Subreddit Scraper - Deep Crawl Posts, Media & Nested Comments
Pricing
from $1.60 / 1,000 results
Extract complete subreddit feeds (Hot, New, Top, Rising, Controversial), historical post archives, media galleries, flairs, and nested discussion comment trees from any Reddit community. Download clean, structured JSON/CSV data with AI sentiment and content taxonomy enrichment.
You can access the Subreddit Scraper - Deep Crawl Posts, Media & Nested Comments programmatically from your own applications by using the Apify API. You can also choose the language preference from below. To use the Apify API, youโll need an Apify account and your API token, found in API & Integrations in Apify Console.
{ "openapi": "3.0.1", "info": { "version": "0.0", "x-build-id": "TbAgvDyGFwPJOMaHf" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/mikolabs~subreddit-scraper-deep-crawl-posts-media-nested-comments/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-mikolabs-subreddit-scraper-deep-crawl-posts-media-nested-comments", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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/mikolabs~subreddit-scraper-deep-crawl-posts-media-nested-comments/runs": { "post": { "operationId": "runs-sync-mikolabs-subreddit-scraper-deep-crawl-posts-media-nested-comments", "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/mikolabs~subreddit-scraper-deep-crawl-posts-media-nested-comments/run-sync": { "post": { "operationId": "run-sync-mikolabs-subreddit-scraper-deep-crawl-posts-media-nested-comments", "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": { "subreddits": { "title": "Subreddits to Scrape", "type": "array", "description": "List of subreddit names (without r/) to scrape.", "items": { "type": "string" } }, "sort": { "title": "Feed Sorting Order", "enum": [ "hot", "new", "top", "rising", "controversial" ], "type": "string", "description": "How to sort posts in the subreddit feed.", "default": "hot" }, "timeframe": { "title": "Timeframe for Top / Controversial", "enum": [ "all", "year", "month", "week", "day", "hour" ], "type": "string", "description": "Time window for Top or Controversial posts.", "default": "all" }, "fullSubredditMode": { "title": "Full Deep Crawl Mode", "type": "boolean", "description": "Deep crawl mode โ paginates as far back as Reddit allows for maximum historical post extraction.", "default": false }, "maxPostsPerSubreddit": { "title": "Max Posts per Subreddit", "minimum": 1, "type": "integer", "description": "Maximum number of posts to collect per subreddit.", "default": 100 }, "maxTotalItems": { "title": "Max Total Items (Safety Cap)", "minimum": 1, "type": "integer", "description": "Safety ceiling for total items (posts + comments) across the entire run.", "default": 500 }, "includeComments": { "title": "Scrape Comments for Each Post", "type": "boolean", "description": "When enabled, extracts the comment thread and replies for every scraped post.", "default": false }, "maxCommentsPerPost": { "title": "Max Comments per Post", "minimum": 1, "type": "integer", "description": "Maximum number of comments to extract per post thread.", "default": 25 }, "commentsSort": { "title": "Comment Sort Order", "enum": [ "confidence", "top", "new", "controversial", "old", "qa" ], "type": "string", "description": "Ranking method for comments in threads.", "default": "confidence" }, "flattenComments": { "title": "Flatten Comments into Dataset Rows", "type": "boolean", "description": "When true, pushes each comment as its own dataset row instead of nesting under parent post.", "default": false }, "sentiment_analysis": { "title": "AI Sentiment Analysis", "type": "boolean", "description": "Enriches each post and comment with sentiment score, confidence, and label (positive, negative, neutral, mixed, uncertain).", "default": false }, "content_analysis": { "title": "AI Content Taxonomy Classification", "type": "boolean", "description": "Classifies posts against an enterprise topic taxonomy (category label and hierarchical path).", "default": false }, "postType": { "title": "Post Media Format", "enum": [ "all", "text", "image", "video", "gallery", "link" ], "type": "string", "description": "Filter posts by media type.", "default": "all" }, "minScore": { "title": "Minimum Post Upvotes (Score)", "type": "integer", "description": "Only keep posts with at least this score." }, "minComments": { "title": "Minimum Comment Count", "type": "integer", "description": "Only keep posts with at least this many comments." }, "postsCreatedAfter": { "title": "Posts Created After Date", "type": "string", "description": "Only keep posts created on or after this date (YYYY-MM-DD)." }, "postsCreatedBefore": { "title": "Posts Created Before Date", "type": "string", "description": "Only keep posts created on or before this date (YYYY-MM-DD)." }, "flairContains": { "title": "Flair Contains Keyword", "type": "string", "description": "Only keep posts with flair text containing this keyword." }, "titleContains": { "title": "Title Contains Keyword", "type": "string", "description": "Only keep posts whose title contains this keyword." }, "excludeStickied": { "title": "Exclude Stickied/Pinned Posts", "type": "boolean", "description": "Exclude moderator announcements and pinned posts.", "default": false }, "excludeKeywords": { "title": "Exclude Keywords", "type": "array", "description": "Exclude posts containing any of these keywords.", "items": { "type": "string" } }, "includeNsfw": { "title": "Include NSFW (18+) Posts", "type": "boolean", "description": "Include posts marked as NSFW/18+ in output dataset.", "default": true } } }, "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 } } } } } } } } }}OpenAPI is a standard for designing and describing RESTful APIs, allowing developers to define API structure, endpoints, and data formats in a machine-readable way. It simplifies API development, integration, and documentation.
OpenAPI is effective when used with AI agents and GPTs by standardizing how these systems interact with various APIs, for reliable integrations and efficient communication.
By defining machine-readable API specifications, OpenAPI allows AI models like GPTs to understand and use varied data sources, improving accuracy. This accelerates development, reduces errors, and provides context-aware responses, making OpenAPI a core component for AI applications.
You can download the OpenAPI definitions for Subreddit Scraper - Deep Crawl Posts, Media & Nested Comments from the options below:
If youโd like to learn more about how OpenAPI powers GPTs, read our blog post.
You can also check out our other API clients: