# Reddit Scraper | Enterprise Grade (`scrapers-hub/reddit-scraper-enterprise-grade`) Actor Reddit Scraper Enterprise Grade extracts publicly available posts, comments, subreddits, user profiles, engagement metrics, timestamps, and other Reddit data at scale 💬📊 Perfect for sentiment analysis, brand monitoring, market research, trend tracking, AI datasets, and competitive intelligence. - **URL**: https://apify.com/scrapers-hub/reddit-scraper-enterprise-grade.md - **Developed by:** [Scrapers Hub](https://apify.com/scrapers-hub) (community) - **Categories:** AI, Social media, Developer tools - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $1.99 / 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/docs.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python/docs.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/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 Search Scraper (Apify Actor) Searches Reddit for one or more keyword queries and returns **enriched post objects** (and optionally comments) as structured JSON in the Actor dataset. Uses Reddit's public `.json` endpoints — no OAuth/API key required. ### Input ```json { "queries": ["Cheesecake", "Swimming Pool"], "maxPosts": 100, "maxComments": 100, "sort": "relevance", "timeframe": "all", "subredditSort": "relevance", "subredditTimeframe": "all", "includeNsfw": false, "scrapeComments": false, "strictSearch": false, "strictTokenFilter": false, "maximize_coverage": false, "forceSortNewForTimeFilteredRuns": false, "content_analysis": false, "sentiment_analysis": false } ```` | Field | Type | Meaning | |---|---|---| | `queries` | string\[] | Keywords/phrases to search. A value like `r/pics cats` restricts the search to a subreddit. | | `maxPosts` | int | Max posts collected **per query** (paginates in pages of 100). | | `sort` / `timeframe` | enum | Reddit search sort (`relevance/hot/top/new/comments`) and time window (`all/year/month/week/day/hour`). | | `subredditSort` / `subredditTimeframe` | enum | Same, applied when a query targets a specific `r/subreddit`. | | `strictSearch` | bool | Keep only posts where **every** query token appears in the title/body. | | `strictTokenFilter` | bool | Keep only posts containing the **exact query phrase**. | | `maximize_coverage` | bool | Sweep multiple sort orders to gather more unique posts. | | `forceSortNewForTimeFilteredRuns` | bool | Force `new` sort whenever `timeframe != all`. | | `includeNsfw` | bool | Include `over_18` posts. | | `scrapeComments` / `maxComments` | bool / int | Also fetch and flatten each post's comment tree. | | `content_analysis` | bool | Attach a `content_analysis` object (keywords, token stats, question/URL detection). | | `sentiment_analysis` | bool | Attach a lexicon-based `sentiment` object (`positive/negative/neutral`). | ### Output Each dataset item is either a **post** (`"kind": "post"`) or a **comment** (`"kind": "comment"`). Posts include the raw Reddit fields plus derived metrics: - `age_hours`, `score_per_hour`, `comments_per_hour` - `engagement_total`, `comment_to_score_ratio`, `is_high_engagement` - `media_type`, `has_media`, `gallery_images`, `gallery_count`, `outbound_url_host` - `title_length`, `body_length`, `word_count` - `is_deleted_or_removed`, `content_flags` - `canonical_url`, `old_reddit_url`, `retrieved_at` See `src/enrich.js` for the exact shape. ### How it avoids being blocked Reddit returns a hard **403** to plain HTTP clients (even ones that impersonate a TLS fingerprint) because they can't solve Reddit's JS/Cloudflare "Please wait for verification" challenge. This Actor drives a real headless **Chromium (Playwright)** session: it loads a Reddit page so the browser solves the challenge and earns a valid session cookie, then fetches the `.json` endpoints **from inside the page** (same-origin, `credentials: 'include'`). One warmed session is reused for all search pagination and comment fetches; on a block/403 it relaunches with a fresh residential proxy. See `RedditBrowser` in `src/reddit.py`. ### Project layout (Python) ``` .actor/actor.json Actor config .actor/input_schema.json Input UI Dockerfile apify/actor-python-playwright:3.13 (Chromium preinstalled) requirements.txt apify (pydantic/browserforge pinned) src/__main__.py Entry point (python -m src) src/main.py Orchestration + Playwright session lifecycle src/reddit.py RedditBrowser (browser fetch) + search/pagination src/comments.py Comment scraping src/enrich.py Derived fields src/analysis.py Content + sentiment analysis ``` ### Run locally ```bash pip install -r requirements.txt apify run # or: python -m src (with local input in storage/) ``` ### Deploy ```bash apify login apify push # builds a NEW image with the current code ``` ### Notes - **Use residential proxies.** Reddit blocks datacenter IPs; the default `proxyConfiguration` is `useApifyProxy` + `RESIDENTIAL`. - Because it runs a real browser, give the Actor enough memory (**≥ 2–4 GB**). - If a network blocks/redirects Reddit itself (e.g. some ISPs), local runs will fail — validate on the Apify platform where the residential proxy is used. - Content/sentiment analysis are lightweight offline heuristics — replace with a real NLP service if you need higher accuracy. # Actor input Schema ## `queries` (type: `array`): One or more keywords / phrases to search across all of Reddit. ## `sort` (type: `string`): How Reddit ranks the search results. ## `timeframe` (type: `string`): Only include results from this time window. ## `subredditName` (type: `string`): Subreddit name, with or without the r/ prefix (e.g. 'food' or 'r/food'). ## `subredditKeywords` (type: `array`): Optional keywords to search inside the subreddit. Leave empty to browse the subreddit's posts. ## `subredditSort` (type: `string`): How Reddit ranks results within the subreddit. ## `subredditTimeframe` (type: `string`): Only include subreddit results from this time window. ## `urls` (type: `array`): Full Reddit post URLs to scrape directly. ## `scrapeComments` (type: `boolean`): Also collect the comments of every scraped post. ## `maxComments` (type: `integer`): Maximum number of comments to collect per post. ## `dateFrom` (type: `string`): Keep only posts created on or after this date (YYYY-MM-DD, UTC). ## `dateTo` (type: `string`): Keep only posts created on or before this date (YYYY-MM-DD, UTC). ## `commentDateFrom` (type: `string`): Keep only comments created on or after this date (YYYY-MM-DD, UTC). ## `commentDateTo` (type: `string`): Keep only comments created on or before this date (YYYY-MM-DD, UTC). ## `forceSortNewForTimeFilteredRuns` (type: `boolean`): Force 'new' sort whenever a time range is set, so recent posts aren't missed. ## `includeNsfw` (type: `boolean`): Include posts marked over\_18 / NSFW. ## `strictSearch` (type: `boolean`): Keep only posts where every query token appears in the title or body. ## `strictTokenFilter` (type: `boolean`): Keep only posts that contain the exact query phrase. ## `maxPosts` (type: `integer`): Maximum number of posts to collect per search / subreddit / URL. ## `maximize_coverage` (type: `boolean`): Sweep multiple sort orders per seed to gather more unique posts. ## `sentiment_analysis` (type: `boolean`): Attach a lexicon-based sentiment score and label to each post. ## `content_analysis` (type: `boolean`): Attach a content category (Finance, Sports, Gaming, Politics, …) and stats to each post. ## `mcpConnectors` (type: `array`): Connector IDs to hand off the run summary to (optional). ## Actor input object example ```json { "queries": [ "Cheesecake", "Swimming Pool" ], "sort": "relevance", "timeframe": "all", "subredditSort": "relevance", "subredditTimeframe": "all", "scrapeComments": false, "maxComments": 50000, "forceSortNewForTimeFilteredRuns": false, "includeNsfw": false, "strictSearch": false, "strictTokenFilter": false, "maxPosts": 50000, "maximize_coverage": false, "sentiment_analysis": false, "content_analysis": false } ``` # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "queries": [ "Cheesecake", "Swimming Pool" ] }; // Run the Actor and wait for it to finish const run = await client.actor("scrapers-hub/reddit-scraper-enterprise-grade").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 = { "queries": [ "Cheesecake", "Swimming Pool", ] } # Run the Actor and wait for it to finish run = client.actor("scrapers-hub/reddit-scraper-enterprise-grade").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 '{ "queries": [ "Cheesecake", "Swimming Pool" ] }' | apify call scrapers-hub/reddit-scraper-enterprise-grade --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=scrapers-hub/reddit-scraper-enterprise-grade", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Reddit Scraper | Enterprise Grade", "description": "Reddit Scraper Enterprise Grade extracts publicly available posts, comments, subreddits, user profiles, engagement metrics, timestamps, and other Reddit data at scale 💬📊 Perfect for sentiment analysis, brand monitoring, market research, trend tracking, AI datasets, and competitive intelligence.", "version": "1.0", "x-build-id": "cgzry2MVLv7BiddGB" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/scrapers-hub~reddit-scraper-enterprise-grade/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-scrapers-hub-reddit-scraper-enterprise-grade", "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/scrapers-hub~reddit-scraper-enterprise-grade/runs": { "post": { "operationId": "runs-sync-scrapers-hub-reddit-scraper-enterprise-grade", "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/scrapers-hub~reddit-scraper-enterprise-grade/run-sync": { "post": { "operationId": "run-sync-scrapers-hub-reddit-scraper-enterprise-grade", "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": { "queries": { "title": "Add Search Keywords", "type": "array", "description": "One or more keywords / phrases to search across all of Reddit.", "items": { "type": "string" } }, "sort": { "title": "Choose How Search Results Are Ranked", "enum": [ "relevance", "hot", "top", "new", "comments" ], "type": "string", "description": "How Reddit ranks the search results.", "default": "relevance" }, "timeframe": { "title": "Limit Results by Time Range", "enum": [ "all", "year", "month", "week", "day", "hour" ], "type": "string", "description": "Only include results from this time window.", "default": "all" }, "subredditName": { "title": "Choose a Subreddit to Search", "type": "string", "description": "Subreddit name, with or without the r/ prefix (e.g. 'food' or 'r/food')." }, "subredditKeywords": { "title": "Add Keywords Within That Subreddit", "type": "array", "description": "Optional keywords to search inside the subreddit. Leave empty to browse the subreddit's posts.", "items": { "type": "string" } }, "subredditSort": { "title": "Choose How Subreddit Results Are Ranked", "enum": [ "relevance", "hot", "top", "new", "comments" ], "type": "string", "description": "How Reddit ranks results within the subreddit.", "default": "relevance" }, "subredditTimeframe": { "title": "Limit Subreddit Results by Time Range", "enum": [ "all", "year", "month", "week", "day", "hour" ], "type": "string", "description": "Only include subreddit results from this time window.", "default": "all" }, "urls": { "title": "Add Reddit URLs to Scrape", "type": "array", "description": "Full Reddit post URLs to scrape directly.", "items": { "type": "string" } }, "scrapeComments": { "title": "Include Comments from Each Post", "type": "boolean", "description": "Also collect the comments of every scraped post.", "default": false }, "maxComments": { "title": "Set a Comment Limit per Post", "minimum": 1, "type": "integer", "description": "Maximum number of comments to collect per post.", "default": 50000 }, "dateFrom": { "title": "Keep Posts Starting From a Specific Date", "type": "string", "description": "Keep only posts created on or after this date (YYYY-MM-DD, UTC)." }, "dateTo": { "title": "Keep Posts Up to a Specific Date", "type": "string", "description": "Keep only posts created on or before this date (YYYY-MM-DD, UTC)." }, "commentDateFrom": { "title": "Keep Comments Starting From a Specific Date", "type": "string", "description": "Keep only comments created on or after this date (YYYY-MM-DD, UTC)." }, "commentDateTo": { "title": "Keep Comments Up to a Specific Date", "type": "string", "description": "Keep only comments created on or before this date (YYYY-MM-DD, UTC)." }, "forceSortNewForTimeFilteredRuns": { "title": "Favor Newest Results for Better Time Coverage (Recommended for Time Frame Filtered Searches)", "type": "boolean", "description": "Force 'new' sort whenever a time range is set, so recent posts aren't missed.", "default": false }, "includeNsfw": { "title": "Include NSFW and 18+ Posts", "type": "boolean", "description": "Include posts marked over_18 / NSFW.", "default": false }, "strictSearch": { "title": "Strict Reddit Search to Follow Your Keywords More Closely", "type": "boolean", "description": "Keep only posts where every query token appears in the title or body.", "default": false }, "strictTokenFilter": { "title": "Keep Only Posts That Clearly Match the Full Query", "type": "boolean", "description": "Keep only posts that contain the exact query phrase.", "default": false }, "maxPosts": { "title": "Set a Post Limit for Each Input", "minimum": 1, "type": "integer", "description": "Maximum number of posts to collect per search / subreddit / URL.", "default": 50000 }, "maximize_coverage": { "title": "Expand Each Search Seed for Broader Reddit Coverage", "type": "boolean", "description": "Sweep multiple sort orders per seed to gather more unique posts.", "default": false }, "sentiment_analysis": { "title": "Add Sentiment Scores and Labels to Posts and Comments", "type": "boolean", "description": "Attach a lexicon-based sentiment score and label to each post.", "default": false }, "content_analysis": { "title": "Classify Posts into Content Categories", "type": "boolean", "description": "Attach a content category (Finance, Sports, Gaming, Politics, …) and stats to each post.", "default": false }, "mcpConnectors": { "title": "MCP Delivery Connectors", "type": "array", "description": "Connector IDs to hand off the run summary to (optional).", "items": { "type": "string" } } } }, "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 } } } } } } } } } } ```