# Google Autocomplete Actor (`scraperoka/google-autocomplete-actor`) Actor 🎭 Google Autocomplete Actor captures real-time search suggestions from Google as users type—fast, accurate, and scalable. 🔎 Perfect for SEO research, keyword discovery, SERP insights, and competitive intelligence. - **URL**: https://apify.com/scraperoka/google-autocomplete-actor.md - **Developed by:** [Scraperoka](https://apify.com/scraperoka) (community) - **Categories:** SEO tools, AI, Developer tools - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $0.01 / 1,000 results This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage. 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 ### Google Autocomplete Scraper ⚡ Manually guessing keyword variations for autocomplete research wastes time you could spend building faster SEO and content plans. **Google Autocomplete Scraper** pulls autocomplete suggestions for your chosen query and language/country in bulk—ideal for marketers, researchers, and growth teams. With this Google Autocomplete Scraper (and related tools like keyword suggestions scraper, Google suggest keyword scraper, and autocomplete data scraper), you can quickly capture a wide range of query expansions in minutes. --- ### What You Get: Sample Output Here's a sample record from a single run: ```json [ { "query": "apple watch", "suggestion_01": "apple watch series", "suggestion_02": "apple watch deals", "suggestion_03": "apple watch price", "suggestion_04": "apple watch bands", "suggestion_05": "apple watch waterproof", "suggestion_06": "apple watch battery life", "suggestion_07": "apple watch SE", "suggestion_08": "apple watch vs galaxy watch", "suggestion_09": "apple watch cellular", "suggestion_10": "apple watch trade in" }, { "query": "a apple watch", "suggestion_01": "a apple watch series", "suggestion_02": "a apple watch deals", "suggestion_03": "a apple watch price", "suggestion_04": "a apple watch bands", "suggestion_05": "a apple watch waterproof", "suggestion_06": "a apple watch battery life", "suggestion_07": "a apple watch SE", "suggestion_08": "a apple watch vs galaxy watch", "suggestion_09": "a apple watch cellular", "suggestion_10": "a apple watch trade in" } ] ```` | Field | Type | What It Tells You | |---|---|---| | `query` | string | The exact input query (or generated prefix/suffix variant) you requested suggestions for | | `suggestion_01` | string | The first autocomplete suggestion for that `query` | | `suggestion_02` | string | A second suggestion you can use for SEO autocomplete keyword research tool workflows | | `suggestion_03` | string | Additional keyword expansion discovered via autocomplete extraction | | `suggestion_04` | string | Another candidate phrase for content planning and keyword clustering | | `suggestion_05` | string | Useful autocomplete output for search result autocomplete scraper–style keyword discovery | | `suggestion_06` | string | More autocomplete options to test in your keyword strategy | | `suggestion_07` | string | A seventh expansion for your keyword suggestions scraper dataset | | `suggestion_08` | string | Further autocomplete keyword ideas for your topical maps | | `suggestion_09` | string | A ninth suggestion returned in the same structured format | | `suggestion_10` | string | The tenth suggestion (the actor truncates fetched results to 10 items) | Export your dataset as JSON, CSV, or Excel — straight from the Apify dashboard. *** ### Why Google Autocomplete Scraper? There are a lot of ways to pull data from web autocomplete experiences—here's what sets **Google Autocomplete Scraper** apart. #### Query-level flexibility for keyword research You provide a `query`, and you can target results by `language` and `country`, making this useful for SEO autocomplete scraper workflows across markets. #### Supports prefix and suffix expansions Enable `use_prefix` and/or `use_suffix` to generate additional query variants automatically, which helps you expand beyond a single seed phrase like a Google autocomplete keyword tool would. #### Clean, structured output for automation Every result is returned in a consistent JSON structure with `query` and `suggestion_XX` fields (from `suggestion_01` onward), making it straightforward to feed into analysis pipelines and keyword clustering. #### Resilient fetching behavior If a request fails for a generated query variant, the actor returns an empty suggestions list for that variant rather than stopping the entire run—helpful for long autocomplete data scraper sessions. *** ### Configuring Your Run Drop this into your `input.json` to get started: ```json { "query": "apple watch", "language": "English", "country": "United States", "use_prefix": false, "use_suffix": true } ``` | Parameter | Required | What It Does | |---|---|---| | `query` | ✅ | The search term to get suggestions for | | `language` | ⬜ | Select your language (mapped internally to a language code) | | `country` | ⬜ | Select your country (mapped internally to a country code) | | `use_prefix` | ⬜ | Whether to add alphabetic prefixes to the query | | `use_suffix` | ⬜ | Whether to add alphabetic suffixes to the query | *** ### Core Capabilities #### Autocomplete suggestions for a single query (and more) Google Autocomplete Scraper fetches suggestions for your provided seed `query`. If you turn on prefix or suffix generation, it also pulls suggestions for those additional variants—ideal for broad keyword suggestions scraper runs. #### Language and country targeting By setting `language` and `country`, you can tailor autocomplete extraction to the context of your audience, making your keyword suggestions scraper dataset more relevant. #### Prefix and suffix keyword expansion With `use_prefix` and `use_suffix`, this Google autocomplete keyword research tool can help you discover more long-tail query forms than you’d get from a single seed phrase. #### Structured output ready for analysis The actor formats each result as an object with `query` plus `suggestion_01` through `suggestion_10`. This makes the output integration-ready for downstream keyword research, reporting, or content planning. #### Run-friendly for automation Results are pushed to the actor’s default dataset in a structured format, which makes it easier to run Google suggest keyword scraper jobs repeatedly for different keywords over time. *** ### Who Gets the Most Out of This **SEO strategists & marketers** — Use Google Autocomplete Scraper to quickly build a keyword expansion list from a seed term, then turn those autocomplete extraction results into content clusters and optimization ideas. **Content researchers** — Generate additional variants with prefixes and suffixes to uncover question-like and intent-driven expansions, helping you map topics faster than manual keyword suggestion searches. **Keyword researchers working across regions** — Set `language` and `country` to tailor autocomplete data scraper outputs to where your audience actually is. **Automation and data teams** — Feed the consistent `query` + `suggestion_XX` JSON objects into your own analysis tooling, dashboards, or enrichment workflows, treating this as a reusable Google autocomplete API–style data source. *** ### Step-by-Step: How to Use It No coding needed. Here's how to run Google Autocomplete Scraper from start to finish: 1. **Open the actor on Apify** — go to [console.apify.com](https://console.apify.com) and open Google Autocomplete Scraper. 2. **Enter your inputs** — set `query` (required), plus optional `language`, `country`, `use_prefix`, and `use_suffix`. 3. **Configure proxy settings** — if you want improved scraping reliability for larger jobs, enable Apify proxy support in the run configuration. 4. **Hit Run and watch the live log** — monitor progress as suggestions are fetched for the main query and any generated variants. 5. **View results in the dataset tab** — each pulled keyword set appears as structured JSON objects with `query` and `suggestion_01`–`suggestion_10`. 6. **Export as JSON, CSV, or Excel** — use the dataset export options directly in the Apify dashboard. The whole process takes under 5 minutes to set up. *** ### Integrations & Export Options Once your data is collected, Google Autocomplete Scraper plugs directly into your existing workflow. You can download your results from the Apify dataset tab as **JSON, CSV, or Excel**. If you want to push data into other tools, you can use Apify’s native integrations or no-code automation like **Zapier** and **Make (Integromat)** to move autocomplete data scraper outputs automatically. For developers and data engineers, you can also use the **Apify API** to retrieve run results programmatically (see the [Apify API docs](https://apify.com/docs/api)). For orchestration, consider **webhooks** to trigger downstream actions (like syncing to a CRM or notifying a Slack channel) when a run completes, and set up **scheduled runs** so autocomplete keyword research runs automatically on a cron schedule. *** ### Pricing & Free Trial Google Autocomplete Scraper runs on the Apify platform, which offers a **free tier** — no credit card required to get started. Apify credits are typically enough for several test runs, and then you can scale using pay-as-you-go pricing. For exact pricing details, check the Apify pricing page in your account dashboard—this listing does not hardcode specific dollar amounts. Start for free at [apify.com](https://apify.com) and scale when you're ready. *** ### Reliability & Performance | What We Handle | How | |---|---| | Rate limiting | Built for steady, run-friendly data collection from public sources | | Generated query variants | Fetching continues across variants so one failure doesn’t stop the whole run | | Error handling | If a fetch fails, that variant returns no suggestions instead of breaking output format | | Output consistency | Always returns `query` plus `suggestion_XX` fields (where available) | **Limitations:** This actor works with publicly available autocomplete suggestions and returns the top portion of suggestions as structured records. Private, login-gated, or non-public content is not accessible. For enterprise-scale runs, contact us to discuss custom configurations. *** ### Frequently Asked Questions #### Is there a free plan or trial? Yes, Apify provides a free tier/credits to help you test runs before scaling. You can start on [apify.com](https://apify.com) and review your available credits in the dashboard. #### Do I need to log in to use Google Autocomplete Scraper? No. The actor is designed to scrape autocomplete suggestions from publicly available sources without requiring a user login. #### How accurate is the data? The output reflects the autocomplete suggestions returned during the run and is limited to the structured suggestions the actor extracts. For keyword research accuracy, treat the results as live autocomplete keyword suggestions that can vary over time. #### How many results can I get per run? Each formatted suggestion object includes `suggestion_01` through `suggestion_10`. If you enable `use_prefix` and/or `use_suffix`, the actor creates additional query variants and returns structured suggestion sets for each variant. #### How often is the data updated / how fresh is it? The data freshness corresponds to when you run the actor. For the most current keyword suggestions scraper output, schedule runs to refresh your dataset periodically. #### Is this legal? Does it comply with GDPR / CCPA? Yes in the sense that the actor collects **publicly available data** and does not access login-gated content. You’re responsible for using the results in compliance with GDPR, CCPA, platform Terms of Service, and any applicable local regulations. #### Can I export results to Google Sheets or Excel? Yes. You can export from the Apify dataset tab as JSON, CSV, or Excel, and then import into tools like spreadsheets. For fully automated workflows, you can also connect the results through Apify integrations or automation platforms. #### Can I run this on a schedule automatically? Yes. You can configure scheduled runs on the Apify platform so Google Autocomplete Scraper repeats automatically on a cron schedule. #### Can I access this via API? Yes. You can access run results programmatically using the Apify API (see [Apify API docs](https://apify.com/docs/api)). #### What happens if the actor hits an error? If a fetch fails for a particular generated query variant, the actor logs the error and returns an empty suggestions list for that variant while allowing the run to complete. The output format stays consistent so you can still process partial results safely. *** ### Need Help or Have a Request? Got a question about Google Autocomplete Scraper or want a new feature added? Reach out at . We actively maintain this actor based on user feedback, and we welcome ideas like webhook notifications on run completion and batch keyword inputs for faster autocomplete keyword extraction. *** ### Disclaimer & Responsible Use *Google Autocomplete Scraper is the fastest, most reliable way to collect autocomplete keyword suggestions—start your free run today.* This actor collects **publicly available data**. It does not access private accounts, login-gated content, or password-protected pages. You are responsible for complying with GDPR, CCPA, platform Terms of Service, and any applicable local regulations when using or storing the output. For data-removal requests, contact . Use responsibly, ethically, and only for lawful purposes. # Actor input Schema ## `query` (type: `string`): The search term to get suggestions for. ## `language` (type: `string`): Select your language ## `country` (type: `string`): Select your country ## `use_prefix` (type: `boolean`): Whether to add alphabetic prefixes to the query. ## `use_suffix` (type: `boolean`): Whether to add alphabetic suffixes to the query. ## Actor input object example ```json { "query": "apple watch", "language": "English", "country": "United States", "use_prefix": false, "use_suffix": false } ``` # 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 = {}; // Run the Actor and wait for it to finish const run = await client.actor("scraperoka/google-autocomplete-actor").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 = {} # Run the Actor and wait for it to finish run = client.actor("scraperoka/google-autocomplete-actor").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 '{}' | apify call scraperoka/google-autocomplete-actor --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=scraperoka/google-autocomplete-actor", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Google Autocomplete Actor", "description": "🎭 Google Autocomplete Actor captures real-time search suggestions from Google as users type—fast, accurate, and scalable. 🔎 Perfect for SEO research, keyword discovery, SERP insights, and competitive intelligence.", "version": "1.0", "x-build-id": "2I7nS9D13NiUAaxAV" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/scraperoka~google-autocomplete-actor/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-scraperoka-google-autocomplete-actor", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/scraperoka~google-autocomplete-actor/runs": { "post": { "operationId": "runs-sync-scraperoka-google-autocomplete-actor", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/scraperoka~google-autocomplete-actor/run-sync": { "post": { "operationId": "run-sync-scraperoka-google-autocomplete-actor", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "query" ], "properties": { "query": { "title": "Query", "type": "string", "description": "The search term to get suggestions for.", "default": "apple watch" }, "language": { "title": "Language", "enum": [ "Afrikaans", "Akan", "Albanian", "Amharic", "Arabic", "Armenian", "Azerbaijani", "Basque", "Belarusian", "Bengali", "Bihari", "Bosnian", "Breton", "Bulgarian", "Catalan", "Croatian", "Czech", "Danish", "Dutch", "English", "Esperanto", "Estonian", "Finnish", "French", "Frisian", "Galician", "Georgian", "German", "Greek", "Guarani", "Gujarati", "Haitian Creole", "Hausa", "Hebrew", "Hindi", "Hungarian", "Icelandic", "Indonesian", "Irish", "Italian", "Japanese", "Javanese", "Kannada", "Kazakh", "Kinyarwanda", "Korean", "Kurdish", "Kyrgyz", "Latin", "Latvian", "Lithuanian", "Macedonian", "Malagasy", "Malay", "Malayalam", "Maltese", "Maori", "Marathi", "Mongolian", "Nepali", "Norwegian", "Oriya", "Pashto", "Persian", "Polish", "Portuguese", "Punjabi", "Quechua", "Romanian", "Russian", "Scottish Gaelic", "Serbian", "Serbo-Croatian", "Sesotho", "Shona", "Sindhi", "Sinhalese", "Slovak", "Slovenian", "Somali", "Spanish", "Swahili", "Swedish", "Tajik", "Tamil", "Tatar", "Telugu", "Thai", "Tigrinya", "Turkish", "Turkmen", "Ukrainian", "Urdu", "Uzbek", "Vietnamese", "Welsh", "Xhosa", "Yiddish", "Yoruba", "Zulu" ], "type": "string", "description": "Select your language", "default": "English" }, "country": { "title": "Country", "enum": [ "Afghanistan", "Albania", "Algeria", "American Samoa", "Andorra", "Angola", "Anguilla", "Antarctica", "Antigua and Barbuda", "Argentina", "Armenia", "Aruba", "Australia", "Austria", "Azerbaijan", "Bahamas", "Bahrain", "Bangladesh", "Barbados", "Belarus", "Belgium", "Belize", "Benin", "Bermuda", "Bhutan", "Bolivia", "Bosnia and Herzegovina", "Botswana", "Bouvet Island", "Brazil", "British Indian Ocean Territory", "Brunei Darussalam", "Bulgaria", "Burkina Faso", "Burundi", "Cambodia", "Cameroon", "Canada", "Cape Verde", "Cayman Islands", "Central African Republic", "Chad", "Chile", "China", "Christmas Island", "Cocos (Keeling) Islands", "Colombia", "Comoros", "Congo", "Congo, The Democratic Republic of the", "Cook Islands", "Costa Rica", "Côte d'Ivoire", "Croatia", "Cuba", "Cyprus", "Czech Republic", "Denmark", "Djibouti", "Dominica", "Dominican Republic", "Ecuador", "Egypt", "El Salvador", "Equatorial Guinea", "Eritrea", "Estonia", "Ethiopia", "Falkland Islands (Malvinas)", "Faroe Islands", "Fiji", "Finland", "France", "French Guiana", "French Polynesia", "French Southern Territories", "Gabon", "Gambia", "Georgia", "Germany", "Ghana", "Gibraltar", "Greece", "Greenland", "Grenada", "Guadeloupe", "Guam", "Guatemala", "Guinea", "Guinea-Bissau", "Guyana", "Haiti", "Heard Island and Mcdonald Islands", "Holy See (Vatican City State)", "Honduras", "Hong Kong", "Hungary", "Iceland", "India", "Indonesia", "Iran, Islamic Republic of", "Iraq", "Ireland", "Israel", "Italy", "Jamaica", "Japan", "Jordan", "Kazakhstan", "Kenya", "Kiribati", "Korea, Democratic People's Republic of", "Korea, Republic of", "Kuwait", "Kyrgyzstan", "Lao People's Democratic Republic", "Latvia", "Lebanon", "Lesotho", "Liberia", "Libya", "Liechtenstein", "Lithuania", "Luxembourg", "Macao", "Macedonia, The Former Yugoslav Republic of", "Madagascar", "Malawi", "Malaysia", "Maldives", "Mali", "Malta", "Marshall Islands", "Martinique", "Mauritania", "Mauritius", "Mayotte", "Mexico", "Micronesia, Federated States of", "Moldova, Republic of", "Monaco", "Mongolia", "Montserrat", "Morocco", "Mozambique", "Myanmar", "Namibia", "Nauru", "Nepal", "Netherlands", "Netherlands Antilles", "New Caledonia", "New Zealand", "Nicaragua", "Niger", "Nigeria", "Niue", "Norfolk Island", "Northern Mariana Islands", "Norway", "Oman", "Pakistan", "Palau", "Palestinian Territory, Occupied", "Panama", "Papua New Guinea", "Paraguay", "Peru", "Philippines", "Pitcairn", "Poland", "Portugal", "Puerto Rico", "Qatar", "Réunion", "Romania", "Russian Federation", "Rwanda", "Saint Helena", "Saint Kitts and Nevis", "Saint Lucia", "Saint Pierre and Miquelon", "Saint Vincent and The Grenadines", "Samoa", "San Marino", "Sao Tome and Principe", "Saudi Arabia", "Senegal", "Serbia", "Seychelles", "Sierra Leone", "Singapore", "Slovakia", "Slovenia", "Solomon Islands", "Somalia", "South Africa", "South Georgia and The South Sandwich Islands", "Spain", "Sri Lanka", "Sudan", "Suriname", "Svalbard and Jan Mayen", "Swaziland", "Sweden", "Switzerland", "Syrian Arab Republic", "Taiwan, Province of China", "Tajikistan", "Tanzania, United Republic of", "Thailand", "Timor-Leste", "Togo", "Tokelau", "Tonga", "Trinidad and Tobago", "Tunisia", "Turkey", "Turkmenistan", "Turks and Caicos Islands", "Tuvalu", "Uganda", "Ukraine", "United Arab Emirates", "United Kingdom", "United States", "United States Minor Outlying Islands", "Uruguay", "Uzbekistan", "Vanuatu", "Venezuela", "Viet Nam", "Virgin Islands, British", "Virgin Islands, U.S.", "Wallis and Futuna", "Western Sahara", "Yemen", "Zambia", "Zimbabwe" ], "type": "string", "description": "Select your country", "default": "United States" }, "use_prefix": { "title": "Use Prefix", "type": "boolean", "description": "Whether to add alphabetic prefixes to the query.", "default": false }, "use_suffix": { "title": "Use Suffix", "type": "boolean", "description": "Whether to add alphabetic suffixes to the query.", "default": false } } }, "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 } } } } } } } } } } ```