# Reddit Intelligence Scraper (Pay per Event) (`eiv/reddit-intelligence-scraper`) Actor Scrape Reddit posts, full comment trees, user profiles, and search results. Features subreddit monitoring with webhook alerts, batch comparison across multiple subreddits, and AI-native markdown output ready for LLM pipelines and vector databases. - **URL**: https://apify.com/eiv/reddit-intelligence-scraper.md - **Developed by:** [Eimantas V](https://apify.com/eiv) (community) - **Categories:** AI, Developer tools, Social media - **Stats:** 3 total users, 2 monthly users, 95.5% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $3.00 / 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 Intelligence Scraper Extract posts, full comment trees, user profiles, search results, and trending topics from Reddit — with **AI-native structured output** designed to drop directly into LLM pipelines, vector databases, and RAG systems without preprocessing. ### 🚀 What Can This Reddit Scraper Extract? | Data Type | Fields Extracted | |-----------|-----------------| | **Posts** | Title, body (markdown + plain text), score, upvote ratio, awards, flair, author, timestamps, crosspost data | | **Comments** | Full nested tree (all depths), per-comment score, author, edited flag, reply count | | **Users** | Karma breakdown, account age, post/comment history, profile bio | | **Search Results** | Full-text Reddit search with subreddit filtering, sorting, and time windows | | **Subreddit Metadata** | Subscriber count, active users, description, creation date, icons | | **Batch Comparison** | Side-by-side stats for 10+ subreddits in a single run | ### ✨ Key Features - **🔄 Subreddit monitoring mode** — Poll any subreddit for new posts matching keyword filters and deliver alerts via webhook in real-time - **🌲 Full comment tree traversal** — Not just top-level comments. Fetches deeply nested replies via Reddit's `morechildren` API, up to configurable depth - **🤖 AI-native output** — Every result includes a `_markdown_document` field: a clean, structured markdown document ready for LLM context windows or vector embedding - **📊 Batch subreddit comparison** — Pull top posts from up to 20 subreddits in one run with aggregated stats — ideal for market research and competitive analysis - **⚡ Reliable session rotation** — Rotates User-Agents, respects `X-Ratelimit-*` headers, and uses exponential backoff — the #1 failure mode for Reddit scrapers, solved - **🔍 Advanced filtering** — Filter by flair, keyword, score threshold, date range, NSFW flag, and sort order (hot/new/top/rising) - **📋 Schema-versioned output** — Every item carries `_schema: "reddit-intelligence/v1"` so your pipeline always knows what it's getting --- ### 📖 How to Use the Reddit Intelligence Scraper #### Step 1 — Choose a mode | Mode | What it does | |------|-------------| | `subreddit` | Scrape posts from one or more subreddits | | `post` | Scrape a specific post URL with all comments | | `user` | Scrape a user's profile, posts, and comment history | | `search` | Full-text Reddit search with filters | | `batch` | Compare top posts across multiple subreddits | | `monitor` | Watch subreddits for new posts and deliver webhook alerts | #### Step 2 — Configure your run **Scrape the top posts from r/MachineLearning this week:** ```json { "mode": "subreddit", "subreddits": ["MachineLearning"], "sortBy": "top", "timeFilter": "week", "maxPostsPerSubreddit": 50, "includeComments": true, "maxCommentsPerPost": 100, "outputFormat": "both" } ```` **Compare 5 subreddits for market research:** ```json { "mode": "batch", "subreddits": ["entrepreneur", "startups", "SaaS", "indiehackers", "smallbusiness"], "sortBy": "top", "timeFilter": "month", "maxPostsPerSubreddit": 10 } ``` **Monitor r/ArtificialIntelligence for mentions of "GPT" and alert via webhook:** ```json { "mode": "monitor", "subreddits": ["ArtificialIntelligence"], "keywordFilter": ["GPT", "Claude", "Gemini", "LLM"], "monitoringInterval": 5, "webhookUrl": "https://your-server.com/webhooks/reddit" } ``` **Scrape a specific post with full comment tree:** ```json { "mode": "post", "postUrls": ["https://www.reddit.com/r/MachineLearning/comments/abc123/example_post/"], "maxCommentsPerPost": 500, "commentDepth": 10 } ``` #### Step 3 — Use the output Every post result includes a ready-to-use markdown document in the `_markdown_document` field: ``` ## Why GPT-4 is changing enterprise software **r/MachineLearning** | Score: **4,231** (96% upvoted) | Comments: **312** Author: u/ml_researcher | Posted: 2024-03-15T14:22:00Z ### Post Content The shift from rule-based to generative AI... ### Top Comments #### u/ai_engineer (Score: 847) This is exactly what we're seeing in production... > ##### u/skeptic99 (Score: 234) > Worth noting the cost implications here... ``` Paste this directly into your LLM prompt or chunk it for RAG. *** ### 💰 How Much Does It Cost to Scrape Reddit? Reddit Intelligence Scraper is priced per result (pay-per-event): | Task | Approximate Cost | |------|-----------------| | 1,000 posts (metadata only) | ~$3.00 | | 1,000 posts with 100 comments each | ~$3.00 | | User profile (1 user, 25 posts) | ~$0.12 | | Batch comparison (10 subs × 10 posts) | ~$0.30 | | Monitor run (24h, low-traffic sub) | ~$1.50–6.00 | **Pricing:** $3.00 per 1,000 results. Each post, comment thread, user profile, or search result page counts as one result. **Tip:** Disable `includeComments` and set `outputFormat: "json"` for faster runs when you only need post metadata. *** ### 📤 Output Format #### Post object (JSON) ```json { "_schema": "reddit-intelligence/v1", "_scraped_at": "2024-03-15T14:30:00.000Z", "type": "post", "id": "abc123", "url": "https://www.reddit.com/r/MachineLearning/comments/abc123/...", "subreddit": "MachineLearning", "title": "Why GPT-4 is changing enterprise software", "body_markdown": "The shift from rule-based to generative AI...", "body_text": "The shift from rule-based to generative AI...", "score": 4231, "upvote_ratio": 0.96, "num_comments": 312, "total_awards_received": 7, "flair_text": "Discussion", "author": "ml_researcher", "created_utc": "2024-03-15T14:22:00.000Z", "comments": [...], "subreddit_meta": { "subscribers": 2800000, "active_user_count": 4200, ... }, "_markdown_document": "## Why GPT-4 is changing..." } ``` #### Webhook payload (monitor mode) ```json { "event": "keyword_match", "timestamp": "2024-03-15T14:35:00.000Z", "subreddit": "ArtificialIntelligence", "matched_keywords": ["GPT", "LLM"], "post": { "id": "xyz789", "title": "New GPT-4 benchmark results are wild", "url": "https://www.reddit.com/r/...", "score": 142, "body_preview": "Just ran the full MMLU suite..." } } ``` *** ### 🤔 Frequently Asked Questions #### Is scraping Reddit legal? Reddit's public data is accessible without authentication. This actor only scrapes publicly available content — the same data accessible in a browser without logging in. Always review Reddit's [Terms of Service](https://www.redditinc.com/policies/user-agreement) and ensure your use complies with applicable laws. This tool is intended for research, analytics, and AI training use cases. #### Why is the actor not returning all 1000 posts I requested? Reddit's `top` sort with longer time windows (`year`, `all`) is the best way to get high-quality historical posts. The API occasionally returns fewer results than requested — this is a Reddit limitation. Try increasing `maxPostsPerSubreddit` and setting `sortBy: "new"` for completeness. #### What's the difference between `outputFormat: "json"`, `"markdown"`, and `"both"`? - `json` — returns the full structured JSON object, ideal for data pipelines and databases - `markdown` — returns only the `_markdown_document` field (the AI-ready version), minimal storage - `both` — returns full JSON **and** the markdown document in every result #### Can I use this to feed Reddit data into a vector database? Yes — this is a primary use case. Use `outputFormat: "markdown"`, split on `### Top Comments` to get post and comment chunks, and embed each chunk separately. #### Does it handle private or restricted subreddits? No. This actor only accesses public Reddit content. Private subreddits require OAuth authentication with approved account credentials. #### How does the monitoring mode work exactly? On first run, the actor seeds its state with the current latest posts (no webhook fires). On subsequent polling cycles (default: every 5 minutes), any new post that matches your filters triggers a dataset push and optionally a webhook. State is persisted in Apify Key-Value Store so it survives between runs. #### Why use a proxy? Without a proxy, repeated scraping from a single IP can trigger Reddit's rate limiting (HTTP 429). Apify's residential proxy pool rotates IPs automatically, making your scraper much more reliable at scale. *** ### 🔗 Related Actors - **Web Scraper** — General-purpose web scraping - **Twitter Scraper** — Social media monitoring on X/Twitter - **YouTube Scraper** — Video and comment data from YouTube *** ### 📬 Support & Feedback Found a bug or have a feature request? Open an issue or contact us through the Apify platform. We monitor this actor actively and publish updates regularly. # Actor input Schema ## `mode` (type: `string`): Select what to scrape: subreddit posts, a specific post, user profiles, search results, batch comparison across subreddits, or live monitoring. ## `subreddits` (type: `array`): List of subreddit names to scrape (without r/ prefix). Used for subreddit, batch, and monitor modes. ## `postUrls` (type: `array`): Full Reddit post URLs to scrape (including all comments). Used in post mode. ## `usernames` (type: `array`): Reddit usernames to scrape (without u/ prefix). Used in user mode. ## `searchQuery` (type: `string`): Search query string. Used in search mode. ## `searchSubreddits` (type: `array`): Restrict search to specific subreddits. Leave empty to search all of Reddit. ## `sortBy` (type: `string`): How to sort posts or search results. ## `timeFilter` (type: `string`): Time window for top/search sort. Only applies when Sort Order is 'top' or 'relevance'. ## `maxPostsPerSubreddit` (type: `integer`): Maximum number of posts to fetch per subreddit. Higher values increase cost. ## `includeComments` (type: `boolean`): Fetch and include full comment trees for each post. Disable for faster, cheaper runs when you only need post metadata. ## `maxCommentsPerPost` (type: `integer`): Maximum number of comments to fetch per post. Includes replies at all depths. ## `commentDepth` (type: `integer`): Maximum depth for nested comment replies (1 = top-level only, 10 = full tree). ## `flairFilter` (type: `string`): Only include posts matching this flair text (case-insensitive, partial match). ## `keywordFilter` (type: `array`): Only include posts/comments containing at least one of these keywords (case-insensitive). ## `minScore` (type: `integer`): Skip posts with score below this threshold. Useful for filtering out low-quality content. ## `dateFrom` (type: `string`): Only include posts created after this date/time (ISO 8601 format, e.g. 2024-01-01T00:00:00Z). Note: Reddit's API doesn't natively support date filtering — posts will be fetched and filtered client-side. ## `dateTo` (type: `string`): Only include posts created before this date/time (ISO 8601 format). ## `includeNSFW` (type: `boolean`): Include posts marked as NSFW (Not Safe For Work). ## `includeSubredditMeta` (type: `boolean`): Attach subreddit metadata (subscriber count, description, etc.) to each result. ## `outputFormat` (type: `string`): json: structured JSON only. markdown: AI-ready markdown document. both: include both in every result. ## `webhookUrl` (type: `string`): POST endpoint to receive new matching posts in monitor mode. Required for monitor mode. ## `monitoringInterval` (type: `integer`): How often to poll Reddit for new posts in monitor mode. Minimum 2 minutes. ## `proxyConfiguration` (type: `object`): Apify proxy configuration. Strongly recommended to avoid rate limiting. ## `maxConcurrency` (type: `integer`): Maximum number of parallel requests. Keep low (1-3) to respect Reddit rate limits. ## `debugMode` (type: `boolean`): Enable verbose logging for troubleshooting. ## Actor input object example ```json { "mode": "subreddit", "subreddits": [ "wallstreetbets", "technology", "MachineLearning" ], "postUrls": [ "https://www.reddit.com/r/technology/comments/abc123/example_post/" ], "usernames": [ "spez", "gallowboob" ], "searchQuery": "GPT-4 use cases", "searchSubreddits": [ "MachineLearning", "artificial" ], "sortBy": "hot", "timeFilter": "week", "maxPostsPerSubreddit": 25, "includeComments": true, "maxCommentsPerPost": 100, "commentDepth": 5, "flairFilter": "Discussion", "keywordFilter": [ "AI", "GPT", "machine learning" ], "minScore": 0, "dateFrom": "2024-01-01T00:00:00Z", "dateTo": "2024-12-31T23:59:59Z", "includeNSFW": false, "includeSubredditMeta": true, "outputFormat": "both", "webhookUrl": "https://hooks.example.com/reddit-alerts", "monitoringInterval": 5, "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] }, "maxConcurrency": 2, "debugMode": false } ``` # Actor output Schema ## `results` (type: `string`): All scraped items in the default dataset. Each item carries a `type` field — post, user, search, batch, or monitor\_event — and a `_markdown_document` field with AI-ready formatted output. ## `datasetOverview` (type: `string`): View and filter results in the Apify dataset browser. ## `keyValueStore` (type: `string`): Stores monitor mode state (seen post IDs per subreddit) and the actor input. Used to persist state across monitor polling cycles. ## `liveStatus` (type: `string`): Real-time progress endpoint. Available during the run at the actor container URL. # 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 '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "subreddits": [ "technology" ], "maxPostsPerSubreddit": 25, "maxCommentsPerPost": 100, "commentDepth": 5, "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } }; // Run the Actor and wait for it to finish const run = await client.actor("eiv/reddit-intelligence-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 '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "subreddits": ["technology"], "maxPostsPerSubreddit": 25, "maxCommentsPerPost": 100, "commentDepth": 5, "proxyConfiguration": { "useApifyProxy": True, "apifyProxyGroups": ["RESIDENTIAL"], }, } # Run the Actor and wait for it to finish run = client.actor("eiv/reddit-intelligence-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": [ "technology" ], "maxPostsPerSubreddit": 25, "maxCommentsPerPost": 100, "commentDepth": 5, "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } }' | apify call eiv/reddit-intelligence-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=eiv/reddit-intelligence-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Reddit Intelligence Scraper (Pay per Event)", "description": "Scrape Reddit posts, full comment trees, user profiles, and search results. Features subreddit monitoring with webhook alerts, batch comparison across multiple subreddits, and AI-native markdown output ready for LLM pipelines and vector databases.", "version": "0.0", "x-build-id": "GDFSR2pDyt4l3W0lT" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/eiv~reddit-intelligence-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-eiv-reddit-intelligence-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/eiv~reddit-intelligence-scraper/runs": { "post": { "operationId": "runs-sync-eiv-reddit-intelligence-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/eiv~reddit-intelligence-scraper/run-sync": { "post": { "operationId": "run-sync-eiv-reddit-intelligence-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "mode" ], "properties": { "mode": { "title": "Scraping Mode", "enum": [ "subreddit", "post", "user", "search", "batch", "monitor" ], "type": "string", "description": "Select what to scrape: subreddit posts, a specific post, user profiles, search results, batch comparison across subreddits, or live monitoring.", "default": "subreddit" }, "subreddits": { "title": "Subreddits", "type": "array", "description": "List of subreddit names to scrape (without r/ prefix). Used for subreddit, batch, and monitor modes.", "items": { "type": "string" } }, "postUrls": { "title": "Post URLs", "type": "array", "description": "Full Reddit post URLs to scrape (including all comments). Used in post mode.", "items": { "type": "string" } }, "usernames": { "title": "Usernames", "type": "array", "description": "Reddit usernames to scrape (without u/ prefix). Used in user mode.", "items": { "type": "string" } }, "searchQuery": { "title": "Search Query", "type": "string", "description": "Search query string. Used in search mode." }, "searchSubreddits": { "title": "Search within Subreddits", "type": "array", "description": "Restrict search to specific subreddits. Leave empty to search all of Reddit.", "items": { "type": "string" } }, "sortBy": { "title": "Sort Order", "enum": [ "hot", "new", "top", "rising", "relevance", "comments" ], "type": "string", "description": "How to sort posts or search results.", "default": "hot" }, "timeFilter": { "title": "Time Filter", "enum": [ "hour", "day", "week", "month", "year", "all" ], "type": "string", "description": "Time window for top/search sort. Only applies when Sort Order is 'top' or 'relevance'.", "default": "week" }, "maxPostsPerSubreddit": { "title": "Max Posts Per Subreddit", "minimum": 1, "maximum": 1000, "type": "integer", "description": "Maximum number of posts to fetch per subreddit. Higher values increase cost.", "default": 25 }, "includeComments": { "title": "Include Comments", "type": "boolean", "description": "Fetch and include full comment trees for each post. Disable for faster, cheaper runs when you only need post metadata.", "default": true }, "maxCommentsPerPost": { "title": "Max Comments Per Post", "minimum": 0, "maximum": 500, "type": "integer", "description": "Maximum number of comments to fetch per post. Includes replies at all depths.", "default": 100 }, "commentDepth": { "title": "Max Comment Depth", "minimum": 1, "maximum": 10, "type": "integer", "description": "Maximum depth for nested comment replies (1 = top-level only, 10 = full tree).", "default": 5 }, "flairFilter": { "title": "Flair Filter", "type": "string", "description": "Only include posts matching this flair text (case-insensitive, partial match)." }, "keywordFilter": { "title": "Keyword Filter", "type": "array", "description": "Only include posts/comments containing at least one of these keywords (case-insensitive).", "items": { "type": "string" } }, "minScore": { "title": "Minimum Score", "minimum": 0, "type": "integer", "description": "Skip posts with score below this threshold. Useful for filtering out low-quality content.", "default": 0 }, "dateFrom": { "title": "Date From (UTC)", "type": "string", "description": "Only include posts created after this date/time (ISO 8601 format, e.g. 2024-01-01T00:00:00Z). Note: Reddit's API doesn't natively support date filtering — posts will be fetched and filtered client-side." }, "dateTo": { "title": "Date To (UTC)", "type": "string", "description": "Only include posts created before this date/time (ISO 8601 format)." }, "includeNSFW": { "title": "Include NSFW Content", "type": "boolean", "description": "Include posts marked as NSFW (Not Safe For Work).", "default": false }, "includeSubredditMeta": { "title": "Include Subreddit Metadata", "type": "boolean", "description": "Attach subreddit metadata (subscriber count, description, etc.) to each result.", "default": true }, "outputFormat": { "title": "Output Format", "enum": [ "json", "markdown", "both" ], "type": "string", "description": "json: structured JSON only. markdown: AI-ready markdown document. both: include both in every result.", "default": "both" }, "webhookUrl": { "title": "Webhook URL", "type": "string", "description": "POST endpoint to receive new matching posts in monitor mode. Required for monitor mode." }, "monitoringInterval": { "title": "Monitoring Interval (minutes)", "minimum": 2, "maximum": 60, "type": "integer", "description": "How often to poll Reddit for new posts in monitor mode. Minimum 2 minutes.", "default": 5 }, "proxyConfiguration": { "title": "Proxy Configuration", "type": "object", "description": "Apify proxy configuration. Strongly recommended to avoid rate limiting." }, "maxConcurrency": { "title": "Max Concurrency", "minimum": 1, "maximum": 5, "type": "integer", "description": "Maximum number of parallel requests. Keep low (1-3) to respect Reddit rate limits.", "default": 2 }, "debugMode": { "title": "Debug Mode", "type": "boolean", "description": "Enable verbose logging for troubleshooting.", "default": false } } }, "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 } } } } } } } } } } ```