        {
            "url": "https://api.apify.com/v2"
        }
    ],
    "paths": {
        "/acts/scrapeforge~reddit-scraper/run-sync-get-dataset-items": {
            "post": {
                "operationId": "run-sync-get-dataset-items-scrapeforge-reddit-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": {
                                "$ref": "#/components/schemas/inputSchema"
                            }
                        }
                    }
                },
                "parameters": [
                    {
                        "name": "token",
                        "in": "query",
                        "required": true,
                        "schema": {
                            "type": "string"
                        },
                        "description": "Enter your Apify token here"
                    }
                ],
                "responses": {
                    "200": {
                        "description": "OK"
                    }
                }
            }
        },
        "/acts/scrapeforge~reddit-scraper/runs": {
            "post": {
                "operationId": "runs-sync-scrapeforge-reddit-scraper",
                "x-openai-isConsequential": false,
                "summary": "Executes an Actor and returns information about the initiated run in response.",
                "tags": [
                    "Run Actor"
                ],
                "requestBody": {
                    "required": true,
                    "content": {
                        "application/json": {
                            "schema": {
                                "$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": {
                                    "$ref": "#/components/schemas/runsResponseSchema"
                                }
                            }
                        }
                    }
                }
            }
        },
        "/acts/scrapeforge~reddit-scraper/run-sync": {
            "post": {
                "operationId": "run-sync-scrapeforge-reddit-scraper",
                "x-openai-isConsequential": false,
                "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.",
                "tags": [
                    "Run Actor"
                ],
                "requestBody": {
                    "required": true,
                    "content": {
                        "application/json": {
                            "schema": {
                                "$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",
                "properties": {
                    "startUrls": {
                        "title": "Start URLs",
                        "type": "array",
                        "description": "Reddit URLs to scrape: subreddit URLs (r/python), post URLs, user profiles (u/username), or search URLs.",
                        "items": {
                            "type": "object",
                            "required": [
                                "url"
                            ],
                            "properties": {
                                "url": {
                                    "type": "string",
                                    "title": "URL of a web page",
                                    "format": "uri"
                                }
                            }
                        }
                    },
                    "searchTerms": {
                        "title": "Search Terms",
                        "type": "array",
                        "description": "Keywords to search across Reddit.",
                        "items": {
                            "type": "string"
                        }
                    },
                    "subreddits": {
                        "title": "Subreddits",
                        "type": "array",
                        "description": "Subreddit names to scrape posts from (without r/ prefix).",
                        "items": {
                            "type": "string"
                        }
                    },
                    "usernames": {
                        "title": "Usernames",
                        "type": "array",
                        "description": "Reddit usernames to scrape posts/comments from (without u/ prefix).",
                        "items": {
                            "type": "string"
                        }
                    },
                    "maxItems": {
                        "title": "Max Items Per Source",
                        "minimum": 1,
                        "maximum": 10000,
                        "type": "integer",
                        "description": "Maximum number of posts to extract per source.",
                        "default": 100
                    },
                    "scrapeComments": {
                        "title": "Scrape comments",
                        "type": "boolean",
                        "description": "Turn ON to extract comments. ⚠️ Each comment is counted as a result (it adds to cost) and appears as its own row in the dataset, linked to its post. Turn OFF and comments are never fetched (no cost, no rows).",
                        "default": false
                    },
                    "maxComments": {
                        "title": "Max Comments Per Post",
                        "minimum": 1,
                        "maximum": 5000,
                        "type": "integer",
                        "description": "Maximum comments to extract per post. Only applies when 'Scrape comments' is ON.",
                        "default": 100
                    },
                    "commentDepth": {
                        "title": "Comment Reply Depth",
                        "minimum": 1,
                        "maximum": 20,
                        "type": "integer",
                        "description": "Maximum depth of nested replies to follow. Only applies when 'Scrape comments' is ON.",
                        "default": 3
                    },
                    "fetchPostDetails": {
                        "title": "Fetch Post Details",
                        "type": "boolean",
                        "description": "Extract full post detail — body text and upvote ratio. More complete data, but slower (one extra request per post). Turn OFF for fast, low-cost runs that return post metadata only (title, score, author, dates, media, flags).",
                        "default": true
                    },
                    "maxConcurrency": {
                        "title": "Max Concurrency",
                        "minimum": 1,
                        "maximum": 20,
                        "type": "integer",
                        "description": "How many posts to process in parallel. Higher = faster; lower = gentler.",
                        "default": 5
                    },
                    "maximizeCoverage": {
                        "title": "Maximize Search Coverage",
                        "type": "boolean",
                        "description": "For search terms, gather results more thoroughly and de-duplicate them to return more posts per query. Only affects searchTerms.",
                        "default": true
                    },
                    "sort": {
                        "title": "Sort Order",
                        "enum": [
                            "hot",
                            "new",
                            "top",
                            "rising",
                            "relevance",
                            "comments"
                        ],
                        "type": "string",
                        "description": "Sort order for subreddit posts and search results.",
                        "default": "hot"
                    },
                    "timeFilter": {
                        "title": "Time Filter",
                        "enum": [
                            "hour",
                            "day",
                            "week",
                            "month",
                            "year",
                            "all"
                        ],
                        "type": "string",
                        "description": "Time range filter (for 'top' and search sorting).",
                        "default": "all"
                    },
                    "startDate": {
                        "title": "Start Date",
                        "type": "string",
                        "description": "Only include posts after this date (YYYY-MM-DD)."
                    },
                    "endDate": {
                        "title": "End Date",
                        "type": "string",
                        "description": "Only include posts before this date (YYYY-MM-DD)."
                    },
                    "minScore": {
                        "title": "Minimum Score",
                        "minimum": 0,
                        "type": "integer",
                        "description": "Only include posts with at least this score."
                    },
                    "includeNSFW": {
                        "title": "Include NSFW",
                        "type": "boolean",
                        "description": "Include NSFW (Not Safe For Work) posts.",
                        "default": false
                    },
                    "mediaOnly": {
                        "title": "Media Only",
                        "type": "boolean",
                        "description": "Only include posts that contain media (images, videos, galleries).",
                        "default": false
                    },
                    "customMapFunction": {
                        "title": "Custom Map Function",
                        "type": "string",
                        "description": "JavaScript function to transform each post object. Receives 'post' as argument, must return an object."
                    }
                }
            },
            "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
                                    }
                                }
                            }
                        }
                    }
                }
            }
        }
    }
}
```