# Reddit Post Comments Scraper (`electrabot.info/reddit-post-comments`) Actor Scrapes full comment trees from Reddit posts — user handles, upvotes, nested replies, and per-comment sentiment. - **URL**: https://apify.com/electrabot.info/reddit-post-comments.md - **Developed by:** [electra bot](https://apify.com/electrabot.info) (community) - **Categories:** Social media, AI, Lead generation - **Stats:** 2 total users, 1 monthly users, 80.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $4.00 / 1,000 comments 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 Post Comments Scraper Extract **every comment** from any Reddit post — the full nested reply tree, with author, score, depth, timestamps, and **built-in sentiment analysis** — as JSON, CSV, or Excel. Paste one or many post URLs. Comments come back flattened with `depth` and `parentId` so you can rebuild the tree or analyze it flat. **Pay per result** — you're charged per comment delivered. Failed or unreachable posts cost nothing. --- ### What can I use it for? - **Brand & product sentiment** — every comment is scored positive/negative/neutral out of the box; aggregate the mood of a thread in one pass. - **Market & customer research** — mine discussion threads for pain points, feature requests, and objections in your niche. - **AI training & RAG** — clean, structured comment text with threading intact. - **Community & moderation analytics** — who's active, what scores well, how deep conversations go. - **Trend monitoring** — track how a topic is discussed across many posts. --- ### Input | Field | Required | Description | |-------|----------|-------------| | **Post URLs** | ✅ | Reddit post links — full `www`/`old`/`np` URLs or `redd.it` short links. Each comment found is one result. | | **Comment sort** | – | `best` (default), `top`, `new`, `controversial`, `old`, `qa`. Matters when a post has more comments than the limit. | | **Max reply depth** | – | How deep into reply threads to go (0 = top-level only; default 10). | | **Max comments per post** | – | Upper bound per post (1–500; default 500). | | **Proxy configuration** | – | **Automatic by default:** datacenter proxy first, auto-escalating to RESIDENTIAL when Reddit blocks it. | ### Output One record per comment: ```json { "postUrl": "https://www.reddit.com/r/programming/comments/1uo1w91/...", "postId": "1uo1w91", "postTitle": "What ORMs have taught me: just learn SQL", "subreddit": "programming", "commentId": "abc123", "parentId": null, "depth": 0, "author": "some_user", "body": "Honestly this matches my experience...", "score": 148, "createdAt": "2026-06-30T14:22:01Z", "permalink": "https://www.reddit.com/r/programming/comments/1uo1w91/.../abc123/", "sentiment": "positive", "sentimentScore": 0.6597, "isTopLevel": true } ```` | Field | Description | |-------|-------------| | `depth` / `parentId` / `isTopLevel` | Reconstruct the thread tree, or analyze flat | | `sentiment` / `sentimentScore` | VADER sentiment (tuned for social text): label + compound score (−1…+1) | | `score` | Comment's net upvotes | | `author` / `createdAt` / `permalink` | Who, when, and a direct link | *** ### Why this scraper is reliable - **Beats Reddit's 2026 anti-bot walls** — Reddit now hard-blocks plain HTTP clients (even through residential proxies). This actor uses a real stealth browser session to reach the structured comment data, so you get clean JSON, not brittle HTML scraping. - **Automatic proxy escalation** — starts on a cheap datacenter proxy and escalates to residential only when Reddit blocks it, so you get reliability without paying residential rates for every request. - **Sentiment included** — no separate NLP step; every comment ships with a label and score. - **Honest run statuses** — deleted/removed comments are skipped; unreachable posts are reported per post in the `SUMMARY` and never charged; a run with zero comments is marked **Failed**, never a silent empty dataset. - **No silent truncation** — Reddit collapses the tail of huge threads into "load more" stubs. If a thread has more comments than were retrieved, the run says so and the `SUMMARY.posts` array reports `commentsAvailable` vs `commentsScraped` per post. You always know whether you got the whole thread. - **Batch-safe** — comments are saved incrementally and runs are checkpointed: an interruption never loses finished posts or double-charges. ### Tips & limits - **Big threads:** Reddit returns at most ~500 comments per request, and the tail of a large discussion collapses into "load more" stubs. Set **Max comments per post** to 500 to get as much as Reddit will serve; the run and `SUMMARY.posts` tell you exactly how many of the thread's comments you received (`commentsScraped` vs `commentsAvailable`). - Deleted and removed comments are omitted (no body worth storing). - For private, quarantined, or removed posts, the post is reported as failed in the `SUMMARY` — you're not charged for it. ### FAQ **Does it get comments from a whole subreddit?** This actor takes post URLs. Pair it with a subreddit/post-listing scraper and feed the post URLs in — each comment is one result. **What sentiment engine is used?** VADER — a lexicon tuned for social-media text (handles emphasis, negation, emoji, slang). `sentimentScore` is the compound score from −1 (most negative) to +1 (most positive). **Why did a post fail?** Check the run's `SUMMARY` — each failed post is listed with a reason (not found, private, removed). Failed posts are never charged. **Is scraping Reddit legal?** This actor accesses only publicly visible posts and comments. You are responsible for complying with applicable laws and Reddit's User Agreement. Don't scrape private or personal data. *** ### Disclaimer **This is an unofficial tool. It is not affiliated with, endorsed by, sponsored by, or in any way officially connected to Reddit, Inc.** "Reddit" and related names, marks, and logos are trademarks of their respective owners and are used here for descriptive purposes only. This actor accesses only **publicly available** information. You are responsible for ensuring your use complies with applicable laws, Reddit's User Agreement and API terms, and applicable rate-limiting rules. Use it ethically and at your own risk. # Actor input Schema ## `postUrls` (type: `array`): Reddit post links: full www/old/np URLs or redd.it short links. Each comment found becomes one result. ## `sort` (type: `string`): Which comments Reddit surfaces first (matters when a post has more comments than the per-post limit). ## `maxDepth` (type: `integer`): How deep into reply threads to go (0 = top-level comments only). ## `maxComments` (type: `integer`): Upper bound on comments loaded per post (1-500, Reddit's per-request ceiling). ## `proxyConfiguration` (type: `object`): Default (recommended): automatic tiering - cheap datacenter proxy first, auto-escalating to RESIDENTIAL only if Reddit blocks it. ## Actor input object example ```json { "postUrls": [ "https://www.reddit.com/r/programming/comments/1uo1w91/what_orms_have_taught_me_just_learn_sql/" ], "sort": "best", "maxDepth": 10, "maxComments": 500, "proxyConfiguration": { "useApifyProxy": true } } ``` # Actor output Schema ## `runSummary` (type: `string`): Requested/scraped/failed counts and per-video failure reasons. ## `comments` (type: `string`): One record per video: full plain-text transcript, timed segments, language info, and video metadata. # 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 = { "postUrls": [ "https://www.reddit.com/r/programming/comments/1uo1w91/what_orms_have_taught_me_just_learn_sql/" ], "proxyConfiguration": { "useApifyProxy": true } }; // Run the Actor and wait for it to finish const run = await client.actor("electrabot.info/reddit-post-comments").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 = { "postUrls": ["https://www.reddit.com/r/programming/comments/1uo1w91/what_orms_have_taught_me_just_learn_sql/"], "proxyConfiguration": { "useApifyProxy": True }, } # Run the Actor and wait for it to finish run = client.actor("electrabot.info/reddit-post-comments").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 '{ "postUrls": [ "https://www.reddit.com/r/programming/comments/1uo1w91/what_orms_have_taught_me_just_learn_sql/" ], "proxyConfiguration": { "useApifyProxy": true } }' | apify call electrabot.info/reddit-post-comments --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=electrabot.info/reddit-post-comments", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Reddit Post Comments Scraper", "description": "Scrapes full comment trees from Reddit posts — user handles, upvotes, nested replies, and per-comment sentiment.", "version": "2.0", "x-build-id": "D1ncyW1RHDRaPZ6Ft" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/electrabot.info~reddit-post-comments/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-electrabot.info-reddit-post-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/electrabot.info~reddit-post-comments/runs": { "post": { "operationId": "runs-sync-electrabot.info-reddit-post-comments", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/electrabot.info~reddit-post-comments/run-sync": { "post": { "operationId": "run-sync-electrabot.info-reddit-post-comments", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "required": [ "postUrls" ], "properties": { "postUrls": { "title": "Post URLs", "type": "array", "description": "Reddit post links: full www/old/np URLs or redd.it short links. Each comment found becomes one result.", "items": { "type": "string" } }, "sort": { "title": "Comment sort", "enum": [ "best", "top", "new", "controversial", "old", "qa" ], "type": "string", "description": "Which comments Reddit surfaces first (matters when a post has more comments than the per-post limit).", "default": "best" }, "maxDepth": { "title": "Max reply depth", "minimum": 0, "maximum": 50, "type": "integer", "description": "How deep into reply threads to go (0 = top-level comments only).", "default": 10 }, "maxComments": { "title": "Max comments per post", "minimum": 1, "maximum": 500, "type": "integer", "description": "Upper bound on comments loaded per post (1-500, Reddit's per-request ceiling).", "default": 500 }, "proxyConfiguration": { "title": "Proxy configuration", "type": "object", "description": "Default (recommended): automatic tiering - cheap datacenter proxy first, auto-escalating to RESIDENTIAL only if Reddit blocks it.", "default": { "useApifyProxy": 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 } } } } } } } } } } ```