# Reddit Scraper (`botflowtech/reddit-scraper`) Actor Reddit Scraper - **URL**: https://apify.com/botflowtech/reddit-scraper.md - **Developed by:** [BotFlowTech](https://apify.com/botflowtech) (community) - **Categories:** Social media - **Stats:** 1 total users, 0 monthly users, 0.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing Pay per usage This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-usage ## 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 Personal Loan Lead Scraper This actor searches specified Reddit subreddits for **personal-loan** related posts, normalizes them into a unified lead format, and can optionally filter them using a built-in heuristic (LLM-style scoring). ### What it does - Iterates over `subreddit × keyword` combinations. - Scrapes posts for each combination (you plug in Reddit API / Apify actor / HTTP logic in `scrapeReddit`). - Normalizes posts to a common schema: - `platform`, `title`, `body`, `author`, `url`, `keyword`, `context` (subreddit), `createdAt`, `upvotes`, `numComments`. - Optionally runs a simple LLM-like filter to keep only posts that look like genuine loan seekers. > Note: The current `scrapeReddit` function is a stub returning an empty array. Replace it with Reddit API calls or `Actor.call()` to a store Reddit scraper actor before using in production. ### Input Configured via `INPUT_SCHEMA.json`: - `redditSubreddits` (array, required) Subreddits to search, e.g. `["hyderabad", "personalfinanceindia"]`. - `redditKeywords` (array, required) Loan-related keywords, e.g. `["personal loan hyderabad", "need loan hyderabad"]`. - `maxResultsPerSource` (integer) Max posts to fetch per subreddit × keyword combination. - `enableLlmFiltering` (boolean) When `true`, only items classified as Hot/Warm loan leads by the heuristic `callLeadLlm` are kept. You can edit these inputs in the Apify Console actor input form or via the API. ### Output Each dataset item looks like: ```json { "platform": "Reddit", "title": "Need a personal loan in Hyderabad", "body": "I am looking for a 3L personal loan...", "author": "some_user", "url": "https://reddit.com/r/hyderabad/...", "keyword": "personal loan hyderabad", "context": "hyderabad", "createdAt": "2026-03-18T10:00:00.000Z", "upvotes": 12, "numComments": 5, "llmVerdict": { "is_genuine_loan_seeker": true, "is_hyderabad_area": true, "lead_score": "Hot", "urgency": "High" } } # Actor input Schema ## `redditSubreddits` (type: `array`): List of subreddits to search for personal-loan related posts. ## `redditKeywords` (type: `array`): Keywords to search for in each subreddit. ## `maxResultsPerSource` (type: `integer`): Maximum number of posts to fetch per subreddit × keyword combination. ## `enableLlmFiltering` (type: `boolean`): If enabled, run built-in heuristic/LLM-style filtering to keep only Hot/Warm loan leads. ## Actor input object example ```json { "redditSubreddits": [ "hyderabad", "personalfinanceindia", "IndianCreditCards", "IndiaBusiness" ], "redditKeywords": [ "personal loan hyderabad", "need loan hyderabad", "loan agent personal loan hyderabad", "loan hyderabad" ], "maxResultsPerSource": 50, "enableLlmFiltering": 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 = {}; // Run the Actor and wait for it to finish const run = await client.actor("botflowtech/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/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = {} # Run the Actor and wait for it to finish run = client.actor("botflowtech/reddit-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{}' | apify call botflowtech/reddit-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=botflowtech/reddit-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Reddit Scraper", "description": "Reddit Scraper", "version": "0.0", "x-build-id": "hKyExiFtwZiu9rOBK" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/botflowtech~reddit-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-botflowtech-reddit-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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/botflowtech~reddit-scraper/runs": { "post": { "operationId": "runs-sync-botflowtech-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/botflowtech~reddit-scraper/run-sync": { "post": { "operationId": "run-sync-botflowtech-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", "required": [ "redditSubreddits", "redditKeywords" ], "properties": { "redditSubreddits": { "title": "Reddit subreddits", "type": "array", "description": "List of subreddits to search for personal-loan related posts.", "items": { "type": "string" }, "default": [ "hyderabad", "personalfinanceindia", "IndianCreditCards", "IndiaBusiness" ] }, "redditKeywords": { "title": "Reddit keywords", "type": "array", "description": "Keywords to search for in each subreddit.", "items": { "type": "string" }, "default": [ "personal loan hyderabad", "need loan hyderabad", "loan agent personal loan hyderabad", "loan hyderabad" ] }, "maxResultsPerSource": { "title": "Max results per subreddit/keyword", "minimum": 1, "maximum": 200, "type": "integer", "description": "Maximum number of posts to fetch per subreddit × keyword combination.", "default": 50 }, "enableLlmFiltering": { "title": "Enable LLM filtering", "type": "boolean", "description": "If enabled, run built-in heuristic/LLM-style filtering to keep only Hot/Warm loan leads.", "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 } } } } } } } } } } ```