# Wikipedia Page Summaries Scraper (`parseforge/wikipedia-rest-summaries-scraper`) Actor Pull Wikipedia article summaries via REST API. Returns title, description, extract (plain + HTML), thumbnail, lang, page ID, content URLs (desktop + mobile + edit), coordinates, page type, timestamps. Look up specific titles or get search results. - **URL**: https://apify.com/parseforge/wikipedia-rest-summaries-scraper.md - **Developed by:** [ParseForge](https://apify.com/parseforge) (community) - **Categories:** Education, News, Other - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $8.00 / 1,000 result items 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 ![ParseForge Banner](https://github.com/ParseForge/apify-assets/blob/ad35ccc13ddd068b9d6cba33f323962e39aed5b2/banner.jpg?raw=true) ## 📚 Wikipedia Article Summary Scraper > 🚀 **Pull Wikipedia article summaries with thumbnail, extract, coordinates, Wikidata link, revision ID, and language. Lookup or search modes.** > 🕒 **Last updated:** 2026-05-08 · **📊 25 fields** per record · **60M+ Wikipedia pages** · 300+ languages · summary extract, thumbnail, coords, Wikidata, revision · lookup or search The **Wikipedia Article Summary Scraper** pulls structured summaries from Wikipedia's REST API. Output includes thumbnail and original-image URLs (with widths and heights), page ID, title and display title, normalized + canonical title, description and description source, summary extract (plain text + HTML), page type, namespace, Wikibase item ID, language code and direction, last-modified timestamp, revision ID, geographic coordinates, and desktop / mobile / edit / revisions URLs. Two modes in one Actor: lookup by title (one per line), and search (using Wikipedia's opensearch). The dataset covers Wikipedia in any of 300+ languages. Set the language input to `es`, `fr`, `de`, etc. | 🎯 Target Audience | 💡 Primary Use Cases | |---|---| | Knowledge-graph builders, content marketers, ML researchers, journalists, encyclopedia apps, education platforms | Knowledge-graph extraction, encyclopedic-content displays, summary embeddings, fact-card UIs, education content | --- ### 📋 What the Wikipedia Article Summary Scraper does Five filtering workflows in a single run: - 🔍 **Lookup mode.** One title per line, returns rich summary per page. - 🔍 **Search mode.** Wikipedia's opensearch with ranked matches. - 🌐 **300+ languages.** Switch language with a single input. - 🗺️ **Coordinates included.** Lat / lng for places, when the page is geo-tagged. - 🔗 **Wikidata link.** Direct Wikibase item ID for cross-language joins. > 💡 **Why it matters:** clean, server-side filtering and fresh data on every run. --- ### 🎬 Full Demo _🚧 Coming soon: a 3-minute walkthrough showing how to go from sign-up to a downloaded dataset._ --- ### ⚙️ Input
InputTypeDefaultBehavior
maxItemsinteger10Records to return. Free plan caps at 10, paid plan up to 1,000,000.
modestring"lookup"lookup or search.
titlesstring""Newline-separated titles (lookup mode).
querystring""Search term (search mode).
languagestring"en"Wikipedia language code (e.g. `en`, `es`, `fr`, `de`, `ja`).
**Example: look up famous scientists.** ```json { "maxItems": 50, "mode": "lookup", "titles": "Albert Einstein\nMarie Curie\nIsaac Newton\nCharles Darwin\nGalileo Galilei", "language": "en" } ```` **Example: search topic in Spanish.** ```json { "maxItems": 20, "mode": "search", "query": "fotografía", "language": "es" } ``` *** ### 📊 Output Each record contains **25 fields**. Download as CSV, Excel, JSON, or XML. #### 🧾 Schema | Field | Type | Example | |---|---|---| | 🖼️ `thumbnailUrl` | string | `"https://upload.wikimedia.org/.../thumb.jpg"` | | 🆔 `pageId` | number | `736` | | 📛 `title` | string | `"Albert Einstein"` | | 📛 `displayTitle` | string | `"Albert Einstein"` | | 📛 `normalizedTitle` | string | `"Albert Einstein"` | | 📛 `canonicalTitle` | string | `"Albert_Einstein"` | | 📜 `description` | string | `"German-born theoretical physicist (1879-1955)"` | | 📝 `extract` | string | `"Albert Einstein was a German-born theoretical physicist..."` | | 📝 `extractHtml` | string | `"

Albert Einstein was a German-born theoretical physicist..."` | | 🏷️ `type` | string | `"standard"` | | 🌐 `language` | string | `"en"` | | 🔤 `languageCode` | string | `"en"` | | 🔗 `wikibaseItem` | string | `"Q937"` | | 🗺️ `coordinatesLat` | number | `52.5` | | 🗺️ `coordinatesLng` | number | `13.4` | | 📅 `timestamp` | string | `"2026-04-29T14:32:11Z"` | | 🆔 `revisionId` | number | `1238762345` | | 🌐 `desktopUrl` | string | `"https://en.wikipedia.org/wiki/Albert_Einstein"` | | 📱 `mobileUrl` | string | `"https://en.m.wikipedia.org/wiki/Albert_Einstein"` | | ✏️ `editDesktopUrl` | string | `"https://en.wikipedia.org/wiki/Albert_Einstein?action=edit"` | #### 📦 Sample records

👨‍🔬 Albert Einstein ```json {"pageId":736,"title":"Albert Einstein","description":"German-born theoretical physicist (1879-1955)","wikibaseItem":"Q937","language":"en"} ```
🏛️ Tokyo ```json {"title":"Tokyo","coordinatesLat":35.689,"coordinatesLng":139.692,"wikibaseItem":"Q1490"} ```
*** ### ✨ Why choose this Actor | | Capability | |---|---| | 🔗 | **Wikidata link.** Wikibase item ID lets you join across languages and other knowledge graphs. | | 🌍 | **300+ languages.** Same Actor pulls summaries from any Wikipedia language. | | 🗺️ | **Geo coordinates.** Lat / lng exposed when the page is geo-tagged. | | 📜 | **Plain + HTML extracts.** Both formats per record. | | 🆓 | **No auth.** Wikipedia REST is open. | *** ### 📈 How it compares to alternatives | Approach | Cost | Coverage | Refresh | Filters | Setup | |---|---|---|---|---|---| | **⭐ This Actor** | $5 free credit | **60M+ pages** | Live per run | 2 modes | ⚡ 2 min | | Wikipedia REST direct | Free | Same | Live | DIY | 🐢 Code | | DBpedia / Wikidata | Free | Triplestore | Live | SPARQL | 🐢 Hours | | Manual scraping | Free | All | Live | DIY | 🐢 Days | *** ### 🚀 How to use 1. 📝 **Sign up.** [Create a free account with $5 credit](https://console.apify.com/sign-up?fpr=vmoqkp) (takes 2 minutes). 2. 🌐 **Open the Actor.** Find the Wikipedia Article Summary Scraper on the Apify Store. 3. 🎯 **Set input.** Pick filters and `maxItems`. 4. 🚀 **Run it.** Click **Start**. 5. 📥 **Download.** Grab results in the **Dataset** tab as CSV, Excel, JSON, or XML. > ⏱️ Total time from signup to dataset: **3-5 minutes.** No coding required. *** ### 💼 Business use cases
#### 📚 Knowledge + Education - Encyclopedia-app summaries - Quiz / trivia content - Reference card UIs - Reading-comprehension exercises #### 🤖 ML + Search - Summary embeddings - Fine-tune QA models - Knowledge-graph seeding - Multilingual training data
#### 📰 Journalism + Content - Background fact cards - Multi-language coverage - Topic-page generation - Subject-A vs subject-B comparisons #### 🌐 Localization - Multi-language content seeding - Cross-language entity matching - Translated summaries - Localized SEO content
*** ### 🔌 Automating Wikipedia Article Summary Scraper Control the scraper programmatically: - 🟢 **Node.js.** Install the `apify-client` NPM package. - 🐍 **Python.** Use the `apify-client` PyPI package. - 📚 See the [Apify API documentation](https://docs.apify.com/api/v2) for full details. The [Apify Schedules feature](https://docs.apify.com/platform/schedules) lets you trigger this Actor on any cron interval. *** ### 🌟 Beyond business use cases Data like this powers more than commercial workflows.
#### 🎓 Research and academia - Reproducible Wikipedia corpora - Cross-language entity studies - Educational fact-card content - Knowledge-graph research #### 🎨 Personal and creative - Personal study aids - Trivia apps - Side projects with summary data - Reading-list backbones
#### 🤝 Non-profit and civic - Free encyclopedic content - Library reference tools - Heritage knowledge preservation - Educational outreach #### 🧪 Experimentation - Train summarization models - Prototype QA systems - Build entity-disambiguation tools - Test multilingual pipelines
*** ### 🤖 Ask an AI assistant about this scraper Open a ready-to-send prompt in the AI of your choice: - 💬 [**ChatGPT**](https://chat.openai.com/?q=How%20do%20I%20use%20the%20Wikipedia%20Article%20Summary%20Scraper%20by%20ParseForge%20on%20Apify%3F%20Show%20me%20input%20examples%2C%20output%20fields%2C%20common%20use%20cases%2C%20and%20how%20to%20integrate%20it%20into%20a%20workflow.) - 🧠 [**Claude**](https://claude.ai/new?q=How%20do%20I%20use%20the%20Wikipedia%20Article%20Summary%20Scraper%20by%20ParseForge%20on%20Apify%3F%20Show%20me%20input%20examples%2C%20output%20fields%2C%20common%20use%20cases%2C%20and%20how%20to%20integrate%20it%20into%20a%20workflow.) - 🔍 [**Perplexity**](https://perplexity.ai/search?q=How%20do%20I%20use%20the%20Wikipedia%20Article%20Summary%20Scraper%20by%20ParseForge%20on%20Apify%3F%20Show%20me%20input%20examples%2C%20output%20fields%2C%20common%20use%20cases%2C%20and%20how%20to%20integrate%20it%20into%20a%20workflow.) - 🅒 [**Copilot**](https://copilot.microsoft.com/?q=How%20do%20I%20use%20the%20Wikipedia%20Article%20Summary%20Scraper%20by%20ParseForge%20on%20Apify%3F%20Show%20me%20input%20examples%2C%20output%20fields%2C%20common%20use%20cases%2C%20and%20how%20to%20integrate%20it%20into%20a%20workflow.) *** ### ❓ Frequently Asked Questions #### 🧩 How does it work? Pick lookup or search mode and supply titles or a query. The Actor calls the Wikipedia REST API and returns one record per page. #### 📊 How many fields per record? 25, including thumbnail, page ID, title fields, description, extract (plain + HTML), type, language metadata, Wikibase item, coordinates, timestamps, and URLs. #### 🌍 Which languages are supported? Any Wikipedia language. Set the language input to the standard code (`en`, `es`, `fr`, `de`, `ja`, `zh`, `ar`, etc). #### 🗺️ Are geo-coordinates always present? Only on geo-tagged pages (places, landmarks). Other pages have null. #### 🔗 What's the wikibaseItem field? The Wikidata Q-number for the entity. Lets you join across languages and other knowledge bases. #### 📜 Is the full article body returned? No, only the summary extract (lead section). Use Wikipedia's full-content API for the entire body. #### 🆓 Do I need an API key? No. Wikipedia REST is open. #### 🔁 Can I schedule runs? Yes. Schedule daily to refresh summaries. #### ⚖️ Is this data free to use? Yes. Wikipedia content is licensed CC-BY-SA. Attribution required for redistribution. #### 💳 Do I need a paid Apify plan? No. The free plan covers preview runs (10 records). *** ### 🔌 Integrate with any app Wikipedia Article Summary Scraper connects to any cloud service via [Apify integrations](https://apify.com/integrations): - [**Make**](https://docs.apify.com/platform/integrations/make) - Automate multi-step workflows - [**Zapier**](https://docs.apify.com/platform/integrations/zapier) - Connect with 5,000+ apps - [**Slack**](https://docs.apify.com/platform/integrations/slack) - Get run notifications - [**Airbyte**](https://docs.apify.com/platform/integrations/airbyte) - Pipe data into your warehouse - [**GitHub**](https://docs.apify.com/platform/integrations/github) - Trigger runs from commits - [**Google Drive**](https://docs.apify.com/platform/integrations/drive) - Export datasets to Sheets *** ### 🔗 Recommended Actors - [**🌐 Wikidata Entity Search**](https://apify.com/parseforge/wikidata-entity-search-scraper) - 100M+ open knowledge-graph entities - [**🌍 Wikivoyage Travel Articles**](https://apify.com/parseforge/wikivoyage-articles-scraper) - Wikivoyage city and country articles with image, geo - [**🌍 REST Countries Reference Data**](https://apify.com/parseforge/rest-countries-scraper) - Every country with flag, capital, currency, languages - [**📊 Stack Exchange Questions**](https://apify.com/parseforge/stackexchange-questions-scraper) - Search 170+ Stack Exchange Q\&A sites - [**🌍 GeoNames Places + Postal Codes**](https://apify.com/parseforge/geonames-places-scraper) - 12M+ places with admin hierarchy, lat/lng, alternate names > 💡 **Pro Tip:** browse the complete [ParseForge collection](https://apify.com/parseforge) for more reference-data scrapers. *** **🆘 Need Help?** [**Open our contact form**](https://tally.so/r/BzdKgA) to request a new scraper, propose a custom data project, or report an issue. *** > **⚠️ Disclaimer:** this Actor is an independent tool and is not affiliated with, endorsed by, or sponsored by the Wikimedia Foundation, Wikipedia editors, or any cited reference work. All trademarks mentioned are the property of their respective owners. Only publicly available open data is collected. # Actor input Schema ## `maxItems` (type: `integer`): Free users: Limited to 10 items (preview). Paid users: Optional, max 1,000,000 ## `mode` (type: `string`): lookup = direct titles; search = OpenSearch suggestion + summary fetch. ## `titles` (type: `string`): Wikipedia article titles, one per line (URL-style with underscores or spaces both OK). E.g. `Albert_Einstein` or `Albert Einstein`. ## `query` (type: `string`): Free-text Wikipedia search. ## `language` (type: `string`): ISO 639-1 (en, es, fr, de, it, ja, zh, ru, pt, ar, hi). ## Actor input object example ```json { "maxItems": 10, "mode": "lookup", "titles": "Albert Einstein\nMarie Curie\nAda Lovelace\nAlan Turing\nNikola Tesla", "query": "quantum computing", "language": "en" } ``` # 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 = { "maxItems": 10, "mode": "lookup", "titles": `Albert Einstein Marie Curie Ada Lovelace Alan Turing Nikola Tesla`, "query": "quantum computing", "language": "en" }; // Run the Actor and wait for it to finish const run = await client.actor("parseforge/wikipedia-rest-summaries-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 = { "maxItems": 10, "mode": "lookup", "titles": """Albert Einstein Marie Curie Ada Lovelace Alan Turing Nikola Tesla""", "query": "quantum computing", "language": "en", } # Run the Actor and wait for it to finish run = client.actor("parseforge/wikipedia-rest-summaries-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 '{ "maxItems": 10, "mode": "lookup", "titles": "Albert Einstein\\nMarie Curie\\nAda Lovelace\\nAlan Turing\\nNikola Tesla", "query": "quantum computing", "language": "en" }' | apify call parseforge/wikipedia-rest-summaries-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=parseforge/wikipedia-rest-summaries-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Wikipedia Page Summaries Scraper", "description": "Pull Wikipedia article summaries via REST API. Returns title, description, extract (plain + HTML), thumbnail, lang, page ID, content URLs (desktop + mobile + edit), coordinates, page type, timestamps. Look up specific titles or get search results.", "version": "1.0", "x-build-id": "4CW0lfdXhdnTmdbxH" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/parseforge~wikipedia-rest-summaries-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-parseforge-wikipedia-rest-summaries-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/parseforge~wikipedia-rest-summaries-scraper/runs": { "post": { "operationId": "runs-sync-parseforge-wikipedia-rest-summaries-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/parseforge~wikipedia-rest-summaries-scraper/run-sync": { "post": { "operationId": "run-sync-parseforge-wikipedia-rest-summaries-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "maxItems": { "title": "Max Items", "minimum": 1, "maximum": 1000000, "type": "integer", "description": "Free users: Limited to 10 items (preview). Paid users: Optional, max 1,000,000" }, "mode": { "title": "Mode", "enum": [ "lookup", "search" ], "type": "string", "description": "lookup = direct titles; search = OpenSearch suggestion + summary fetch.", "default": "lookup" }, "titles": { "title": "Article titles (lookup mode)", "type": "string", "description": "Wikipedia article titles, one per line (URL-style with underscores or spaces both OK). E.g. `Albert_Einstein` or `Albert Einstein`." }, "query": { "title": "Search query (search mode)", "type": "string", "description": "Free-text Wikipedia search." }, "language": { "title": "Wikipedia language code", "type": "string", "description": "ISO 639-1 (en, es, fr, de, it, ja, zh, ru, pt, ar, hi)." } } }, "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 } } } } } } } } } } ```