# Reddit Search Scraper (`myagizm/reddit-search-scraper`) Actor Search Reddit by keyword and export matching posts, communities and users as structured JSON. No login, no API key. - **URL**: https://apify.com/myagizm/reddit-search-scraper.md - **Developed by:** [MYM](https://apify.com/myagizm) (community) - **Categories:** Social media - **Stats:** 2 total users, 0 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing $1.40 / 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 Search Scraper 🔍 Search **Reddit by keyword** and export matching **posts, communities, and users** as structured JSON. No login, no API key. Great for keyword monitoring, brand tracking, lead generation, and research. ### What you get - Posts: title, author, score, comments, selftext, subreddit, url - Communities: name, subscribers, description - Users: name, karma, account age Restrict to specific subreddits, choose sort and time window. ### Example input ```json { "searchQueries": ["machine learning", "python"], "searchFor": ["posts", "communities"], "sort": "relevance", "time": "month" } ```` ### Output One record per result (see the **Results** view in the Output tab). Export as JSON, CSV, Excel, or via API. ### 💵 Pricing **$1.40 per 1,000 results** — pay only for what you scrape. No monthly fee. ### ⏱️ Limits A run lasts at most ~10 minutes; only one long-running job runs at a time. ### Notes Reads only public Reddit data. Reddit no longer supports true comment search. Please scrape responsibly. *** ### 🔎 Keywords reddit search scraper, reddit keyword search, reddit keyword monitor, reddit brand monitoring, reddit search api, reddit lead generation, reddit mentions, search reddit posts, reddit communities search, reddit user search, reddit trends, no login reddit # Actor input Schema ## `searchQueries` (type: `array`): Keywords to search on Reddit. Each query runs for every type selected in "Search for". ## `searchFor` (type: `array`): Which entity types each query returns. ## `searchInSubreddits` (type: `array`): If set, each query is restricted to these subreddits. ## `sort` (type: `string`): Result ordering. ## `time` (type: `string`): Time window for the search. ## `includeSelftext` (type: `boolean`): Include the body text of matched posts. ## `includeNSFW` (type: `boolean`): Include results flagged over-18 / NSFW. ## `maxItems` (type: `integer`): Hard cap on results saved. A run lasts at most ~10 minutes. ## `maxPostsPerSource` (type: `integer`): Cap on results kept per query. ## `maxRetries` (type: `integer`): Retry attempts per failed request. ## `requestDelayMs` (type: `integer`): Politeness delay between requests. ## `debug` (type: `boolean`): Emit verbose logs. ## Actor input object example ```json { "searchQueries": [ "machine learning" ], "searchFor": [ "posts" ], "searchInSubreddits": [ "learnpython" ], "sort": "relevance", "time": "month", "includeSelftext": true, "includeNSFW": false, "maxItems": 50, "maxPostsPerSource": 25, "maxRetries": 3, "requestDelayMs": 300, "debug": false } ``` # Actor output Schema ## `results` (type: `string`): All scraped items as structured JSON. # 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 = { "searchQueries": [ "python developer" ], "searchFor": [ "posts" ], "sort": "relevance", "time": "month", "includeSelftext": true, "includeNSFW": false, "maxItems": 50, "maxPostsPerSource": 25, "maxRetries": 3, "requestDelayMs": 300, "debug": false }; // Run the Actor and wait for it to finish const run = await client.actor("myagizm/reddit-search-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 = { "searchQueries": ["python developer"], "searchFor": ["posts"], "sort": "relevance", "time": "month", "includeSelftext": True, "includeNSFW": False, "maxItems": 50, "maxPostsPerSource": 25, "maxRetries": 3, "requestDelayMs": 300, "debug": False, } # Run the Actor and wait for it to finish run = client.actor("myagizm/reddit-search-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 '{ "searchQueries": [ "python developer" ], "searchFor": [ "posts" ], "sort": "relevance", "time": "month", "includeSelftext": true, "includeNSFW": false, "maxItems": 50, "maxPostsPerSource": 25, "maxRetries": 3, "requestDelayMs": 300, "debug": false }' | apify call myagizm/reddit-search-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=myagizm/reddit-search-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Reddit Search Scraper", "description": "Search Reddit by keyword and export matching posts, communities and users as structured JSON. No login, no API key.", "version": "0.1", "x-build-id": "EsS2CLd4Qg1yqmvkJ" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/myagizm~reddit-search-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-myagizm-reddit-search-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/myagizm~reddit-search-scraper/runs": { "post": { "operationId": "runs-sync-myagizm-reddit-search-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/myagizm~reddit-search-scraper/run-sync": { "post": { "operationId": "run-sync-myagizm-reddit-search-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "searchQueries": { "title": "Search queries", "type": "array", "description": "Keywords to search on Reddit. Each query runs for every type selected in \"Search for\".", "items": { "type": "string" } }, "searchFor": { "title": "Search for", "type": "array", "description": "Which entity types each query returns.", "items": { "type": "string", "enum": [ "posts", "communities", "users", "media" ], "enumTitles": [ "Posts", "Communities", "Users", "Media posts only" ] }, "default": [ "posts" ] }, "searchInSubreddits": { "title": "Restrict to subreddits", "type": "array", "description": "If set, each query is restricted to these subreddits.", "items": { "type": "string" } }, "sort": { "title": "Sort", "enum": [ "relevance", "new", "hot", "top", "comments" ], "type": "string", "description": "Result ordering.", "default": "relevance" }, "time": { "title": "Time range", "enum": [ "hour", "day", "week", "month", "year", "all" ], "type": "string", "description": "Time window for the search.", "default": "all" }, "includeSelftext": { "title": "Include post text", "type": "boolean", "description": "Include the body text of matched posts.", "default": true }, "includeNSFW": { "title": "Include NSFW", "type": "boolean", "description": "Include results flagged over-18 / NSFW.", "default": false }, "maxItems": { "title": "Max items", "minimum": 1, "maximum": 100, "type": "integer", "description": "Hard cap on results saved. A run lasts at most ~10 minutes.", "default": 50 }, "maxPostsPerSource": { "title": "Max results per query", "minimum": 1, "maximum": 100, "type": "integer", "description": "Cap on results kept per query.", "default": 25 }, "maxRetries": { "title": "Max request retries", "minimum": 0, "maximum": 6, "type": "integer", "description": "Retry attempts per failed request.", "default": 3 }, "requestDelayMs": { "title": "Delay between requests (ms)", "minimum": 0, "maximum": 10000, "type": "integer", "description": "Politeness delay between requests.", "default": 300 }, "debug": { "title": "Debug logging", "type": "boolean", "description": "Emit verbose logs.", "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 } } } } } } } } } } ```