# Reddit Scraper (`epctex/reddit-scraper`) Actor
Tap into the wealth of Reddit's data with our Reddit Scraper. Extract valuable insights from posts, subreddits, comments, and user data effortlessly. Simplify analysis and gain valuable insights from the diverse Reddit community with our user-friendly and efficient tool.
- **URL**: https://apify.com/epctex/reddit-scraper.md
- **Developed by:** [epctex](https://apify.com/epctex) (community)
- **Categories:** Social media, News
- **Features:** Limited permissions
- **Stats:** 2,070 total users, 83 monthly users, 99.9% runs succeeded, 47 bookmarks
- **User rating**: 5.00 out of 5 stars
## Pricing
from $1.00 / 1,000 dataset items
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/actors/running/actors-in-store.md#pay-per-event
## What's an Apify Actor?
An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
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.
Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.
## 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.
Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.
For examples already wired to this Actor's own input schema, see the [API](#api) section below.
Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).
# README
## Reddit Scraper
Reddit Scraper is a commercial-grade Reddit API built for teams that require dependable, structured Reddit data without maintaining scraping infrastructure in-house. The actor allows you to scrape Reddit posts, Reddit comments, subreddits, Reddit users, and Reddit communities within a single job — either by running a Reddit search against any keyword, or by supplying the Reddit URLs your workflow already depends on.
This Reddit scraping solution is designed around two operating modes that can be executed independently or in combination. Keyword mode performs a Reddit search across posts, communities, or people. URL mode performs direct Reddit data extraction from landing feeds, subreddit pages, individual post pages, user profiles, and community pages. Because both modes accept input in the same run, a single execution can cover exploratory keyword research and targeted URL collection simultaneously.
### Reddit Scraper Capabilities
The Reddit API supports the following features:
- **Search by keyword** — Search Reddit for posts, communities, or people.
- **Scrape by URL** — Provide direct links to landing feeds, subreddits, posts, user profiles, or communities.
- **Combine search and URLs** — Run keyword search and direct URL scraping together in a single job.
- **Include comments** — Pull full nested comment threads under any scraped post.
- **Sort and filter results** — Sort by relevance, hot, top, new, or comments, and filter by time range.
### Supported Reddit Data Sources
| Reddit Source | How to Target It | What It Covers |
|---|---|---|
| Reddit posts | search with `searchMode: link`, or direct post URLs in `startUrls` | Individual Reddit posts returned by keyword search or direct link |
| Subreddits | Subreddit URLs in `startUrls`, or `/r/{subreddit}/about` | Subreddit post listings and subreddit information pages |
| Reddit communities | search with `searchMode: sr` | Community results matching your keyword |
| Reddit users | search with `searchMode: user`, or user profile URLs in `startUrls` | People search results and user profile content |
| Reddit comments | `includeComments: true` | Full nested comment threads attached to each scraped post |
| Landing feeds | Feed URLs in `startUrls` | Reddit landing feed listings |
### Who Can Use This Reddit Scraper
The Reddit Scraper is applicable wherever public Reddit discussion carries commercial or analytical value. Typical adopters include:
**Market research and consumer insight teams.** Run keyword-driven Reddit search across relevant time ranges to observe how a category, product, or need state is discussed in the user's own language, rather than through survey instruments.
**Brand monitoring and communications functions.** Track brand, competitor, and executive mentions across Reddit posts and comment threads, using the time filter to isolate a specific day, week, or month around a campaign or incident.
**Product and UX organizations.** Scrape subreddits where your product category is discussed and pull nested comment threads to surface recurring complaints, feature requests, and workaround behavior.
**Academic and social science researchers.** Collect reproducible Reddit datasets defined by subreddit, keyword, sort order, and time window, with explicit item caps for controlled sample sizes.
**AI and machine learning teams.** Assemble conversational corpora from Reddit posts and threaded comments for model training, evaluation, retrieval augmentation, and benchmarking.
**SEO and content strategy teams.** Identify the questions, terminology, and long-tail phrasing real users apply to a topic, and locate the communities where a topic holds sustained attention.
**Investment research and financial analysis.** Monitor sentiment-bearing discussion in finance-oriented subreddits with `sort: new` for time-sensitive coverage or `sort: top` for consensus positions.
**Community and moderation teams.** Retrieve subreddit information and post listings for reporting on community activity and growth.
**Recruitment and talent research.** Use `searchMode: user` to locate people discussing specific technologies, domains, or professional topics.
**Journalists and OSINT analysts.** Combine direct URL collection with keyword search to document how a story propagated across Reddit communities.
### Pricing: Transparent Event-Based Costs
Pay only for what you scrape. No subscriptions, no hidden fees.
| Event Type | Price | What's Included |
|---|---|---|
| List Query | $0.025 per search/list | One landing feed, subreddit, user posts list, or search |
| Comments Query | $0.1 per post/user thread | Full comment thread for one post or user, replies included, flat price regardless of size |
| Detail Query | $0.003 per item | Each direct post URL or `/r/{subreddit}/about` |
| Dataset Items | $0.001 per item stored | First page (up to ~100 items) of each query included FREE on paid plans |
#### Cost Examples
| Scenario | Charges | Calculation | Total Cost |
|---|---|---|---|
| 1 search, 20 results | 1 list query | $0.025 × 1 | $0.025 |
| 1 direct post URL | 1 detail query + 1 dataset item | $0.003 + $0.001 | $0.004 |
| 1 direct post URL, with comments | 1 detail query + 1 comments query + 1 dataset item | $0.003 + $0.1 + $0.001 | $0.104 |
| 1 user's comment history | 1 comments query | $0.1 × 1 | $0.100 |
| Community search, 25 results | 1 list query | $0.025 × 1 | $0.025 |
### Controlling Reddit Scraping Costs
The event-based model rewards precise job design. Four principles follow directly from the rate card:
- **Enable comments deliberately.** A comments query is billed at $0.1 per post or user thread, which is the largest single line item in the model. Set `includeComments: false` when post-level data is sufficient.
- **Target high-value threads when comments are needed.** The comments query price is flat regardless of thread size, so a thread with thousands of replies costs the same as one with a handful. Prioritise dense discussions.
- **Stay within the free first page where possible.** On paid plans, the first page of each query — up to roughly 100 items — is included at no dataset-item cost. Jobs scoped to that range avoid per-item storage charges entirely.
- **Use direct URLs when you already have them.** A detail query is $0.003 per item against $0.025 for a list query, so known post URLs and `/r/{subreddit}/about` endpoints are the economical path when discovery is not required.
Use `maxItems` and `endPage` to enforce hard ceilings on any run before scaling it. On the Free plan, `maxItems` is not user-adjustable — every demo run is capped at 10 items regardless of what you set (see [Demo Mode](#demo-mode)). On paid plans, `maxItems` is respected up to your plan's own per-run ceiling, whichever is lower.
### Demo Mode
Free-plan users can try this actor without a subscription. The limit is 5 runs per month and 10 items per run, and this cap overrides any `maxItems` value you provide — the Free plan does not let you scrape past 10 items per run. The API is not available on the Free plan. For unrestricted use, subscribe to a paid plan.
### How to Use the Reddit Scraper
1. **Define your targets.** Supply `startUrls`, `search`, or both. At least one is required.
2. **Select a search mode.** Set `searchMode` to `link` for Reddit posts, `sr` for communities, or `user` for people.
3. **Apply sorting and time filters.** Set `sort` to `relevance`, `hot`, `top`, `new`, or `comments`, and `time` to `all`, `year`, `month`, `week`, `day`, or `hour`.
4. **Decide on comments.** Set `includeComments: true` only if nested comment threads are required, and account for the associated cost.
5. **Set volume limits.** Apply `maxItems` and, where relevant, `endPage`. On the Free plan these are capped regardless of the value you set — see [Demo Mode](#demo-mode).
6. **Run a small test first.** Execute a low-volume run to review the returned structure before committing to a large job.
7. **Scale.** Increase limits once the output matches your requirements.
### Input Parameters
| Field | Type | Description | Default |
|---|---|---|---|
| `startUrls` | array | Reddit URLs to scrape (feeds, subreddits, posts, users, or communities). | `[]` |
| `search` | string | Keyword to search for on Reddit. Used together with `searchMode`, can be combined with `startUrls`. | — |
| `searchMode` | string | What the search returns: `link` (posts), `sr` (communities), or `user` (people). | `link` |
| `sort` | string | Sort order for results: `relevance`, `hot`, `top`, `new`, or `comments`. Not every value applies everywhere. | `relevance` |
| `time` | string | Time range for post search: `all`, `year`, `month`, `week`, `day`, or `hour`. | `all` |
| `includeComments` | boolean | Fetch comments for every scraped post and nest them under it. | `false` |
| `maxItems` | number | Maximum number of items to return. Respected on paid plans up to your plan's own cap; on the Free plan every run is capped at 10 items regardless of this value. | unlimited |
| `endPage` | number | Maximum number of pages to fetch per start URL or search. | unlimited |
| `customMapFunction` | string | Function that takes each object as an argument and returns a mapped object. Must be a single synchronous function; it runs in a sandbox with plain JavaScript only (no network requests, `require` or `console`) and about 1 second per item. An unusable function is ignored and the original items are saved. | `null` |
| `outputConnector` | string | MCP connector to deliver the results to — pick one (see [Send Results to Notion, Todoist and More (MCP Connectors)](#send-results-to-notion-todoist-and-more-mcp-connectors)). | — |
| `deliverTarget` | string | Where the connector writes — paste the URL or ID (Notion example: `https://www.notion.so/My-Posts-24f8a1b2c3d44e5f8a9b0c1d2e3f4a5b`); some services need none. | — |
| `deliverMode` | string | `perPost` (one record per item) or `summary` (one roll-up per run). | `perPost` |
| `deliverMaxItems` | number | Optional cap on how many records `perPost` delivers (ignored in `summary`). | — |
### Input Examples
**Search Reddit communities by keyword**
```json
{
"search": "apify",
"searchMode": "sr",
"maxItems": 20
}
```
**Scrape recent Reddit posts on a topic**
```json
{
"search": "web scraping",
"searchMode": "link",
"sort": "new",
"time": "week",
"maxItems": 100
}
```
**Scrape Reddit posts with full comment threads**
```json
{
"search": "data engineering",
"searchMode": "link",
"sort": "top",
"time": "month",
"includeComments": true,
"maxItems": 50
}
```
**Combine direct Reddit URLs with a keyword search**
```json
{
"startUrls": ["https://www.reddit.com/r/datasets/"],
"search": "open dataset",
"searchMode": "link",
"sort": "relevance",
"endPage": 3
}
```
**Find Reddit users discussing a topic**
```json
{
"search": "machine learning",
"searchMode": "user",
"maxItems": 25
}
```
### Output Examples
Every scraped item is stored as a JSON object. The exact shape depends on what was scraped: posts, comments, communities, or users.
**Post**
```json
{
"type": "post",
"inputSource": "https://www.reddit.com/r/webscraping/",
"id": "t3_1abcdef",
"url": "https://www.reddit.com/r/webscraping/comments/1abcdef/best_practices_for_scraping_reddit_in_2026/",
"title": "Best practices for scraping Reddit in 2026",
"flair": "Discussion",
"flairs": [
{ "type": "text", "text": "Discussion" }
],
"subreddit": "webscraping",
"subredditId": "t5_2r2gk",
"author": "data_nomad42",
"authorId": "t2_9f8g7h",
"authorFlair": null,
"text": "I've been scraping Reddit for a market research project and wanted to share a few lessons learned around rate limiting and pagination.",
"textHTML": "I've been scraping Reddit for a market research project and wanted to share a few lessons learned around rate limiting and pagination.
Rotating residential proxies made the biggest difference for us, especially for the search endpoints.
Good call, we saw the same thing once we hit a few hundred requests.
A community for discussing web scraping techniques, tools, and best practices.