# Google Trends Scraper API π (`scraperpro/google-trends-scraper-api`) Actor
Extract Real-Time Trends, Historical Data, Regional Demand, and Related Queries. Native proxy rotation bypasses rate limits. Pay-per-result pricing.
- **URL**: https://apify.com/scraperpro/google-trends-scraper-api.md
- **Developed by:** [ScraperPro](https://apify.com/scraperpro) (community)
- **Categories:** SEO tools, E-commerce, News
- **Stats:** 5 total users, 2 monthly users, 100.0% runs succeeded, 1 bookmarks
- **User rating**: 5.00 out of 5 stars
## Pricing
from $1.20 / 1,000 results
This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.
Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have.
Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event
## What's an Apify Actor?
Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Actors are written with capital "A".
## How to integrate an Actor?
If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
The best way to integrate Actors is as follows.
In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js/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
## π Google Trends Scraper β 5 Endpoints, 1 Actor, $0.0025/result
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**The most reliable Google Trends API on Apify.** Extract real-time trending searches, historical timeline data, regional interest maps, related queries, and related topics β all from a single actor at the lowest per-result price on the market.
*Tired of runs that fail silently? This actor applies exponential backoff, native residential proxy rotation, and structured error reporting so you get data, not timeouts.*
---
### π₯ Why Switch to This Actor?
The most-used Google Trends actor on Apify has a **71.8% success rate** β meaning nearly 1 in 3 runs fails. Ours runs at **100%**, and if Google does return an error, you're only charged $0.0025 for the error record, not for a full failed run.
| Feature | This Actor | Most Competitors |
|---|---|---|
| **All 5 trend endpoints in one** | β
| β Need separate actors |
| **Success rate** | β
~100% | β οΈ 71β97% |
| **Price per result** | β
$0.0025 | β οΈ $0.001β$0.025 |
| **Hidden compute/proxy fees** | β
None β included | β οΈ Common |
| **Rate limit (429) handling** | β
Native exponential backoff | β Often crashes |
| **Normalized flat JSON output** | β
CSV/Excel/Pandas-ready | β οΈ Varies |
| **Keyword comparison (up to 5)** | β
| β οΈ Often 1 at a time |
---
### π‘ 5 Intelligence Endpoints in One Actor
Set `scrape_type` to choose your data source. No switching actors, no extra cost.
#### 1. π₯ `trending_now` β Real-Time Pulse
What is the internet searching for *right now*? Updated hourly with volume estimates, traffic growth percentages, topic categories, and related news articles.
**Best for:** News aggregators, viral content creators, reactive social media teams.
```json
{
"keyword": "yankees vs mets",
"volume": 100000,
"volume_growth_pct": 1000,
"topic_names": ["Sports"],
"trend_keywords": ["yankees vs mets", "mets game today"],
"started_timestamp": "2026-05-15T22:20:00+00:00",
"is_trend_finished": false,
"geo": "US"
}
````
#### 2. π `interest_over_time` β Historical Timeline (2004βToday)
Track normalized search interest (0β100) for up to **5 keywords simultaneously** across any time range β from the last hour to the full history since 2004.
**Best for:** Seasonal demand forecasting, brand monitoring, trend correlation analysis.
```json
{
"keyword": "Web scraping",
"value": 35,
"date": "2025-05-11T00:00:00",
"isPartial": false
}
```
#### 3. πΊοΈ `interest_by_region` β Geographic Demand Map
See exactly where interest in your keyword is highest. Break down by **Country, Region (State), DMA, or City**.
**Best for:** Local SEO targeting, PPC geo-bidding, regional product launches.
#### 4. π `related_queries` β Long-Tail Keyword Discovery
Extract the exact search queries Google groups with your keyword. Flags **"Rising" (breakout)** vs **"Top" (established)** queries β the fastest way to find what competitors haven't targeted yet.
**Best for:** SEO content planning, keyword gap analysis, PPC expansion.
#### 5. π·οΈ `related_topics` β Knowledge Graph Entity Extraction
Google's own entity groupings for your keyword. Reveals how Google *understands* your topic β invaluable for semantic SEO and brand positioning.
***
### π° Pricing β Fully Predictable, Zero Surprises
**$2.50 per 1,000 results ($0.0025/result).** Proxy rotation and compute are included. You only pay for data you receive.
| Use Case | Results | Cost |
|---|---|---|
| Verify output quality | 10 items | **$0.025** |
| Starter / test run | 100 items | **$0.25** |
| Full historical analysis | 1,000 items | **$2.50** |
| Monthly trending dashboard | ~3,000/month | **~$7.50/month** |
> **Zero-risk failure policy:** If Google returns an error, you're billed $0.0025 for the error record β not for the entire run.
***
### π― Use Cases
#### π¦ E-commerce & Dropshipping
Identify what's trending *before* it saturates. Run `trending_now` daily across multiple countries. Cross-reference with `interest_over_time` to separate short spikes from sustained demand. Find products going viral on TikTok before they show up on Amazon.
#### βοΈ SEO & Content Marketing
Use `related_queries` to discover long-tail keywords with rising search volume that your competitors haven't written about yet. Use `interest_over_time` to time content publishing to peak seasonal demand.
#### πΈ Quantitative Finance & Trading
Correlate `interest_over_time` spikes for ticker symbols or company names with price action. Research has shown search volume predicts price volatility for retail-driven assets.
#### π Market Research & Brand Intelligence
Track brand awareness over time vs competitors using `interest_over_time` with up to 5 keywords. Use `interest_by_region` to find underserved markets and geographic strongholds.
#### π€ Automated Dashboards & Pipelines
Schedule this actor daily or weekly. Export to CSV/Excel, or pipe directly to Pandas DataFrames β the output is flat, normalized JSON with consistent field names across all 5 endpoints.
```python
from apify_client import ApifyClient
client = ApifyClient("YOUR_API_TOKEN")
run = client.actor("scraperpro/google-trends-ppe").call(run_input={
"scrape_type": "interest_over_time",
"keywords": ["ChatGPT", "Claude", "Gemini"],
"predefined_timeframe": "today 12-m",
"common_geo": "US",
"max_events": 500
})
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
print(f"{item['keyword']}: {item['value']} on {item['date']}")
```
***
### βοΈ Input Parameters
| Parameter | Type | Description |
|---|---|---|
| `scrape_type` | string | **Required.** One of: `trending_now`, `interest_over_time`, `interest_by_region`, `related_queries`, `related_topics` |
| `keywords` | array | Up to 5 keywords. Required for all types except `trending_now` |
| `predefined_timeframe` | string | `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` |
| `common_geo` | string | Country code (e.g. `US`, `GB`, `DE`) or leave empty for worldwide |
| `geo_resolution` | string | `COUNTRY`, `REGION`, `CITY`, or `DMA` (for `interest_by_region`) |
| `gprop` | string | Data source: `""` (Web), `images`, `news`, `froogle` (Shopping), `youtube` |
| `max_events` | int | Cap on results returned. Default: 100. Lower to 10 for a free test |
***
### β FAQ
**Q: How is this different from the official Apify Google Trends scraper?**
A: The official actor has a 71.8% success rate β nearly 1 in 3 runs fails. Ours handles 429 rate limits with exponential backoff and residential proxy rotation natively, hitting ~100% success. We also offer all 5 endpoints in one actor vs needing multiple.
**Q: Can I compare multiple keywords at once?**
A: Yes β up to 5 keywords simultaneously in `interest_over_time` and `interest_by_region`. Each keyword gets its own row in the output, making it easy to analyze side-by-side.
**Q: What happens if Google blocks the request?**
A: The actor applies invisible exponential backoff automatically. If it still can't get data after retries, it pushes a clean error record to your dataset and charges only $0.0025 β your run doesn't crash.
**Q: Is there a free test?**
A: Set `max_events` to 10 for a test run that costs ~$0.025 and returns real data instantly.
**Q: Can I schedule this to run daily?**
A: Yes. Use Apify's built-in scheduler to run on any cron schedule. The flat JSON output integrates cleanly with Google Sheets, BigQuery, or any data pipeline.
***
*Keywords: Google Trends API, Google Trends scraper, trending searches API, interest over time scraper, related queries extractor, Google Trends data extraction, real-time trends API, trending now scraper, keyword trend tracker, SEO trend analysis, Google Trends Python, Google Trends historical data, regional interest data, breakout keywords, rising queries Google Trends*
# Actor input Schema
## `scrape_type` (type: `string`):
What to retrieve from Google Trends.
## `keywords` (type: `array`):
Keywords to analyze (Max 5). Required for all types except 'trending\_now'. For 'related\_\*', only the first keyword is used.
## `timeframe_type` (type: `string`):
Use a predefined timeframe or a custom range.
## `predefined_timeframe` (type: `string`):
Common timeframes used by Google Trends.
## `custom_timeframe` (type: `string`):
Custom date range (e.g., '2023-01-01 2023-06-30') or hourly.
## `geo_selection_type` (type: `string`):
Choose between a common country code or a custom geo code.
## `common_geo` (type: `string`):
Two-letter country code like 'US', 'GB', 'DE'. Leave empty for global.
## `custom_geo_code` (type: `string`):
Specific geo code (e.g., 'US-CA' for California).
## `gprop` (type: `string`):
Filter by Google service.
## `geo_resolution` (type: `string`):
Controls the level of geographic detail.
## `inc_low_vol` (type: `boolean`):
Include regions with low search volume. (Warning: high event output).
## `trending_language` (type: `string`):
Language code for realtime trending (e.g., 'en', 'es').
## `trending_hours` (type: `integer`):
Time window (1-191 hours) for realtime trending.
## `max_events` (type: `integer`):
Caps the number of items yielded. Default 100 costs ~$0.25. Limit to 10 for a $0.025 test run!
## `acknowledge_costs` (type: `boolean`):
Check this box if you plan to extract >1000 items ($2.40+) in a single run.
## `debug_mode` (type: `boolean`):
Enable verbose logging and save raw HTML/responses to Apify Key-Value Store on failure.
## `proxyConfiguration` (type: `object`):
Apify Proxy (Residential) is used automatically inside the actor code. Leave default.
## Actor input object example
```json
{
"scrape_type": "trending_now",
"keywords": [
"Web scraping"
],
"timeframe_type": "predefined",
"predefined_timeframe": "today 12-m",
"geo_selection_type": "Common Countries",
"common_geo": "US",
"custom_geo_code": "",
"gprop": "web",
"geo_resolution": "COUNTRY",
"inc_low_vol": false,
"trending_language": "en",
"trending_hours": 24,
"max_events": 100,
"acknowledge_costs": false,
"debug_mode": false,
"proxyConfiguration": {
"useApifyProxy": true,
"apifyProxyGroups": [
"RESIDENTIAL"
]
}
}
```
# Actor output Schema
## `results` (type: `string`):
No description
# API
You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.
## JavaScript example
```javascript
import { ApifyClient } from 'apify-client';
// Initialize the ApifyClient with your Apify API token
// Replace the '' with your token
const client = new ApifyClient({
token: '',
});
// Prepare Actor input
const input = {
"keywords": [
"Web scraping"
],
"proxyConfiguration": {
"useApifyProxy": true,
"apifyProxyGroups": [
"RESIDENTIAL"
]
}
};
// Run the Actor and wait for it to finish
const run = await client.actor("scraperpro/google-trends-scraper-api").call(input);
// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`πΎ Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
console.dir(item);
});
// π Want to learn more π? Go to β 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": ["Web scraping"],
"proxyConfiguration": {
"useApifyProxy": True,
"apifyProxyGroups": ["RESIDENTIAL"],
},
}
# Run the Actor and wait for it to finish
run = client.actor("scraperpro/google-trends-scraper-api").call(run_input=run_input)
# Fetch and print Actor results from the run's dataset (if there are any)
print("πΎ Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"])
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
print(item)
# π Want to learn more π? Go to β https://docs.apify.com/api/client/python/docs/quick-start
```
## CLI example
```bash
echo '{
"keywords": [
"Web scraping"
],
"proxyConfiguration": {
"useApifyProxy": true,
"apifyProxyGroups": [
"RESIDENTIAL"
]
}
}' |
apify call scraperpro/google-trends-scraper-api --silent --output-dataset
```
## MCP server setup
```json
{
"mcpServers": {
"apify": {
"command": "npx",
"args": [
"mcp-remote",
"https://mcp.apify.com/?tools=scraperpro/google-trends-scraper-api",
"--header",
"Authorization: Bearer "
]
}
}
}
```
## OpenAPI specification
```json
{
"openapi": "3.0.1",
"info": {
"title": "Google Trends Scraper API π",
"description": "Extract Real-Time Trends, Historical Data, Regional Demand, and Related Queries. Native proxy rotation bypasses rate limits. Pay-per-result pricing.",
"version": "2.6",
"x-build-id": "ygLZwn2z25cxkpB10"
},
"servers": [
{
"url": "https://api.apify.com/v2"
}
],
"paths": {
"/acts/scraperpro~google-trends-scraper-api/run-sync-get-dataset-items": {
"post": {
"operationId": "run-sync-get-dataset-items-scraperpro-google-trends-scraper-api",
"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": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
},
"/acts/scraperpro~google-trends-scraper-api/runs": {
"post": {
"operationId": "runs-sync-scraperpro-google-trends-scraper-api",
"x-openai-isConsequential": false,
"summary": "Executes an Actor and returns information about the initiated run in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$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": {
"$ref": "#/components/schemas/runsResponseSchema"
}
}
}
}
}
}
},
"/acts/scraperpro~google-trends-scraper-api/run-sync": {
"post": {
"operationId": "run-sync-scraperpro-google-trends-scraper-api",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$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": [
"scrape_type"
],
"properties": {
"scrape_type": {
"title": "Scrape Type",
"enum": [
"trending_now",
"interest_over_time",
"interest_by_region",
"related_queries",
"related_topics"
],
"type": "string",
"description": "What to retrieve from Google Trends.",
"default": "trending_now"
},
"keywords": {
"title": "Keywords",
"maxItems": 5,
"type": "array",
"description": "Keywords to analyze (Max 5). Required for all types except 'trending_now'. For 'related_*', only the first keyword is used.",
"default": [
"Web scraping"
],
"items": {
"type": "string"
}
},
"timeframe_type": {
"title": "Timeframe Type",
"enum": [
"predefined",
"custom"
],
"type": "string",
"description": "Use a predefined timeframe or a custom range.",
"default": "predefined"
},
"predefined_timeframe": {
"title": "Predefined Timeframe",
"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": "Common timeframes used by Google Trends.",
"default": "today 12-m"
},
"custom_timeframe": {
"title": "Custom Timeframe",
"type": "string",
"description": "Custom date range (e.g., '2023-01-01 2023-06-30') or hourly."
},
"geo_selection_type": {
"title": "Geographic Selection Type",
"enum": [
"Common Countries",
"Custom Geo Code"
],
"type": "string",
"description": "Choose between a common country code or a custom geo code.",
"default": "Common Countries"
},
"common_geo": {
"title": "Common Country (2-letter code)",
"type": "string",
"description": "Two-letter country code like 'US', 'GB', 'DE'. Leave empty for global.",
"default": "US"
},
"custom_geo_code": {
"title": "Custom Geo Code",
"type": "string",
"description": "Specific geo code (e.g., 'US-CA' for California).",
"default": ""
},
"gprop": {
"title": "Search Property (gprop)",
"enum": [
"web",
"images",
"news",
"shopping",
"youtube"
],
"type": "string",
"description": "Filter by Google service.",
"default": "web"
},
"geo_resolution": {
"title": "Geographic Resolution (for interest_by_region)",
"enum": [
"COUNTRY",
"REGION",
"DMA",
"CITY"
],
"type": "string",
"description": "Controls the level of geographic detail.",
"default": "COUNTRY"
},
"inc_low_vol": {
"title": "Include Low Volume Regions",
"type": "boolean",
"description": "Include regions with low search volume. (Warning: high event output).",
"default": false
},
"trending_language": {
"title": "Trending Now: Language",
"type": "string",
"description": "Language code for realtime trending (e.g., 'en', 'es').",
"default": "en"
},
"trending_hours": {
"title": "Trending Now: Hours",
"minimum": 1,
"maximum": 191,
"type": "integer",
"description": "Time window (1-191 hours) for realtime trending.",
"default": 24
},
"max_events": {
"title": "Maximum events to output",
"minimum": 1,
"maximum": 10000,
"type": "integer",
"description": "Caps the number of items yielded. Default 100 costs ~$0.25. Limit to 10 for a $0.025 test run!",
"default": 100
},
"acknowledge_costs": {
"title": "Acknowledge High Volume Runs",
"type": "boolean",
"description": "Check this box if you plan to extract >1000 items ($2.40+) in a single run.",
"default": false
},
"debug_mode": {
"title": "Debug Mode",
"type": "boolean",
"description": "Enable verbose logging and save raw HTML/responses to Apify Key-Value Store on failure.",
"default": false
},
"proxyConfiguration": {
"title": "Proxy configuration",
"type": "object",
"description": "Apify Proxy (Residential) is used automatically inside the actor code. Leave default."
}
}
},
"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
}
}
}
}
}
}
}
}
}
}
```