# Google Scholar Scraper - Low-cost๐Ÿ’ฒ๐Ÿ”ฅ๐Ÿ“š๐ŸŽ“ (`delectable_incubator/google-scholar-scraper-low-cost`) Actor Scrape Google Scholar academic papers ๐Ÿ“š๐Ÿ” with a powerful research scraper. Extract paper titles, authors, publication dates, journals/sources, citations, and direct links to full texts. Ideal for academic research, literature reviews, citation analysis, AI/NLP training, and knowledge discovery ๐Ÿš€ - **URL**: https://apify.com/delectable\_incubator/google-scholar-scraper-low-cost.md - **Developed by:** [Prime Scrape](https://apify.com/delectable_incubator) (community) - **Categories:** SEO tools, Automation, AI - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $0.00005 / actor start This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage. 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

PrimeScrape Google Scholar Scraper

## ๐Ÿ“š๐ŸŽ“ Google Scholar Scraper | Academic Papers & Research Data Extractor | Apify Actor ### ๐Ÿš€ Extract Google Scholar Data in Seconds (No Code) The **Google Scholar Scraper (PrimeScrape Apify Actor)** is a powerful, scalable and SEO-optimized academic data extraction tool designed to help you scrape research papers, citations, authors, and scholarly metadata from Google Scholar in bulk. Perfect for researchers, data analysts, AI training datasets, SEO content teams, universities, and market intelligence professionals. --- ### ## ๐Ÿ”ฅ Why This Google Scholar Scraper? โœ” Best Google Scholar scraper on Apify โœ” Supports bulk keyword & author scraping โœ” Fast & scalable academic data extraction โœ” 100% structured JSON / CSV / Excel output โœ” Ideal for research, AI & bibliometric analysis โœ” No coding required โœ” Works globally ๐ŸŒ --- ### ๐ŸŽฏ What This Scraper Does This Apify Actor extracts real-time academic results from Google Scholar search pages. #### ๐Ÿ“Œ Core Features: โœ… Scrape Google Scholar search results โœ… Bulk keyword, topic, or author scraping (SEO BOOST ๐Ÿš€) โœ… Extract titles, authors, citations, year, snippets โœ… Extract publication sources & domains โœ… Extract direct article & PDF links โœ… Pagination handling for large datasets โœ… Clean structured dataset output โœ… High-speed extraction engine ### โšก Input Configuration #### ๐Ÿ”ฅ BULK KEYWORD MODE (SEO BOOST ๐Ÿš€) ```` { "keywords": \[ "artificial intelligence", "machine learning", "data science", "blockchain technology", "neural networks", "computer vision" ], "language": "en", "country": "US", "max\_items": 200 } ``` ### ๐Ÿ“Š Extracted Academic Data | Field | Description | | -------- | -------------------------------- | | title | Article title | | authors | Authors + publication year | | snippet | Short abstract/preview | | source | Journal or website | | link | Direct article URL | | pdf_link | PDF download link (if available) | | domain | Source domain | | cited_by | Citation count | | versions | Number of versions | --- ### ๐Ÿ’ก Use Cases ๐Ÿ“š Academic research automation ๐Ÿง  AI training datasets ๐Ÿ“Š Bibliometric analysis ๐ŸŽ“ Thesis & literature reviews ๐Ÿ” Scientific trend analysis ๐Ÿข R&D intelligence ๐ŸŒ Global research monitoring --- ### ๐Ÿš€ Key Features โšก Bulk keyword & author scraping ๐ŸŒ Global academic coverage ๐Ÿ“Œ Smart pagination system ๐Ÿง  Clean structured output ๐Ÿ“Š High-speed extraction engine ๐Ÿ” Auto retry system ๐Ÿ’พ Export-ready datasets โš™๏ธ Apify cloud scalable execution --- ### ๐Ÿ“ค Output Formats โœ” JSON โœ” CSV โœ” Excel โœ” XML โœ” HTML --- ### ๐Ÿ“ฆ Example Output ``` { "Id": 1, "Title": "The rise of socialbots", "Authors & Year": "E Ferrara, O Varol, 2016", "Source": "ACM", "Snippet": "Overview of socialbot detection challenges...", "Link": "https://dl.acm.org/...", "PDF Link": "https://dl.acm.org/pdf/...", "Domain": "dl.acm.org", "Cited\_by": "1250", "Versions": "18" } ```` --- ### ๐Ÿ”ฅ Why This is the BEST Google Scholar Scraper โœ” Optimized for Apify ranking โœ” High-performance scraping engine โœ” Bulk keyword support โœ” Clean structured research datasets โœ” Enterprise-ready scalability โœ” Perfect for SEO & AI datasets --- ### ๐Ÿ’ธ Pricing ๐Ÿ’ณ $1.99 / 1,000 results --- ### โ“ FAQ Can I scrape multiple topics? Yes โ€” bulk keyword mode supported. Is it good for AI training? Yes โ€” perfect for LLM datasets. Is coding required? No โ€” 100% no-code. Can I export data? Yes โ€” JSON, CSV, Excel, XML. --- ### โš ๏ธ Disclaimer This tool is not affiliated with Google or Google Scholar. --- ### ๐ŸŒ PrimeScrape Ecosystem ๐Ÿ“Š Research scraping ๐Ÿง  AI datasets ๐Ÿ“ˆ Market intelligence โš™๏ธ Automation tools --- ### ๐Ÿ“ฌ Support โญโญโญโญโญ Leave a review if you like this scraper ๐Ÿ“ฉ Contact for enterprise/custom solutions # Actor input Schema ## `keywords` (type: `array`): The keywords or subjects you wish to search for on Google Scholar ๐Ÿ”๐ŸŽ“๐Ÿ“ฐ. Add one keyword per line. ## `maxitems` (type: `integer`): Maximum number of results you want to scrape per keyword ๐Ÿ“Š ## `language` (type: `string`): Select a language ๐ŸŒ ## `country` (type: `string`): Select your preferred country ๐ŸŒ ## Actor input object example ```json { "keywords": [ "CNN", "deep learning" ], "maxitems": 30, "language": "English", "country": "Any ๐ŸŒ" } ```` # Actor output Schema ## `overview` (type: `string`): No description # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "keywords": [ "CNN", "deep learning" ], "maxitems": 30, "language": "English", "country": "Any ๐ŸŒ" }; // Run the Actor and wait for it to finish const run = await client.actor("delectable_incubator/google-scholar-scraper-low-cost").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`๐Ÿ’พ 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); }); // ๐Ÿ“š Want to learn more ๐Ÿ“–? Go to โ†’ https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "keywords": [ "CNN", "deep learning", ], "maxitems": 30, "language": "English", "country": "Any ๐ŸŒ", } # Run the Actor and wait for it to finish run = client.actor("delectable_incubator/google-scholar-scraper-low-cost").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("๐Ÿ’พ Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # ๐Ÿ“š Want to learn more ๐Ÿ“–? Go to โ†’ https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "keywords": [ "CNN", "deep learning" ], "maxitems": 30, "language": "English", "country": "Any ๐ŸŒ" }' | apify call delectable_incubator/google-scholar-scraper-low-cost --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=delectable_incubator/google-scholar-scraper-low-cost", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Google Scholar Scraper - Low-cost๐Ÿ’ฒ๐Ÿ”ฅ๐Ÿ“š๐ŸŽ“", "description": "Scrape Google Scholar academic papers ๐Ÿ“š๐Ÿ” with a powerful research scraper. Extract paper titles, authors, publication dates, journals/sources, citations, and direct links to full texts. Ideal for academic research, literature reviews, citation analysis, AI/NLP training, and knowledge discovery ๐Ÿš€", "version": "0.0", "x-build-id": "i7xFyHDvklQk1jCVS" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/delectable_incubator~google-scholar-scraper-low-cost/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-delectable_incubator-google-scholar-scraper-low-cost", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/delectable_incubator~google-scholar-scraper-low-cost/runs": { "post": { "operationId": "runs-sync-delectable_incubator-google-scholar-scraper-low-cost", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/delectable_incubator~google-scholar-scraper-low-cost/run-sync": { "post": { "operationId": "run-sync-delectable_incubator-google-scholar-scraper-low-cost", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "keywords" ], "properties": { "keywords": { "title": "The keywords or subjects you wish to search for on Google Scholar ๐Ÿ”๐ŸŽ“", "type": "array", "description": "The keywords or subjects you wish to search for on Google Scholar ๐Ÿ”๐ŸŽ“๐Ÿ“ฐ. Add one keyword per line.", "items": { "type": "string" } }, "maxitems": { "title": "Maximum number of results you want to scrape per keyword ๐Ÿ“Š", "type": "integer", "description": "Maximum number of results you want to scrape per keyword ๐Ÿ“Š", "default": 30 }, "language": { "title": "Select a language ๐ŸŒ", "enum": [ "English", "French", "Spanish", "German", "Italian", "Portuguese", "Russian", "Chinese", "Japanese", "Korean", "Arabic", "Hindi", "Bengali", "Punjabi", "Polish", "Turkish", "Vietnamese", "Thai", "Malay", "Czech", "Romanian", "Hungarian", "Slovak", "Ukrainian", "Greek", "Indonesian", "Swedish", "Norwegian", "Finnish", "Danish", "Dutch", "Serbian", "Croatian", "Bosnian", "Macedonian", "Albanian", "Slovenian", "Lithuanian", "Latvian", "Estonian", "Icelandic", "Maltese", "Georgian", "Amharic", "Swahili", "Tagalog", "Latin", "Yiddish", "Marathi", "Gujarati", "Telugu", "Tamil", "Kannada", "Malayalam", "Odia", "Sinhala", "Nepali", "Khmer", "Burmese", "Lao", "Urdu", "Pashto", "Divehi", "Sindhi", "Quechua", "Modern Hebrew", "Basque", "Welsh", "Galician", "Catalan", "Tok Pisin", "Hmong", "Xhosa", "Zulu" ], "type": "string", "description": "Select a language ๐ŸŒ", "default": "English" }, "country": { "title": "Select your preferred country ๐ŸŒ", "enum": [ "Any ๐ŸŒ", "Australia ๐Ÿ‡ฆ๐Ÿ‡บ", "Brazil ๐Ÿ‡ง๐Ÿ‡ท", "Canada ๐Ÿ‡จ๐Ÿ‡ฆ", "India ๐Ÿ‡ฎ๐Ÿ‡ณ", "United Kingdom ๐Ÿ‡ฌ๐Ÿ‡ง", "United States ๐Ÿ‡บ๐Ÿ‡ธ", "Argentina ๐Ÿ‡ฆ๐Ÿ‡ท", "France ๐Ÿ‡ซ๐Ÿ‡ท", "Germany ๐Ÿ‡ฉ๐Ÿ‡ช", "Japan ๐Ÿ‡ฏ๐Ÿ‡ต", "South Korea ๐Ÿ‡ฐ๐Ÿ‡ท", "Russia ๐Ÿ‡ท๐Ÿ‡บ", "Mexico ๐Ÿ‡ฒ๐Ÿ‡ฝ", "Spain ๐Ÿ‡ช๐Ÿ‡ธ", "Italy ๐Ÿ‡ฎ๐Ÿ‡น", "Turkey ๐Ÿ‡น๐Ÿ‡ท", "Netherlands ๐Ÿ‡ณ๐Ÿ‡ฑ", "Poland ๐Ÿ‡ต๐Ÿ‡ฑ", "Sweden ๐Ÿ‡ธ๐Ÿ‡ช", "Switzerland ๐Ÿ‡จ๐Ÿ‡ญ", "Belgium ๐Ÿ‡ง๐Ÿ‡ช", "China ๐Ÿ‡จ๐Ÿ‡ณ", "Singapore ๐Ÿ‡ธ๐Ÿ‡ฌ", "Vietnam ๐Ÿ‡ป๐Ÿ‡ณ", "Thailand ๐Ÿ‡น๐Ÿ‡ญ", "Indonesia ๐Ÿ‡ฎ๐Ÿ‡ฉ", "Malaysia ๐Ÿ‡ฒ๐Ÿ‡พ", "Philippines ๐Ÿ‡ต๐Ÿ‡ญ", "South Africa ๐Ÿ‡ฟ๐Ÿ‡ฆ", "Egypt ๐Ÿ‡ช๐Ÿ‡ฌ", "Nigeria ๐Ÿ‡ณ๐Ÿ‡ฌ", "Kenya ๐Ÿ‡ฐ๐Ÿ‡ช", "Chile ๐Ÿ‡จ๐Ÿ‡ฑ", "Colombia ๐Ÿ‡จ๐Ÿ‡ด", "Peru ๐Ÿ‡ต๐Ÿ‡ช", "Saudi Arabia ๐Ÿ‡ธ๐Ÿ‡ฆ", "United Arab Emirates ๐Ÿ‡ฆ๐Ÿ‡ช", "Pakistan ๐Ÿ‡ต๐Ÿ‡ฐ", "Bangladesh ๐Ÿ‡ง๐Ÿ‡ฉ", "Sri Lanka ๐Ÿ‡ฑ๐Ÿ‡ฐ", "Nepal ๐Ÿ‡ณ๐Ÿ‡ต", "Afghanistan ๐Ÿ‡ฆ๐Ÿ‡ซ", "Iraq ๐Ÿ‡ฎ๐Ÿ‡ถ", "Kuwait ๐Ÿ‡ฐ๐Ÿ‡ผ", "Qatar ๐Ÿ‡ถ๐Ÿ‡ฆ", "Oman ๐Ÿ‡ด๐Ÿ‡ฒ", "Jordan ๐Ÿ‡ฏ๐Ÿ‡ด", "Lebanon ๐Ÿ‡ฑ๐Ÿ‡ง", "Syria ๐Ÿ‡ธ๐Ÿ‡พ", "Bahrain ๐Ÿ‡ง๐Ÿ‡ญ", "Yemen ๐Ÿ‡พ๐Ÿ‡ช", "Algeria ๐Ÿ‡ฉ๐Ÿ‡ฟ", "Morocco ๐Ÿ‡ฒ๐Ÿ‡ฆ", "Tunisia ๐Ÿ‡น๐Ÿ‡ณ", "Libya ๐Ÿ‡ฑ๐Ÿ‡พ", "Mali ๐Ÿ‡ฒ๐Ÿ‡ฑ", "Ivory Coast ๐Ÿ‡จ๐Ÿ‡ฎ", "Ghana ๐Ÿ‡ฌ๐Ÿ‡ญ", "Senegal ๐Ÿ‡ธ๐Ÿ‡ณ", "Angola ๐Ÿ‡ฆ๐Ÿ‡ด", "Mozambique ๐Ÿ‡ฒ๐Ÿ‡ฟ", "Tanzania ๐Ÿ‡น๐Ÿ‡ฟ", "Uganda ๐Ÿ‡บ๐Ÿ‡ฌ", "Rwanda ๐Ÿ‡ท๐Ÿ‡ผ", "Zambia ๐Ÿ‡ฟ๐Ÿ‡ฒ", "Zimbabwe ๐Ÿ‡ฟ๐Ÿ‡ผ", "Botswana ๐Ÿ‡ง๐Ÿ‡ผ", "Namibia ๐Ÿ‡ณ๐Ÿ‡ฆ", "Eswatini ๐Ÿ‡ธ๐Ÿ‡ฟ", "Lesotho ๐Ÿ‡ฑ๐Ÿ‡ธ", "Mauritius ๐Ÿ‡ฒ๐Ÿ‡บ", "Seychelles ๐Ÿ‡ธ๐Ÿ‡จ", "Madagascar ๐Ÿ‡ฒ๐Ÿ‡ฌ", "Comoros ๐Ÿ‡ฐ๐Ÿ‡ฒ", "Somalia ๐Ÿ‡ธ๐Ÿ‡ด", "Gabon ๐Ÿ‡ฌ๐Ÿ‡ฆ", "Congo ๐Ÿ‡จ๐Ÿ‡ฌ", "Democratic Republic of the Congo ๐Ÿ‡จ๐Ÿ‡ฉ", "Chad ๐Ÿ‡น๐Ÿ‡ฉ", "Central African Republic ๐Ÿ‡จ๐Ÿ‡ซ", "Cameroon ๐Ÿ‡จ๐Ÿ‡ฒ", "Equatorial Guinea ๐Ÿ‡ฌ๐Ÿ‡ถ", "South Sudan ๐Ÿ‡ธ๐Ÿ‡ธ", "Sudan ๐Ÿ‡ธ๐Ÿ‡ฉ", "Ethiopia ๐Ÿ‡ช๐Ÿ‡น", "Mauritania ๐Ÿ‡ฒ๐Ÿ‡ท", "Liberia ๐Ÿ‡ฑ๐Ÿ‡ธ", "Sierra Leone ๐Ÿ‡ธ๐Ÿ‡ฑ", "Guinea ๐Ÿ‡ฌ๐Ÿ‡ณ", "Cรดte d'Ivoire ๐Ÿ‡จ๐Ÿ‡ฎ", "Burkina Faso ๐Ÿ‡ง๐Ÿ‡ซ", "Togo ๐Ÿ‡น๐Ÿ‡ฌ", "Benin ๐Ÿ‡ง๐Ÿ‡ฏ", "Niger ๐Ÿ‡ณ๐Ÿ‡ช", "Gambia ๐Ÿ‡ฌ๐Ÿ‡ณ", "Guinea-Bissau ๐Ÿ‡ฌ๐Ÿ‡ผ", "Sรฃo Tomรฉ and Prรญncipe ๐Ÿ‡ธ๐Ÿ‡น", "Honduras ๐Ÿ‡ญ๐Ÿ‡ณ", "El Salvador ๐Ÿ‡ธ๐Ÿ‡ป", "Costa Rica ๐Ÿ‡จ๐Ÿ‡ท", "Panama ๐Ÿ‡ต๐Ÿ‡ฆ", "Belize ๐Ÿ‡ง๐Ÿ‡ฟ", "Guatemala ๐Ÿ‡ฌ๐Ÿ‡น", "Nicaragua ๐Ÿ‡ณ๐Ÿ‡ฎ", "Dominican Republic ๐Ÿ‡ฉ๐Ÿ‡ด", "Cuba ๐Ÿ‡จ๐Ÿ‡บ", "Jamaica ๐Ÿ‡ฏ๐Ÿ‡ฒ", "Trinidad and Tobago ๐Ÿ‡น๐Ÿ‡น", "Barbados ๐Ÿ‡ง๐Ÿ‡ง", "Saint Lucia ๐Ÿ‡ฑ๐Ÿ‡จ", "Saint Vincent and the Grenadines ๐Ÿ‡ป๐Ÿ‡จ", "Grenada ๐Ÿ‡ฌ๐Ÿ‡ฉ", "Saint Kitts and Nevis ๐Ÿ‡ฐ๐Ÿ‡ณ", "Antigua and Barbuda ๐Ÿ‡ฆ๐Ÿ‡ฌ", "Bahamas ๐Ÿ‡ง๐Ÿ‡ธ", "Saint Pierre and Miquelon ๐Ÿ‡ต๐Ÿ‡ฒ", "Martinique ๐Ÿ‡ฒ๐Ÿ‡ถ", "Guadeloupe ๐Ÿ‡ฌ๐Ÿ‡ต", "French Guiana ๐Ÿ‡ฌ๐Ÿ‡ซ", "Bermuda ๐Ÿ‡ง๐Ÿ‡ฒ", "Montserrat ๐Ÿ‡ฒ๐Ÿ‡ธ", "Cayman Islands ๐Ÿ‡ฐ๐Ÿ‡พ", "Turks and Caicos Islands ๐Ÿ‡น๐Ÿ‡จ", "Falkland Islands ๐Ÿ‡ซ๐Ÿ‡ฐ", "Aruba ๐Ÿ‡ฆ๐Ÿ‡ผ", "Curaรงao ๐Ÿ‡จ๐Ÿ‡ผ", "Bonaire ๐Ÿ‡ง๐Ÿ‡ถ", "Sint Eustatius ๐Ÿ‡ธ๐Ÿ‡ญ", "Saba ๐Ÿ‡ธ๐Ÿ‡ง", "Saint Barthรฉlemy ๐Ÿ‡ง๐Ÿ‡ฑ", "Saint Martin ๐Ÿ‡ฒ๐Ÿ‡ถ", "Sint Maarten ๐Ÿ‡ธ๐Ÿ‡ฝ" ], "type": "string", "description": "Select your preferred country ๐ŸŒ", "default": "Any ๐ŸŒ" } } }, "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 } } } } } } } } } } ```