# Youtube Autocomplete Scraper (`scrapedrift/youtube-autocomplete-scraper`) Actor YouTube Autocomplete Scraper collects keyword suggestions directly from YouTube search autocomplete results. Discover trending queries, long-tail keywords, content ideas, and audience search intent for SEO, video optimization, competitor research, and content planning. - **URL**: https://apify.com/scrapedrift/youtube-autocomplete-scraper.md - **Developed by:** [ScrapeDrift](https://apify.com/scrapedrift) (community) - **Categories:** SEO tools, Developer tools, Other - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $4.99 / 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 ### Youtube Autocomplete Scraper 🚀 Getting YouTube keyword suggestions one by one is painfully slow—and it makes keyword research feel like guesswork. **Youtube Autocomplete Scraper** pulls YouTube autocomplete suggestions for your query in a single run, so you can extract ideas fast. It’s perfect for a youtube autocomplete scraper, youtube search suggestions scraper, and anyone doing youtube keyword research tool autocomplete. It’s built for marketers, data analysts, and researchers who want a reliable way to scrape youtube autocomplete results at scale. Run it once, get structured suggestions back immediately, and stop manually copying suggestions from the UI. --- ### See the Data: Sample Output Here's a real record from a single run: ```json { "query": "apple watch", "suggestion_01": "apple watch series", "suggestion_02": "apple watch bands", "suggestion_03": "apple watch setup", "suggestion_04": "apple watch battery drain", "suggestion_05": "apple watch not charging", "suggestion_06": "apple watch troubleshooting", "suggestion_07": "apple watch workout", "suggestion_08": "apple watch se", "suggestion_09": "apple watch update", "suggestion_10": "apple watch waterproof" } ```` | Field | Type | What It Tells You | |---|---|---| | `query` | string | The input query (or the generated prefix/suffix variation) used to fetch suggestions. | | `suggestion_01` | string | The top autocomplete suggestion for that query variation—useful as your first keyword lead. | | `suggestion_02` | string | A second-level idea you can expand into content topics or ad groups. | | `suggestion_03` | string | More long-tail keyword directions to test for search intent. | | `suggestion_04` | string | An additional suggestion that helps diversify your keyword list. | | `suggestion_05` | string | Useful for quickly building a larger youtube autocomplete keyword list. | | `suggestion_06` | string | Helps you go beyond the first few suggestions without extra manual work. | | `suggestion_07` | string | Another candidate keyword from autocomplete results. | | `suggestion_08` | string | Great for building variations when you’re doing bulk youtube autocomplete scraper workflows. | | `suggestion_09` | string | Provides more autocomplete keyword coverage per query. | | `suggestion_10` | string | The 10th suggestion (when `max_results` allows it), ready for export and analysis. | | `error_message` | string | If the actor logs an error internally and returns empty suggestions, this field would represent the error details (note: the actor pushes `result` data as shown above). | Export your full dataset as JSON, CSV, or Excel from the Apify dashboard. *** ### Setting It Up Drop this into your `input.json` and you're ready to go: ```json { "query": "apple watch", "language": "English", "country": "United States", "use_prefix": false, "use_suffix": false } ``` | Parameter | Required | What It Does | |---|---:|---| | `query` | ✅ | The search term you want autocomplete suggestions for. | | `language` | ⬜ | Select the language used for autocomplete results (default: `English`). | | `country` | ⬜ | Select the country used to shape autocomplete results (default: `United States`). | | `use_prefix` | ⬜ | Whether to add alphabetic prefixes to the query to generate more autocomplete runs. | | `use_suffix` | ⬜ | Whether to add alphabetic suffixes to the query to generate more autocomplete runs. | *** ### What It Does This actor scrapes YouTube autocomplete suggestions for a given query and outputs them in structured JSON records. #### Fetches autocomplete suggestions for your query Youtube Autocomplete Scraper takes your `query`, requests autocomplete suggestions, and returns them as `suggestion_01`, `suggestion_02`, and so on up to the configured limit. #### Lets you target language and country By selecting `language` and `country`, you can generate autocomplete keyword ideas that better match your target market—useful when you’re building a youtube autocomplete api-style dataset for localized research. #### Expands results using prefixes and suffixes When `use_prefix` and/or `use_suffix` are enabled, the actor runs additional variations of your query with alphabetic additions, which helps you scrape youtube autocomplete more broadly than a single query call. #### Produces a dataset that’s easy to analyze All suggestions are stored per `query` record, making it straightforward to convert into a youtube autocomplete keyword list, deduplicate, cluster by intent, and feed directly into spreadsheets or downstream automation. #### Includes error handling for resilient runs If a request fails or the response can’t be parsed, the actor logs the error and returns an empty suggestions list for that request, keeping your run stable so you can still work with partial output when needed. Overall, Youtube Autocomplete Scraper turns autocomplete into clean, export-ready keyword research data. *** ### Why Youtube Autocomplete Scraper? There are plenty of ways to pull data from YouTube—here’s why Youtube Autocomplete Scraper stands out. #### Designed for structured youtube autocomplete scraping Instead of copying suggestions manually, the actor returns consistent JSON records for each `query` variation (including prefixes/suffixes). That structure makes youtube autocomplete data scraping much easier to process in bulk. #### Flexible query expansion (without custom logic) With `use_prefix` and `use_suffix`, you can quickly generate more suggestion coverage from one starting idea. This is especially handy for bulk youtube autocomplete scraper workflows where you want breadth fast. #### Built for repeatable keyword research runs You can control `language` and `country` each time you run, so your youtube keyword autocomplete tool outputs are comparable across time and audiences—ideal for ongoing research and reporting. *** ### Real-World Use Cases **SEO teams** use Youtube Autocomplete Scraper to speed up keyword discovery for new content clusters. Instead of hunting for ideas one query at a time, they run a base query and optionally expand it with prefixes/suffixes to gather a larger set of youtube autocomplete scraping tool leads for briefs. **Marketing analysts** run the actor across a spreadsheet of seed terms to build a repeatable youtube autocomplete keyword list. They then deduplicate, tag themes, and turn suggestions into testable topic lists for campaigns and landing pages. **Content researchers** use the output to understand how autocomplete shifts by market. By changing `language` and `country`, they capture region-relevant suggestions that help tailor content intent, making youtube search suggestions scraper outputs more actionable. **Automation specialists** integrate the results into their pipelines by exporting the dataset and pushing it into downstream systems. They use the consistent per-query JSON structure from Youtube Autocomplete Scraper to power reporting dashboards and repeatable research workflows. **Agencies** use it during onboarding to quickly map client niche keyword directions. One run provides a structured starting dataset they can refine into video briefs and ad group keyword banks. *** ### How to Run It No code required. Here's how to get your first results in under 5 minutes: 1. **Open the actor on Apify** — visit [console.apify.com](https://console.apify.com) and open this actor listing. 2. **Enter your inputs** — set `query` (required), and optionally `language`, `country`, `use_prefix`, and `use_suffix`. 3. **Configure proxy settings (optional)** — if you want additional reliability for heavier runs, enable your preferred proxy setting in the run configuration. 4. **Start the run and watch the live log** — monitor progress in the actor logs to confirm it’s fetching suggestions for each query variation. 5. **Open the Dataset tab** — see your records appear and verify suggestions for your seed query. 6. **Export in your preferred format** — download your dataset as JSON, CSV, or Excel for analysis or import. 7. **Iterate on query strategy** — rerun with different `language`/`country` values or enable `use_prefix` / `use_suffix` for broader coverage. The whole setup takes under 5 minutes — results start appearing within seconds of launch. *** ### Export & Integration Options Once your data is collected, Youtube Autocomplete Scraper fits directly into your existing workflow. You can export results from the Apify dashboard as **JSON, CSV, or Excel** from the dataset tab, which makes it easy to move into spreadsheets for clustering, deduplication, and reporting. If you want automation, you can connect your run to tools using Apify integrations such as **Zapier / Make**, use **API access** to pull results programmatically, and use **webhooks** to trigger downstream actions when the run completes. *** ### Pricing Youtube Autocomplete Scraper runs on Apify, which includes a **free tier** — no credit card needed to start. You can begin with the free tier (including $5 platform credits on sign-up) for several real test runs, then move to Apify’s pay-as-you-go model when you need heavier workloads. Subscription plans are available for larger usage, and billing is based on Apify Actor compute unit (CU) consumption. Start free at [apify.com](https://apify.com) — scale up when you need to. *** ### Reliability & Limitations | What We Handle | How | |---|---| | Rate-limited responses | Returns empty suggestions for failed requests while keeping the run stable. | | Parsing failures | Error handling logs parse issues and continues. | | Partial outputs | You still get dataset records for successfully processed query variations. | | Output consistency | Suggestions are returned in structured `suggestion_01`…`suggestion_10` fields per `query`. | | Scaling query breadth | `use_prefix` / `use_suffix` expands coverage when you want more than a single fetch. | Limitations: this actor works with publicly available autocomplete content and focuses on suggestions for a given `query` (and its prefix/suffix variations). It does not provide any additional metadata beyond what’s returned in the autocomplete suggestions dataset. If you need a fully customized enrichment pipeline (extra transformations, scoring, or deduplication), handle that after export or in your automation layer. For enterprise-scale needs or custom configurations, reach out and we'll help. *** ### Frequently Asked Questions #### Is there a free plan? Yes. Apify offers a free tier with monthly usage credits, which is typically enough to test Youtube Autocomplete Scraper with real queries. #### Do I need to log in or create an account on YouTube to use this actor? No. This actor is designed to scrape autocomplete suggestions for your provided `query` without requiring you to log in to access content. #### How accurate is the extracted data? The suggestions returned reflect what autocomplete provides for the query under the selected `language` and `country`. For a youtube autocomplete keyword list, the accuracy is directly tied to the live autocomplete suggestions returned during the run. #### How many results can I get per run? The actor uses `max_results` in code (defaulting to `10` in the implementation). It outputs `suggestion_01` through `suggestion_10` based on that limit per `query`. #### How fresh is the data? The data freshness depends on when you run the actor. Each run requests autocomplete suggestions live for your input `query`. #### Is this legal? Does it comply with GDPR / CCPA? This actor works with **publicly available data**. It’s your responsibility to comply with GDPR, CCPA, and relevant platform Terms of Service when storing or using the results. #### Can I export to Google Sheets or Excel? Yes. You can export the dataset as **JSON, CSV, or Excel** from the Apify dashboard, then import it into Google Sheets or your spreadsheet workflow. #### Can I schedule this to run automatically? Yes. You can schedule Apify actors to run automatically using Apify scheduling features, which is useful for recurring keyword research and trend monitoring. #### Can I access results via the API? Yes. You can retrieve run results programmatically using the Apify API, based on the dataset created by the run. #### What happens when the actor encounters an error? When a request fails or parsing doesn’t work, the actor logs the error and returns empty suggestions for that request so the run can still complete. Your dataset will include records for processed query variations, which helps you work with partial results when needed. *** ### Get Help & Use Responsibly Got a question about Youtube Autocomplete Scraper or a feature you'd like added? Reach out to — we respond quickly and can help tailor the run to your keyword research workflow. If you want improvements like stronger deduplication outputs or enhanced keyword shaping options, tell us what you need. **publicly available data** is used. The actor does not access private accounts, login-gated pages, or password-protected content. You’re responsible for complying with GDPR, CCPA, and platform Terms of Service when collecting and using results. 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("scrapedrift/youtube-autocomplete-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 = {} # Run the Actor and wait for it to finish run = client.actor("scrapedrift/youtube-autocomplete-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 '{}' | apify call scrapedrift/youtube-autocomplete-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=scrapedrift/youtube-autocomplete-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Youtube Autocomplete Scraper", "description": "YouTube Autocomplete Scraper collects keyword suggestions directly from YouTube search autocomplete results. Discover trending queries, long-tail keywords, content ideas, and audience search intent for SEO, video optimization, competitor research, and content planning.", "version": "1.0", "x-build-id": "J5AoLaWf74DKvAyXa" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/scrapedrift~youtube-autocomplete-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-scrapedrift-youtube-autocomplete-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/scrapedrift~youtube-autocomplete-scraper/runs": { "post": { "operationId": "runs-sync-scrapedrift-youtube-autocomplete-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/scrapedrift~youtube-autocomplete-scraper/run-sync": { "post": { "operationId": "run-sync-scrapedrift-youtube-autocomplete-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "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 } } } } } } } } } } ```