# Bayt Jobs Scraper (`agentx/bayt-jobs-scraper`) Actor Scrape Bayt job listings across GCC and MENA markets by keyword, country, and location. Returns job, company, salary, description, location, and posting metadata when available. - **URL**: https://apify.com/agentx/bayt-jobs-scraper.md - **Developed by:** [AgentX](https://apify.com/agentx) (community) - **Categories:** Jobs, Lead generation, Agents - **Stats:** 3 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $3.20 / 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. 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 ## Bayt Jobs Scraper - Job Listings Data Extraction API **Bayt Jobs Scraper is a MENA-focused job listings API that extracts structured Bayt.com postings by keyword, country, and location for recruitment analytics, salary benchmarking, regional hiring research, and job board enrichment. It returns normalized job records with title, company, location, description, salary fields, employment details, posting URL, and source metadata when available.** The Bayt coverage supports United Arab Emirates, Saudi Arabia, Qatar, Kuwait, Oman, Bahrain, Egypt, and Pakistan. The default country is United Arab Emirates because Bayt has strong UAE and Gulf-region job inventory, and `Sales Executive` is used as the default keyword based on Bayt/UAE demand signals. Up to 10,000 job records can be requested per run, with pay-per-result pricing and no monthly minimum. [![Bayt](https://img.shields.io/badge/Bayt-Jobs_API-2563eb?style=for-the-badge)](https://apify.com/agentx/bayt-jobs-scraper?fpr=aiagentapi) [![Hiring Intelligence](https://img.shields.io/badge/Hiring_Intelligence-0f766e?style=for-the-badge)](https://apify.com/agentx/bayt-jobs-scraper?fpr=aiagentapi) [![Pay Per Result](https://img.shields.io/badge/Pay_Per_Result-$3.20%2F1K-7c3aed?style=for-the-badge)](https://apify.com/agentx/bayt-jobs-scraper?fpr=aiagentapi) --- ### Why Choose This API #### Bayt MENA Job Data With Regional Hiring Coverage **Structured job records** Get one normalized dataset item per job posting with consistent fields for title, company, location, salary, job description, posting date, and source URL. **Platform-specific extraction** This actor focuses on Bayt only. Inputs and documentation are scoped to what the platform coverage supports, avoiding unsupported filters. **Salary and compensation signals** When the source exposes salary data, the actor maps salary minimum, maximum, currency, and interval into structured fields. The `currency` input can normalize salary values for cross-market comparison. **Location intelligence** Use country and location inputs to target the right market. Output includes platform location text and structured fields when available. **Scalable Apify workflow** Results are stored in the default dataset and can be exported as JSON, CSV, Excel, XML, RSS, or consumed with the Apify REST API and client SDKs. **Transparent pricing** The actor uses a pay-per-result model. You pay a small start event plus a flat result event for each job saved to the dataset. --- ### Quick Start Guide #### How to Extract Bayt Job Data in 3 Steps ##### Step 1: Define Your Search Parameters Enter a high-coverage keyword such as `Sales Executive`, select a supported country, optionally add a city or region, and set `max_results`. ##### Step 2: Configure and Run the Actor [Open Actor Input](https://console.apify.com/actors/agentx/bayt-jobs-scraper/input?fpr=aiagentapi) Set the parameters, then click **Start**. Use broad keywords for market scans and specific titles for sourcing workflows. ##### Step 3: Download Your Data Export the default dataset as JSON, CSV, Excel, XML, or pull items programmatically through the Apify API. --- ### Input Parameters #### Required Configuration Fields | Parameter | Type | Required | Description | Example | | --- | --- | --- | --- | --- | | `keyword` | string | Yes | Job title, skill, company, or search keyword | `"Sales Executive"` | | `country` | select | Yes | Supported country or market | `"United Arab Emirates"` | | `max_results` | integer | Yes | Maximum job records to extract, from 10 to 10,000 | `100` | | `location` | string | No | City, region, or location text inside the selected country | `"Dubai"` | | `currency` | select | No | Target currency for salary normalization | `"AED"` | #### Example Input Configuration ```json { "keyword": "Sales Executive", "country": "United Arab Emirates", "location": "Dubai", "max_results": 100, "currency": "AED" } ```` #### Date Format Options This actor does not expose `posted_since` because Bayt does not consistently provide a reliable posting-date filter for this coverage. Posted-date values are still returned in output when the source listing provides them. #### Location Formatting Best Practices - Use city and region names when you need local results. - Use country-level searches when you want maximum coverage for a keyword. - Keep keywords specific enough to avoid unrelated aggregator matches, but broad enough to return enough results for analysis. - If remote status is available in source data, it is returned as an output signal rather than an input filter. #### Supported Countries for Job Scraping The Bayt coverage supports United Arab Emirates, Saudi Arabia, Qatar, Kuwait, Oman, Bahrain, Egypt, and Pakistan. The default country is United Arab Emirates because Bayt has strong UAE and Gulf-region job inventory, and `Sales Executive` is used as the default keyword based on Bayt/UAE demand signals. #### Country-Aware Platform Routing This is a single-platform actor. It does not route requests to other job boards. If you need automatic routing across multiple sources, use [All Jobs Scraper](https://apify.com/agentx/all-jobs-scraper?fpr=aiagentapi). *** ### Output Data Schema #### Complete Job Listing Data Structure Each extracted Bayt job is stored as one dataset item. Field availability depends on what the source listing exposes, but the actor maps source data into a consistent job schema. #### Job Metadata Fields | Field | Description | | --- | --- | | `platform` | Source platform label, usually Bayt | | `platform_url` | Bayt job URL | | `official_url` | Apply or original URL when available | | `title` | Job position title | | `company_name` | Hiring company name | | `company_url` | Company URL when available | | `company_logo` | Company logo URL when available | | `location` | Job location text | | `posted_date` | Posting date when available | | `valid_through` | Expiration date when available | | `description` | Job description content | | `job_type` | Employment type or tag text when available | | `requirements` | Requirements parsed from structured job data when available | | `salary_minimum` | Minimum salary when available | | `salary_maximum` | Maximum salary when available | | `salary_currency` | Salary currency | | `salary_period` | Salary interval | #### Employment Details Employment fields can include `job_type`, `is_remote`, `requirements`, `skills`, and other platform-specific values when the source exposes those values. #### Salary Information Salary fields include `salary_minimum`, `salary_maximum`, `salary_currency`, and `salary_period`. Salary extraction is source-dependent and may be empty for valid jobs. #### Company Data Company fields can include `company_name`, `company_url`, `company_logo`, `company_website`, `company_industry`, and related metadata when available. #### Example JSON Output ```json { "platform": "Bayt", "platform_url": "https://www.bayt.com/en/uae/jobs/example-123456/", "title": "Sales Executive", "company_name": "Example Trading LLC", "location": "Dubai, United Arab Emirates", "description": "Manage client relationships and grow regional sales accounts.", "salary_currency": "AED", "salary_minimum": 8000, "salary_maximum": 12000 } ``` #### Export Formats - **JSON** - Full structured records with nested objects and arrays preserved. - **CSV** - Spreadsheet-compatible exports for BI and reporting workflows. - **Excel** - Download-ready tabular files for analysts and recruiters. - **XML / RSS** - Feed-style exports where supported by Apify datasets. - **API Access** - Pull items programmatically via the Apify REST API or official SDKs. *** ### Integration Examples #### Actor ID for Platform Integration ```text agentx/bayt-jobs-scraper ``` #### Make.com Setup 1. Add Apify **Run an Actor**. 2. Set Actor to `agentx/bayt-jobs-scraper`. 3. Paste your input JSON. 4. Enable synchronous run if your workflow should wait. 5. Read results with **Get dataset items**. #### N8N.io Setup 1. Add the Apify node. 2. Choose **Run an Actor and get dataset**. 3. Use Actor ID `agentx/bayt-jobs-scraper`. 4. Map dataset items into your workflow. #### Python Integration Example ```python from apify_client import ApifyClient client = ApifyClient("YOUR_API_TOKEN") run_input = { "keyword": "Sales Executive", "country": "United Arab Emirates", "location": "Dubai", "max_results": 100, "currency": "AED" } run = client.actor("agentx/bayt-jobs-scraper").call(run_input=run_input) items = list(client.dataset(run["defaultDatasetId"]).iterate_items()) print(f"Fetched {len(items)} jobs") ``` #### JavaScript/Node.js Integration ```javascript import { ApifyClient } from 'apify-client'; const client = new ApifyClient({ token: 'YOUR_API_TOKEN' }); const input = { "keyword": "Sales Executive", "country": "United Arab Emirates", "location": "Dubai", "max_results": 100, "currency": "AED" }; const run = await client.actor('agentx/bayt-jobs-scraper').call(input); const { items } = await client.dataset(run.defaultDatasetId).listItems(); console.log(`Fetched ${items.length} jobs`); ``` #### JSON-LD Metadata ```json { "@context": "https://schema.org", "@type": "SoftwareApplication", "name": "Bayt Jobs Scraper", "applicationCategory": "BusinessApplication", "operatingSystem": "Cloud API", "url": "https://apify.com/agentx/bayt-jobs-scraper?fpr=aiagentapi", "description": "Scrape Bayt job listings across GCC and MENA markets by keyword, country, and location. Returns job, company, salary, description, location, and posting metadata when available.", "offers": { "@type": "Offer", "price": "0.0032", "priceCurrency": "USD" } } ``` *** ### Pricing & Cost Calculator #### Transparent Pay-Per-Use Model | Event Type | Price | Description | | --- | --- | --- | | **Actor Start** | `$0.01` | One-time charge per Actor run | | **result** | `$0.0032` | Charged for each Bayt job posting saved to the default dataset | #### Cost Examples **Small Scale** (100 jobs): - Job Data: 100 × `$0.0032` = `$0.32` - Actor Start: `$0.01` - **Total**: `$0.33` **Medium Scale** (1,000 jobs): - Job Data: 1,000 × `$0.0032` = `$3.20` - Actor Start: `$0.01` - **Total**: `$3.21` **Large Scale** (10,000 jobs): - Job Data: 10,000 × `$0.0032` = `$32.00` - Actor Start: `$0.01` - **Total**: `$32.01` #### Competitive Pricing Comparison | Feature | Bayt Jobs Scraper | Manual Collection | Generic Browser Scraper | Enterprise Data Vendor | | --- | --- | --- | --- | --- | | Cost model | Pay per result | Labor hours | Compute + maintenance | Contract pricing | | API access | Yes | No | Custom work required | Usually yes | | Output schema | Structured job data | Inconsistent | Custom parsing required | Varies | | Maintenance | Managed actor | Manual | User-owned | Vendor-owned | | Best for | Fast job data extraction | Small one-off checks | Custom internal crawlers | Large procurement workflows | *** ### Use Cases & Applications #### Recruitment & Talent Acquisition **Hiring pipeline monitoring** Track new jobs by title, company, location, and posting date to understand employer demand and recruitment velocity. **Candidate matching workflows** Feed structured job descriptions, requirements, skills, and locations into candidate matching systems or internal search tools. **Competitor hiring analysis** Monitor which companies are expanding, what roles they hire for, and how job requirements shift across locations. #### Market Research & Business Intelligence **Labor market dashboards** Build dashboards that show role demand, location density, salary availability, and company-level hiring patterns. **Salary benchmarking** Analyze published salary ranges where available and normalize values into the selected currency. **Regional market entry analysis** Compare job volume and role mix across countries, cities, or regions before hiring or expansion decisions. #### AI & Machine Learning Applications **Training data for job matching** Use job descriptions and requirements as training or evaluation data for semantic search, matching, classification, and recommendation systems. **Skill extraction and taxonomy mapping** Map job descriptions into standardized skills, roles, departments, and seniority levels for workforce intelligence. **Automated alerts** Trigger notifications when new jobs matching a keyword, company, salary, or location appear in the dataset. #### Workforce Planning & HR Analytics **Skills gap analysis** Identify commonly requested skills and qualifications in job postings to guide training plans and workforce planning. **Hiring trend reports** Build weekly or monthly reports that summarize job volume, salary ranges, and demand by role or location. **Talent market benchmarking** Compare hiring signals across companies and geographies for recruiting strategy and compensation planning. #### Career Services & Education **Career guidance** Use live job market data to inform career advice, resume coaching, and learning path recommendations. **Curriculum alignment** Analyze job requirements and skills to keep courses aligned with employer demand. **Student job feeds** Power filtered job feeds for students, alumni, or workforce development programs. *** ### FAQ #### How do I scrape Bayt jobs with this actor? Open the actor input page, set `keyword`, `country`, and `max_results`, add an optional `location`, and run the actor. Results are saved in the default Apify dataset. #### What is included in each Bayt job record? Typical records include title, company, location, platform URL, description, posting date, salary fields, and source metadata when available. #### How many jobs can I extract per run? The input schema allows up to 10,000 requested results. Actual output depends on source availability, keyword breadth, selected location, available result volume, and source availability. #### Which countries are supported? The Bayt coverage supports United Arab Emirates, Saudi Arabia, Qatar, Kuwait, Oman, Bahrain, Egypt, and Pakistan. The default country is United Arab Emirates because Bayt has strong UAE and Gulf-region job inventory, and `Sales Executive` is used as the default keyword based on Bayt/UAE demand signals. #### How fresh is the data? The actor fetches live source results at run time. Posted-date values are returned in output when the source provides them. #### Why are some salary fields empty? Salary fields are populated only when the source listing publishes salary information. Many employers do not include salary ranges in every job post. #### Why are some company fields empty? Company metadata depends on what the source returns for a listing. The actor maps available values and leaves unavailable fields empty instead of fabricating data. #### Can I integrate this with Make, N8N, Zapier, or my own backend? Yes. Use the Apify API, official Python and JavaScript clients, Make's Apify modules, N8N's Apify node, or dataset export URLs. #### What if no jobs are found? Try a broader keyword, remove narrow location filters, increase `max_results`, or use a country-level search. #### Is this compatible with AI frameworks? Yes. The JSON output can be used with LangChain, vector databases, custom ranking systems, enrichment workflows, and internal recruitment agents. *** ### SEO Keywords & Search Terms #### Primary Keywords Bayt scraper API, Bayt jobs scraper, Bayt.com job listings API, UAE jobs scraper, GCC job data API #### Long-Tail Keywords how to scrape Bayt jobs, extract Bayt job descriptions, Bayt UAE salary data scraper, Bayt recruitment analytics dataset, MENA job listings API #### Industry Terms job scraping API, job board scraper, job data extraction, hiring intelligence API, recruitment analytics, labor market data, salary benchmarking, job listing dataset, workforce analytics, talent intelligence. #### Location-Based Keywords country job data API, city job scraper, remote jobs dataset, regional hiring trends, local job market intelligence, international job listings API. #### Use Case Keywords competitor hiring monitoring, job board enrichment, talent market research, salary range extraction, skills demand tracking, recruitment automation, AI job matching dataset. *** ### Trust & Certifications - **Public data workflow** - Designed for publicly available job listing data. - **Transparent billing** - Pay-per-result pricing with clear start and result events. - **API-first delivery** - Works with Apify datasets, REST API, Python, JavaScript, Make, and N8N. - **Structured output** - Normalized fields reduce cleanup work for analysts and engineers. - **Maintenance-oriented design** - Platform-specific parsing can be updated as source pages evolve. *** ### Legal & Compliance #### Data Rights & Usage This actor extracts publicly available job listing data. Users are responsible for ensuring their use of output data complies with applicable laws, contractual requirements, and internal policies. #### Privacy Compliance The actor is intended for job listing and employer-side market intelligence workflows, not for collecting private candidate data. Users should apply GDPR, CCPA, and other privacy requirements to downstream storage and processing. #### Platform Terms of Service Users must review and comply with Bayt terms and any applicable policies before using extracted data in production workflows. #### Enterprise Support For enterprise usage, compliance questions, private deployments, or custom data workflows, contact [AgentX support](https://t.me/AiAgentApi). *** ### Related Tools #### Jobs & Hiring - **[All Jobs Scraper](https://apify.com/agentx/all-jobs-scraper?fpr=aiagentapi)** - Multi-Platform Job Listings Intelligence API - **[Glassdoor Hiring Scraper](https://apify.com/agentx/glassdoor-hiring-scraper?fpr=aiagentapi)** - Glassdoor Job Listings Intelligence API - **[Glints Employer Data Extractor](https://apify.com/agentx/glints-employer-data-extractor?fpr=aiagentapi)** - Glints Employer Intelligence API - **[Glints Jobs Data Extractor](https://apify.com/agentx/glints-jobs-data-extractor?fpr=aiagentapi)** - Glints Job Listings Intelligence API - 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Zomato Restaurant Search Intelligence API #### Other - **[Global Weather Scraper](https://apify.com/agentx/global-weather-scraper?fpr=aiagentapi)** - Global Weather Intelligence API *** ### Support & Community - **Community**: [@Apify\_Actor](https://t.me/Apify_Actor) - **Contact Team**: [@AiAgentApi](https://t.me/AiAgentApi) - **All AgentX APIs**: *** **Last Updated:** May 25, 2026 # Actor input Schema ## `keyword` (type: `string`): Job title, skill, or company name to search for ## `country` (type: `string`): Country where the target job listings are located ## `max_results` (type: `integer`): Maximum number of jobs to return ## `location` (type: `string`): City or region to focus the job search results on ## `currency` (type: `string`): Target currency for converting salary figures ## Actor input object example ```json { "keyword": "Sales Executive", "country": "United Arab Emirates", "max_results": 10, "currency": "AED" } ``` # Actor output Schema ## `results` (type: `string`): All job listings found across platforms with full details including salary, company info, and contact details # 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 = { "keyword": "Sales Executive", "country": "United Arab Emirates", "max_results": 10, "currency": "AED" }; // Run the Actor and wait for it to finish const run = await client.actor("agentx/bayt-jobs-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 = { "keyword": "Sales Executive", "country": "United Arab Emirates", "max_results": 10, "currency": "AED", } # Run the Actor and wait for it to finish run = client.actor("agentx/bayt-jobs-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 '{ "keyword": "Sales Executive", "country": "United Arab Emirates", "max_results": 10, "currency": "AED" }' | apify call agentx/bayt-jobs-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=agentx/bayt-jobs-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Bayt Jobs Scraper", "description": "Scrape Bayt job listings across GCC and MENA markets by keyword, country, and location. Returns job, company, salary, description, location, and posting metadata when available.", "version": "1.0", "x-build-id": "5KqWiaSQ0DYJcdzRX" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/agentx~bayt-jobs-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-agentx-bayt-jobs-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/agentx~bayt-jobs-scraper/runs": { "post": { "operationId": "runs-sync-agentx-bayt-jobs-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/agentx~bayt-jobs-scraper/run-sync": { "post": { "operationId": "run-sync-agentx-bayt-jobs-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "keyword", "country", "max_results" ], "properties": { "keyword": { "title": "🔍 Keyword", "type": "string", "description": "Job title, skill, or company name to search for" }, "country": { "title": "🌍 Country", "enum": [ "Bahrain", "Egypt", "Kuwait", "Oman", "Pakistan", "Qatar", "Saudi Arabia", "United Arab Emirates" ], "type": "string", "description": "Country where the target job listings are located" }, "max_results": { "title": "📊 Max Results", "minimum": 10, "maximum": 10000, "type": "integer", "description": "Maximum number of jobs to return" }, "location": { "title": "📍 Location", "type": "string", "description": "City or region to focus the job search results on" }, "currency": { "title": "💱 Currency", "enum": [ "AED", "AFN", "ALL", "AMD", "ANG", "AOA", "ARS", "AUD", "AWG", "AZN", "BAM", "BBD", "BDT", "BGN", "BHD", "BIF", "BMD", "BND", "BOB", "BRL", "BSD", "BTN", "BWP", "BYN", "BZD", "CAD", "CDF", "CHF", "CLF", "CLP", "CNH", "CNY", "COP", "CRC", "CUP", "CVE", "CZK", "DJF", "DKK", "DOP", "DZD", "EGP", "ERN", "ETB", "EUR", "FJD", "FKP", "FOK", "GBP", "GEL", "GGP", "GHS", "GIP", "GMD", "GNF", "GTQ", "GYD", "HKD", "HNL", "HRK", "HTG", "HUF", "IDR", "ILS", "IMP", "INR", "IQD", "IRR", "ISK", "JEP", "JMD", "JOD", "JPY", "KES", "KGS", "KHR", "KID", "KMF", "KRW", "KWD", "KYD", "KZT", "LAK", "LBP", "LKR", "LRD", "LSL", "LYD", "MAD", "MDL", "MGA", "MKD", "MMK", "MNT", "MOP", "MRU", "MUR", "MVR", "MWK", "MXN", "MYR", "MZN", "NAD", "NGN", "NIO", "NOK", "NPR", "NZD", "OMR", "PAB", "PEN", "PGK", "PHP", "PKR", "PLN", "PYG", "QAR", "RON", "RSD", "RUB", "RWF", "SAR", "SBD", "SCR", "SDG", "SEK", "SGD", "SHP", "SLE", "SLL", "SOS", "SRD", "SSP", "STN", "SYP", "SZL", "THB", "TJS", "TMT", "TND", "TOP", "TRY", "TTD", "TVD", "TWD", "TZS", "UAH", "UGX", "USD", "UYU", "UZS", "VES", "VND", "VUV", "WST", "XAF", "XCD", "XCG", "XDR", "XOF", "XPF", "YER", "ZAR", "ZMW", "ZWG", "ZWL" ], "type": "string", "description": "Target currency for converting salary figures" } } }, "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 } } } } } } } } } } ```