# Reddit Scraper – Posts, Comments, AI Answers & Products (`yumitori/reddit-scraper`) Actor
Reliable Reddit scraper that just works — scrape posts, every comment, users, communities & search. No login or API key, every field returned, export to CSV/JSON. Plus Reddit AI answers, product picks with live prices, native comment search & keyword/audience intelligence.
- **URL**: https://apify.com/yumitori/reddit-scraper.md
- **Developed by:** [Yakugusa Yumitori](https://apify.com/yumitori) (community)
- **Categories:** Social media, AI, E-commerce
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet
## Pricing
from $2.00 / 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.
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 Scraper
Posts · Comments · Users · Communities · Search · AI Answers · Intelligence
The fast, reliable Reddit comment & post scraper — scrape every comment (including nested replies), plus posts, users, communities & search, as clean structured data. Bulk comment extraction, every field returned, export to CSV/Excel/JSON.
No login. No API key. No app setup. Pay only for results.
⚡ No blocks · No timeouts · Every field, every time | 🧵 Every comment in a thread | 🤖 AI answers & product picks | 💲 From $2 / 1,000 results
---
### What it does
Give it a **subreddit, keyword, username, category, question, or URL** — get back structured JSON (also CSV, Excel, XML). It pulls posts, full comment threads, user profiles, and community data, and layers on intelligence most people don't know Reddit has: AI-synthesized answers with product picks, the algorithmic feed, keyword/audience sizing, and more.
| Feature | What you get |
|---|---|
| 🧵 **Every comment** | Full threads incl. nested replies — not just the first page. Flat or threaded. |
| 🤖 **Ask Reddit AI** | A synthesized answer to any question, with citations |
| 🛍️ **Product picks** | Shopping questions return product cards — name, image, prices & **buy links** |
| 🧭 **Algorithmic feed** | Reddit's actual ranked feed, incl. the recommendations it injects |
| 💬 **Comment search** | Live, relevance-ranked search across comment bodies |
| 🔑 **Keyword intelligence** | A keyword → communities, **total addressable audience**, related communities, topics, top conversations |
| 🗂️ **Category crawl** | Enter a topic ("Fitness", "Crypto") → auto-finds & crawls the top communities |
| 🔀 **Virality & influence** | Crosspost spread graph · subs a user moderates · participant lists |
| 📊 **Built-in analytics** | Sentiment, themes & engagement-ranked pain points |
> ⚡ **Fast & reliable by design.** No blocks, no browser-driven timeouts, and **every field is always present** — no "enable detailed fields" toggle. IP rotation is built in, with nothing for you to configure.
---
### Why it beats other Reddit scrapers
| What people complain about elsewhere | Here |
|---|---|
| *"Gets blocked / 403s / times out"* | ✅ Reliable at scale, no blocks |
| *"So slow"* | ✅ Fast — no browser overhead |
| *"Only ~200 comments"* | ✅ **Every** comment, recursively |
| *"Flat list, no nested replies"* | ✅ Optional threaded trees |
| *"Charged for runs that return nothing"* | ✅ Pay per result — empty runs cost ~nothing |
| *"Missing fields unless you toggle a setting"* | ✅ 70+ fields, always present |
| *"Just raw data, no insights"* | ✅ AI answers, sentiment, keyword & audience intel |
---
### How to use it
1. **Create a free Apify account** (or log in).
2. Pick at least one source — a **subreddit, keyword, username, category, question, or URL**.
3. (Optional) toggle add-ons: full comments, analytics, post intelligence, etc.
4. Click **Start** and download as JSON, CSV, or Excel — or pull via API / MCP.
> 🟢 **New here? Just put one subreddit in `subreddits` and hit Start.** Everything else is optional. The recipes below are copy-paste ready — paste one into the JSON editor (the **{}** tab) and run.
---
### Recipes — copy, paste, run
Each recipe is a complete input. Use the **JSON** input tab, paste, and **Start**.
**1. Posts from a subreddit** — newest / top / hot posts of a community
```json
{ "subreddits": ["technology"], "sort": "top", "time": "week", "maxPostsPerSource": 100 }
````
**2. Only the *popular* posts (filter by upvotes/comments)** — skip the noise
```json
{ "subreddits": ["technology"], "sort": "new", "minScore": 500, "minComments": 50, "maxPostsPerSource": 200 }
```
**3. Every comment on a post** — full thread, including nested replies
```json
{ "startUrls": [{ "url": "https://www.reddit.com/r/AskReddit/comments/abc123/post_title/" }],
"includeComments": true, "maxCommentsPerPost": 5000, "threadedComments": false }
```
**4. Posts + their comments from a subreddit**
```json
{ "subreddits": ["buildapc"], "sort": "top", "time": "month", "maxPostsPerSource": 50,
"includeComments": true, "maxCommentsPerPost": 200 }
```
**5. Every recent comment across a whole subreddit** — mass comment extraction
```json
{ "subredditComments": ["wallstreetbets"], "maxPostsPerSource": 1000 }
```
**6. Search posts or comments by keyword**
```json
{ "searches": ["electric vehicles"], "searchType": "comments", "sort": "top", "time": "month", "maxPostsPerSource": 200 }
```
*Set `searchType` to `posts`, `comments`, `communities`, or `users`. Add `"searchCommunity": "cars"` to search inside one subreddit.*
**7. Crawl a whole topic (no subreddit names needed)**
```json
{ "categories": ["Crypto"], "categoryMaxCommunities": 10, "sort": "top", "time": "week", "maxPostsPerSource": 50 }
```
**8. Size a keyword — communities + audience + related subs**
```json
{ "keywords": ["ozempic"] }
```
**9. Ask Reddit AI + get product picks with prices**
```json
{ "answers": ["best budget mechanical keyboard under $100"], "answersProducts": true }
```
**10. Scrape a user's posts + comments**
```json
{ "users": ["spez"], "includeComments": true, "includeUserInfluence": true }
```
**11. Monitor a brand (run daily on a schedule)**
```json
{ "searches": ["YourBrand"], "searchType": "posts", "sort": "new", "time": "day",
"minScore": 5, "includeAnalytics": true }
```
***
### Input — every setting explained
**Add at least one source; everything else is optional.** The input form is grouped into collapsible sections — here's every field, what it does, and when to use it.
**📥 Sources — pick at least one**
| Setting | What it does |
|---|---|
| `subreddits` | Communities to scrape. Start typing for the 500 most popular, or enter any name. |
| `categories` | A topic ("Fitness", "Crypto") → auto-finds and crawls the top communities in it. Best when you don't know subreddit names. |
| `searches` | Keywords to search. Pair with `searchType` to choose what comes back. |
| `subredditComments` | A subreddit → **every recent comment across all its posts** (mass comment pull). |
| `users` | Usernames → profile + their posts (and comments, if enabled). |
| `keywords` | A keyword → its whole landscape: communities, total audience, related subs, topics, top conversations. |
| `answers` | Questions for Reddit's AI → a synthesized answer (+ product cards for shopping questions). |
| `startUrls` | Paste any Reddit URLs (post, user, subreddit, or search) — the type is auto-detected. |
**🔧 Search & feed**
| Setting | What it does | Default |
|---|---|---|
| `searchType` | What `searches` returns: `posts`, `comments`, `communities`, or `users`. | posts |
| `searchCommunity` | Limit a search to one subreddit (name only, e.g. `cars`). | (all of Reddit) |
| `feedMode` | `listing` = classic sorted; `algorithmic` = Reddit's real ranked feed. | listing |
| `sort` / `time` | Order (hot/new/top/rising/controversial/best) and window (hour…all). | top / week |
| `maxPostsPerSource` | Cap posts pulled per subreddit/search/user. | 100 |
| `maxItems` | Hard cap on total results for the whole run. | 10000 |
**💬 Comments**
| Setting | What it does | Default |
|---|---|---|
| `includeComments` | Pull the full comment thread of each post (every comment). | off |
| `threadedComments` | Output comments as a nested reply tree instead of a flat list. | off |
| `maxCommentsPerPost` | Cap comments fetched per post. | 500 |
**🎚️ Filters — keep only what you want**
| Setting | What it does | Default |
|---|---|---|
| `minScore` | Only posts with at least this many upvotes (0 = no filter). | 0 |
| `minComments` | Only posts with at least this many comments. | 0 |
| `minUpvoteRatio` | Only posts above this upvote ratio (0–1). | 0 |
| `includeNSFW` | Include 18+ content. | off |
**✨ Intelligence & enrichments (optional add-ons)**
| Setting | What it does |
|---|---|
| `postIntelligence` | Per post: related questions + products named in its comments. |
| `includeCrosspostGraph` | Adds `crossposted_to` — every place a post spread to. |
| `includeUserInfluence` | Adds the subreddits a user moderates + trophies (when scraping users). |
| `collectUsers` | Emits the deduped list of everyone who participated. |
| `includeAnalytics` | Adds sentiment, top themes & ranked pain points per subreddit/post. |
| `answersProducts` | Include product cards (with prices) in AI answers. |
| `categoryMaxCommunities` / `keywordMaxCommunities` / `keywordConversations` | Tune breadth of the category & keyword modes. |
***
### Output
Clean JSON — API / MCP / spreadsheet / LLM-ready. Organized views: **🤖 AI Answers · 📋 Posts · 💬 Comments · 👥 Communities & Users · 🔑 Keyword Intel · 📊 Analytics**.
**Post** (70+ fields, incl. computed engagement analytics):
```jsonc
{
"type": "post",
"title": "What's the best mechanical keyboard under $100?",
"subreddit": "MechanicalKeyboards",
"author": "…",
"score": 1542, "upvote_ratio": 0.97, "num_comments": 387,
"created_utc": 1781348353,
"permalink": "https://www.reddit.com/r/MechanicalKeyboards/comments/…",
"age_hours": 76.3, "score_per_hour": 20.2, "comments_per_hour": 5.1,
"engagement_total": 1929, "is_high_engagement": true,
"word_count": 27, "outbound_url_host": null
}
```
**Comment** (self-contained — carries its post context + analytics):
```jsonc
{
"type": "comment",
"body": "Keychron V1 is unbeatable at that price…",
"author": "…", "score": 214, "controversiality": 0,
"depth": 1, "num_replies": 3,
"post_title": "What's the best mechanical keyboard under $100?",
"subreddit": "MechanicalKeyboards",
"age_hours": 70.1, "score_per_hour": 3.05, "word_count": 9,
"permalink": "https://www.reddit.com/r/…/comment/…"
}
```
**Ask Reddit AI** (`{ "answers": ["best budget mechanical keyboard under $100"] }`):
```jsonc
{
"type": "answer",
"query": "best budget mechanical keyboard under $100",
"answer": "Redditors frequently recommend Keychron, Aula…",
"products": [
{ "title": "Aula F75 Wireless Mechanical Keyboard…", "image_url": "https://…",
"offers": [
{ "retailer": "Amazon", "price": "$65.99", "purchase_url": "https://www.amazon.com/…" },
{ "retailer": "Walmart", "price": "$59.39", "purchase_url": "https://www.walmart.com/…" } ] }
],
"source_subreddits": ["MechanicalKeyboards", "budgetkeebs"]
}
```
***
### Use cases
- **Product & affiliate research** — what Reddit recommends to buy, with prices & buy links
- **Market & pain-point research** — sentiment, themes, and ranked unmet needs by niche
- **Brand & topic monitoring** — AI summaries + sentiment from real threads
- **Audience & influence mapping** — who participates, who moderates, which communities overlap
- **AI / LLM training data** — clean posts + complete comment threads
***
### Pricing
Pay-per-result — no subscription, no idle fees.
- **From $2 per 1,000 results** · failed or empty runs cost ~nothing
- 1,000 items ≈ **$2** · 10,000 ≈ $20
***
### FAQ
**Do I need a Reddit account or API key?** No — none required. Paste a subreddit, keyword, or URL and run.
**My old Reddit scraper stopped working / keeps returning empty — why?** Many Reddit scrapers broke recently and now return nothing, 403 errors, or missing score and comment fields. This one is actively maintained and built to keep working — and you only pay for results, so a run that returns nothing costs ~nothing.
**How do I scrape all comments from a Reddit post?** Paste the post URL into `startUrls`, set `includeComments: true`, and raise `maxCommentsPerPost`. You get **every** comment, including deeply nested replies — flat or as a threaded tree. See Recipe 3.
**How do I get every comment from a whole subreddit?** Use `subredditComments` with the subreddit name — it pulls every recent comment across all of its posts in one run (Recipe 5). This is the fastest way to do mass comment extraction.
**Can I search Reddit comments by keyword?** Yes — live, relevance-ranked comment search across all of Reddit or inside one community (`searchType: comments`).
**How do I scrape a whole subreddit's posts?** Put the name in `subreddits`, choose `sort` (hot/new/top/rising) and `time`, and set `maxPostsPerSource` (Recipe 1).
**How do I export Reddit data to CSV or Excel?** Run the actor, then download the dataset as CSV, Excel, XML, JSON, or HTML — or pull it via API, MCP, n8n, Make, or Zapier. Dates come out as readable ISO timestamps, so CSVs open clean.
**Is scraping Reddit legal?** This collects only **public** Reddit data — no private messages, no logged-in account data, no moderator-only data. As always, comply with applicable laws and terms for your use case.
**How much does it cost?** Pay-per-result, from **$2 / 1,000 items** — no subscription, no idle fees, and failed or empty runs cost ~nothing.
# Actor input Schema
## `startUrls` (type: `array`):
👉 The easy way: paste any Reddit URL — a post, subreddit, user, or search page — and hit Start. The type is detected automatically. Add as many as you want. (Or use one of the source fields below instead.)
## `subreddits` (type: `array`):
Communities to scrape. Start typing to pick from the 500 most popular, or enter ANY name. Example: streetwear, AskReddit.
## `searches` (type: `array`):
Keywords to search across Reddit (or one community, via "Search within community" below). Returns the type chosen in "Search returns".
## `searchType` (type: `string`):
What your Search keywords return. "Comments" is the live comment search Reddit removed from its public API.
## `searchCommunity` (type: `string`):
Restrict searches to one subreddit (name only, e.g. "fashion"). Leave blank to search all of Reddit.
## `users` (type: `array`):
Reddit usernames → profile + their posts (and comments). Example: spez.
## `keywords` (type: `array`):
A keyword → its community landscape: matching communities, total addressable audience, related communities, Reddit topics, and live top conversations. Example: ozempic.
## `categories` (type: `array`):
Start a crawl from a topic — no subreddit names needed. The actor finds the top communities in each category and crawls them. Pick from Reddit's official categories or type any topic. e.g. "Crypto", "Computers & Hardware", "Fitness".
## `categoryMaxCommunities` (type: `integer`):
How many top communities to crawl per category.
## `answers` (type: `array`):
Questions for Reddit's AI answer engine → a synthesized answer from real threads + citations. Shopping questions also return product cards with prices and buy links. Example: best budget mechanical keyboard under $100.
## `answersProducts` (type: `boolean`):
For AI answers, include product cards + retailer prices when the question has shopping intent.
## `subredditComments` (type: `array`):
Subreddit names → EVERY recent comment across the whole sub (all posts), not per-post. Mass comment extraction. e.g. "AskReddit".
## `sort` (type: `string`):
Order for subreddit posts (used when feed mode = Listing).
## `time` (type: `string`):
For Top / Controversial sorts and searches.
## `feedMode` (type: `string`):
How subreddit posts are pulled. Algorithmic returns Reddit's actual ranked feed with `feed_rank` and the recommendation cells the app injects.
## `maxPostsPerSource` (type: `integer`):
Posts to pull per subreddit / search / user. Reddit caps any single listing at ~1,000 — combine sorts & time ranges to exceed it.
## `maxItems` (type: `integer`):
Hard cap on total records the run returns. Pay-per-result: you're only charged for what's returned.
## `includeComments` (type: `boolean`):
Fetch EVERY comment of each post — recursively expanding hidden/collapsed replies (most scrapers stop at ~200). Adds requests per post.
## `threadedComments` (type: `boolean`):
Output comments as a nested reply tree — each comment carries its `replies`, preserving the full thread hierarchy (instead of a flat list). Requires "Include full comment threads".
## `maxCommentsPerPost` (type: `integer`):
Upper bound on comments fetched per post when the above is on.
## `minScore` (type: `integer`):
Keep only posts with at least this score. 0 = no filter.
## `minComments` (type: `integer`):
Keep only posts with at least this many comments. 0 = no filter.
## `minUpvoteRatio` (type: `number`):
Only keep posts with at least this upvote ratio (0–1). 0 = no filter.
## `includeNSFW` (type: `boolean`):
Include over-18 content. Off = filtered out.
## `postIntelligence` (type: `boolean`):
For each post, add related\_questions (questions associated with the post's topic — content ideation) and mentioned\_products (products named in its comments, with counts). One extra lookup per post.
## `includeCrosspostGraph` (type: `boolean`):
For crossposted posts, add `crossposted_to` — every other post + subreddit the same content spread to. Virality & repost-network tracking (no other scraper surfaces this). One extra request per crossposted post.
## `includeUserInfluence` (type: `boolean`):
When scraping users, add the subreddits they MODERATE (control) + trophies — power/network mapping no other scraper has. Two extra requests per user.
## `collectUsers` (type: `boolean`):
Emit a deduped list of every username that participated (posted or commented) in each subreddit/post — audience & power-user extraction. Forces comment fetch to gather commenters.
## `includeAnalytics` (type: `boolean`):
Compute sentiment (positive/negative/neutral), top themes, and ranked PAIN POINTS (unmet needs/complaints, weighted by engagement) over the harvested posts+comments of each subreddit/post. Forces comment fetch. Great for market research & product-gap discovery.
## `keywordMaxCommunities` (type: `integer`):
How many matching communities to return per keyword (each adds one lookup for live active-user counts).
## `keywordConversations` (type: `integer`):
How many current top posts mentioning the keyword to attach. 0 = skip.
## `country` (type: `string`):
Country context (ISO-2). Affects regional ranking.
## Actor input object example
```json
{
"startUrls": [
{
"url": "https://www.reddit.com/r/technology/"
}
],
"subreddits": [],
"searches": [],
"searchType": "posts",
"users": [],
"keywords": [],
"categories": [],
"categoryMaxCommunities": 10,
"answers": [],
"answersProducts": true,
"subredditComments": [],
"sort": "top",
"time": "week",
"feedMode": "listing",
"maxPostsPerSource": 100,
"maxItems": 10000,
"includeComments": false,
"threadedComments": false,
"maxCommentsPerPost": 500,
"minScore": 0,
"minComments": 0,
"minUpvoteRatio": 0,
"includeNSFW": false,
"postIntelligence": false,
"includeCrosspostGraph": false,
"includeUserInfluence": false,
"collectUsers": false,
"includeAnalytics": false,
"keywordMaxCommunities": 15,
"keywordConversations": 8,
"country": "us"
}
```
# Actor output Schema
## `data` (type: `string`):
All posts / comments / users / communities.
## `summary` (type: `string`):
Record count + config.
# 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 = {
"startUrls": [
{
"url": "https://www.reddit.com/r/technology/"
}
],
"subreddits": [],
"searches": [],
"users": [],
"keywords": [],
"categories": [],
"answers": [],
"subredditComments": []
};
// Run the Actor and wait for it to finish
const run = await client.actor("yumitori/reddit-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 = {
"startUrls": [{ "url": "https://www.reddit.com/r/technology/" }],
"subreddits": [],
"searches": [],
"users": [],
"keywords": [],
"categories": [],
"answers": [],
"subredditComments": [],
}
# Run the Actor and wait for it to finish
run = client.actor("yumitori/reddit-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 '{
"startUrls": [
{
"url": "https://www.reddit.com/r/technology/"
}
],
"subreddits": [],
"searches": [],
"users": [],
"keywords": [],
"categories": [],
"answers": [],
"subredditComments": []
}' |
apify call yumitori/reddit-scraper --silent --output-dataset
```
## MCP server setup
```json
{
"mcpServers": {
"apify": {
"command": "npx",
"args": [
"mcp-remote",
"https://mcp.apify.com/?tools=yumitori/reddit-scraper",
"--header",
"Authorization: Bearer "
]
}
}
}
```
## OpenAPI specification
```json
{
"openapi": "3.0.1",
"info": {
"title": "Reddit Scraper – Posts, Comments, AI Answers & Products",
"description": "Reliable Reddit scraper that just works — scrape posts, every comment, users, communities & search. No login or API key, every field returned, export to CSV/JSON. Plus Reddit AI answers, product picks with live prices, native comment search & keyword/audience intelligence.",
"version": "0.1",
"x-build-id": "sVWvKcgEX6vN7yCcn"
},
"servers": [
{
"url": "https://api.apify.com/v2"
}
],
"paths": {
"/acts/yumitori~reddit-scraper/run-sync-get-dataset-items": {
"post": {
"operationId": "run-sync-get-dataset-items-yumitori-reddit-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": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
},
"/acts/yumitori~reddit-scraper/runs": {
"post": {
"operationId": "runs-sync-yumitori-reddit-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor and returns information about the initiated run in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$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": {
"$ref": "#/components/schemas/runsResponseSchema"
}
}
}
}
}
}
},
"/acts/yumitori~reddit-scraper/run-sync": {
"post": {
"operationId": "run-sync-yumitori-reddit-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$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",
"properties": {
"startUrls": {
"title": "Reddit URLs — paste & Start",
"type": "array",
"description": "👉 The easy way: paste any Reddit URL — a post, subreddit, user, or search page — and hit Start. The type is detected automatically. Add as many as you want. (Or use one of the source fields below instead.)",
"items": {
"type": "string"
}
},
"subreddits": {
"title": "Subreddits",
"type": "array",
"description": "Communities to scrape. Start typing to pick from the 500 most popular, or enter ANY name. Example: streetwear, AskReddit.",
"items": {
"type": "string",
"enumSuggestedValues": [
"Home",
"AskReddit",
"NoStupidQuestions",
"BaldursGate3",
"facepalm",
"interestingasfuck",
"Damnthatsinteresting",
"LivestreamFail",
"pics",
"Palworld",
"AmItheAsshole",
"mildlyinfuriating",
"Piracy",
"PeterExplainsTheJoke",
"funny",
"AITAH",
"movies",
"Helldivers",
"gaming",
"worldnews",
"leagueoflegends",
"pcmasterrace",
"Unexpected",
"news",
"politics",
"wallstreetbets",
"todayilearned",
"nottheonion",
"memes",
"PublicFreakout",
"Wellthatsucks",
"explainlikeimfive",
"OutOfTheLoop",
"OnePiece",
"BlackPeopleTwitter",
"buildapc",
"HonkaiStarRail",
"SipsTea",
"Minecraft",
"mildlyinteresting",
"nfl",
"BeAmazed",
"DIY",
"nba",
"MapPorn",
"Steam",
"Overwatch",
"Genshin_Impact",
"classicwow",
"soccer",
"Eldenring",
"badroommates",
"personalfinance",
"antiwork",
"anime",
"wow",
"DnD",
"technology",
"WhitePeopleTwitter",
"EscapefromTarkov",
"unpopularopinion",
"popculturechat",
"videos",
"BestofRedditorUpdates",
"youtube",
"legaladvice",
"ffxiv",
"sysadmin",
"MadeMeSmile",
"CombatFootage",
"relationship_advice",
"discordapp",
"pcgaming",
"Games",
"ChatGPT",
"GlobalOffensive",
"2007scape",
"formula1",
"CuratedTumblr",
"Gamingcirclejerk",
"TikTokCringe",
"PiratedGames",
"techsupport",
"shitposting",
"theydidthemath",
"malelivingspace",
"WTF",
"cyberpunkgame",
"OldSchoolCool",
"coolguides",
"AskMen",
"dankmemes",
"feedthebeast",
"Warframe",
"UkraineWarVideoReport",
"SteamDeck",
"college",
"manga",
"CrazyFuckingVideos",
"rareinsults",
"amiwrong",
"Nijisanji",
"Kanye",
"KitchenConfidential",
"Fauxmoi",
"europe",
"iphone",
"Cooking",
"television",
"Truckers",
"ExplainTheJoke",
"marvelstudios",
"TwoXChromosomes",
"TrueOffMyChest",
"StableDiffusion",
"HonkaiStarRail_leaks",
"tifu",
"pathofexile",
"DotA2",
"Tekken",
"meirl",
"Weird",
"therewasanattempt",
"SquaredCircle",
"entertainment",
"nvidia",
"nextfuckinglevel",
"OculusQuest",
"BoomersBeingFools",
"jobs",
"HolUp",
"AskUK",
"Twitch",
"CrackWatch",
"Destiny",
"comics",
"CasualUK",
"cscareerquestions",
"PERSoNA",
"Millennials",
"Hololive",
"3Dprinting",
"travel",
"VirtualYoutubers",
"JoeRogan",
"learnprogramming",
"Scams",
"JuJutsuKaisen",
"apexlegends",
"GenZ",
"KidsAreFuckingStupid",
"magicTCG",
"Tinder",
"clevercomebacks",
"pokemon",
"Genshin_Impact_Leaks",
"PersonalFinanceCanada",
"Music",
"apple",
"ImTheMainCharacter",
"SweatyPalms",
"dndnext",
"ProgrammerHumor",
"VALORANT",
"books",
"australia",
"FortNiteBR",
"StardewValley",
"cats",
"de",
"diablo4",
"PS5",
"ThatsInsane",
"povertyfinance",
"geography",
"skyrim",
"teenagers",
"Amd",
"gamedev",
"skyrimmods",
"Animemes",
"germany",
"LifeProTips",
"Frugal",
"recruitinghell",
"AskHistorians",
"Jujutsufolk",
"Asmongold",
"BG3Builds",
"canada",
"snowboarding",
"ukraine",
"TooAfraidToAsk",
"Warthunder",
"selfhosted",
"RPClipsGTA",
"homelab",
"AskWomen",
"Philippines",
"india",
"tumblr",
"webdev",
"HistoryMemes",
"FashionReps",
"Costco",
"ask",
"NonCredibleDefense",
"dataisbeautiful",
"TwoHotTakes",
"copypasta",
"DataHoarder",
"hockey",
"aww",
"yakuzagames",
"StarWars",
"196",
"shittymoviedetails",
"BuyItForLife",
"changemyview",
"sex",
"MMA",
"TheLastAirbender",
"Marvel",
"whatisthisthing",
"Teachers",
"HazbinHotel",
"MechanicalKeyboards",
"redditonwiki",
"Windows10",
"science",
"stocks",
"MonsterHunter",
"Windows11",
"greentext",
"totalwar",
"LegalAdviceUK",
"GamingLeaksAndRumours",
"relationships",
"offmychest",
"Bitcoin",
"Roms",
"csMajors",
"YouShouldKnow",
"LinusTechTips",
"DestinyTheGame",
"deadbydaylight",
"GranblueFantasyRelink",
"Construction",
"LocalLLaMA",
"motorcycles",
"MonsterHunterWorld",
"gameofthrones",
"MacOS",
"learnpython",
"SkincareAddiction",
"CryptoCurrency",
"h3h3productions",
"trees",
"Grimdank",
"NintendoSwitch",
"mac",
"oddlysatisfying",
"space",
"TaylorSwift",
"hearthstone",
"france",
"Conservative",
"HomeNetworking",
"ontario",
"blender",
"Terraria",
"videogames",
"Persona5",
"Showerthoughts",
"headphones",
"cars",
"Fitness",
"tf2",
"Sims4",
"help",
"ADHD",
"chess",
"ufc",
"Enshrouded",
"godot",
"whenthe",
"virtualreality",
"FinalFantasy",
"Funnymemes",
"reddeadredemption",
"XboxSeriesX",
"askscience",
"aviation",
"formuladank",
"gachagaming",
"HomeImprovement",
"ApplyingToCollege",
"dating_advice",
"PleX",
"halo",
"instacart",
"CleaningTips",
"AusFinance",
"Accounting",
"stupidquestions",
"doordash",
"NewsOfTheStupid",
"golf",
"LeopardsAteMyFace",
"Seattle",
"UFOs",
"fightporn",
"LowSodiumCyberpunk",
"CrackSupport",
"wholesomememes",
"lego",
"careerguidance",
"LastEpoch",
"ChainsawMan",
"CrusaderKings",
"Jokes",
"Polska",
"mapporncirclejerk",
"Starfield",
"conspiracy",
"london",
"Warhammer40k",
"Finanzen",
"law",
"Whatcouldgowrong",
"Art",
"comicbookmovies",
"melbourne",
"playstation",
"gtaonline",
"Money",
"skiing",
"midjourney",
"argentina",
"4chan",
"Entrepreneur",
"baseball",
"MurderedByWords",
"RimWorld",
"lotr",
"boardgames",
"goodanimemes",
"hmmm",
"lostarkgame",
"Economics",
"unrealengine",
"maybemaybemaybe",
"nbacirclejerk",
"computers",
"notinteresting",
"projectzomboid",
"oculus",
"Satisfyingasfuck",
"Competitiveoverwatch",
"MouseReview",
"Fantasy",
"horror",
"OpenAI",
"Fallout",
"BatmanArkham",
"Guitar",
"FluentInFinance",
"AbruptChaos",
"rust",
"blunderyears",
"hoi4",
"TheSilphRoad",
"IdiotsInCars",
"singapore",
"pettyrevenge",
"49ers",
"privacy",
"Guildwars2",
"Monitors",
"atheism",
"TombRaider",
"starcitizen",
"PoliticalHumor",
"Rainbow6",
"30PlusSkinCare",
"CrappyDesign",
"software",
"investing",
"singularity",
"sydney",
"GooglePixel",
"40kLore",
"newzealand",
"grandorder",
"dating",
"factorio",
"footballmanagergames",
"BG3",
"funnyvideos",
"unitedkingdom",
"CreditCards",
"loseit",
"homeowners",
"brasil",
"BrandNewSentence",
"RealEstate",
"eu4",
"OnePunchMan",
"homeassistant",
"amazonprime",
"Advice",
"MechanicAdvice",
"JRPG",
"vancouver",
"MemePiece",
"hiphopheads",
"WerWieWas",
"IAmA",
"AskCulinary",
"ChikaPH",
"delta",
"DCcomics",
"marvelmemes",
"PrequelMemes",
"Unity3D",
"runescape",
"excel",
"MarvelStudiosSpoilers",
"askTO",
"patientgamers",
"MaliciousCompliance",
"manhwa",
"holdmycatnip",
"Jujutsushi",
"DeepRockGalactic",
"ios",
"nhl",
"AskNYC",
"buildapcsales",
"ich_iel",
"BollyBlindsNGossip",
"programming",
"ShingekiNoKyojin",
"Watches",
"SwiftlyNeutral",
"geometrydash",
"nostalgia",
"askSingapore",
"Parenting",
"JEENEETards",
"Naruto",
"reactjs",
"gamingsuggestions",
"popheads",
"yugioh",
"summonerschool",
"UKPersonalFinance",
"windows",
"chrome",
"medicalschool",
"IAmTheMainCharacter",
"Bogleheads",
"texts",
"rupaulsdragrace",
"EDH",
"KGBTR",
"linux",
"dndmemes",
"cursedcomments",
"Presidents",
"HollowKnight",
"Superstonk",
"TerrifyingAsFuck",
"VisionPro",
"DMAcademy",
"UkrainianConflict",
"SpidermanPS4",
"linux_gaming",
"pokemongo",
"Deltarune",
"FFVIIRemake",
"GoodAssSub",
"osugame",
"whatcarshouldIbuy",
"KansasCityChiefs",
"LeagueOfMemes",
"linuxquestions",
"writing",
"thalassophobia",
"civ",
"UnethicalLifeProTips",
"perfectlycutscreams",
"Target",
"valheim",
"notliketheothergirls",
"comicbooks",
"arknights",
"StardustCrusaders",
"Futurology",
"AMDHelp"
]
}
},
"searches": {
"title": "Search keywords",
"type": "array",
"description": "Keywords to search across Reddit (or one community, via \"Search within community\" below). Returns the type chosen in \"Search returns\".",
"items": {
"type": "string"
}
},
"searchType": {
"title": "Search returns",
"enum": [
"posts",
"comments",
"communities",
"users"
],
"type": "string",
"description": "What your Search keywords return. \"Comments\" is the live comment search Reddit removed from its public API.",
"default": "posts"
},
"searchCommunity": {
"title": "Search within community",
"type": "string",
"description": "Restrict searches to one subreddit (name only, e.g. \"fashion\"). Leave blank to search all of Reddit."
},
"users": {
"title": "Usernames",
"type": "array",
"description": "Reddit usernames → profile + their posts (and comments). Example: spez.",
"items": {
"type": "string"
}
},
"keywords": {
"title": "Keyword intelligence",
"type": "array",
"description": "A keyword → its community landscape: matching communities, total addressable audience, related communities, Reddit topics, and live top conversations. Example: ozempic.",
"items": {
"type": "string"
}
},
"categories": {
"title": "Categories / topics",
"type": "array",
"description": "Start a crawl from a topic — no subreddit names needed. The actor finds the top communities in each category and crawls them. Pick from Reddit's official categories or type any topic. e.g. \"Crypto\", \"Computers & Hardware\", \"Fitness\".",
"items": {
"type": "string",
"enumSuggestedValues": [
"3D Printing",
"Accessories & Jewelry",
"Action Games",
"Action Movies & Series",
"Activism",
"Addiction Support",
"Adult Content",
"Adventure Games",
"Alcoholic Beverages",
"Amazing",
"Animals & Pets",
"Animated Movies & Series",
"Anime & Cosplay",
"Anime & Manga",
"Architecture",
"Art",
"Aviation",
"Baking & Desserts",
"Barbecues & Grilling",
"Baseball",
"Basketball",
"Beauty & Grooming",
"Bikes & Cycling",
"Biological Sciences",
"Boating & Sailing",
"Books & Literature",
"Business & Finance",
"Business News & Discussion",
"Camping & Hiking",
"Career",
"Cars & Trucks",
"Celebrities",
"Chemistry",
"Classical Music",
"Climate & Environment",
"Collectibles",
"Collectibles & Other Hobbies",
"College Sports",
"Comedy Movies & Series",
"Comics",
"Computers & Hardware",
"Consumer Electronics",
"Cosplay",
"Country Music",
"Crazy & Shocking",
"Creators & Influencers",
"Creepy",
"Cricket",
"Cringe & Facepalm",
"Crypto",
"Culture, Race, & Ethnicity",
"DIY & Crafts",
"DIY Electronics",
"Dance & Electronic Music",
"Data Science",
"Deals & Marketplace",
"Design",
"Diet & Nutrition",
"Digital Art",
"Documentary Movies & Series",
"Drama Movies & Series",
"Economics",
"Education & Career",
"Engineering",
"Esports",
"Ethics & Philosophy",
"Family & Parenting",
"Fantasy Movies & Series",
"Fashion",
"Fashion & Beauty",
"Filmmaking",
"Fishing",
"Fitness",
"Food & Drinks",
"Food & Recipes",
"Food industry & Restaurants",
"Football",
"Funny",
"Gambling",
"Games",
"Gaming Consoles & Gear",
"Gaming News & Discussion",
"Gardening & Farming",
"Gender & Sexual Orientation",
"Generations & Nostalgia",
"Geography",
"Golf",
"Guns & Weapons",
"Hair",
"Health",
"Hip-Hop & Rap Music",
"History",
"Home & Garden",
"Home Improvement",
"Home Inspiration & Decor",
"Horror Movies & Series",
"House Plants",
"Humanities & Law",
"Hunting",
"Ice Hockey",
"Identity & Relationships",
"Illegal & Recreational Drugs",
"Indie & Alternative Music",
"Interesting",
"Internet Culture",
"Jazz Music",
"K-Pop",
"Languages",
"Law",
"Love & Dating",
"Makeup",
"Mathematics",
"Medical Health",
"Memes",
"Mental Health",
"Metal Music",
"Military",
"Mobile Games",
"Model Building",
"Motivation & Self-Improvement",
"Motor Sports",
"Motorcycles",
"Movie News & Discussion",
"Movies & TV",
"Music",
"Music News & Discussion",
"Music Production",
"Musical Instruments & Singing",
"Nails",
"Nature & Outdoors",
"Nature & Wildlife",
"News",
"News & Politics",
"Non-Alcoholic Beverages",
"Oddly Satisfying",
"Other Games",
"Other Hobbies",
"Other Music Genres",
"Other Sciences",
"Other Sports",
"Paranormal & Unexplained",
"Performing Arts",
"Personal Finance",
"Photography",
"Physics",
"Places & Travel",
"Places in Africa",
"Places in Asia",
"Places in Australia & Oceania",
"Places in Europe",
"Places in North America",
"Places in South America",
"Places in the Middle East",
"Podcasts",
"Politics",
"Pop Culture",
"Pop Music",
"Pregnancy",
"Programming",
"Psychology & Sociology",
"Q&As",
"Q&As & Stories",
"R&B Music",
"Racket Sports",
"Reading & Writing",
"Real Estate",
"Reality TV",
"Reddit Meta",
"Relationships",
"Religion & Spirituality",
"Rock Music",
"Role-Playing Games",
"Romance Movies & Series",
"Rugby",
"Sci-Fi Movies & Series",
"Science News & Discussion",
"Sciences",
"Simulation Games",
"Skincare",
"Smoking & Vaping",
"Soccer",
"Software & Apps",
"Space & Astronomy",
"Spooky",
"Sports",
"Sports & Racing Games",
"Sports News & Discussion",
"Startups & Entrepreneurship",
"Stocks & Investing",
"Stories & Confessions",
"Strategy Games",
"Streamers",
"Streaming Services",
"Streetwear & Sneakers",
"Studying & Education",
"Superhero Movies & Series",
"Sustainable Living",
"TV News & Discussion",
"Tabletop Games",
"Tarot & Astrology",
"Tattoos & Piercings",
"Tech News & Discussion",
"Technology",
"Toys",
"Trains & Public Transportation",
"Trauma Support",
"Travel & Holiday",
"True Crime",
"Vegetarian & Vegan Food",
"Vehicles",
"Virtual & Augmented Reality",
"Watches",
"Water Sports",
"Weddings",
"Weight Loss",
"Weird & Unusual",
"Wellness",
"Wholesome & Heartwarming",
"Winter Sports",
"Wrestling & Combat Sports",
"Writing"
]
}
},
"categoryMaxCommunities": {
"title": "Communities per category",
"minimum": 1,
"maximum": 25,
"type": "integer",
"description": "How many top communities to crawl per category.",
"default": 10
},
"answers": {
"title": "Ask Reddit AI",
"type": "array",
"description": "Questions for Reddit's AI answer engine → a synthesized answer from real threads + citations. Shopping questions also return product cards with prices and buy links. Example: best budget mechanical keyboard under $100.",
"items": {
"type": "string"
}
},
"answersProducts": {
"title": "Include product recommendations in AI answers",
"type": "boolean",
"description": "For AI answers, include product cards + retailer prices when the question has shopping intent.",
"default": true
},
"subredditComments": {
"title": "Subreddit comment firehose",
"type": "array",
"description": "Subreddit names → EVERY recent comment across the whole sub (all posts), not per-post. Mass comment extraction. e.g. \"AskReddit\".",
"items": {
"type": "string"
}
},
"sort": {
"title": "Sort posts by",
"enum": [
"hot",
"new",
"top",
"rising",
"controversial",
"best"
],
"type": "string",
"description": "Order for subreddit posts (used when feed mode = Listing).",
"default": "top"
},
"time": {
"title": "Time range",
"enum": [
"hour",
"day",
"week",
"month",
"year",
"all"
],
"type": "string",
"description": "For Top / Controversial sorts and searches.",
"default": "week"
},
"feedMode": {
"title": "Subreddit feed mode",
"enum": [
"listing",
"algorithmic"
],
"type": "string",
"description": "How subreddit posts are pulled. Algorithmic returns Reddit's actual ranked feed with `feed_rank` and the recommendation cells the app injects.",
"default": "listing"
},
"maxPostsPerSource": {
"title": "Max posts per source",
"minimum": 1,
"type": "integer",
"description": "Posts to pull per subreddit / search / user. Reddit caps any single listing at ~1,000 — combine sorts & time ranges to exceed it.",
"default": 100
},
"maxItems": {
"title": "Max items (whole run)",
"minimum": 1,
"type": "integer",
"description": "Hard cap on total records the run returns. Pay-per-result: you're only charged for what's returned.",
"default": 10000
},
"includeComments": {
"title": "Include full comment threads",
"type": "boolean",
"description": "Fetch EVERY comment of each post — recursively expanding hidden/collapsed replies (most scrapers stop at ~200). Adds requests per post.",
"default": false
},
"threadedComments": {
"title": "Threaded (nested) comments",
"type": "boolean",
"description": "Output comments as a nested reply tree — each comment carries its `replies`, preserving the full thread hierarchy (instead of a flat list). Requires \"Include full comment threads\".",
"default": false
},
"maxCommentsPerPost": {
"title": "Max comments per post",
"minimum": 0,
"type": "integer",
"description": "Upper bound on comments fetched per post when the above is on.",
"default": 500
},
"minScore": {
"title": "Min score",
"minimum": 0,
"type": "integer",
"description": "Keep only posts with at least this score. 0 = no filter.",
"default": 0
},
"minComments": {
"title": "Min comments",
"minimum": 0,
"type": "integer",
"description": "Keep only posts with at least this many comments. 0 = no filter.",
"default": 0
},
"minUpvoteRatio": {
"title": "Min upvote ratio",
"minimum": 0,
"maximum": 1,
"type": "number",
"description": "Only keep posts with at least this upvote ratio (0–1). 0 = no filter.",
"default": 0
},
"includeNSFW": {
"title": "Include NSFW",
"type": "boolean",
"description": "Include over-18 content. Off = filtered out.",
"default": false
},
"postIntelligence": {
"title": "Post intelligence (related questions + products)",
"type": "boolean",
"description": "For each post, add related_questions (questions associated with the post's topic — content ideation) and mentioned_products (products named in its comments, with counts). One extra lookup per post.",
"default": false
},
"includeCrosspostGraph": {
"title": "Crosspost / virality graph",
"type": "boolean",
"description": "For crossposted posts, add `crossposted_to` — every other post + subreddit the same content spread to. Virality & repost-network tracking (no other scraper surfaces this). One extra request per crossposted post.",
"default": false
},
"includeUserInfluence": {
"title": "User influence map (moderated subs + trophies)",
"type": "boolean",
"description": "When scraping users, add the subreddits they MODERATE (control) + trophies — power/network mapping no other scraper has. Two extra requests per user.",
"default": false
},
"collectUsers": {
"title": "Collect participant usernames",
"type": "boolean",
"description": "Emit a deduped list of every username that participated (posted or commented) in each subreddit/post — audience & power-user extraction. Forces comment fetch to gather commenters.",
"default": false
},
"includeAnalytics": {
"title": "Analytics — sentiment, themes & pain points",
"type": "boolean",
"description": "Compute sentiment (positive/negative/neutral), top themes, and ranked PAIN POINTS (unmet needs/complaints, weighted by engagement) over the harvested posts+comments of each subreddit/post. Forces comment fetch. Great for market research & product-gap discovery.",
"default": false
},
"keywordMaxCommunities": {
"title": "Max communities per keyword",
"minimum": 1,
"maximum": 25,
"type": "integer",
"description": "How many matching communities to return per keyword (each adds one lookup for live active-user counts).",
"default": 15
},
"keywordConversations": {
"title": "Top conversations per keyword",
"minimum": 0,
"maximum": 25,
"type": "integer",
"description": "How many current top posts mentioning the keyword to attach. 0 = skip.",
"default": 8
},
"country": {
"title": "Market (country)",
"type": "string",
"description": "Country context (ISO-2). Affects regional ranking.",
"default": "us"
}
}
},
"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
}
}
}
}
}
}
}
}
}
}
```