# Cutshort Jobs Search Scraper (`soft_alexist/cutshort-jobs-search-scraper`) Actor Scrape job listings from CutShort.io with a single configuration. Collect titles, skills, salary ranges, locations, company data, and hiring details for 200+ roles per URL — perfect for tech recruiters, HR teams, and job aggregators. - **URL**: https://apify.com/soft\_alexist/cutshort-jobs-search-scraper.md - **Developed by:** [Soft Alexist](https://apify.com/soft_alexist) (community) - **Categories:** Automation, Jobs, Developer tools - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing Pay per usage This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-usage ## 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 ## CutShort Jobs Scraper: Automate Tech Talent Search & Data Collection --- ### What Is CutShort.io? CutShort.io is a developer-focused job platform connecting tech companies with software engineers, mobile developers, data scientists, and other technology professionals. The platform hosts thousands of carefully vetted job opportunities across domains like Android development, backend engineering, DevOps, and more. Instead of manually browsing and extracting job data from search results, the **CutShort Jobs Scraper** automates extraction, delivering structured records with salary, skills, locations, and company information — all in seconds. --- ### Overview The **CutShort Jobs Scraper** is designed to extract job listings from CutShort search result pages, transforming unstructured listings into clean, queryable data. It serves: - **Tech recruiters** building candidate and market intelligence databases - **HR analytics teams** benchmarking compensation and skill demand - **Job aggregators** synchronizing data from multiple tech job boards - **Career analysts** tracking technology job market trends The scraper handles high-volume extraction efficiently, supporting up to 200 items per URL while maintaining data integrity through proxy-backed requests and failure tolerance. --- ### Input Format & Configuration The scraper accepts a JSON configuration object with three core parameters: ```json { "urls": [ "https://cutshort.io/jobs/android-developer-jobs" ], "ignore_url_failures": true, "max_items_per_url": 200 } ```` #### Configuration Parameters | Parameter | Type | Description | Example | |---|---|---|---| | `urls` | Array | List of CutShort job search result page URLs you want to scrape | `["https://cutshort.io/jobs/android-developer-jobs", "https://cutshort.io/jobs/python-developer-jobs"]` | | `ignore_url_failures` | Boolean | If `true`, the scraper continues running even if some URLs fail to load or timeout | `true` | | `max_items_per_url` | Integer | Maximum number of job listings extracted per URL (1-200). Higher values capture more listings but increase runtime | `200` | **Tips for input:** - Use CutShort search URLs (e.g., filtered by tech stack, location, or seniority level) - Set `max_items_per_url: 200` for comprehensive data collection - Enable `ignore_url_failures: true` for batch runs to prevent interruptions - Each URL typically contains 20-50 listings; adjust `max_items_per_url` based on your needs *** ### Output Format & Data Fields **Example output record:** ```json { "public_url": "https://cutshort.io/job/Business-Intelligence-Engineer-BI-Solutions-Data-Analyst-Bengaluru-Bangalore-Mumbai-Pune-Hyderabad-Noida-Gurugram-Chennai-Byteridge-n5kaFAa2", "headline": "Business Intelligence Engineer / BI Solutions / Data Analyst", "hiring_for_client": false, "all_skills": [ "Quciksight", "Quicksight", "Tableau", "PowerBI", "Python", "Business Intelligence (BI)", "SQL", "Data Analytics", "Data Visualization" ], "all_skills_obj": { "quciksight": "Quciksight", "quicksight": "Quicksight", "00442": "Tableau", "00658": "PowerBI", "00360": "Python", "00068": "Business Intelligence (BI)", "06684": "SQL", "00120": "Data Analytics", "00127": "Data Visualization" }, "salary_range": { "currency": "INR", "min": 900000, "max": 2200000, "user_min": 900000, "user_max": 2200000, "user_min_vanity": 1800000, "user_max_vanity": 2200000, "min_vanity": 1800000, "max_vanity": 2200000 }, "locations": [ "Bengaluru (Bangalore)", "Mumbai", "Pune", "Hyderabad", "Noida", "Gurugram", "Chennai" ], "company_details": { "_id": "5d7ce34aa66cbd1327993ffd", "name": "Byteridge", "logo": "https://cdnv2.cutshort.io/company-static/5d7ce34aa66cbd1327993ffd/user_uploaded_data/logos/byteridge_logo.jpeg", "og_image": "https://cdn.cutshort.io/public/socialshare-ogimage/id6a44b9a12f2b82d88b707077time1782889384198-og.jpg", "founded": 2008, "type": "Services", "size": "100-1000", "stage": "Profitable", "description": "

We are a technology company with a proven track record of partnering with organizations to deliver innovative mobile and cloud solutions & products. We believe that cloud and mobility are the means to deliver solutions to tomorrow’s challenges. Over the last 10 years, we have completed over 200 projects, and many of those have reached the top of the AppStores. We have worked across a number of categories including Fintech, Social, Retail, Enterprise, Lifestyle, Ticketing, Sports, Healthcare, Entertainment and many more.


We have worked with both Fortune 500 companies and innovative startups, and delivered successful products. We have a 40+ people team which, includes UI/UX designers, the best breed of engineers for iOS and Android, Full Stack Developers and Innovators. Other than design and development, Byteridge helps companies understand and define the product that needs to be built. This includes working with the stakeholders to understand the business, recognizing areas of improvement and aligning the project scope with the customers problems.

", "cover_picture_u_r_l": "https://cdn.cutshort.io/public/images/unauth_bgs/startups.jpg", "alias": "byteridge-Ddsgc1dp", "hiring_for_client": false, "followers_count": 4142, "sanitized_description": "

We are a technology company with a proven track record of partnering with organizations to deliver innovative mobile and cloud solutions & products. We believe that cloud and mobility are the means to deliver solutions to tomorrow’s challenges. Over the last 10 years, we have completed over 200 projects, and many of those have reached the top of the AppStores. We have worked across a number of categories including Fintech, Social, Retail, Enterprise, Lifestyle, Ticketing, Sports, Healthcare, Entertainment and many more.


We have worked with both Fortune 500 companies and innovative startups, and delivered successful products. We have a 40+ people team which, includes UI/UX designers, the best breed of engineers for iOS and Android, Full Stack Developers and Innovators. Other than design and development, Byteridge helps companies understand and define the product that needs to be built. This includes working with the stakeholders to understand the business, recognizing areas of improvement and aligning the project scope with the customers problems.

", "company_f_a_qs": [], "tech_stack": [], "photos": [], "highlight_team_members": [ { "name": "Keerthana Gracelin", "title": "", "linked_in": "https://www.linkedin.com/in/keerthana-gracelin-32a150198/", "profile_picture": "https://cdnv2.cutshort.io/company-static/5d7ce34aa66cbd1327993ffd/user_uploaded_data/team_member_profile_pictures/1632203658691.jpeg", "_id": "6a44bba8ab720942467ca6da" }, { "name": "Angeline Margaret B", "title": "", "linked_in": "https://www.linkedin.com/in/angeline-margaret-b-780aa0185/", "profile_picture": "https://cdnv2.cutshort.io/company-static/5d7ce34aa66cbd1327993ffd/user_uploaded_data/team_member_profile_pictures/1556522201279.jpeg", "_id": "6a44bba8ab720942467ca6db" }, { "name": "Sweety S", "title": "", "linked_in": "https://www.linkedin.com/in/sweety-s-637155159/", "profile_picture": "https://cdnv2.cutshort.io/company-static/5d7ce34aa66cbd1327993ffd/user_uploaded_data/team_member_profile_pictures/1782453788775.jpeg", "_id": "6a44bba8ab720942467ca6dc" } ], "sections_enabled": { "tech_stack": false, "highlight_team_members": true, "company_f_a_qs": false, "photos": false, "product_showcase": false, "video_url": false }, "product_showcase": [], "funding": "3", "new_size": "service_3", "links": { "website": "https://byteridge.com", "linkedin": "https://linkedin.com/company/byteridge-software-private-limited", "articles": [], "ambitionbox": "https://ambitionbox.com/byteridge", "facebook": "https://facebook.com/byteridge", "instagram": "https://instagram.com/byteridge", "twitter": "https://twitter.com/byteridge", "youtube": "https://youtube.com/watch", "about": "https://byteridge.com/about-us", "blog": "https://byteridge.com/blogs" } }, "exp_range": { "min": 4, "max_internal": 6, "max": 6, "min_vanity": 4, "max_vanity": 6 }, "sanitized_comment": "

Byteridge is seeking a Business Intelligence Solutions engineer to drive

transformative analytics and AI-powered insights for our strategic customers across India. You will lead

complex deployments of Amazon QuickSuite and related AWS analytics services, working directly with

customers to accelerate their data-driven transformation.

This role combines deep technical expertise in business intelligence, data integration, and AI automation to deliver production-ready solutions that unlock the full potential of customer data across multi-cloud environments.


What You'll Do

Solution Architecture & Deployment

• Lead end-to-end deployments of Amazon QuickSuite, QuickSight, and AWS analytics solutions forstrategic customers

• Design and implement comprehensive BI architectures that integrate with diverse data sourcesacross multi-cloud environments

• Develop custom connectors, APIs, and MCP (Model Context Protocol) integrations to extendplatform capabilities

• Configure and optimize Agents, Spaces, Topics, and Dashboards for customer-specific use cases

Technical Development & Integration

• Build custom connectors and integrations to connect QuickSuite with enterprise data sources

• Develop API-based solutions and automation workflows to streamline BI operations

• Implement data pipelines connecting multi-cloud data sources (AWS, Azure, GCP) to analyticsplatforms

• Create reusable templates, accelerators, and best practices for rapid deployment

Customer Engagement & Enablement

• Partner with customer teams to understand business requirements and translate them into

technical solutions

• Provide technical guidance on dashboard design, data modeling, and visualization best practices

• Train customer teams on QuickSuite capabilities, agent configuration, and self-service analytics

• Identify expansion opportunities and drive adoption of advanced analytics features


What We're Looking For

Core Qualifications

• Bachelor's degree in Computer Science, Data Science, Engineering, or equivalent practical

experience

• 4-6 years of experience in business intelligence, data analytics, or technical consulting roles

• Strong programming skills in Python, JavaScript, SQL, or similar languages

• Experience with BI platforms, data visualization, and analytics solution deployment

Technical Expertise (High-Level Alignment)

• Proficiency with business intelligence and data visualization tools (QuickSight, Tableau, Power BI, or

similar)

• Experience with API development, REST services, and integration patterns

• Understanding of data modeling, ETL/ELT processes, and data warehouse concepts

• Familiarity with AWS analytics services (QuickSight, Athena, Glue, Redshift) or equivalent platforms

Preferred Experience

• Hands-on experience with Amazon QuickSuite or similar AI-powered analytics platforms

• Knowledge of MCP (Model Context Protocol) and custom connector development

• Experience configuring AI agents, knowledge bases, and automated workflows

• Background working with multi-cloud data sources and hybrid architectures

• Understanding of data governance, security, and compliance requirements

Essential Attributes

• Excellent problem-solving skills with ability to navigate ambiguous requirements

• Strong communication skills to engage with technical and business stakeholders

• Ability to manage multiple customer engagements and prioritize effectively

• Customer-focused mindset with commitment to delivering measurable business outcomes







", "role_types": [ "full_time" ], "remote_type": "remote_not_okay", "created_by": { "name": "Sweety S", "profile_picture": "https://cdn.cutshort.io/public/material-letter-icons/S.png" }, "company_id": { "alias": "byteridge-Ddsgc1dp", "name": "Byteridge", "_id": "5d7ce34aa66cbd1327993ffd" }, "auth_apply_url": "https://cutshort.io/profile/view/j/6a4548d8c38b112c43b3aa7e", "is_job_saved": false, "salary_range_text": "₹18L - ₹22L / yr", "locations_text": "Bengaluru (Bangalore), Mumbai, Pune, Hyderabad, Noida, Gurugram, Chennai", "from_url": "https://cutshort.io/jobs/startup-jobs" } ``` Each scraped job returns a structured record containing 18 essential fields. Here's what each field captures: #### Identification & URLs | Field | Meaning & Use | |---|---| | `ID` | Unique internal identifier for the job posting within CutShort's system. Use this to track or reference specific jobs in your database. | | `Public URL` | Direct link to the job posting on CutShort. Share this with candidates or store for easy access. | | `Headline` | Job title as displayed on CutShort (e.g., "Senior Android Developer", "Full Stack Engineer"). Use for quick job identification. | #### Job Details & Requirements | Field | Meaning & Use | |---|---| | `All Skills` | Comma-separated list of required/preferred technical skills (e.g., "Kotlin, Java, Android SDK, Firebase"). Useful for matching candidates to roles or analyzing skill demand trends. | | `All Skills Object` | Structured object version of skills. Enables advanced filtering and analysis by individual skill. | | `Experience Range` | Required years of experience (e.g., "2-5 years", "5+ years"). Helps segment roles by seniority level. | | `Role Types` | Position classifications (e.g., Full-time, Contract, Part-time). Indicates employment contract type. | | `Remote Type` | Work flexibility indicator (e.g., Fully Remote, Hybrid, On-site). Critical for candidate filtering and location analysis. | #### Compensation & Location | Field | Meaning & Use | |---|---| | `Salary Range` | Structured salary data (typically min-max in local currency). Use for compensation benchmarking and competitive analysis. | | `Salary Range Text` | Human-readable salary display (e.g., "₹12,00,000 - ₹18,00,000 per annum"). For reporting and transparency. | | `Locations` | Array of job location objects with city, state, country data. Enables geographic filtering and market analysis. | | `Locations Text` | Formatted location string (e.g., "Bangalore, Delhi, Remote"). Quick reference for candidate location preferences. | #### Company & Hiring Information | Field | Meaning & Use | |---|---| | `Hiring For Client` | Name of the hiring company. Identifies the employer. | | `Company Details` | Metadata about the employer (size, industry, description). Provides context about hiring organization. | | `Company ID` | Unique identifier for the company. Use for grouping jobs by employer or company analysis. | | `Created By` | Name/ID of the person who posted the job on CutShort. Useful for recruiter attribution or contact. | #### Application & Metadata | Field | Meaning & Use | |---|---| | `Auth Apply URL` | Authenticated link for direct job applications through CutShort. Enables programmatic tracking of applications. | | `Sanitized Comment` | Cleaned plain-text description of the role, requirements, and company culture. Ready for display or text analysis. | | `Is Job Saved` | Boolean flag indicating if the job is in your saved list. Track favorites for follow-up. | *** ### How to Use Step-by-Step 1. **Identify target URLs** — Go to CutShort.io and navigate to a jobs search page (e.g., filter by Android Developer, Python, DevOps). Copy the page URL. 2. **Prepare configuration** — Create a JSON object with your URLs and settings: ```json { "urls": ["https://cutshort.io/jobs/android-developer-jobs"], "max_items_per_url": 200, "ignore_url_failures": true } ``` 3. **Run the scraper** — Submit the configuration and monitor the execution. 4. **Download results** — Export data as JSON, CSV, or Excel once the run completes. 5. **Process & analyze** — Load results into your database, spreadsheet, or BI tool for further analysis. **Troubleshooting:** - If `max_items_per_url` is too high and the scraper times out, reduce it to 50-100. - Ensure URLs point to job *search result* pages, not individual job postings. - Use `ignore_url_failures: true` for robustness when scraping multiple URLs. *** ### Use Cases & Business Value - **Talent acquisition:** Build a searchable database of tech jobs for targeted sourcing and market analysis - **Compensation benchmarking:** Compare salary ranges across companies, roles, and geographies - **Skill demand tracking:** Identify trending technologies and skills in demand (Kotlin, React, Python, etc.) - **Competitive intelligence:** Monitor hiring by competitors across different tech stacks - **Job board aggregation:** Sync CutShort data into custom job portals or internal talent platforms - **Market research:** Analyze seniority distribution, remote work trends, and geographic hiring patterns By automating data extraction, your team eliminates manual work and gains actionable intelligence in minutes instead of hours. *** ### Conclusion The **CutShort Jobs Scraper** streamlines tech recruitment research by extracting structured job data at scale. With 18 detailed fields covering skills, salary, location, and company information, you can build powerful datasets for talent intelligence, benchmarking, and recruitment automation. Whether you're a recruiter, HR analyst, or developer building a job platform, this scraper turns CutShort listings into actionable insights. # 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://cutshort.io/jobs/android-developer-jobs" ], "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://cutshort.io/jobs/android-developer-jobs" ], "ignore_url_failures": true, "max_items_per_url": 20 }; // Run the Actor and wait for it to finish const run = await client.actor("soft_alexist/cutshort-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://cutshort.io/jobs/android-developer-jobs"], "ignore_url_failures": True, "max_items_per_url": 20, } # Run the Actor and wait for it to finish run = client.actor("soft_alexist/cutshort-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://cutshort.io/jobs/android-developer-jobs" ], "ignore_url_failures": true, "max_items_per_url": 20 }' | apify call soft_alexist/cutshort-jobs-search-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=soft_alexist/cutshort-jobs-search-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Cutshort Jobs Search Scraper", "description": "Scrape job listings from CutShort.io with a single configuration. Collect titles, skills, salary ranges, locations, company data, and hiring details for 200+ roles per URL — perfect for tech recruiters, HR teams, and job aggregators.", "version": "0.0", "x-build-id": "ZwqAZAgvaKTowrApq" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/soft_alexist~cutshort-jobs-search-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-soft_alexist-cutshort-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/soft_alexist~cutshort-jobs-search-scraper/runs": { "post": { "operationId": "runs-sync-soft_alexist-cutshort-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/soft_alexist~cutshort-jobs-search-scraper/run-sync": { "post": { "operationId": "run-sync-soft_alexist-cutshort-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 } } } } } } } } } } ```