# Levels Fyi Salary Scraper (`shhh_lab/levels-fyi-salary-scraper`) Actor
Scrape individual salary submissions from Levels.fyi — base, stock, bonus, TC by company, role, level, and location.
- **URL**: https://apify.com/shhh\_lab/levels-fyi-salary-scraper.md
- **Developed by:** [ShhhLabs](https://apify.com/shhh_lab) (community)
- **Categories:** Jobs, Developer tools, Automation
- **Stats:** 6 total users, 3 monthly users, 100.0% runs succeeded, NaN bookmarks
- **User rating**: 5.00 out of 5 stars
## Pricing
from $2.80 / 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
## Levels.fyi Salary Scraper
Scrape salary data from [Levels.fyi](https://www.levels.fyi) — individual salary submissions with company, role, level, location, YoE, and full comp breakdown. No API key needed.
### Features
- **1 row = 1 salary submission**: each individual submission is its own row with full comp breakdown
- **2 scraping modes**: specific company×role combos, or all roles for given companies
- **Per-level context**: median TC, base, stock, bonus for each career level (L3–L8, IC1–IC6, etc.) denormalized on each row
- **Percentile data**: p10/p25/p50/p75/p90 for total comp, base salary, stock grants, and bonus
- **80 job families**: software engineer, product manager, data scientist, and 77 more
- **3,000+ companies**: from FAANG to startups — every company with data on Levels.fyi
- **Company metadata**: industry, HQ location, employee count, funding stage, vesting type, ticker
- **Sub-title breakdowns**: specializations within each role (e.g. "Backend SWE", "ML Engineer") with median TC
- **No headless browser**: pure HTTP + JSON — fast, cheap, reliable
### Input
| Field | Type | Default | Description |
|---|---|---|---|
| `mode` | `string` | `"specific"` | `"specific"` = exact company+role combos. `"companies"` = all roles for given companies. |
| `companies` | `string[]` | `["google"]` | Company slugs. Find slugs in Levels.fyi URLs (e.g. `levels.fyi/companies/google` → `"google"`). |
| `roles` | `string[]` | — | Role slugs. Used in `specific` mode only — ignored in `companies` mode. See full list below. |
| `maxResults` | `integer` | `0` | Maximum rows to output. Actor stops when reached. `0` = unlimited. |
| `maxRequestsPerSecond` | `number` | `20` | Rate limit (1–50 req/s). |
| `timeoutSeconds` | `integer` | `300` | Max run time in seconds before graceful stop. |
#### Usage Examples
**Scrape Google Software Engineer salaries:**
```json
{
"mode": "specific",
"companies": ["google"],
"roles": ["software-engineer"]
}
````
**Scrape all roles at FAANG companies:**
```json
{
"mode": "companies",
"companies": ["google", "meta", "apple", "amazon", "netflix"]
}
```
**Scrape multiple roles at multiple companies:**
```json
{
"mode": "specific",
"companies": ["stripe", "coinbase", "databricks"],
"roles": ["software-engineer", "product-manager", "data-scientist"]
}
```
### Output
Each result is one **individual salary submission**. For example, "Google × Software Engineer" at level L3 with 15 recent submissions produces 15 rows. Company, role, and level metadata is denormalized into every row for easy filtering and export.
#### Example Row
```json
{
"uuid": "d0c6e935-...",
"offerDate": "2026-03-18T10:02:08.653+00:00",
"yearsOfExperience": 12,
"yearsAtCompany": 3,
"focusTag": "Data",
"location": "New York, NY",
"baseSalary": 120000,
"totalCompensation": 160000,
"stockGrantAnnual": 40000,
"bonusAnnual": 0,
"company": "Google",
"companySlug": "google",
"companyId": 1,
"industry": "Tech",
"ticker": "GOOG",
"hqCity": "Mountain View",
"hqState": "California",
"employeeCount": 258750,
"fundingStage": "post_ipo",
"vestingType": "RSU",
"role": "Software Engineer",
"roleSlug": "software-engineer",
"level": "L3",
"levelSecondaryName": "SWE II",
"levelMedianTC": 204005,
"levelAvgBase": 157074,
"levelAvgStock": 33157,
"levelAvgBonus": 13774,
"levelSubmissions": 54,
"levelSubmissionsLast12Mo": 904,
"levelUrl": "/companies/google/salaries/software-engineer/levels/l3",
"roleTotalSubmissions": 21959,
"percentiles": {
"totalComp": { "p10": 175000, "p25": 206000, "p50": 319000, "p75": 398750, "p90": 490000 },
"baseSalary": { "p10": 150000, "p25": 166000, "p50": 199000, "p75": 220000, "p90": 242000 },
"stockGrant": { "p10": 25000, "p25": 40000, "p50": 90000, "p75": 140000, "p90": 200000 },
"bonus": { "p10": 0, "p25": 0, "p50": 30000, "p75": 38750, "p90": 48000 }
},
"subTitles": [
{ "title": "Backend Software Engineer", "slug": "backend-software-engineer", "medianTC": 285000, "count": 524 }
],
"currency": "USD",
"scrapedAt": "2026-04-16T17:30:00Z",
"sourceUrl": "https://www.levels.fyi/companies/google/salaries/software-engineer"
}
```
#### Output Fields
| Field | Type | Description |
|---|---|---|
| `uuid` | string | Unique submission identifier |
| `offerDate` | string | When the salary was submitted |
| `yearsOfExperience` | number | Total years of professional experience |
| `yearsAtCompany` | number | Years at the current company |
| `focusTag` | string | null | Specialization (e.g. "Data", "ML", "Backend") |
| `location` | string | Submitter's work location |
| `baseSalary` | number | Annual base salary |
| `totalCompensation` | number | Total annual compensation (base + stock + bonus) |
| `stockGrantAnnual` | number | Annual stock grant value |
| `bonusAnnual` | number | Annual bonus amount |
| `company` | string | Company display name |
| `companySlug` | string | URL-safe company identifier |
| `companyId` | number | Levels.fyi internal company ID |
| `industry` | string | null | Industry classification |
| `ticker` | string | null | Stock ticker (public companies) |
| `hqCity` / `hqState` | string | null | Company HQ location |
| `employeeCount` | number | null | Approximate employee count |
| `fundingStage` | string | null | pre\_seed through post\_ipo |
| `vestingType` | string | null | RSU, ISO, etc. |
| `role` | string | Job family display name |
| `roleSlug` | string | URL-safe role identifier |
| `level` | string | Primary level name (e.g. "L3", "ICT4") |
| `levelSecondaryName` | string | Alternative level name (e.g. "SWE II") |
| `levelMedianTC` | number | Median total compensation at this level |
| `levelAvgBase` | number | Average base salary at this level |
| `levelAvgStock` | number | Average annual stock grant at this level |
| `levelAvgBonus` | number | Average annual bonus at this level |
| `levelSubmissions` | number | Salary submissions at this level |
| `levelSubmissionsLast12Mo` | number | Submissions in the last 12 months |
| `levelUrl` | string | Level-specific page path |
| `roleTotalSubmissions` | number | Total submissions across all levels for this company × role |
| `percentiles` | object | p10/p25/p50/p75/p90 for TC, base, stock, bonus (role-wide) |
| `subTitles[]` | array | Role specializations with median TC |
| `currency` | string | Always "USD" |
| `scrapedAt` | string | ISO 8601 timestamp |
| `sourceUrl` | string | Levels.fyi page URL |
### Pricing
**Pay Per Result** — each individual salary submission is one row.
| Scenario | Rows (approx.) | Description |
|---|---|---|
| 1 company, 1 role | ~50–150 | 10–20 submissions × 5–8 levels |
| 5 FAANG companies, all roles | ~3,000–6,000 | ~10–20 submissions per level |
| Top 200 companies, 1 role | ~10,000–30,000 | varies by company size |
**Free tier**: test with a few company×role combos before committing.
### Available Role Slugs
All 80 job families supported by Levels.fyi:
Click to expand full list
| Slug | Name |
|---|---|
| `software-engineer` | Software Engineer |
| `product-designer` | Product Designer |
| `product-manager` | Product Manager |
| `data-scientist` | Data Scientist |
| `management-consultant` | Management Consultant |
| `investment-banker` | Investment Banker |
| `software-engineering-manager` | Software Engineering Manager |
| `biomedical-engineer` | Biomedical Engineer |
| `civil-engineer` | Civil Engineer |
| `technical-program-manager` | Technical Program Manager |
| `accountant` | Accountant |
| `human-resources` | Human Resources |
| `marketing` | Marketing |
| `marketing-operations` | Marketing Operations |
| `recruiter` | Recruiter |
| `sales` | Sales |
| `hardware-engineer` | Hardware Engineer |
| `mechanical-engineer` | Mechanical Engineer |
| `solution-architect` | Solution Architect |
| `business-analyst` | Business Analyst |
| `customer-service` | Customer Service |
| `business-development` | Business Development |
| `security-analyst` | Cybersecurity Analyst |
| `industrial-designer` | Industrial Designer |
| `fashion-designer` | Fashion Designer |
| `administrative-assistant` | Administrative Assistant |
| `information-technologist` | Information Technologist |
| `geological-engineer` | Geological Engineer |
| `financial-analyst` | Financial Analyst |
| `venture-capitalist` | Venture Capitalist |
| `chief-of-staff` | Chief of Staff |
| `legal` | Legal |
| `program-manager` | Program Manager |
| `project-manager` | Project Manager |
| `data-science-manager` | Data Science Manager |
| `product-design-manager` | Product Design Manager |
| `founder` | Founder |
| `technical-writer` | Technical Writer |
| `copywriter` | Copywriter |
| `sales-engineer` | Sales Engineer |
| `facilities-manager` | Facilities Manager |
| `property-manager` | Property Manager |
| `real-estate-agent` | Real Estate Agent |
| `data-analyst` | Data Analyst |
| `corp-dev` | Corporate Development |
| `biz-ops` | Business Operations |
| `bizops-manager` | Business Operations Manager |
| `partner-manager` | Partner Manager |
| `customer-service-ops` | Customer Service Operations |
| `ux-researcher` | UX Researcher |
| `graphic-designer` | Graphic Designer |
| `electrical-engineer` | Electrical Engineer |
| `controls-engineer` | Controls Engineer |
| `regulatory-affairs` | Regulatory Affairs |
| `physician` | Physician |
| `chemical-engineer` | Chemical Engineer |
| `aerospace-engineer` | Aerospace Engineer |
| `materials-engineer` | Materials Engineer |
| `optical-engineer` | Optical Engineer |
| `mep-engineer` | MEP Engineer |
| `total-rewards` | Total Rewards |
| `people-ops` | People Operations |
| `actuary` | Actuary |
| `underwriter` | Underwriter |
| `claims-adjuster` | Claims Adjuster |
| `customer-success` | Customer Success |
| `toxicologist` | Toxicologist |
| `meteorologist` | Meteorologist |
| `revops` | Revenue Operations |
| `sales-enablement` | Sales Enablement |
| `prompt-engineer` | Prompt Engineer |
| `trust-and-safety` | Trust and Safety |
| `tam` | Technical Account Manager |
| `gtm-engineer` | Go-To-Market Engineer |
| `lab-tech` | Lab Technician |
| `paralegal` | Paralegal |
| `compliance-officer` | Compliance Officer |
| `legal-ops` | Legal Operations |
| `nurse` | Nurse |
| `data-annotator` | Data Annotator |
### What Stops the Actor
The actor stops when **any** of these conditions is met (whichever comes first):
1. **All requests completed** — every company × role combination has been scraped.
2. **Max results reached** — the `maxResults` limit is hit. The actor saves all rows collected so far and stops.
3. **Timeout reached** — the `timeoutSeconds` limit is hit. The actor saves all data collected so far and exits gracefully.
In all cases, data already pushed to the dataset is preserved.
### Limitations
- **Data freshness**: Levels.fyi caches pages at CDN for 6 hours. Data reflects submissions up to that window.
- **Coverage**: Not all companies have data for all 80 roles. Most companies have 2–10 roles with salary data.
- **Currency**: All compensation figures are in USD. Non-US salaries are converted to USD by Levels.fyi.
- **Submissions per level**: Each level returns 10–20 recent submissions, not the full history.
- **BuildId rotation**: Levels.fyi changes its internal buildId on each deploy. The actor handles this automatically — if a request fails, it re-extracts the buildId and retries.
- **Volume**: ~20,000–30,000 company×role pages exist in total. A full catalog crawl takes several hours. Use `maxResults` or `timeoutSeconds` to cap runs.
# Actor input Schema
## `mode` (type: `string`):
How to discover company × role combinations to scrape.
## `companies` (type: `array`):
Company slugs to scrape (e.g. google, meta, apple). Find slugs in Levels.fyi URLs: levels.fyi/companies/{slug}. Used in 'specific' and 'companies' modes.
## `roles` (type: `array`):
Roles to scrape. Only used in 'Specific' mode — completely ignored in 'Companies' mode.
## `maxResults` (type: `integer`):
Maximum number of rows to output. The actor stops once this limit is reached and saves all data collected. 0 = unlimited.
## `maxRequestsPerSecond` (type: `number`):
Rate limit for HTTP requests.
## `timeoutSeconds` (type: `integer`):
Maximum time the actor will run before gracefully stopping. The actor saves all data collected so far.
## Actor input object example
```json
{
"mode": "specific",
"companies": [
"google",
"meta",
"apple"
],
"roles": [
"software-engineer"
],
"maxResults": 1000,
"maxRequestsPerSecond": 20,
"timeoutSeconds": 300
}
```
# 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 = {
"companies": [
"google",
"meta",
"apple"
],
"roles": [
"software-engineer"
]
};
// Run the Actor and wait for it to finish
const run = await client.actor("shhh_lab/levels-fyi-salary-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 = {
"companies": [
"google",
"meta",
"apple",
],
"roles": ["software-engineer"],
}
# Run the Actor and wait for it to finish
run = client.actor("shhh_lab/levels-fyi-salary-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 '{
"companies": [
"google",
"meta",
"apple"
],
"roles": [
"software-engineer"
]
}' |
apify call shhh_lab/levels-fyi-salary-scraper --silent --output-dataset
```
## MCP server setup
```json
{
"mcpServers": {
"apify": {
"command": "npx",
"args": [
"mcp-remote",
"https://mcp.apify.com/?tools=shhh_lab/levels-fyi-salary-scraper",
"--header",
"Authorization: Bearer "
]
}
}
}
```
## OpenAPI specification
```json
{
"openapi": "3.0.1",
"info": {
"title": "Levels Fyi Salary Scraper",
"description": "Scrape individual salary submissions from Levels.fyi — base, stock, bonus, TC by company, role, level, and location.",
"version": "0.0",
"x-build-id": "FZUgUSzlMzOVfBL94"
},
"servers": [
{
"url": "https://api.apify.com/v2"
}
],
"paths": {
"/acts/shhh_lab~levels-fyi-salary-scraper/run-sync-get-dataset-items": {
"post": {
"operationId": "run-sync-get-dataset-items-shhh_lab-levels-fyi-salary-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": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
},
"/acts/shhh_lab~levels-fyi-salary-scraper/runs": {
"post": {
"operationId": "runs-sync-shhh_lab-levels-fyi-salary-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor and returns information about the initiated run in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$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": {
"$ref": "#/components/schemas/runsResponseSchema"
}
}
}
}
}
}
},
"/acts/shhh_lab~levels-fyi-salary-scraper/run-sync": {
"post": {
"operationId": "run-sync-shhh_lab-levels-fyi-salary-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$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",
"required": [
"mode"
],
"properties": {
"mode": {
"title": "Scraping Mode",
"enum": [
"specific",
"companies"
],
"type": "string",
"description": "How to discover company × role combinations to scrape.",
"default": "specific"
},
"companies": {
"title": "Company Slugs",
"type": "array",
"description": "Company slugs to scrape (e.g. google, meta, apple). Find slugs in Levels.fyi URLs: levels.fyi/companies/{slug}. Used in 'specific' and 'companies' modes.",
"default": [
"google"
],
"items": {
"type": "string"
}
},
"roles": {
"title": "Roles",
"type": "array",
"description": "Roles to scrape. Only used in 'Specific' mode — completely ignored in 'Companies' mode.",
"items": {
"type": "string",
"enum": [
"software-engineer",
"product-designer",
"product-manager",
"data-scientist",
"management-consultant",
"investment-banker",
"software-engineering-manager",
"biomedical-engineer",
"civil-engineer",
"technical-program-manager",
"accountant",
"human-resources",
"marketing",
"marketing-operations",
"recruiter",
"sales",
"hardware-engineer",
"mechanical-engineer",
"solution-architect",
"business-analyst",
"customer-service",
"business-development",
"security-analyst",
"industrial-designer",
"fashion-designer",
"administrative-assistant",
"information-technologist",
"geological-engineer",
"financial-analyst",
"venture-capitalist",
"chief-of-staff",
"legal",
"program-manager",
"project-manager",
"data-science-manager",
"product-design-manager",
"founder",
"technical-writer",
"copywriter",
"sales-engineer",
"facilities-manager",
"property-manager",
"real-estate-agent",
"data-analyst",
"corp-dev",
"biz-ops",
"bizops-manager",
"partner-manager",
"customer-service-ops",
"ux-researcher",
"graphic-designer",
"electrical-engineer",
"controls-engineer",
"regulatory-affairs",
"physician",
"chemical-engineer",
"aerospace-engineer",
"materials-engineer",
"optical-engineer",
"mep-engineer",
"total-rewards",
"people-ops",
"actuary",
"underwriter",
"claims-adjuster",
"customer-success",
"toxicologist",
"meteorologist",
"revops",
"sales-enablement",
"prompt-engineer",
"trust-and-safety",
"tam",
"gtm-engineer",
"lab-tech",
"paralegal",
"compliance-officer",
"legal-ops",
"nurse",
"data-annotator"
],
"enumTitles": [
"Software Engineer",
"Product Designer",
"Product Manager",
"Data Scientist",
"Management Consultant",
"Investment Banker",
"Software Engineering Manager",
"Biomedical Engineer",
"Civil Engineer",
"Technical Program Manager",
"Accountant",
"Human Resources",
"Marketing",
"Marketing Operations",
"Recruiter",
"Sales",
"Hardware Engineer",
"Mechanical Engineer",
"Solution Architect",
"Business Analyst",
"Customer Service",
"Business Development",
"Cybersecurity Analyst",
"Industrial Designer",
"Fashion Designer",
"Administrative Assistant",
"Information Technologist",
"Geological Engineer",
"Financial Analyst",
"Venture Capitalist",
"Chief of Staff",
"Legal",
"Program Manager",
"Project Manager",
"Data Science Manager",
"Product Design Manager",
"Founder",
"Technical Writer",
"Copywriter",
"Sales Engineer",
"Facilities Manager",
"Property Manager",
"Real Estate Agent",
"Data Analyst",
"Corporate Development",
"Business Operations",
"Business Operations Manager",
"Partner Manager",
"Customer Service Operations",
"UX Researcher",
"Graphic Designer",
"Electrical Engineer",
"Controls Engineer",
"Regulatory Affairs",
"Physician",
"Chemical Engineer",
"Aerospace Engineer",
"Materials Engineer",
"Optical Engineer",
"MEP Engineer",
"Total Rewards",
"People Operations",
"Actuary",
"Underwriter",
"Claims Adjuster",
"Customer Success",
"Toxicologist",
"Meteorologist",
"Revenue Operations",
"Sales Enablement",
"Prompt Engineer",
"Trust and Safety",
"Technical Account Manager",
"Go-To-Market Engineer",
"Lab Technician",
"Paralegal",
"Compliance Officer",
"Legal Operations",
"Nurse",
"Data Annotator"
]
}
},
"maxResults": {
"title": "Max Results",
"minimum": 0,
"type": "integer",
"description": "Maximum number of rows to output. The actor stops once this limit is reached and saves all data collected. 0 = unlimited.",
"default": 1000
},
"maxRequestsPerSecond": {
"title": "Max Requests Per Second",
"minimum": 1,
"maximum": 50,
"type": "number",
"description": "Rate limit for HTTP requests.",
"default": 20
},
"timeoutSeconds": {
"title": "Timeout (seconds)",
"minimum": 30,
"maximum": 86400,
"type": "integer",
"description": "Maximum time the actor will run before gracefully stopping. The actor saves all data collected so far.",
"default": 300
}
}
},
"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
}
}
}
}
}
}
}
}
}
}
```