# Reddit Search Scraper (`phazonoverload/reddit-search`) Actor \[Unofficial] Scrapes Reddit search results for a given terms and filters by date. - **URL**: https://apify.com/phazonoverload/reddit-search.md - **Developed by:** [Kevin Lewis](https://apify.com/phazonoverload) (community) - **Categories:** Social media - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 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 Post Search Scraper > **This is NOT an official Reddit product or service. This Actor is not affiliated with, endorsed by, or connected to Reddit Inc. Reddit is a registered trademark of Reddit Inc.** **Reddit Post Search Scraper** is an Apify Actor that finds Reddit posts matching your search terms across all of Reddit. It uses old.reddit.com for server-rendered HTML — no JavaScript required. ### Why use Reddit Post Search Scraper? - **Brand monitoring** — Find every post mentioning your product, company, or keyword - **Market research** — Discover what people are posting about in your niche - **Competitor research** — Track competitor mentions across subreddits - **Content discovery** — Find relevant posts to engage with or learn from ### How to use 1. **Search terms** — Enter one or more terms 2. **Since date** — Optional ISO 8601 filter (e.g., `2024-01-15T14:30:00Z`) 3. **Max posts** — How many matching posts to find (0 = unlimited) 4. Run and get structured data back ### Input | Field | Type | Required | Default | Description | |-------|------|----------|---------|-------------| | `searchTerms` | string[] | Yes | — | One or more terms to search | | `since` | string | No | `2020-01-01T00:00:00Z` | ISO 8601 datetime filter (minute precision) | | `maxResults` | integer | No | 50 | Max matching posts to find. 0 = unlimited | | `proxyConfiguration` | proxy | No | Apify SERP proxy | Proxy configuration | ### Output schema One record per matching post: ```json { "type": "post", "id": "t3_1sy0cqn", "postId": "t3_1sy0cqn", "postTitle": "30 days in, 100+ users, 2 paying. Is my free tier eating me alive?", "postUrl": "https://old.reddit.com/r/SaaS/comments/1sy0cqn/.../", "subreddit": "SaaS", "author": "mplacona", "score": 5, "postedAt": "2026-04-28T12:44:23+00:00", "body": "Hey r/SaaS, looking for a gut check...", "permalink": "/r/SaaS/comments/1sy0cqn/.../", "commentCount": 28 } ```` ### Data fields | Field | Type | Description | |-------|------|-------------| | `type` | string | Always `"post"` | | `id` | string | Post fullname (`t3_xxx`) | | `postId` | string | Same as `id` | | `postTitle` | string | Post title | | `postUrl` | string | Link to the post (old.reddit.com) | | `subreddit` | string | Subreddit name (no `r/` prefix) | | `author` | string | Post author | | `score` | number | Upvote score | | `postedAt` | string | ISO 8601 timestamp | | `body` | string or null | Post self-text | | `permalink` | string or null | Direct link to the post | | `commentCount` | number | Total comments on the post (0; not extracted in this version) | ### Pricing This Actor runs compute units for HTTP requests to old.reddit.com. Most runs complete in seconds. Check the [Apify pricing page](https://apify.com/pricing) for details. ### Tips - Use **SERP proxy groups** to avoid Reddit rate limiting - The `since` field supports ISO 8601 with time: `2024-01-15T14:30:00Z` (minute precision) - Add multiple `searchTerms` — duplicates across terms are auto-deduplicated - Set `maxResults` to 0 for unlimited (caution: depends on Reddit's search depth) - The search uses `type=link` which matches posts by their title or body. Comments are not searched directly. ### FAQ **Q: Why does the URL use old.reddit.com?** A: The new Reddit interface requires JavaScript rendering. old.reddit.com is fully server-rendered and works with HTTP scraping. **Q: How precise is the date filtering?** A: Minute-level. The `data-timestamp` attribute on each post page is compared against your `since` value. **Q: What happens if Reddit blocks the request?** A: The Actor logs the HTTP status and exits cleanly. Enable Apify Proxy with SERP groups to avoid blocks. **Q: Is this affiliated with Reddit?** A: No. This is an independent tool and is not affiliated with or endorsed by Reddit Inc. **Q: Why only posts?** A: This actor focuses on post-level search. For comment-level analysis, the search scope would be much broader and unreliable across Reddit's current search API. Comment search on old.reddit.com redirects to the www endpoint, which caps results and can't be paginated from a headless browser. We chose to ship a reliable post-only tool rather than an unreliable comment tool. **Q: How many results will I get?** A: Old.reddit's search returns up to ~10 results per page and supports `?after=` cursor pagination up to 20 pages. The actual count depends on Reddit's search depth for your term. ### Support For issues and feature requests, use the [Issues](https://github.com/anomalyco/actors/issues) tab. # Actor input Schema ## `searchTerms` (type: `array`): One or more terms to search for on Reddit. Duplicate posts across terms are removed. ## `since` (type: `string`): Only return posts made after this date/time. Picker: YYYY-MM-DD. Enter time via JSON mode: YYYY-MM-DDTHH:mm:ssZ (e.g. 2024-01-15T14:30:00Z). Default: 2020-01-01T00:00:00Z ## `maxResults` (type: `integer`): Maximum number of matching posts to find. Set to 0 for no limit. ## `proxyConfiguration` (type: `object`): Proxy settings for Reddit searches. ## Actor input object example ```json { "searchTerms": [ "example search term" ], "since": "2020-01-01T00:00:00Z", "maxResults": 50, "proxyConfiguration": { "useApifyProxy": 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 = { "searchTerms": [ "example search term" ] }; // Run the Actor and wait for it to finish const run = await client.actor("phazonoverload/reddit-search").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 = { "searchTerms": ["example search term"] } # Run the Actor and wait for it to finish run = client.actor("phazonoverload/reddit-search").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 '{ "searchTerms": [ "example search term" ] }' | apify call phazonoverload/reddit-search --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=phazonoverload/reddit-search", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Reddit Search Scraper", "description": "[Unofficial] Scrapes Reddit search results for a given terms and filters by date.", "version": "1.0", "x-build-id": "Bg8jExaC0CEOnYq4M" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/phazonoverload~reddit-search/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-phazonoverload-reddit-search", "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/phazonoverload~reddit-search/runs": { "post": { "operationId": "runs-sync-phazonoverload-reddit-search", "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/phazonoverload~reddit-search/run-sync": { "post": { "operationId": "run-sync-phazonoverload-reddit-search", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "required": [ "searchTerms" ], "properties": { "searchTerms": { "title": "Search Terms", "type": "array", "description": "One or more terms to search for on Reddit. Duplicate posts across terms are removed.", "items": { "type": "string" } }, "since": { "title": "Since Date", "pattern": "^(\\d{4})-(0[1-9]|1[0-2])-(0[1-9]|[12]\\d|3[01])(T[0-2]\\d:[0-5]\\d(:[0-5]\\d)?(\\.\\d+)?Z?)?$|^(\\d+)\\s*(minute|hour|day|week|month|year)s?$", "type": "string", "description": "Only return posts made after this date/time. Picker: YYYY-MM-DD. Enter time via JSON mode: YYYY-MM-DDTHH:mm:ssZ (e.g. 2024-01-15T14:30:00Z). Default: 2020-01-01T00:00:00Z", "default": "2020-01-01T00:00:00Z" }, "maxResults": { "title": "Max Posts", "minimum": 0, "type": "integer", "description": "Maximum number of matching posts to find. Set to 0 for no limit.", "default": 50 }, "proxyConfiguration": { "title": "Proxy Configuration", "type": "object", "description": "Proxy settings for Reddit searches.", "default": { "useApifyProxy": 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 } } } } } } } } } } ```