# Google Trends Scraper — Interest, Regions, Related & Trending (`herus13/google-trends-scraper`) Actor
Scrape Google Trends data: interest over time, interest by region, top and rising related queries, and country trending searches. Clean CSV/JSON output, no official API key.
- **URL**: https://apify.com/herus13/google-trends-scraper.md
- **Developed by:** [bootforge](https://apify.com/herus13) (community)
- **Categories:** Developer tools, SEO tools, Other
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet
## Pricing
from $5.00 / 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/docs.md):
```bash
npm install apify-client
```
In Python projects, use official [Python client library](https://docs.apify.com/api/client/python/docs.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/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
## Google Trends Scraper — Interest, Regions, Related & Trending
Google Trends Scraper is an Apify actor that extracts data from [Google Trends](https://trends.google.com) — search-interest over time, interest by region, top and rising related queries, and today's country-level trending searches — without an official API key.
Use it to spot rising keywords before you write content, benchmark a brand or product's search interest across countries, feed a trend-monitoring dashboard, or catch a topic the moment it starts trending in a country — exported to JSON, CSV, or Excel.
### Table of contents
- [What the Google Trends Scraper does](#what-the-google-trends-scraper-does)
- [How to scrape Google Trends data](#how-to-scrape-google-trends-data)
- [Google Trends scraper input](#google-trends-scraper-input)
- [What data you get](#what-data-you-get)
- [Pricing](#pricing)
- [Why residential proxy for Google Trends](#why-residential-proxy-for-google-trends)
- [Why this Google Trends scraper](#why-this-google-trends-scraper)
- [FAQ](#faq)
- [Rate this actor](#rate-this-actor-)
- [Related actors](#related-actors)
### What the Google Trends Scraper does
- 📈 **Interest over time** — the 0–100 search-interest index per date for one or more keywords, so you can chart momentum and seasonality.
- 🌍 **Interest by region** — the same 0–100 index broken down by country/region, so you can see where a keyword is hottest.
- 🔎 **Related queries** — the top and rising related searches Google Trends surfaces for a keyword, great for keyword-research and content ideation.
- 🔥 **Trending now** — today's trending searches for a country, no keyword required — catch what's blowing up right now.
- ⚡ **HTTP-only, no anti-bot browser tier** — no login, no CAPTCHA solving; runs are fast and cheap when a residential proxy keeps requests unblocked.
### How to scrape Google Trends data
1. Click **Try for free** and open the actor.
2. Choose `data_type` — **one per run**: `interest_over_time` (default), `interest_by_region`, `related_queries`, or `trending_now`. Each produces a clean, single-schema dataset.
3. For the three keyword-based types, enter 1–5 `keywords`. For `trending_now`, enter a `geo` country code instead (no keywords needed).
4. Optionally narrow with `geo` (country code), `timeframe` (e.g. `today 12-m`), and `category`.
5. Click **Start** and watch results stream into the dataset.
6. Export as **JSON, CSV, or Excel**, or pull from the [Apify API](https://docs.apify.com/api/v2).
Interest over time for two keywords, last 12 months, worldwide:
```json
{
"data_type": "interest_over_time",
"keywords": ["bitcoin", "ethereum"],
"timeframe": "today 12-m"
}
````
Interest by region for one keyword, US only:
```json
{
"data_type": "interest_by_region",
"keywords": ["bitcoin"],
"geo": "US"
}
```
Top and rising related queries for a keyword:
```json
{
"data_type": "related_queries",
"keywords": ["bitcoin"],
"timeframe": "today 12-m"
}
```
Today's trending searches in the US (no keyword needed):
```json
{
"data_type": "trending_now",
"geo": "US"
}
```
### Google Trends scraper input
| Field | Type | Default | Description |
|---|---|---|---|
| `data_type` | enum | `interest_over_time` | One per run: `interest_over_time`, `interest_by_region`, `related_queries`, or `trending_now`. |
| `keywords` | string\[] | — | 1–5 search terms. Required for all data types except `trending_now`. |
| `geo` | string | `""` (worldwide) | Two-letter country code, e.g. `US`, `GB`, `VN`. **Required** for `trending_now`. |
| `timeframe` | select | `Past 12 months` | Time range to measure: Past hour / 4 hours / day / 7 days / 30 days / 90 days / 12 months / 5 years / 2004–present. Used by interest & related types only. |
| `category` | select | `All categories` | Narrow to a Google Trends topic (Finance, Sports, Health, …) — disambiguates terms like `apple` (Finance = stock, Food & Drink = fruit). Default: all categories. |
| `hl` | string | `en-US` | UI language for the underlying Trends request. |
| `tz` | int | `-420` | Timezone offset in minutes used by Trends (e.g. `-420` for PDT). |
| `max_records` | int | — | Cap total rows per run — useful for `interest_by_region` / `trending_now`. |
| `proxy` | object | — | Apify Proxy configuration. **Residential strongly recommended** — see [Why residential proxy](#why-residential-proxy-for-google-trends). |
### What data you get
#### Interest over time (`data_type: interest_over_time`)
One row per date per keyword. Sample from a live run:
```json
{
"data_type": "interest_over_time",
"keyword": "bitcoin",
"date": "2026-06-14",
"value": 62,
"is_partial": false,
"geo": "",
"timeframe": "today 12-m",
"category": 0,
"scraped_at": "2026-07-17T09:12:44.118203+00:00"
}
```
#### Interest by region (`data_type: interest_by_region`)
One row per region per keyword. Sample from a live run:
```json
{
"data_type": "interest_by_region",
"keyword": "bitcoin",
"geo_name": "California",
"geo_code": "US-CA",
"value": 100,
"geo": "US",
"timeframe": "today 12-m",
"category": 0,
"scraped_at": "2026-07-17T09:12:44.118203+00:00"
}
```
#### Related queries (`data_type: related_queries`)
One row per top/rising related query per keyword. Sample from a live run:
```json
{
"data_type": "related_queries",
"keyword": "bitcoin",
"rank_type": "rising",
"query": "bitcoin etf",
"value": 850,
"geo": "",
"timeframe": "today 12-m",
"scraped_at": "2026-07-17T09:12:44.118203+00:00"
}
```
#### Trending now (`data_type: trending_now`)
One row per trending topic for the requested country. Sample from a live run:
```json
{
"data_type": "trending_now",
"geo": "US",
"rank": 1,
"title": "NBA Draft",
"search_volume": "200K+",
"started": "2026-07-17T08:00:00Z",
"related_terms": "NBA Draft 2026, draft order, mock draft",
"scraped_at": "2026-07-17T09:12:44.118203+00:00"
}
```
| Field | Description |
|---|---|
| `data_type` | Which of the four data types this row belongs to (matches the run's `data_type` input). |
| `keyword` | The search term this row is about (interest/related types only). |
| `date` / `value` / `is_partial` | Date, 0–100 search-interest index, and whether that data point is a still-incomplete final period (interest over time). |
| `geo_name` / `geo_code` / `value` | Region name, region code, and 0–100 interest index (interest by region). |
| `rank_type` / `query` / `value` | `top` or `rising`, the related search term, and its relative value (related queries). |
| `rank` / `title` / `search_volume` / `started` / `related_terms` | Trending topic's rank, title, estimated search volume, start time, and related terms (trending now). |
| `geo`, `timeframe`, `category`, `scraped_at` | Request parameters echoed back plus the capture timestamp. |
### Pricing
This actor uses **pay-per-event** pricing — you pay for what you scrape, not for time. Pricing below is **provisional** until Console monetization is finalized (see the Monetization tab for current live pricing).
| Event | USD | Per 1,000 |
|---|---|---|
| Actor start (per run) | $0.001 | — |
| Trend result scraped (`trend-result`) | $0.005 | $5 |
| Typical run | Cost |
|---|---|
| 1 keyword, interest over time | ~$0.006 |
| 5 keywords, interest over time | ~$0.026 |
| 1 country, trending now | ~$0.006 |
A "result" is one delivered keyword result set (interest-over-time series, interest-by-region breakdown, or related-queries set for one keyword) or one country's trending feed — not per individual row, so a 12-month daily timeline still bills as a single event.
### Why residential proxy for Google Trends
Google Trends aggressively rate-limits and blocks datacenter IPs (typically HTTP 429) after a handful of requests. **A residential proxy is strongly recommended** for anything beyond a one-off run — set it under **Proxy configuration** in the input. Apify Proxy (residential) works out of the box.
If you run your own scrapers (inside or outside Apify) and need reliable residential proxies for scale, we use **[DataImpulse](https://dataimpulse.com/?aff=404588\&utm_source=apify)** — pay-as-you-go IPs with per-country targeting and no monthly minimum:
👉 **[Get DataImpulse proxies](https://dataimpulse.com/?aff=404588\&utm_source=apify)** (referral link)
### Why this Google Trends scraper
- **Four data types, one actor** — interest over time, interest by region, related queries, and trending now, each a clean single-schema dataset; pick one per run.
- **No anti-bot browser tax** — HTTP-only, no browser, no CAPTCHA solving, so runs are fast and cheap as long as requests stay unblocked.
- **No official API key needed** — Google Trends has no public API; this actor replicates the same requests the trends.google.com website makes.
- **Validated output** — every row is Pydantic-validated before it's pushed; malformed entries are dropped, not shipped with garbage fields.
- **Open source** — the underlying `google-trends-scraper` Python package ships a Typer CLI and a FastAPI server; the Apify wrapper is a thin layer.
### FAQ
**Is this the official Google Trends API?** No — Google Trends has no official public API. This actor scrapes the same public data the trends.google.com website displays, via the same requests the site's own frontend makes.
**Why are values 0–100 instead of raw search counts?** That's how Google Trends itself reports interest — a relative index scaled to the highest point in the selected timeframe/region (100 = peak popularity), not an absolute search-volume count. Google does not publish raw numbers.
**How many keywords can I compare at once?** Up to 5 per run, matching Google Trends' own comparison limit for `interest_over_time`, `interest_by_region`, and `related_queries`.
**Do I need a proxy?** Not strictly, but Google Trends blocks datacenter IPs quickly (HTTP 429). A residential proxy (Apify Proxy or your own) is strongly recommended beyond light, occasional use — see [Why residential proxy](#why-residential-proxy-for-google-trends).
**Can I get multiple data types in one run?** One `data_type` per run by design, so every run's dataset has a single clean schema. Run the actor again with a different `data_type` to get another.
**Is scraping Google Trends legal?** This actor collects only publicly available, aggregated search-interest data — no personal data. You are responsible for complying with Google's terms and applicable laws.
### Rate this actor ⭐
If the Google Trends Scraper saved you time, please **leave a review on its Apify Store page** — ratings help other people find it and tell us what to build next. Hit a bug or missing field? Open an issue or contact us through the actor's **Issues** tab and we'll fix it fast — recency and reliability are what keep this actor ranking.
### Related actors
Building a trend-research or content-intelligence pipeline? Pair this actor with our other scrapers — same proxy config format, same Pydantic-validated output, all open source.
- **[levels.fyi Salary Scraper](https://apify.com/herus13/levels-fyi-salary-scraper)** — another HTTP-only, no-anti-bot actor if you're assembling a lightweight-scrape toolkit.
- **[Indeed Job Scraper](https://apify.com/herus13/indeed-scraper)** — cross-reference job-market demand against the keywords trending here.
- **[Google Play App Search & Reviews Scraper](https://apify.com/herus13/google-play-reviews-scraper)** — pair app search-interest trends with real app reviews.
# Actor input Schema
## `data_type` (type: `string`):
Pick ONE per run — each produces a clean, single-schema dataset.
- Interest over time — search-interest index (0–100) per date for your keyword(s).
- Interest by region — interest index per country/region.
- Related queries — top + rising related searches for a keyword.
- Trending now — today's trending searches for a country (no keyword needed).
## `keywords` (type: `array`):
1–5 search terms. Required for all data types except Trending now. Multiple terms are compared against each other (Google Trends compares up to 5).
## `geo` (type: `string`):
Two-letter country code, e.g. US, GB, VN. Empty = Worldwide (keyword products). REQUIRED for Trending now.
## `timeframe` (type: `string`):
How far back to measure search interest. Used by Interest over time, Interest by region, and Related queries (ignored for Trending now).
## `category` (type: `string`):
Narrow results to a Google Trends topic category. Useful for ambiguous terms — e.g. apple under Finance = Apple stock, under Food & Drink = the fruit. Default: all categories.
## `hl` (type: `string`):
UI language, e.g. en-US.
## `tz` (type: `integer`):
Timezone offset in minutes used in Trends requests (e.g. -420 for PDT).
## `max_records` (type: `integer`):
Cap total rows per run (useful for Interest by region / Trending now).
## `proxy` (type: `object`):
Proxy settings. RESIDENTIAL strongly recommended — Google Trends blocks datacenter IPs (HTTP 429).
## Actor input object example
```json
{
"data_type": "interest_over_time",
"keywords": [
"bitcoin"
],
"timeframe": "today 12-m",
"category": "0",
"hl": "en-US",
"tz": -420
}
```
# Actor output Schema
## `results` (type: `string`):
Interest-over-time, interest-by-region, related-queries, or trending-now rows for the requested data\_type
# 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 = {
"keywords": [
"bitcoin"
],
"geo": ""
};
// Run the Actor and wait for it to finish
const run = await client.actor("herus13/google-trends-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 = {
"keywords": ["bitcoin"],
"geo": "",
}
# Run the Actor and wait for it to finish
run = client.actor("herus13/google-trends-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 '{
"keywords": [
"bitcoin"
],
"geo": ""
}' |
apify call herus13/google-trends-scraper --silent --output-dataset
```
## MCP server setup
```json
{
"mcpServers": {
"apify": {
"command": "npx",
"args": [
"mcp-remote",
"https://mcp.apify.com/?tools=herus13/google-trends-scraper",
"--header",
"Authorization: Bearer "
]
}
}
}
```
## OpenAPI specification
```json
{
"openapi": "3.0.1",
"info": {
"title": "Google Trends Scraper — Interest, Regions, Related & Trending",
"description": "Scrape Google Trends data: interest over time, interest by region, top and rising related queries, and country trending searches. Clean CSV/JSON output, no official API key.",
"version": "0.1",
"x-build-id": "zvdhqMIeITHLfuGOS"
},
"servers": [
{
"url": "https://api.apify.com/v2"
}
],
"paths": {
"/acts/herus13~google-trends-scraper/run-sync-get-dataset-items": {
"post": {
"operationId": "run-sync-get-dataset-items-herus13-google-trends-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": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
},
"/acts/herus13~google-trends-scraper/runs": {
"post": {
"operationId": "runs-sync-herus13-google-trends-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor and returns information about the initiated run in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$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": {
"$ref": "#/components/schemas/runsResponseSchema"
}
}
}
}
}
}
},
"/acts/herus13~google-trends-scraper/run-sync": {
"post": {
"operationId": "run-sync-herus13-google-trends-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$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": {
"data_type": {
"title": "What to scrape",
"enum": [
"interest_over_time",
"interest_by_region",
"related_queries",
"trending_now"
],
"type": "string",
"description": "Pick ONE per run — each produces a clean, single-schema dataset.
- Interest over time — search-interest index (0–100) per date for your keyword(s).
- Interest by region — interest index per country/region.
- Related queries — top + rising related searches for a keyword.
- Trending now — today's trending searches for a country (no keyword needed).
",
"default": "interest_over_time"
},
"keywords": {
"title": "Keywords",
"type": "array",
"description": "1–5 search terms. Required for all data types except Trending now. Multiple terms are compared against each other (Google Trends compares up to 5).
",
"items": {
"type": "string"
}
},
"geo": {
"title": "Geo (country code)",
"type": "string",
"description": "Two-letter country code, e.g. US, GB, VN. Empty = Worldwide (keyword products). REQUIRED for Trending now."
},
"timeframe": {
"title": "Time range",
"enum": [
"now 1-H",
"now 4-H",
"now 1-d",
"now 7-d",
"today 1-m",
"today 3-m",
"today 12-m",
"today 5-y",
"all"
],
"type": "string",
"description": "How far back to measure search interest. Used by Interest over time, Interest by region, and Related queries (ignored for Trending now).",
"default": "today 12-m"
},
"category": {
"title": "Category",
"enum": [
"0",
"3",
"47",
"44",
"22",
"12",
"5",
"7",
"71",
"8",
"45",
"65",
"11",
"13",
"958",
"19",
"16",
"299",
"14",
"66",
"29",
"533",
"174",
"18",
"20",
"67"
],
"type": "string",
"description": "Narrow results to a Google Trends topic category. Useful for ambiguous terms — e.g. apple under Finance = Apple stock, under Food & Drink = the fruit. Default: all categories.
",
"default": "0"
},
"hl": {
"title": "Language (hl)",
"type": "string",
"description": "UI language, e.g. en-US.",
"default": "en-US"
},
"tz": {
"title": "Timezone offset (minutes)",
"type": "integer",
"description": "Timezone offset in minutes used in Trends requests (e.g. -420 for PDT).",
"default": -420
},
"max_records": {
"title": "Max records",
"minimum": 1,
"type": "integer",
"description": "Cap total rows per run (useful for Interest by region / Trending now)."
},
"proxy": {
"title": "Proxy configuration",
"type": "object",
"description": "Proxy settings. RESIDENTIAL strongly recommended — Google Trends blocks datacenter IPs (HTTP 429)."
}
}
},
"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
}
}
}
}
}
}
}
}
}
}
```