# Reddit Post Comments (`datamagnet/reddit-comments-fetcher`) Actor Fetch and organize comments from any Reddit post into a clean, easy-to-read list. Choose the comment order and return the main comment details in a simple table-like format. - **URL**: https://apify.com/datamagnet/reddit-comments-fetcher.md - **Developed by:** [Datamagnet](https://apify.com/datamagnet) (community) - **Categories:** Social media - **Stats:** 2 total users, 1 monthly users, 60.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $5.00 / 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 Comments Fetcher Get the comments from any Reddit post in a clean, easy-to-read list. ### What it does - Pulls the comments from the Reddit post you provide. - Lets you choose how the comments are ordered, so you can see the newest, top, or most relevant ones first. - Shows the main comment details in a simple table-like format. - Can return just a few comments or more, depending on what you need. - Keeps the output tidy and easy to scan. ### Use cases - Check how people are reacting to a news story, product launch, or announcement in the comments. - Review the top replies on a discussion thread to quickly understand the main opinions. - Collect comment text, scores, and reply structure for research, moderation, or content analysis. ### Input | Field | Description | Required | Example | |---|---|---:|---| | Reddit post URL | The full URL of the Reddit post you want comments from. | Yes | https://www.reddit.com/r/AskReddit/comments/ablzuq/people_who_have_been_to_prison_what_is_it_really/ | | Sort order | Choose how the comments should be ordered. | Yes | new | | Max results | Maximum number of comments to fetch. | No | 10 | ### Output | Field | Description | |---|---| | all_awardings | Any awards attached to the comment. | | approved_at_utc | When the comment was approved, in UTC, if available. | | approved_by | The moderator or user who approved the comment, if available. | | archived | Whether the comment is archived and no longer editable. | | associated_award | The award linked to the comment, if any. | | author | The username of the commenter. | | author_flair_background_color | The background color of the author's flair, if set. | | author_flair_css_class | The flair CSS class, if set. | | author_flair_richtext | Rich text flair details for the author, if available. | | author_flair_template_id | The flair template ID, if available. | | author_flair_text | The text shown in the author's flair, if any. | | author_flair_text_color | The text color used for the author's flair. | | author_flair_type | The type of flair shown on the author profile. | | author_fullname | The internal Reddit user ID for the author, if available. | | author_is_blocked | Whether the author is blocked. | | author_patreon_flair | Whether the author has a special supporter flair. | | author_premium | Whether the author has premium status. | | awarders | Users who gave awards to the comment. | | banned_at_utc | When the comment was banned, in UTC, if available. | | banned_by | The moderator or user who banned the comment, if available. | | body | The full text of the comment. | | body_html | The HTML version of the comment text. | | can_gild | Whether the comment can receive gilding. | | can_mod_post | Whether moderators can act on the comment. | | collapsed | Whether the comment is collapsed. | | collapsed_because_crowd_control | Whether crowd control caused the collapse. | | collapsed_reason | The reason the comment is collapsed, if available. | | collapsed_reason_code | A short code for why the comment is collapsed, if available. | | comment_type | The type of comment, if available. | | controversiality | A score showing how controversial the comment is. | | created | The comment creation time as a Unix timestamp. | | created_utc | The comment creation time in UTC as a Unix timestamp. | | depth | How deep the comment is in the thread. | | distinguished | Whether the comment is distinguished, such as by a moderator. | | downs | The number of downvotes recorded for the comment. | | edited | Whether the comment was edited after posting. | | gilded | How many times the comment was gilded. | | gildings | Details about any gildings on the comment. | | id | The unique ID of the comment. | | is_submitter | Whether the commenter is also the original post author. | | likes | The user's like status for the comment, if available. | | link_id | The ID of the Reddit post the comment belongs to. | | locked | Whether the comment thread is locked. | | mod_note | Any moderator note attached to the comment. | | mod_reason_by | Who set the moderation reason, if available. | | mod_reason_title | The title of the moderation reason, if available. | | mod_reports | Any moderator reports on the comment. | | name | The full Reddit name for the comment. | | no_follow | Whether replies are disabled for the comment. | | num_reports | The number of reports on the comment, if available. | | parent_id | The ID of the parent comment or post. | | permalink | The direct link to the comment. | | removal_reason | The reason the comment was removed, if available. | | report_reasons | The reasons the comment was reported, if available. | | saved | Whether the comment was saved by the user. | | score | The comment score. | | score_hidden | Whether the score is hidden. | | send_replies | Whether replies are enabled for the comment. | | stickied | Whether the comment is pinned to the thread. | | subreddit | The subreddit where the comment was posted. | | subreddit_id | The internal ID of the subreddit. | | subreddit_name_prefixed | The subreddit name with the r/ prefix. | | subreddit_type | The type of subreddit, such as public. | | top_awarded_type | The type of top award, if any. | | total_awards_received | The total number of awards received. | | treatment_tags | Any moderation treatment tags on the comment. | | unrepliable_reason | The reason the comment cannot be replied to, if available. | | ups | The number of upvotes recorded for the comment. | | user_reports | Any user reports on the comment. | ### Sample output ```json { "all_awardings": [], "approved_at_utc": null, "approved_by": null, "archived": true, "associated_award": null, "author": "HACKERB22015", "author_flair_background_color": null, "author_flair_css_class": null, "author_flair_richtext": [], "author_flair_template_id": null, "author_flair_text": null, "author_flair_text_color": null, "author_flair_type": "text", "author_fullname": "t2_7wta0av2", "author_is_blocked": false, "author_patreon_flair": false, "author_premium": false, "awarders": [], "banned_at_utc": null, "banned_by": null, "body": "WHAT I CAN COMMENT- WHAT THE FUUUUUUUUUUUUUUUUUUUUUUU", "body_html": "<div class=\"md\"><p>WHAT I CAN COMMENT- WHAT THE FUUUUUUUUUUUUUUUUUUUUUUU</p>\n</div>", "can_gild": false, "can_mod_post": false, "collapsed": false, "collapsed_because_crowd_control": null, "collapsed_reason": null, "collapsed_reason_code": null, "comment_type": null, "controversiality": 0, "created": 1634330161, "created_utc": 1634330161, "depth": 0, "distinguished": null, "downs": 0, "edited": false, "gilded": 0, "gildings": {}, "id": "hgs7jk8", "is_submitter": false, "likes": null, "link_id": "t3_ablzuq", "locked": false, "mod_note": null, "mod_reason_by": null, "mod_reason_title": null, "mod_reports": [], "name": "t1_hgs7jk8", "no_follow": false, "num_reports": null, "parent_id": "t3_ablzuq", "permalink": "/r/AskReddit/comments/ablzuq/people_who_havent_pooped_in_2019_yet_why_are_you/hgs7jk8/", "removal_reason": null, "report_reasons": null, "saved": false, "score": 4, "score_hidden": false, "send_replies": true, "stickied": false, "subreddit": "AskReddit", "subreddit_id": "t5_2qh1i", "subreddit_name_prefixed": "r/AskReddit", "subreddit_type": "public", "top_awarded_type": null, "total_awards_received": 0, "treatment_tags": [], "unrepliable_reason": null, "ups": 4, "user_reports": [] } ```` # Actor input Schema ## `sort` (type: `string`): How the comments should be ordered. ## `post_url` (type: `string`): The full URL of the Reddit post you want comments from. ## `max_results` (type: `integer`): Maximum number of comments to fetch. ## Actor input object example ```json { "sort": "new", "post_url": "https://www.reddit.com/r/AskReddit/comments/ablzuq/people_who_have_been_to_prison_what_is_it_really/", "max_results": 10 } ``` # 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 = { "sort": "new", "post_url": "https://www.reddit.com/r/AskReddit/comments/ablzuq/people_who_have_been_to_prison_what_is_it_really/" }; // Run the Actor and wait for it to finish const run = await client.actor("datamagnet/reddit-comments-fetcher").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 = { "sort": "new", "post_url": "https://www.reddit.com/r/AskReddit/comments/ablzuq/people_who_have_been_to_prison_what_is_it_really/", } # Run the Actor and wait for it to finish run = client.actor("datamagnet/reddit-comments-fetcher").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 '{ "sort": "new", "post_url": "https://www.reddit.com/r/AskReddit/comments/ablzuq/people_who_have_been_to_prison_what_is_it_really/" }' | apify call datamagnet/reddit-comments-fetcher --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=datamagnet/reddit-comments-fetcher", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Reddit Post Comments", "description": "Fetch and organize comments from any Reddit post into a clean, easy-to-read list. Choose the comment order and return the main comment details in a simple table-like format.", "version": "0.0", "x-build-id": "s9LmCqQdyrIngIZls" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/datamagnet~reddit-comments-fetcher/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-datamagnet-reddit-comments-fetcher", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/datamagnet~reddit-comments-fetcher/runs": { "post": { "operationId": "runs-sync-datamagnet-reddit-comments-fetcher", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/datamagnet~reddit-comments-fetcher/run-sync": { "post": { "operationId": "run-sync-datamagnet-reddit-comments-fetcher", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "post_url", "sort" ], "properties": { "sort": { "title": "Sort order", "enum": [ "confidence", "top", "new", "controversial", "old", "qa" ], "type": "string", "description": "How the comments should be ordered." }, "post_url": { "title": "Reddit post URL", "type": "string", "description": "The full URL of the Reddit post you want comments from." }, "max_results": { "title": "Max results", "type": "integer", "description": "Maximum number of comments to fetch.", "default": 10 } } }, "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 } } } } } } } } } } ```