# Reddit Comments Scraper (`solid-scraper/reddit-comments-scraper`) Actor 🔎 Extract valuable Reddit comments with this Comments Scraper—fast, accurate, and built for research, sentiment, and community insights. 📊✨ Perfect for marketers, analysts, and data teams wanting actionable results. - **URL**: https://apify.com/solid-scraper/reddit-comments-scraper.md - **Developed by:** [SolidScraper](https://apify.com/solid-scraper) (community) - **Categories:** Social media, Developer tools, Other - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $2.99 / 1,000 results This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage. 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 Scraper 📣 **Reddit Comments Scraper** automatically collects comments (including nested replies, when enabled) from one or more Reddit posts and returns a flat record per comment, complete with path and depth metadata. If you’re looking to **scrape reddit comments**, extract reddit thread comments for analysis, or build a bulk reddit comment scraper workflow, this tool helps you get structured comment data at scale—without manually copying threads one by one. Whether you’re a marketer, data analyst, researcher, or developer, you can use this reddit comments extraction actor to speed up collection and save you hours of manual work. --- ### Why choose Reddit Comments Scraper? | Feature | Benefit | | --- | --- | | ✅ **Comments + Nested Replies Collection** | Extracts top-level comments and (optionally) the full reply tree for each post | | ✅ **All-in-One Batch Input** | Lets you scrape comments from multiple post URLs in a single run | | ✅ **Reliable Scraping with Fallback Logic** | Includes retries and handles access challenges using a real browser session | | ✅ **Proxy Support for Stability** | Supports configurable proxy settings to improve scraping reliability | | ✅ **Structured Flat Output** | Returns one JSON record per comment with path/depth metadata for easy downstream processing | | ✅ **Scales with Concurrency Controls** | Uses configurable parallelism via maximum concurrent posts to fit your throughput needs | --- ### Key features - 📊 **Flat comment data with tree metadata**: Produces one record per comment with `commentPath` and `commentDepth` so you can analyze conversation structure. - 💬 **Optional nested reply extraction**: When enabled, replies to comments are also collected (full thread tree); when disabled, only top-level comments are returned. - 🔍 **Sort-controlled comment ordering**: Supports `top`, `best`, `new`, `controversial`, `old`, and `qa` sorting to match your research needs. - 🧠 **Top-level vs reply awareness**: Adds `isTopLevel` and `parentPath` so you can distinguish roots from replies in your analysis. - 🛡️ **Resilient runs with retries**: Uses multiple attempts per post to reduce the chance of partial failures. - 🌐 **Post URL support**: Accepts one or more Reddit post URLs and normalizes them for collection. - 💾 **Dataset-ready results**: Pushes extracted comment records to the Apify dataset as JSON (one item list per successful post). - ⚙️ **Concurrency controls**: Uses `maxConcurrentPosts` so you can balance speed against memory usage. --- ### Input Provide input via an `input.json` file. Example structure: ```json { "postUrls": [ "https://www.reddit.com/r/AskMec/comments/14990m6/les_applications_de_rencontres_fonctionnent_telles/" ], "maxComments": 500, "includeNestedReplies": true, "sortBy": "top", "maxConcurrentPosts": 2, "proxyConfiguration": { "useApifyProxy": false } } ```` #### Input Fields | Field | Required | Description | | --- | --- | --- | | `postUrls` | Yes | One or more Reddit post URLs to scrape comments from. | | `maxComments` | No | Maximum number of comments to extract per post (counts nested replies too). Default is `500`. Must be at least `1`. | | `includeNestedReplies` | No | When enabled, replies to comments are also extracted (the full thread tree). When disabled, only top-level comments are returned. Default is `true`. | | `sortBy` | No | How Reddit should order the comments before they are collected. Options: `top`, `best`, `new`, `controversial`, `old`, `qa`. Default is `top`. | | `maxConcurrentPosts` | No | How many posts to scrape in parallel. Each post runs its own browser, so higher values need more memory. Default is `2` (min `1`, max `10`). | | `proxyConfiguration` | No | Proxy settings for the scraper. If provided, the actor uses your configuration; otherwise it creates a default proxy configuration with residential groups. | *** ### Output The actor saves extracted comments in JSON format by pushing a list of comment records to the Apify dataset (`charged_event_name="result"`) for each successfully processed post. Example output record: ```json [ { "postUrl": "https://www.reddit.com/r/.../comments/.../", "postTitle": "Example post title", "postAuthor": "example_author", "postScore": 12345, "subreddit": "examplesubreddit", "commentDepth": 0, "commentAuthor": "comment_author", "commentText": "This is a comment body.", "commentTimestamp": "2024-01-15T10:22:33.000Z", "commentPath": "0", "parentPath": null, "isTopLevel": true, "replyCount": 2, "scrapedAt": "2024-01-15T10:30:00.000Z" } ] ``` #### Output Fields | Field | Type | Description | | --- | --- | --- | | `postUrl` | string | The normalized Reddit post URL for which the comment was scraped. | | `postTitle` | string | The post title. | | `postAuthor` | string | The post author username. | | `postScore` | number | The post score at the time of collection. | | `subreddit` | string | The subreddit name. | | `commentDepth` | number | Depth of the comment in the thread tree (top-level is `0`). | | `commentAuthor` | string | The comment author username. | | `commentText` | string | The comment body text. | | `commentTimestamp` | string | UTC timestamp (ISO-8601 with milliseconds and trailing `Z`) for when the comment was created. | | `commentPath` | string | Encoded position of the comment within the tree (e.g., `"0"`, `"0/1"`, `"0/1/0"`). | | `parentPath` | string | null | The parent comment’s `commentPath` (or `null` for top-level comments). | | `isTopLevel` | boolean | `true` when `commentDepth` is `0`; otherwise `false`. | | `replyCount` | number | Count of direct replies to this comment. | | `scrapedAt` | string | UTC timestamp (ISO-8601 with milliseconds and trailing `Z`) indicating when the scraping happened. | | `error_message` | string | Not provided in the dataset schema emitted by this actor. Failures are logged and posts that succeed will push records. | You can export the resulting dataset from Apify as JSON or CSV (depending on your chosen export settings in the Apify UI). *** ### How to use Reddit Comments Scraper (via Apify Console) 1. **Open Apify Console**: Go to [console.apify.com](https://console.apify.com) and log in. 2. **Find the actor**: Search for **Reddit Comments Scraper** in the Actors marketplace and open the actor page. 3. **Open the INPUT panel**: In the actor run screen, locate the **INPUT** section. 4. **Add your post URLs**: Paste one or more Reddit post URLs into `postUrls`. 5. **Choose your comment limits and structure**:\ Set `maxComments` (per post), enable/disable `includeNestedReplies`, and pick `sortBy` if you need a specific ordering. 6. **Set concurrency for your budget**: Adjust `maxConcurrentPosts` (each parallel post uses its own browser, so higher values use more memory). 7. **Configure proxy (optional)**: If you have `proxyConfiguration`, add it; otherwise the actor creates a default residential proxy configuration. 8. **Run & monitor**: Click **Run**. Watch logs for progress, extraction counts, and any retry attempts. 9. **Open the OUTPUT dataset**: After completion, go to the dataset tab to preview the extracted reddit comments data and export it to JSON/CSV. No coding required—get reddit comments extraction results in minutes. *** ### Advanced features & SEO optimization - 🔁 **Engineered for “Reddit Comments Scraper” workflows**: The actor is designed for reddit comments to csv scraper style pipelines where you need a clean, flat structure for analysis and BI. - 🧩 **Thread-aware output for conversation mining**: Each comment includes `commentPath`, `parentPath`, `commentDepth`, `replyCount`, and `isTopLevel`, making reddit comments mining and scrape reddit thread comments workflows much easier. - 🕒 **Consistent UTC timestamps**: Uses ISO-8601 `scrapedAt` and `commentTimestamp` values for reliable time-based analysis. - 🧰 **Input-friendly sorting**: With `sortBy`, you can align collection with your research question (for example, focusing on most upvoted or most recent discussions). - 🔍 **Resilience for public web data**: Includes retries and supports configurable proxy settings for stable scraping of publicly available data. *** ### Best use cases - 📈 **Marketing teams**: Collect reddit comments data from multiple posts to find recurring themes and messaging angles for outreach campaigns. - 🧠 **Researchers**: Gather structured reddit comments extraction for qualitative coding and quantifying sentiment or discussion depth. - 💬 **Community managers**: Monitor how conversations evolve by scraping threads with `sortBy` and analyzing commentDepth distributions. - 🏗️ **Data analysts**: Build a conversation graph using `commentPath`, `parentPath`, and `replyCount` from a bulk reddit comment scraper run. - 🧪 **Product teams**: Compare feedback across communities by scraping reddit comments from posts in relevant subreddits and exporting to CSV. - 💻 **Developer pipelines**: Feed structured results into downstream systems (ETL, dashboards, or CRM enrichment steps) with predictable fields per comment. - 🎯 **Content strategists**: Scrape comments from posts to identify what users actually respond to—then iterate your content based on real discussion threads. *** ### Technical specifications - **Supported Input Formats** - ✅ `postUrls`: array of Reddit post URLs - ✅ `maxComments`: integer (default `500`, minimum `1`) - ✅ `includeNestedReplies`: boolean (default `true`) - ✅ `sortBy`: string enum (`top`, `best`, `new`, `controversial`, `old`, `qa`) - ✅ `maxConcurrentPosts`: integer (default `2`, range `1` to `10`) - ✅ Optional `proxyConfiguration` - **Proxy Support** - ✅ Configurable proxy support via `proxyConfiguration` - ✅ Default residential proxy configuration when `proxyConfiguration` is not provided - **Retry Mechanism** - ✅ Retries are built in for each post (multiple attempts per post) - **Dataset Structure** - ✅ JSON records pushed to the dataset with one flat record per comment - ✅ Includes `commentPath`/`parentPath`/`commentDepth` for thread reconstruction - **Rate Limits & Performance** - ✅ Designed for batch processing with configurable concurrency using `maxConcurrentPosts` - ⚠️ Each concurrent post uses its own browser session, so higher concurrency can increase memory usage - **Limitations** - ❌ Mod/bot-pinned comments are skipped (`stickied` items are not included) - ❌ Only publicly accessible comment data from the provided posts is collected *** ### FAQ #### What does Reddit Comments Scraper return? ✅ It returns a flat list of JSON records—one record per comment—with thread metadata like `commentPath`, `parentPath`, and `commentDepth`, plus comment content (`commentText`) and timestamps (`commentTimestamp`). #### Can it scrape nested replies? ✅ Yes. With `includeNestedReplies` enabled, replies to comments are also extracted so you get the full thread tree. If you disable it, only top-level comments are returned. #### How many comments can I extract from each post? You control it with `maxComments`. It sets the maximum number of comments extracted per post and counts nested replies too. #### Can I control the order of comments? ✅ Yes. Use `sortBy` to choose how comments are ordered before they are collected: `top`, `best`, `new`, `controversial`, `old`, or `qa`. #### Does it support scraping multiple Reddit posts at once? ✅ Yes. Provide multiple links in `postUrls`. You can also control parallelism with `maxConcurrentPosts` to balance speed and resource usage. #### Is there a dataset export format other than JSON? Apify datasets can be exported after the run. The actor pushes JSON-formatted records to the dataset, and you can export to CSV from the Apify UI depending on your settings. #### Do I need to use a proxy? ❌ You don’t have to, but you can. If you provide `proxyConfiguration`, the actor will use it; otherwise it creates a default residential proxy configuration to improve scraping reliability. #### Is this compliant with privacy rules? ✅ The actor only collects data from publicly accessible sources. You’re responsible for using the results in accordance with applicable laws (including privacy and platform rules) for your specific use case. *** ### Support & feature requests If you’re using Reddit Comments Scraper for reddit comments web scraper or reddit comments data extraction workflows, we’d love to hear how it’s working for you. - 💡 **Feature Requests**: Examples include additional export controls, adding more post-level metadata fields, or enhancements tailored for bulk reddit comments mining pipelines. - 📧 **Contact**: For questions, support, or feedback, reach out at . Your feedback helps shape the roadmap for this reddit comment scraper tool. *** *Use the Reddit Comments Scraper to collect reddit comments extraction results with structured, thread-aware output—so you can scale analysis without the manual grind.* *** ### Disclaimer **This tool only accesses publicly accessible sources.** It does not access private profiles, authenticated data, or password-protected content. You are responsible for ensuring your use complies with applicable laws (for example, GDPR/CCPA), spam regulations, and the relevant platform terms of service. For data removal requests, contact . Always use Reddit Comments Scraper responsibly, ethically, and for legitimate purposes. # Actor input Schema ## `postUrls` (type: `array`): One or more Reddit post URLs to scrape comments from. ## `maxComments` (type: `integer`): Maximum number of comments to extract per post (counts nested replies too). ## `includeNestedReplies` (type: `boolean`): When enabled, replies to comments are also extracted (the full thread tree). When disabled, only top-level comments are returned. ## `sortBy` (type: `string`): How Reddit should order the comments before they are collected. ## `maxConcurrentPosts` (type: `integer`): How many posts to scrape in parallel. Each post runs its own browser, so higher values need more memory. ## Actor input object example ```json { "postUrls": [ { "url": "https://www.reddit.com/r/AskMec/comments/14990m6/les_applications_de_rencontres_fonctionnent_telles/" } ], "maxComments": 500, "includeNestedReplies": true, "sortBy": "top", "maxConcurrentPosts": 2 } ``` # 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": [ { "url": "https://www.reddit.com/r/AskMec/comments/14990m6/les_applications_de_rencontres_fonctionnent_telles/" } ] }; // Run the Actor and wait for it to finish const run = await client.actor("solid-scraper/reddit-comments-scraper").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": [{ "url": "https://www.reddit.com/r/AskMec/comments/14990m6/les_applications_de_rencontres_fonctionnent_telles/" }] } # Run the Actor and wait for it to finish run = client.actor("solid-scraper/reddit-comments-scraper").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": [ { "url": "https://www.reddit.com/r/AskMec/comments/14990m6/les_applications_de_rencontres_fonctionnent_telles/" } ] }' | apify call solid-scraper/reddit-comments-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=solid-scraper/reddit-comments-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Reddit Comments Scraper", "description": "🔎 Extract valuable Reddit comments with this Comments Scraper—fast, accurate, and built for research, sentiment, and community insights. 📊✨ Perfect for marketers, analysts, and data teams wanting actionable results.", "version": "0.2", "x-build-id": "VoaQJAsiNEvE7FjzE" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/solid-scraper~reddit-comments-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-solid-scraper-reddit-comments-scraper", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/solid-scraper~reddit-comments-scraper/runs": { "post": { "operationId": "runs-sync-solid-scraper-reddit-comments-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/solid-scraper~reddit-comments-scraper/run-sync": { "post": { "operationId": "run-sync-solid-scraper-reddit-comments-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": "Reddit Post URLs", "type": "array", "description": "One or more Reddit post URLs to scrape comments from.", "items": { "type": "object", "required": [ "url" ], "properties": { "url": { "type": "string", "title": "URL of a web page", "format": "uri" } } } }, "maxComments": { "title": "Maximum Comments", "minimum": 1, "type": "integer", "description": "Maximum number of comments to extract per post (counts nested replies too).", "default": 500 }, "includeNestedReplies": { "title": "Include Nested Replies", "type": "boolean", "description": "When enabled, replies to comments are also extracted (the full thread tree). When disabled, only top-level comments are returned.", "default": true }, "sortBy": { "title": "Sort Comments By", "enum": [ "top", "best", "new", "controversial", "old", "qa" ], "type": "string", "description": "How Reddit should order the comments before they are collected.", "default": "top" }, "maxConcurrentPosts": { "title": "Maximum Concurrent Posts", "minimum": 1, "maximum": 10, "type": "integer", "description": "How many posts to scrape in parallel. Each post runs its own browser, so higher values need more memory.", "default": 2 } } }, "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 } } } } } } } } } } ```