# Foundit Jobs Search Scraper (`stealth_mode/foundit-jobs-search-scraper`) Actor
Scrape structured job listings from Foundit.in (formerly Monster India) with 75+ data fields per record. Collect titles, salaries, skills, company info, and application URLs from any search results page — perfect for recruiters, analysts, and job aggregators.
- **URL**: https://apify.com/stealth\_mode/foundit-jobs-search-scraper.md
- **Developed by:** [Stealth mode](https://apify.com/stealth_mode) (community)
- **Categories:** Developer tools, Automation, Jobs
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks
- **User rating**: No ratings yet
## Pricing
from $1.50 / 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.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
## Foundit.in Jobs Scraper: Extract Job Search Data at Scale
**Excerpt:** Scrape structured job listings from Foundit.in (formerly Monster India) with 75+ data fields per record. Collect titles, salaries, skills, company info, and application URLs from any search results page — perfect for recruiters, analysts, and job aggregators.
---
### What Is Foundit.in?
Foundit.in (formerly Monster India) is one of South Asia's largest job portals, hosting millions of listings across industries including IT, finance, engineering, and operations. Its powerful search engine surfaces roles by keyword, location, experience, and salary — making it a valuable source for talent intelligence and labor market research.
Manually collecting this data is impractical at scale. The **Foundit.in Jobs Scraper** automates extraction from search result pages, returning clean, structured records ready for analysis or integration.
---
### Overview
This scraper targets Foundit.in job search URLs and extracts comprehensive listing data — from basic job details to advanced metadata like recruiter identity, salary filters, applicant counts, and hiring urgency flags.
**Ideal for:**
- **Recruiters & HR teams** benchmarking salaries and skills demand
- **Data analysts** studying job market trends in India and Southeast Asia
- **Job aggregator developers** building curated listing feeds
- **Researchers** analyzing employment patterns by industry or function
---
### Input Format
```json
{
"urls": [
"https://www.foundit.in/search/audit-jobs?start=2&limit=20&query=audit&queryDerived=true"
],
"ignore_url_failures": true,
"max_items_per_url": 50
}
````
| Field | Type | Description |
|---|---|---|
| `urls` | `array` | One or more Foundit.in job search page URLs. Supports bulk entry. Example: `https://www.foundit.in/search/audit-jobs?start=2&limit=20&query=audit` |
| `ignore_url_failures` | `boolean` | If `true`, the scraper continues running even when individual URLs fail. Recommended for bulk runs. Default: `true` |
| `max_items_per_url` | `integer` | Maximum number of job records extracted per URL. Default: `20`. Increase for deeper result pages. |
> **Tip:** Adjust the `start` and `limit` query parameters in your URLs to paginate through large result sets. For example, `start=0&limit=50` fetches the first 50 results.
***
### Output Format
**Sample output**
```json
{
"id": "53018670",
"score": 318214048,
"job_id": 53018670,
"kiwi_job_id": "147511767",
"kiwi_company_id": "831382",
"kiwi_recruiter_id": "1131235",
"redirect_url": "https://www.linkedin.com/jobs/view/4413563680/",
"title": "Senior Audit Executive-Information Technology",
"company": {
"company_id": 831636,
"name": "IDFC",
"logo": "https://media.monsterindia.com/logos/xCOMP1_idfcinx1708076187102/jdlogo.gif"
},
"locations": [
{
"city": "Mumbai",
"country": "India",
"state": "Maharashtra",
"lat_lon": "19.075984,72.877656",
"uuid": "db3e442b-e262-4869-bf5e-29c815f41b58",
"iso_code": "IN",
"isd_code": 91,
"std_code": 22
},
{
"country": "India",
"lat_lon": "20.593684,78.962880",
"uuid": "fc71fff2-b98a-4cd8-a482-2e197cb4fc34",
"iso_code": "IN",
"isd_code": 91,
"std_code": 0
}
],
"minimum_experience": {
"years": 7
},
"maximum_experience": {
"years": 9
},
"minimum_salary": {
"currency": "INR",
"absolute_value": 0,
"absolute_monthly_value": 0
},
"maximum_salary": {
"currency": "INR",
"absolute_value": 0,
"absolute_monthly_value": 0
},
"posted_at": 1778893535000,
"created_at": 1778893535000,
"updated_at": 1779043071000,
"industries": [
"Other"
],
"functions": [
"Retail Banking"
],
"description": "Job Requirements
About the Role
As a Senior Audit Executive – Information Technology within the Retail Banking function, you will be responsible for independently managing internal audits of the bank's technology systems. This includes end-to-end ownership of the audit process—from planning and execution to reporting and presentation. You will ensure compliance with internal guidelines, enhance audit efficiency, and contribute to the bank's broader risk management and governance objectives.
Key Responsibilities
Primary Responsibilities
- Conduct internal audits of the bank's IT systems and functions as assigned.
- Plan, scope, and resource complex audit projects, including risk assessments.
- Evaluate the bank's information systems environment to determine system complexity and reliance.
- Perform general and application control reviews for a range of computer information systems using a risk-based approach.
- Review internal control procedures and security measures for systems under development or enhancement.
- Conduct information control reviews covering system development standards, operating procedures, system security, programming controls, communication controls, backup and disaster recovery, and system maintenance.
- Prepare and present quarterly audit committee reports, ensuring all critical issues and action plans are included.
- Actively follow up on compliance with audit findings and recommendations.
Secondary Responsibilities
- Participate in pre-implementation risk assessments for new system developments.
- Promote a culture of collaborative learning and shared responsibility within the audit team.
- Stay updated on current technological trends and developments relevant to IT auditing.
- Evaluate IT infrastructure and security solutions implemented across the bank.
- Compile data and prepare comprehensive audit reports.
- Communicate findings and recommendations clearly, both verbally and in writing.
What We Are Looking For
Education
- Undergraduate Degree in B.Tech
Experience
- Minimum 7 years of relevant experience in auditing, preferably within the banking or financial services sector.
Skills and Attributes
- Strong understanding of IS/IT auditing principles and practices.
- Ability to assess distributed production and application systems.
- Proficiency in evaluating IT infrastructure and security frameworks.
- Excellent data gathering, analysis, and reporting skills.
- Strong interpersonal and negotiation skills.
- Clear and effective communication—both written and verbal.
- Ability to work independently and manage multiple priorities efficiently.
",
"job_types": [
"Permanent Job"
],
"employment_types": [
"Full time"
],
"skills": [
{
"text": "evaluating IT infrastructure and security frameworks"
},
{
"text": "IS IT auditing principles and practices"
}
],
"recruiter_id": 1292876,
"company_id": 831636,
"maximum_salary_inr_filter": null,
"minimum_salary_inr_filter": null,
"maximum_salary_inr_monthly_filter": null,
"minimum_salary_inr_monthly_filter": null,
"minimum_experience_filter": null,
"maximum_experience_filter": null,
"questionnaire": null,
"employer_types": null,
"walk_in_venue": null,
"company_name": "IDFC",
"reference_code": null,
"status": null,
"account_id": null,
"apply_url": "https://www.linkedin.com/jobs/view/4413563680/",
"currency_code": "INR",
"hide_salary": null,
"company_logo_url": "https://media.monsterindia.com/logos/xCOMP1_idfcinx1708076187102/jdlogo.gif",
"hide_company_name": null,
"show_contact_details": null,
"job_source": "SCRAPPING",
"posting_board": "SINGLE",
"grace_job": null,
"quick_job": null,
"job_from": "MOIN_OPERIA",
"iso_code": "en",
"recruiter_name": "IDFC FIRST Bank",
"channel_id": 1,
"channel_name": "India",
"is_bold": null,
"is_jd_logo": null,
"is_search_logo": null,
"site_context": null,
"freshness": 1778893535000,
"closed_at": 1782757800000,
"active_job": true,
"is_job_active": true,
"is_cjt": null,
"is_microsite": null,
"redirect_stage": 2,
"total_applicants": 0,
"is_gptw_company": null,
"job_salary_confidential": false,
"is_urgently_hiring": false,
"quick_apply_job": null,
"job_classification": "SYNDICATE",
"is_test_job": false,
"jd_url": "/job/senior-audit-executive-information-technology-idfc-mumbai-53018670",
"is_saved": false,
"is_applied": false,
"jd_matched": [
{
"value": "audit",
"type": "query"
},
{
"value": "internal audit",
"type": "synonym"
},
{
"value": "audits",
"type": "synonym"
},
{
"value": "auditing",
"type": "synonym"
}
],
"minimum_salary_filter": 0,
"maximum_salary_filter": 0
}
```
Each job record returns up to 75+ fields. Below is a structured breakdown by category:
#### Core Identifiers
| Field | Meaning |
|---|---|
| `ID` | Internal scraper record ID |
| `Job ID` | Foundit.in's unique job identifier |
| `Kiwi Job ID` | Backend system job reference |
| `Kiwi Company ID` | Backend company identifier |
| `Kiwi Recruiter ID` | Backend recruiter identifier |
| `Reference Code` | Employer-assigned reference number |
| `Account ID` | Advertiser account ID |
| `Channel ID` / `Channel Name` | Distribution channel for the listing |
#### Job Details
| Field | Meaning |
|---|---|
| `Title` | Job title as displayed |
| `Description` | Full job description text |
| `Functions` | Job function categories (e.g., Finance, Audit) |
| `Industries` | Target industries |
| `Job Types` | Contract type (e.g., permanent, contract) |
| `Employment Types` | Full-time, part-time, etc. |
| `Skills` | Required skill tags |
| `Job Classification` | Internal classification label |
| `Job Source` | Origin platform of the listing |
| `Posting Board` | Board where the job was posted |
| `JD URL` | Direct link to the full job description page |
| `Redirect URL` | URL used when the candidate clicks "Apply" |
| `Apply URL` | Direct application link |
#### Company & Recruiter
| Field | Meaning |
|---|---|
| `Company` | Company object with metadata |
| `Company Name` | Plain-text company name |
| `Company ID` | Foundit.in company identifier |
| `Company Logo URL` | URL to the company logo image |
| `Hide Company Name` | Whether the employer is anonymous |
| `Recruiter ID` / `Recruiter Name` | Recruiter account details |
| `Employer Types` | Employer category (e.g., staffing agency, direct employer) |
| `Is GPTW Company` | Great Place to Work certified flag |
#### Location & Compensation
| Field | Meaning |
|---|---|
| `Locations` | Job location(s) |
| `ISO Code` | Country ISO code for the listing |
| `Minimum Salary` / `Maximum Salary` | Salary range in the listing's currency |
| `Currency Code` | Salary currency (e.g., INR, USD) |
| `Minimum Salary INR Filter` | Annual salary lower bound in INR (for filtering) |
| `Maximum Salary INR Filter` | Annual salary upper bound in INR |
| `Minimum Salary INR Monthly Filter` | Monthly salary lower bound in INR |
| `Maximum Salary INR Monthly Filter` | Monthly salary upper bound in INR |
| `Minimum Salary Filter` / `Maximum Salary Filter` | Generic salary filter values |
| `Hide Salary` | Whether salary is hidden from candidates |
| `Job Salary Confidential` | Employer-marked salary confidentiality flag |
#### Experience
| Field | Meaning |
|---|---|
| `Minimum Experience` | Minimum years required |
| `Maximum Experience` | Maximum years accepted |
| `Minimum Experience Filter` | Numeric filter value for min experience |
| `Maximum Experience Filter` | Numeric filter value for max experience |
#### Dates & Status
| Field | Meaning |
|---|---|
| `Posted At` | Date the job was publicly posted |
| `Created At` | Record creation timestamp |
| `Updated At` | Last modification timestamp |
| `Closed At` | Date the listing was closed |
| `Freshness` | Recency indicator used for ranking |
| `Status` | Current listing status |
| `Active Job` / `Is Job Active` | Boolean flags for listing activity |
#### Listing Flags & Features
| Field | Meaning |
|---|---|
| `Score` | Relevance score from search ranking |
| `Is Urgently Hiring` | Employer flagged as urgent hire |
| `Quick Apply Job` | Supports one-click application |
| `Quick Job` | Expedited listing type |
| `Grace Job` | Listed under a grace/extended period |
| `Is Bold` | Whether the listing has bold display styling |
| `Is JD Logo` | Logo shown on job description page |
| `Is Search Logo` | Logo shown in search results |
| `Is CJT` | Custom job type flag |
| `Is Microsite` | Associated with a branded microsite |
| `Is Test Job` | Internal test listing flag |
| `Is GPTW Company` | Great Place to Work certification |
| `Redirect Stage` | Stage in the application redirect flow |
| `Job From` | Source attribution label |
| `Site Context` | Site/region context of the listing |
| `Posting Board` | Distribution board used |
#### Application & Interaction
| Field | Meaning |
|---|---|
| `Total Applicants` | Number of applications received |
| `Is Saved` | Whether the job is saved by the user |
| `Is Applied` | Whether the user has applied |
| `JD Matched` | Whether the job matches the user's profile |
| `Show Contact Details` | Whether recruiter contact is visible |
| `Questionnaire` | Pre-application screening questions |
| `Walk In Venue` | Venue details for walk-in interviews |
***
### How to Use
1. **Get search URLs** — Run a search on Foundit.in (e.g., `https://www.foundit.in/search/audit-jobs?query=audit&start=0&limit=50`). Copy the full URL from the browser address bar.
2. **Paste into `urls`** — Add one or more search URLs to the `urls` array. Use bulk edit for large lists.
3. **Set item limit** — Use `max_items_per_url` to control how many records to extract per page. For deeper scraping, paginate by adjusting `start` in the URL.
4. **Enable fault tolerance** — Set `ignore_url_failures: true` to skip broken URLs without stopping the run.
5. **Export** — Download results as JSON, CSV, or Excel for use in your workflow.
**Tips:**
- Use specific keyword queries (e.g., `query=data+engineer&location=bangalore`) for targeted datasets.
- Combine multiple paginated URLs to collect hundreds of listings in a single run.
- Filter results post-export using `Is Urgently Hiring`, `Active Job`, or salary INR filter fields.
***
### Use Cases & Business Value
- **Salary benchmarking:** Use INR salary filter fields to analyze compensation ranges by role or industry
- **Skills gap analysis:** Aggregate `Skills` fields across thousands of listings to identify in-demand competencies
- **Market monitoring:** Track `Total Applicants` and `Freshness` to gauge role competitiveness
- **Job board development:** Feed structured listing data into niche aggregators or internal talent platforms
- **Academic research:** Study hiring patterns, employer types, and geographic distribution across India's job market
***
### Conclusion
# The **Foundit.in Jobs Scraper** delivers one of the most comprehensive job listing datasets available from any South Asian job portal — 75+ fields per record, covering everything from salary ranges and skills to recruiter metadata and applicant counts. Whether you're building a talent intelligence platform or conducting labor market research, this scraper gives you the raw material to work at scale.
# Actor input Schema
## `urls` (type: `array`):
Add the URLs of the Jobs list urls you want to scrape. You can paste URLs one by one, or use the Bulk edit section to add a prepared list.
## `ignore_url_failures` (type: `boolean`):
If true, the scraper will continue running even if some URLs fail to be scraped.
## `max_items_per_url` (type: `integer`):
The maximum number of items to scrape per URL.
## Actor input object example
```json
{
"urls": [
"https://www.foundit.in/search/audit-jobs?start=2&limit=20&query=audit&queryDerived=true"
],
"ignore_url_failures": true,
"max_items_per_url": 20
}
```
# 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 = {
"urls": [
"https://www.foundit.in/search/audit-jobs?start=2&limit=20&query=audit&queryDerived=true"
],
"ignore_url_failures": true,
"max_items_per_url": 20
};
// Run the Actor and wait for it to finish
const run = await client.actor("stealth_mode/foundit-jobs-search-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 = {
"urls": ["https://www.foundit.in/search/audit-jobs?start=2&limit=20&query=audit&queryDerived=true"],
"ignore_url_failures": True,
"max_items_per_url": 20,
}
# Run the Actor and wait for it to finish
run = client.actor("stealth_mode/foundit-jobs-search-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 '{
"urls": [
"https://www.foundit.in/search/audit-jobs?start=2&limit=20&query=audit&queryDerived=true"
],
"ignore_url_failures": true,
"max_items_per_url": 20
}' |
apify call stealth_mode/foundit-jobs-search-scraper --silent --output-dataset
```
## MCP server setup
```json
{
"mcpServers": {
"apify": {
"command": "npx",
"args": [
"mcp-remote",
"https://mcp.apify.com/?tools=stealth_mode/foundit-jobs-search-scraper",
"--header",
"Authorization: Bearer "
]
}
}
}
```
## OpenAPI specification
```json
{
"openapi": "3.0.1",
"info": {
"title": "Foundit Jobs Search Scraper",
"description": "Scrape structured job listings from Foundit.in (formerly Monster India) with 75+ data fields per record. Collect titles, salaries, skills, company info, and application URLs from any search results page — perfect for recruiters, analysts, and job aggregators.",
"version": "0.0",
"x-build-id": "5IRGOEyuuGNR6Sian"
},
"servers": [
{
"url": "https://api.apify.com/v2"
}
],
"paths": {
"/acts/stealth_mode~foundit-jobs-search-scraper/run-sync-get-dataset-items": {
"post": {
"operationId": "run-sync-get-dataset-items-stealth_mode-foundit-jobs-search-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": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
},
"/acts/stealth_mode~foundit-jobs-search-scraper/runs": {
"post": {
"operationId": "runs-sync-stealth_mode-foundit-jobs-search-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor and returns information about the initiated run in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$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": {
"$ref": "#/components/schemas/runsResponseSchema"
}
}
}
}
}
}
},
"/acts/stealth_mode~foundit-jobs-search-scraper/run-sync": {
"post": {
"operationId": "run-sync-stealth_mode-foundit-jobs-search-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$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": {
"urls": {
"title": "URLs of the Jobs list urls to scrape",
"type": "array",
"description": "Add the URLs of the Jobs list urls you want to scrape. You can paste URLs one by one, or use the Bulk edit section to add a prepared list.",
"items": {
"type": "string"
}
},
"ignore_url_failures": {
"title": "Continue running even if some URLs fail to be scraped",
"type": "boolean",
"description": "If true, the scraper will continue running even if some URLs fail to be scraped."
},
"max_items_per_url": {
"title": "Max items per URL",
"type": "integer",
"description": "The maximum number of items to scrape per URL."
}
}
},
"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
}
}
}
}
}
}
}
}
}
}
```