# Reddit Search Posts (`pratikdani/reddit-search-posts`) Actor Collect Reddit posts by keyword, community, and sort order in a few simple steps. - **URL**: https://apify.com/pratikdani/reddit-search-posts.md - **Developed by:** [Pratik Dani](https://apify.com/pratikdani) (community) - **Categories:** Social media, News, Automation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $15.00 / 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. Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have. 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 Posts Find Reddit posts that match a topic, community, or style of sorting in just a few clicks. This tool helps you quickly browse real conversations and popular posts so you can discover ideas, trends, and discussions without digging manually. ### What you get - Post title - Post author - Community name - Post link - Number of comments - Score and popularity signals - Post date - Post text, when available - Media links and thumbnail images - Flair or tag shown on the post - Whether the post is archived, locked, or marked 18+ - Pagination support for more results ### How to use 1. Sign up for the marketplace and open this tool. 2. Enter the words you want to search for, such as a brand, topic, or phrase. 3. Optionally choose a community, sorting style, and time range. 4. Run the search to view matching posts. 5. Download the results and use them in your workflow, research, or review process. ### Inputs | Field | Required | Plain-English description | |---|---|---| | query | Yes | The words or phrase you want to search for in Reddit posts. Example: `nike` | | subreddit | No | A specific community to search within. Leave blank to search across Reddit more broadly. | | sort | No | Chooses how results are arranged: relevance, hot, top, new, or comments. | | time | No | Limits results to a time period such as hour, day, week, month, year, or all. Only works when sorting by top. | | cursor | No | Used to continue from where the previous results ended, so you can view more posts. | | maxResults | No | Sets how many results you want returned at once. | ### Output Each result includes detailed post information in plain English: - **all_awardings**: A list of awards the post received. - **allow_live_comments**: Shows whether live comments are allowed. - **approved_at_utc**: When the post was approved, if that applies. - **approved_by**: Who approved the post, if available. - **archived**: Shows whether the post is archived and no longer changing. - **author**: The username of the person who posted it. - **author_flair_background_color**: The background color of the author’s flair, if any. - **author_flair_css_class**: The flair style class for the author, if any. - **author_flair_richtext**: A richer version of the author flair content. - **author_flair_template_id**: The flair template identifier, if used. - **author_flair_text**: The text shown in the author’s flair. - **author_flair_text_color**: The color of the author flair text. - **author_flair_type**: The type of flair shown for the author. - **author_fullname**: The author’s full internal name. - **author_is_blocked**: Shows whether the author is blocked. - **author_patreon_flair**: Shows whether the author has a special supporter flair. - **author_premium**: Shows whether the author has premium status. - **awarders**: A list of people or accounts that gave awards. - **banned_at_utc**: When the post or author was banned, if that happened. - **banned_by**: Who issued the ban, if available. - **can_gild**: Shows whether the post can receive awards. - **can_mod_post**: Shows whether moderators can post on it. - **category**: The post category, if one exists. - **clicked**: Shows whether the post has been clicked. - **content_categories**: Content category labels, if present. - **contest_mode**: Shows whether contest-style sorting is enabled. - **created**: The creation time as a timestamp. - **created_utc**: The creation time in universal time. - **discussion_type**: The type of discussion, if set. - **distinguished**: Whether the post is marked as official or highlighted. - **domain**: The source site or media domain. - **downs**: Number of downvotes. - **edited**: Shows whether the post was edited. - **gilded**: How many awards the post received. - **gildings**: Award details in structured form. - **hidden**: Shows whether the post is hidden. - **hide_score**: Shows whether the score is hidden. - **id**: The short ID for the post. - **is_created_from_ads_ui**: Shows whether it was created through an ad tool. - **is_crosspostable**: Shows whether it can be shared elsewhere. - **is_meta**: Shows whether it is a meta post. - **is_original_content**: Shows whether it is marked as original content. - **is_reddit_media_domain**: Shows whether the media comes from Reddit. - **is_robot_indexable**: Shows whether search tools can index it. - **is_self**: Shows whether the post is text-based. - **is_video**: Shows whether the post is a video. - **likes**: The current like status, if available. - **link_flair_background_color**: The background color of the post flair. - **link_flair_css_class**: The flair style class for the post. - **link_flair_richtext**: Rich flair content shown on the post. - **link_flair_template_id**: The flair template identifier for the post. - **link_flair_text**: The text label shown as flair. - **link_flair_text_color**: The text color of the flair. - **link_flair_type**: The type of flair used. - **locked**: Shows whether comments are locked. - **media**: Media attached to the post, if any. - **media_embed**: Embedded media details. - **media_only**: Shows whether the post contains only media. - **mod_note**: Moderator note, if present. - **mod_reason_by**: Who applied a moderator action, if available. - **mod_reason_title**: Title of the moderation reason. - **mod_reports**: Moderator reports attached to the post. - **name**: The full post identifier. - **no_follow**: Shows whether search engines should not follow the post. - **num_comments**: Number of comments on the post. - **num_crossposts**: Number of times it was crossposted. - **num_reports**: Number of reports, if available. - **over_18**: Shows whether the content is marked for adults. - **permalink**: The Reddit link path to the post. - **pinned**: Shows whether the post is pinned. - **post_hint**: A hint about the post type, such as image or video. - **preview**: Preview image details and sizes. - **pwls**: Community or content weight indicator. - **quarantine**: Shows whether the post is in a restricted community. - **removal_reason**: Reason the post was removed, if available. - **removed_by**: Who removed the post, if available. - **removed_by_category**: Category of the remover, if available. - **report_reasons**: Reasons the post was reported. - **saved**: Shows whether the post was saved. - **score**: The overall score of the post. - **secure_media**: Secure media details, if any. - **secure_media_embed**: Secure embedded media details. - **selftext**: The text body of the post. - **selftext_html**: The HTML version of the post text. - **send_replies**: Shows whether replies are enabled. - **spoiler**: Shows whether the post is marked as a spoiler. - **stickied**: Shows whether the post is pinned to the top. - **subreddit**: The community where the post was shared. - **subreddit_id**: The internal ID of the community. - **subreddit_name_prefixed**: The community name with the `r/` prefix. - **subreddit_subscribers**: The number of people subscribed to that community. - **subreddit_type**: The community type, such as public. - **suggested_sort**: The suggested way to sort comments, if any. - **thumbnail**: A small preview image link. - **thumbnail_height**: The thumbnail height. - **thumbnail_width**: The thumbnail width. - **title**: The post title. - **top_awarded_type**: The most prominent award type, if any. - **total_awards_received**: Total number of awards received. - **treatment_tags**: Labels attached for moderation or handling. - **ups**: Number of upvotes. - **upvote_ratio**: The share of votes that were upvotes. - **url**: The main link for the post. - **url_overridden_by_dest**: The final destination link, if different. - **user_reports**: Reports submitted by users. - **view_count**: Number of views, if available. - **visited**: Shows whether the post has been visited. - **wls**: Community or content weight indicator. ### Use cases - Track what people are saying about a brand, product, or keyword. - Find popular discussions in a specific community. - Research customer opinions, trends, and recurring questions. - Review recent or top posts for content ideas and market insight. # Actor input Schema ## `query` (type: `string`): What you want to search for. For example: "Nike shoes" or "python jobs". ## `subreddit` (type: `string`): Optional: limit results to one subreddit. For example: "stocks" or "AskReddit". ## `sort` (type: `string`): Choose how the results should be ordered. For example: "relevance" or "new". ## `time` (type: `string`): Optional: choose a time period for top results. Use this only when sort is set to top. For example: "week" or "month". ## `maxResults` (type: `integer`): Maximum number of results to return (default: 20). ## Actor input object example ```json { "query": "nike", "subreddit": "stocks", "sort": "relevance", "maxResults": 20 } ```` # Actor output Schema ## `results` (type: `string`): Formatted table view with labeled columns — ideal for reviewing data in Apify Console ## `rawData` (type: `string`): Unformatted JSON items exactly as collected from the API — use this for programmatic processing # 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 = { "query": "nike", "subreddit": "stocks" }; // Run the Actor and wait for it to finish const run = await client.actor("pratikdani/reddit-search-posts").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 = { "query": "nike", "subreddit": "stocks", } # Run the Actor and wait for it to finish run = client.actor("pratikdani/reddit-search-posts").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 '{ "query": "nike", "subreddit": "stocks" }' | apify call pratikdani/reddit-search-posts --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=pratikdani/reddit-search-posts", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Reddit Search Posts", "description": "Collect Reddit posts by keyword, community, and sort order in a few simple steps.", "version": "0.0", "x-build-id": "rWSREVtUbBI1v7Wxg" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/pratikdani~reddit-search-posts/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-pratikdani-reddit-search-posts", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/pratikdani~reddit-search-posts/runs": { "post": { "operationId": "runs-sync-pratikdani-reddit-search-posts", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/pratikdani~reddit-search-posts/run-sync": { "post": { "operationId": "run-sync-pratikdani-reddit-search-posts", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "query" ], "properties": { "query": { "title": "Search keyword or phrase", "type": "string", "description": "What you want to search for. For example: \"Nike shoes\" or \"python jobs\"." }, "subreddit": { "title": "Subreddit name", "type": "string", "description": "Optional: limit results to one subreddit. For example: \"stocks\" or \"AskReddit\"." }, "sort": { "title": "Sort results by", "enum": [ "relevance", "hot", "top", "new", "comments" ], "type": "string", "description": "Choose how the results should be ordered. For example: \"relevance\" or \"new\".", "default": "relevance" }, "time": { "title": "Time period", "enum": [ "hour", "day", "week", "month", "year", "all" ], "type": "string", "description": "Optional: choose a time period for top results. Use this only when sort is set to top. For example: \"week\" or \"month\"." }, "maxResults": { "title": "Maximum results", "minimum": 1, "maximum": 500, "type": "integer", "description": "Maximum number of results to return (default: 20).", "default": 20 } } }, "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 } } } } } } } } } } ```