# Youtube Autocomplete Scraper (`scrapers-hub/youtube-autocomplete-scraper`) Actor 🚀 Youtube Autocomplete Scraper extracts trending keyword suggestions from YouTube autocomplete fast and accurately. 📈 Perfect for SEO research, content ideation, and competitor insights—save time and boost video discovery with smart keyword data. - **URL**: https://apify.com/scrapers-hub/youtube-autocomplete-scraper.md - **Developed by:** [Scrapers Hub](https://apify.com/scrapers-hub) (community) - **Categories:** SEO tools, Developer tools, Automation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN 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 ### Youtube Autocomplete Scraper 🔍 **Youtube Autocomplete Scraper** collects YouTube autocomplete suggestions for a given query, so you can quickly uncover what viewers are searching for. If you’re doing **YouTube keyword research autocomplete**, building a **YouTube autocomplete SEO tool** workflow, or exploring **YouTube autocomplete data scraper** output for content planning, this actor helps you turn public web suggestions into structured results—saving you hours of manual work. --- ### Why choose Youtube Autocomplete Scraper? | Feature | Benefit | |---|---| | ✅ **All-in-one suggestions scraping** | Get autocomplete suggestions for the original query and (optionally) prefix/suffix variations in one run | | ✅ **Language + country customization** | Tailor results using your selected language and country settings for more relevant suggestion sets | | ✅ **Structured output for easy analysis** | Receive consistently labeled fields (`suggestion_01`, `suggestion_02`, …) for straightforward spreadsheet/BI import | | ✅ **Scale-friendly batching** | Generate multiple records per run by expanding the query with optional prefixes and/or suffixes | | ✅ **Runs fully inside Apify** | Automate extraction as a repeatable workflow you can schedule or rerun during keyword research | | ✅ **Reliable dataset export via Apify** | Actor saves results to the default dataset so you can export as JSON/CSV after completion | --- ### Key features - 🌐 **YouTube autocomplete suggestions for a query**: Scrapes suggestion strings for your provided `query` input - 🗣️ **Language-aware results**: Uses your selected `language` to request suggestions with the correct language setting - 🌍 **Country-aware results**: Uses your selected `country` to request suggestions with the correct country setting - 🔤 **Optional prefix support**: When enabled, expands your query using alphabetic prefixes to surface additional “YouTube search suggestions scraper” style ideas - 🔤 **Optional suffix support**: When enabled, expands your query using alphabetic suffixes for broader keyword coverage - 📊 **Clean, structured fields**: Outputs `suggestion_01`, `suggestion_02`, etc. in a consistent schema for analysis - 💾 **Dataset-first workflow**: Results are pushed to the default dataset at the end of the run for easy downstream export - 💻 **Automation-ready**: Designed for repeatable use in pipelines for “extract YouTube autocomplete queries” and related workflows --- ### Input Provide input via an `input.json` file. Example structure: ```json { "query": "apple watch", "language": "English", "country": "United States", "use_prefix": false, "use_suffix": false } ```` #### Input Fields | Field | Required | Description | |---|---:|---| | `query` | Yes | The search term you want suggestions for (example: `apple watch`). | | `language` | No | Select the language used for autocomplete suggestions. | | `country` | No | Select the country used to tailor autocomplete suggestions. | | `use_prefix` | No | Whether to add alphabetic prefixes to the query to generate additional suggestion records. | | `use_suffix` | No | Whether to add alphabetic suffixes to the query to generate additional suggestion records. | *** ### Output The actor saves each run’s results as JSON records in the default dataset. ```json [ { "query": "apple watch", "suggestion_01": "apple watch series", "suggestion_02": "apple watch bands", "suggestion_03": "apple watch charger", "suggestion_04": "apple watch comparison" } ] ``` #### Output Fields | Field | Type | Description | |---|---|---| | `query` | string | The query string used to fetch autocomplete suggestions (original query or an expanded prefix/suffix query). | | `suggestion_01` | string | The first autocomplete suggestion for that `query`. | | `suggestion_02` | string | The second autocomplete suggestion for that `query`. | | `suggestion_03` | string | The third autocomplete suggestion for that `query`. | | `suggestion_04` | string | The fourth autocomplete suggestion for that `query`. | | `suggestion_05` | string | The fifth autocomplete suggestion for that `query`. | | `suggestion_06` | string | The sixth autocomplete suggestion for that `query`. | | `suggestion_07` | string | The seventh autocomplete suggestion for that `query`. | | `suggestion_08` | string | The eighth autocomplete suggestion for that `query`. | | `suggestion_09` | string | The ninth autocomplete suggestion for that `query`. | | `suggestion_10` | string | The tenth autocomplete suggestion for that `query`. | > Note: The actor currently slices suggestions to `max_results` when building each record (`suggestions[:max_results]`). In the provided source code, `max_results` is read from input but it is **not present in the input schema**—so only set it if you already know your runtime will accept it. *** ### How to use Youtube Autocomplete Scraper (via Apify Console) 1. **Open Apify Console**\ Log in at https://console.apify.com and go to the **Actors** section. 2. **Find the actor**\ Search for **Youtube Autocomplete Scraper** and open its listing. 3. **Go to the INPUT section**\ Enter your values using the built-in form (or upload an `input.json`). 4. **Set your core keyword**\ Paste your target keyword into the `query` field (this is what autocomplete suggestions will be generated for). 5. **Choose language and country**\ Select `language` and `country` to better match the audience you care about—useful for workflows like **YouTube autocomplete keyword scraper** research by region. 6. **Optionally expand coverage**\ Enable `use_prefix` and/or `use_suffix` if you want the actor to create additional query variations (helpful for **extract YouTube autocomplete queries** at scale). 7. **Run the actor**\ Click **Run**. During execution, you’ll see logs about fetched suggestion counts. 8. **Open your dataset & export results**\ After the run completes, open the default dataset to view and export your JSON results (and convert to CSV in your downstream tool if needed). No coding required — get structured **Youtube Autocomplete Scraper** outputs in minutes. ✅ *** ### Advanced features & SEO optimization - 🚀 **Engineered for YouTube keyword research autocomplete**: Built specifically for turning a `query` into autocomplete strings you can use for planning and optimization. - 🌍 **Location and language targeting**: Helpful when your **YouTube autocomplete API scraper** workflow needs region-relevant suggestion behavior. - 🔤 **Prefix/suffix expansion**: Toggle `use_prefix` and `use_suffix` to broaden coverage with alphabetic query variations—great for **YouTube related searches scraper** style ideation. - 📊 **Structured `suggestion_XX` fields**: Consistent labeling makes it easy to map results into spreadsheets, dashboards, or SEO tooling. *** ### Best use cases - 📈 **Content creators and SEO strategists**: Build topic clusters from what viewers actually search via `query`-based autocomplete suggestions. - 🏷️ **YouTube keyword research**: Use suggestion strings to refine titles, tags, and descriptions with evidence from autocomplete. - 🎯 **Marketing teams**: Generate bulk ideation lists by enabling `use_prefix` / `use_suffix` for **YouTube autosuggest scraper** workflows. - 🔎 **Data analysts**: Ingest structured `suggestion_01`… fields into notebooks or BI dashboards to compare suggestion patterns. - 🧠 **Research projects**: Track how keyword intent evolves across languages and countries using the `language` and `country` inputs. - 💼 **Agencies**: Produce repeatable keyword research outputs for multiple clients and regions without manual lookup. - 🧩 **Automation pipelines**: Integrate the actor outputs into ETL jobs for “YouTube autocomplete tool” style processes. *** ### Technical specifications - **Supported Input Formats** - ✅ `query` (string) — required - ✅ `language` (string enum) — optional, defaults to `English` - ✅ `country` (string enum) — optional, defaults to `United States` - ✅ `use_prefix` (boolean) — optional, defaults to `false` - ✅ `use_suffix` (boolean) — optional, defaults to `false` - **Proxy Support** - ❌ Not specified in the provided actor inputs (no proxy input fields are defined in the schema) - **Retry Mechanism** - ✅ Includes error handling and returns an empty list if requests fail or responses can’t be parsed - **Dataset Structure** - ✅ JSON records pushed to the default dataset - ✅ Each record includes `query` plus `suggestion_01` … `suggestion_XX` - **Rate Limits & Performance** - ✅ Designed for automated runs; runtime varies depending on how many expanded queries you generate with `use_prefix` / `use_suffix` - **Limitations** - ❌ No email/contact extraction (this actor is for autocomplete suggestions only) - ❌ The provided input schema does not include `max_results`, even though the source code references it—so you should rely on the schema-backed inputs for predictable behavior *** ### FAQ #### ✅ What does the Youtube Autocomplete Scraper return? It returns JSON records where each record contains the `query` you used and multiple suggestion fields labeled as `suggestion_01`, `suggestion_02`, and so on. #### ✅ Can I scrape autocomplete suggestions in different languages? Yes. Use the `language` input to select the language for the suggestion results. This is useful for workflows like a **YouTube autocomplete keyword scraper** across regions. #### ✅ Can I target a specific country? Yes. Set the `country` input to tailor suggestions. This helps when you’re building region-aware lists using **YouTube search suggestions scraper** style research. #### ✅ How do `use_prefix` and `use_suffix` work? When enabled, the actor generates additional queries by adding alphabetic prefixes and/or suffixes around your original `query`, then fetches suggestions for each expanded query. #### ❌ Do I need any special setup or login? No special setup is required beyond configuring `input.json` in Apify Console. The actor is designed to run as a self-contained Apify job. #### 💻 Can I use the output in Python or spreadsheets? Yes. The actor pushes results to the default dataset in JSON format, which you can export and then load into tools like spreadsheets, notebooks, or any downstream pipeline. #### ❗ Is this actor extracting private or non-public data? No. It’s intended for scraping **publicly available sources** of autocomplete suggestions. #### ⚠️ Why might some suggestions be missing? If a request fails or a response can’t be parsed, the actor returns an empty suggestions list for that query variation. *** ### Support & feature requests If you’re using **Youtube Autocomplete Scraper** for YouTube autocomplete research and want improvements, tell us what would make the output more useful for your workflow. - 💡 **Feature Requests**: Ideas like exporting directly to CSV, adding more structured metadata, or expanding control over suggestion counts are all welcome. - 📧 **Contact**: Send a message to . Your feedback helps shape the roadmap for this YouTube autocomplete SEO tool experience. 🙌 *** ### Closing CTA / Final thoughts *Get the most comprehensive, SEO-optimized results with **Youtube Autocomplete Scraper**—turn autocomplete suggestions into structured keyword research you can scale.* # 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("scrapers-hub/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("scrapers-hub/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 scrapers-hub/youtube-autocomplete-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=scrapers-hub/youtube-autocomplete-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Youtube Autocomplete Scraper", "description": "🚀 Youtube Autocomplete Scraper extracts trending keyword suggestions from YouTube autocomplete fast and accurately. 📈 Perfect for SEO research, content ideation, and competitor insights—save time and boost video discovery with smart keyword data.", "version": "1.0", "x-build-id": "X2W5HCMLpPLKbeYbR" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/scrapers-hub~youtube-autocomplete-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-scrapers-hub-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/scrapers-hub~youtube-autocomplete-scraper/runs": { "post": { "operationId": "runs-sync-scrapers-hub-youtube-autocomplete-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/scrapers-hub~youtube-autocomplete-scraper/run-sync": { "post": { "operationId": "run-sync-scrapers-hub-youtube-autocomplete-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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 } } } } } } } } } } ```