# GDELT News Scraper — Articles, Timeline & Images (`logiover/gdelt-news-scraper`) Actor Scrape GDELT Project by keyword, topic, or GDELT query. Extract article titles, URLs, domains, dates, languages, countries, images, and tone for news monitoring, media analysis, and research. No API key, no login. - **URL**: https://apify.com/logiover/gdelt-news-scraper.md - **Developed by:** [Logiover](https://apify.com/logiover) (community) - **Categories:** News - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $1.50 / 1,000 results This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## GDELT News Scraper — Articles, Timeline & Images API Monitor global news coverage in real time. Scrape thousands of articles, volume trends, and image-rich stories from the GDELT Project's open API — no API key, no login, no cost. ### What does GDELT News Scraper do? GDELT (Global Database of Events, Language, and Tone) monitors the world's broadcast, print, and web news in over 100 languages from nearly every corner of the planet. This actor calls the GDELT Document 2.0 API at `api.gdeltproject.org/api/v2/doc/doc`, supporting three modes: **articles** (full news list with URL, domain, language, country, tone, and social image), **timeline** (hourly/daily volume intensity for trend analysis), and **images** (articles guaranteed to have a social preview image). Pagination works through sliding **date-window** logic — each request fetches up to 250 articles from a time window, then the window slides back in time until your `maxResults` target is reached or the requested `timespan` is exhausted. This means a single run can yield thousands of unique articles across weeks or months of coverage. The actor enforces a 6-second delay between requests to respect GDELT's rate limit. Queries support full GDELT syntax including AND/OR/NOT operators, phrase matching, and field filters like `sourcelang:english` or `sourcecountry:US`. ### Who is it for? - **Journalists and media analysts** tracking global coverage of a story, brand, or event over time. - **Brand reputation managers** monitoring how their company or product is covered worldwide. - **Academic researchers** studying media framing, sentiment trends, or geopolitical discourse. - **Data scientists and NLP engineers** building news corpora for model training or topic modeling. - **Intelligence and geopolitical analysts** watching for emerging narratives across regions and languages. ### Use cases - Monitor coverage of a company name or executive across 50+ countries and 30 languages. - Build a global news feed for any topic — AI regulation, climate events, political elections. - Track volume spikes in timeline mode to detect when a story is breaking. - Collect image-rich articles for social media monitoring dashboards. - Research how a scientific term (e.g., mRNA, quantum computing) is covered in non-English media. ### Why use GDELT News Scraper? - **Completely keyless**: GDELT's API is free and open — zero credentials required. - **Global coverage**: 100+ languages, virtually every country, updated every 15 minutes. - **Bulk output**: Hundreds to thousands of articles per run through date-window pagination. - **Three modes in one**: articles, timeline trends, and image-filtered stories. - **10 fields per article**: title, URL, domain, date, language, country, image, tone, query, mode. - **Export-ready**: Download results as JSON, CSV, or Excel; connect via Google Sheets, Zapier, or Make. - **Pay-per-result pricing**: Only pay for the actual number of articles scraped. ### What data can you extract? Every article record contains the following fields: | Field | Type | Description | |---|---|---| | `title` | string | Article headline as indexed by GDELT | | `url` | string | Full URL of the article | | `domain` | string | Source domain (e.g., `bbc.co.uk`, `nytimes.com`) | | `seendate` | string | When GDELT first indexed the article (format: `20260708T124500Z`) | | `language` | string | Detected language of the article (e.g., `English`, `Spanish`) | | `sourcecountry` | string | Country of the publishing outlet (e.g., `United States`, `Germany`) | | `socialimage` | string | URL of the article's Open Graph / social preview image | | `tone` | string | GDELT tone score — positive values = positive, negative = negative (in articles mode) | | `query` | string | The search query that produced this result | | `mode` | string | Mode used: `articles`, `timeline`, or `images` | In **timeline** mode, records additionally contain `series` (e.g., `Volume Intensity`) and `value` (numeric intensity score) fields, using `seendate` as the timestamp bucket. **Example output record (articles mode):** ```json { "title": "OpenAI Launches New AI Reasoning Model for Enterprise", "url": "https://techcrunch.com/2026/07/08/openai-launches-reasoning-model/", "domain": "techcrunch.com", "seendate": "20260708T100000Z", "language": "English", "sourcecountry": "United States", "socialimage": "https://techcrunch.com/wp-content/uploads/2026/07/openai-og.jpg", "tone": "-1.23", "query": "artificial intelligence", "mode": "articles" } ```` ### How to use #### Option A: Search by keyword or topic 1. Open the actor and set **Search Query** to any keyword, phrase, or GDELT expression. 2. Choose **Mode**: `articles` to get news links, `timeline` for trend charts, `images` for visual stories. 3. Set **Timespan** (e.g., `1w`, `1m`, `3m`) and **Max Results**. 4. Optionally filter by **Language** (e.g., `English`) or **Source Country** (e.g., `US`). 5. Click **Start** and download results as JSON, CSV, or Excel. **Input example (keyword search):** ```json { "query": "artificial intelligence regulation", "mode": "articles", "maxResults": 500, "timespan": "1m", "language": "English", "country": "US", "sortBy": "datedesc" } ``` #### Option B: Advanced GDELT query syntax GDELT supports rich filtering directly in the query string. You can combine operators with field filters for precise targeting. **Input example (advanced GDELT syntax):** ```json { "query": "\"climate change\" AND (floods OR wildfire) sourcelang:english sourcecountry:AU", "mode": "articles", "maxResults": 1000, "timespan": "3m", "sortBy": "datedesc" } ``` ### Input parameters | Parameter | Type | Default | Description | |---|---|---|---| | `query` | string | `artificial intelligence` | GDELT query. Supports AND/OR/NOT, phrases, field filters. | | `mode` | string | `articles` | `articles`, `timeline`, or `images`. | | `maxResults` | integer | 500 | Max articles to scrape (1–10000). Ignored in timeline mode. | | `timespan` | string | `1w` | How far back to search: `1d`, `1w`, `1m`, `3m`, `6m`, `1y`. | | `language` | string | — | Filter by language name (e.g., `English`, `Spanish`). | | `country` | string | — | Filter by 2-letter source country code (e.g., `US`, `DE`). | | `sortBy` | string | `datedesc` | `datedesc`, `dateasc`, `rel`, `hybridrel`, `socialsharecount`. | | `proxyConfiguration` | object | — | Optional Apify proxy configuration. | **Full input JSON:** ```json { "query": "artificial intelligence", "mode": "articles", "maxResults": 500, "timespan": "1w", "language": "", "country": "", "sortBy": "datedesc", "proxyConfiguration": { "useApifyProxy": true } } ``` ### Output example ```json [ { "title": "EU Passes Landmark Artificial Intelligence Safety Act", "url": "https://www.politico.eu/article/eu-ai-safety-act-2026/", "domain": "politico.eu", "seendate": "20260708T080000Z", "language": "English", "sourcecountry": "Belgium", "socialimage": "https://www.politico.eu/cdn-cgi/image/width=1200/polq.eu/uploads/2026/07/ai-act.jpg", "tone": "-2.14", "query": "artificial intelligence", "mode": "articles" }, { "title": "China Deploys AI Models for National Infrastructure Monitoring", "url": "https://www.globaltimes.cn/page/202607/1300001.shtml", "domain": "globaltimes.cn", "seendate": "20260708T070000Z", "language": "English", "sourcecountry": "China", "socialimage": "", "tone": "1.85", "query": "artificial intelligence", "mode": "articles" } ] ``` ### Tips for best results - **Use quoted phrases** for exact matches: `"machine learning"` returns only that phrase, not loose keyword matches. - **Combine filters**: Add `sourcelang:english sourcecountry:US` to the query string to target US English news without using the separate filter fields. - **Timeline mode for trends**: Use `mode: timeline` with `timespan: 1m` to see hourly coverage intensity — perfect for detecting breaking news spikes. - **Images mode for visual content**: Use `mode: images` when you need articles with guaranteed preview images for social cards or dashboards. - **Longer timespans = more windows**: For `maxResults: 2000` over `3m`, the actor will make multiple paginated requests — this is normal and expected. - **Tone values**: Negative tone scores (e.g., `-3.5`) indicate negative news framing; positive scores indicate positive coverage. Zero = neutral. - **Rate limiting is built in**: The actor respects GDELT's 5-second rate limit automatically — do not set very low timeout values. - **Country codes**: Use ISO 3166-1 alpha-2 codes (US, GB, DE, FR, IN, BR, JP, AU). Check GDELT's documentation for the full list of supported country codes. - **Language names**: Use GDELT's language names: `English`, `Spanish`, `French`, `German`, `Arabic`, `Mandarin`, `Russian`, `Portuguese`. - **Large runs**: For `maxResults > 1000`, use a `timespan` of at least `3m` to ensure enough date windows to fill the quota. ### Integrations - **Google Sheets**: Connect the actor's dataset to Google Sheets via Apify's native integration. Every run automatically populates a new sheet tab with the latest articles. - **Slack**: Use Apify Webhooks to post a Slack message whenever a run completes with new results. - **Zapier / Make**: Trigger downstream workflows on new GDELT data — create CRM records, send emails, or post to social media. - **Scheduled runs**: Use Apify Scheduler to run the actor every hour or day and maintain a live news feed for any topic. - **Webhooks**: Configure `afterRun` webhooks to forward data to your API, database, or analytics pipeline. ### API usage **cURL:** ```bash curl -X POST \ "https://api.apify.com/v2/acts/logiover~gdelt-news-scraper/runs?token=YOUR_API_TOKEN" \ -H "Content-Type: application/json" \ -d '{ "query": "artificial intelligence", "mode": "articles", "maxResults": 500, "timespan": "1w" }' ``` **Node.js (Apify client):** ```javascript import { ApifyClient } from 'apify-client'; const client = new ApifyClient({ token: 'YOUR_API_TOKEN' }); const run = await client.actor('logiover~gdelt-news-scraper').call({ query: 'artificial intelligence', mode: 'articles', maxResults: 500, timespan: '1w', }); const { items } = await client.dataset(run.defaultDatasetId).listItems(); console.log(items); ``` **Python:** ```python from apify_client import ApifyClient client = ApifyClient("YOUR_API_TOKEN") run = client.actor("logiover~gdelt-news-scraper").call(run_input={ "query": "artificial intelligence", "mode": "articles", "maxResults": 500, "timespan": "1w", }) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item["title"], item["url"]) ``` ### Use with AI agents (MCP) This actor is available as a tool in Apify's MCP (Model Context Protocol) server, making it directly callable from Claude, ChatGPT plugins, LangChain agents, and other AI pipelines. Simply configure the Apify MCP server and instruct your AI: *"Use the GDELT News Scraper to find all English-language articles about electric vehicles from the past month, then summarize the top themes."* The actor returns structured JSON that AI agents can immediately analyze, cluster, or summarize. ### FAQ #### Does this require an API key or account? No. GDELT's Document API is completely free and open. This actor requires no credentials from you. An Apify account is only needed to run the actor on Apify's cloud infrastructure. #### What is GDELT and how current is the data? GDELT (Global Database of Events, Language, and Tone) is one of the world's largest open news monitoring databases, indexing print, broadcast, and web news across 100+ languages. The dataset is updated every 15 minutes, so articles indexed in the last hour are typically available. #### How many articles can I get per run? The GDELT API returns up to 250 articles per request. This actor paginates through date windows to reach `maxResults` (up to 10,000). Actual yield depends on coverage volume for your query and timespan — popular topics like "artificial intelligence" or "climate change" easily yield thousands of articles per month. #### Why do I get zero results? Zero results usually mean: (1) the query has no matching articles in the requested timespan, (2) a very specific multi-word query has no exact matches — try broadening it, (3) the language/country filter is too restrictive. Try removing filters or extending the timespan first. #### What does the tone field mean? GDELT assigns a "tone" score to each article based on its text. Negative values (e.g., `-4.2`) indicate negative framing; positive values (e.g., `+2.1`) indicate positive framing. The scale is roughly -10 to +10. This is useful for sentiment tracking over time. #### Can I export to CSV or Excel? Yes. On the actor's dataset page, click **Export** and choose CSV, Excel, JSON, or XML. You can also connect the dataset to Google Sheets automatically via the Apify integration. #### How fast is the scraper? Each GDELT API request takes 1–5 seconds. The actor enforces a 6-second inter-request delay to comply with GDELT's rate limit. For 500 articles (typically 2–3 requests), expect a run time of under 2 minutes. #### How does timeline mode work? Timeline mode calls GDELT's `timelinevol` endpoint, which returns hourly volume intensity values for your query over the requested timespan. Each data point has a `seendate` timestamp and a `value` (relative coverage intensity). This is useful for spotting when a story breaks or peaks. #### Is multilingual search supported? Yes. GDELT indexes articles in 100+ languages. You can search across all languages (default) or filter to a specific language using the `language` parameter (e.g., `Spanish`, `French`, `Arabic`). Queries can target specific languages via the `sourcelang:` field filter in the query string. #### How often should I run this actor? For ongoing monitoring, schedule the actor to run every hour (with a `timespan: 2h` to ensure overlap) or every day (`timespan: 2d`). Use Apify's native deduplication or filter by `seendate` to avoid processing the same article twice. #### What GDELT query operators are supported? GDELT supports: `AND`, `OR`, `NOT`, exact phrases (`"in quotes"`), and field filters including `sourcelang:`, `sourcecountry:`, `theme:`, `domain:`, `imageface:`, and more. See the [GDELT Documentation](https://blog.gdeltproject.org/gdelt-doc-2-0-api-debuts/) for a full list. #### Are there related scrapers on Apify? - **Logiover AI News Monitor** — AI-curated multi-source news with summaries - **Logiover CT Monitor** — Certificate Transparency log watcher for domain discovery - **Logiover CVE Advisory Scraper** — NVD/OSV vulnerability feed with CVSS scores ### Is it legal? GDELT publishes its data under an open data license. The actor queries the GDELT Document API, which is a publicly accessible, free service provided by the GDELT Project. This actor does not scrape article content — it only retrieves the metadata (title, URL, domain, date, language, image URL, tone) that GDELT itself has indexed and exposed through its API. As with any data collection, users are responsible for complying with the terms of service of downstream platforms and applicable data protection laws (GDPR, CCPA, etc.). Article URLs belong to their respective publishers; do not scrape full article text without reviewing each publisher's robots.txt and terms of service. # Actor input Schema ## `query` (type: `string`): GDELT query string. Supports keywords, phrases (in quotes), AND/OR/NOT operators, and field filters like sourcelang:english or sourcecountry:US. Example: "artificial intelligence" AND regulation. Leave blank to use the default topic. ## `mode` (type: `string`): articles: returns matching news articles. timeline: returns volume/tone data over time. images: returns articles with social images only. ## `maxResults` (type: `integer`): Maximum number of articles to scrape. GDELT returns up to 250 per request; the actor paginates via date windows to reach higher limits. Ignored in timeline mode. ## `timespan` (type: `string`): How far back to search. Choose a preset or type a custom value like 36h, 10d, 2m. ## `language` (type: `string`): Filter by article language. Leave blank for all languages. ## `country` (type: `string`): Filter by the country the news source is based in. Leave blank for all countries. ## `sortBy` (type: `string`): Sort articles by date (newest first), relevance, or social sharing intensity. ## `proxyConfiguration` (type: `object`): Proxy settings. Apify Proxy (automatic) is recommended so GDELT's per-IP rate limit can be spread across fresh IPs. ## Actor input object example ```json { "query": "artificial intelligence", "mode": "articles", "maxResults": 1000, "timespan": "3m", "language": "", "country": "", "sortBy": "datedesc", "proxyConfiguration": { "useApifyProxy": true } } ``` # Actor output Schema ## `results` (type: `string`): All records extracted by this run. Open the Dataset tab to browse, filter, and export as CSV, JSON, or Excel. # 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 = { "proxyConfiguration": { "useApifyProxy": true } }; // Run the Actor and wait for it to finish const run = await client.actor("logiover/gdelt-news-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 = { "proxyConfiguration": { "useApifyProxy": True } } # Run the Actor and wait for it to finish run = client.actor("logiover/gdelt-news-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 '{ "proxyConfiguration": { "useApifyProxy": true } }' | apify call logiover/gdelt-news-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=logiover/gdelt-news-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "GDELT News Scraper — Articles, Timeline & Images", "description": "Scrape GDELT Project by keyword, topic, or GDELT query. Extract article titles, URLs, domains, dates, languages, countries, images, and tone for news monitoring, media analysis, and research. No API key, no login.", "version": "1.0", "x-build-id": "oerw2ksxfSPHS7W3r" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/logiover~gdelt-news-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-logiover-gdelt-news-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/logiover~gdelt-news-scraper/runs": { "post": { "operationId": "runs-sync-logiover-gdelt-news-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/logiover~gdelt-news-scraper/run-sync": { "post": { "operationId": "run-sync-logiover-gdelt-news-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "query": { "title": "Search Query", "type": "string", "description": "GDELT query string. Supports keywords, phrases (in quotes), AND/OR/NOT operators, and field filters like sourcelang:english or sourcecountry:US. Example: \"artificial intelligence\" AND regulation. Leave blank to use the default topic.", "default": "artificial intelligence" }, "mode": { "title": "Mode", "enum": [ "articles", "timeline", "images" ], "type": "string", "description": "articles: returns matching news articles. timeline: returns volume/tone data over time. images: returns articles with social images only.", "default": "articles" }, "maxResults": { "title": "Max Results", "minimum": 1, "maximum": 10000, "type": "integer", "description": "Maximum number of articles to scrape. GDELT returns up to 250 per request; the actor paginates via date windows to reach higher limits. Ignored in timeline mode.", "default": 1000 }, "timespan": { "title": "Timespan", "enum": [ "1d", "3d", "1w", "2w", "1m", "3m", "6m", "1y" ], "type": "string", "description": "How far back to search. Choose a preset or type a custom value like 36h, 10d, 2m.", "default": "3m" }, "language": { "title": "Language Filter", "enum": [ "", "english", "spanish", "french", "german", "italian", "portuguese", "dutch", "russian", "arabic", "chinese", "japanese", "korean", "turkish", "hindi", "indonesian", "polish", "swedish", "ukrainian", "vietnamese", "persian", "greek", "hebrew", "thai", "romanian" ], "type": "string", "description": "Filter by article language. Leave blank for all languages.", "default": "" }, "country": { "title": "Source Country Filter", "enum": [ "", "US", "GB", "CA", "AU", "IE", "IN", "DE", "FR", "IT", "ES", "PT", "NL", "BE", "CH", "AT", "SE", "NO", "DK", "FI", "PL", "RU", "UA", "TR", "GR", "IL", "AE", "SA", "EG", "ZA", "NG", "KE", "BR", "AR", "MX", "CL", "CO", "CN", "JP", "KR", "ID", "MY", "SG", "PH", "TH", "VN", "PK", "BD" ], "type": "string", "description": "Filter by the country the news source is based in. Leave blank for all countries.", "default": "" }, "sortBy": { "title": "Sort Order", "enum": [ "datedesc", "dateasc", "rel", "hybridrel", "socialsharecount" ], "type": "string", "description": "Sort articles by date (newest first), relevance, or social sharing intensity.", "default": "datedesc" }, "proxyConfiguration": { "title": "Proxy Configuration", "type": "object", "description": "Proxy settings. Apify Proxy (automatic) is recommended so GDELT's per-IP rate limit can be spread across fresh IPs.", "default": { "useApifyProxy": true } } } }, "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 } } } } } } } } } } ```