# Steam Store Games Scraper (`fetch_cat/steam-store-games-scraper`) Actor Extract Steam Store game metadata, localized prices, discounts, genres, platforms, release dates, images, recommendations, and review summaries. - **URL**: https://apify.com/fetch\_cat/steam-store-games-scraper.md - **Developed by:** [Hanna Nosova](https://apify.com/fetch_cat) (community) - **Categories:** E-commerce, Games, Developer tools - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $0.02 / 1,000 result extracteds 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 ## Steam Store Games Scraper Extract public Steam Store game data for market research, price tracking, catalog enrichment, and competitive analysis. ### At a glance - **Best for:** game catalog enrichment, price tracking, market research, launch research, and competitive analysis. - **Inputs:** Steam app IDs, search terms, country, language, maximum games, and optional enrichment toggles. - **Outputs:** one Steam app per row with prices, discounts, genres, platforms, release dates, images, recommendations, and review summaries when enabled. - **Exports:** download CSV, JSON, Excel, XML, RSS, or use the Apify Dataset API. - **Cost:** `$0.005` per run plus the `item` event for each saved game row. ### Ready-to-run examples Use these saved Store examples as starting points. Open any example to prefill the Actor input, then adjust URLs, keywords, limits, or filters for your own run. - **[Scrape VR games from Steam](https://apify.com/fetch_cat/steam-store-games-scraper/examples/steam-vr-games-catalog)** - **[Find upcoming games on Steam](https://apify.com/fetch_cat/steam-store-games-scraper/examples/steam-upcoming-games-research)** - **[Scrape indie games from the Steam Store](https://apify.com/fetch_cat/steam-store-games-scraper/examples/steam-indie-games-dataset)** - **[Export Steam game screenshots and metadata](https://apify.com/fetch_cat/steam-store-games-scraper/examples/steam-game-screenshots-export)** - **[Scrape Steam games with review summaries](https://apify.com/fetch_cat/steam-store-games-scraper/examples/steam-game-review-summary)** - **[Scrape Steam game prices for Germany](https://apify.com/fetch_cat/steam-store-games-scraper/examples/steam-price-localization-germany)** - **[View all ready-to-run examples](https://apify.com/fetch_cat/steam-store-games-scraper/examples)** (10 examples) ### What can it do? Steam Store Games Scraper collects structured game records from the public Steam Store. It can start from search terms such as `counter strike`, from known Steam app IDs such as `730`, or from both in one run. The actor returns clean dataset rows with game names, app IDs, Store URLs, prices, discounts, release dates, developers, publishers, genres, categories, platforms, Metacritic scores, recommendation counts, media links, and optional review summaries. ### Who is it for? - Indie studios researching competing games and launch windows. - Game analysts tracking pricing, genres, and discount patterns. - Ecommerce and product-intelligence teams building catalog snapshots. - Price-monitoring teams watching discounts across titles. - Data teams enriching internal game databases with public Steam metadata. - Content teams building lists of games by topic, platform, or genre. ### Why use this actor? Steam has a huge catalog, but manual Store browsing is slow. This scraper turns Steam catalog pages into repeatable structured data. You can run small checks for a few app IDs or larger keyword searches for hundreds of games. ### Common use cases - Monitor game prices and discount percentages. - Build a catalog of games matching a search phrase. - Compare genres, categories, developers, and publishers. - Track release dates and coming-soon titles. - Enrich a list of Steam app IDs with Store metadata. - Collect recommendation totals and optional review summary counts. - Export Steam game metadata to CSV, JSON, Excel, or your database. ### Output fields | Field | Description | | --- | --- | | `appId` | Steam app ID | | `name` | Game or app name | | `appType` | Steam app type, usually `game` | | `url` | Public Steam Store URL | | `isFree` | Whether the app is free to play | | `price` | Current price in major currency units | | `initialPrice` | Original price before discount | | `currency` | Localized currency code | | `discountPercent` | Current discount percentage | | `priceFormatted` | Display price text from Steam | | `releaseDate` | Release date text | | `comingSoon` | Whether Steam marks the title as upcoming | | `developers` | Developer names | | `publishers` | Publisher names | | `genres` | Steam genres | | `categories` | Steam categories/features | | `platforms` | Windows/macOS/Linux support flags | | `metacriticScore` | Metacritic score when available | | `recommendationsTotal` | Steam recommendation count when available | | `reviewSummary` | Optional public review summary text | | `headerImage` | Header image URL | | `capsuleImage` | Capsule image URL | | `screenshots` | Optional screenshot URLs | | `shortDescription` | Optional short Store description | | `website` | Optional official website | | `dlcAppIds` | Optional DLC app IDs | | `sourceSearchTerm` | Search term that discovered the app | | `scrapedAt` | Extraction timestamp | ### Pricing The actor uses pay-per-event pricing. You pay a small start fee plus a per-game record fee. Current configured pricing is a $0.005 run-start fee plus tiered per-game pricing: FREE $0.045398 per 1,000 games, BRONZE $0.039476 per 1,000, SILVER $0.030791 per 1,000, GOLD $0.023686 per 1,000, PLATINUM $0.015790 per 1,000, and DIAMOND $0.011053 per 1,000. Apify shows the exact live price before each run. ### Input configuration #### Search terms Use `searchTerms` when you want the actor to discover games from the public Steam search catalog. Example: ```json { "searchTerms": ["counter strike", "survival crafting"], "maxItems": 25 } ```` #### App IDs Use `appIds` when you already know the Steam apps you want. Example: ```json { "appIds": ["730", "570", "440"], "maxItems": 3 } ``` #### Country and language Use `country` to localize prices and `language` to localize supported text. Example: ```json { "searchTerms": ["strategy"], "country": "US", "language": "english", "maxItems": 50 } ``` ### Optional enrichment Turn on optional fields only when you need them. - `includeDescriptions` adds short descriptions and official websites. - `includeScreenshots` adds screenshot URLs. - `includeDlc` adds DLC app IDs. - `includeReviewsSummary` adds public review summary counts. Review summaries require one extra lightweight request per game, so large runs may be faster without them. ### Output example ```json { "appId": 730, "name": "Counter-Strike 2", "appType": "game", "url": "https://store.steampowered.com/app/730/", "isFree": true, "price": 0, "currency": "USD", "discountPercent": 0, "releaseDate": "Aug 21, 2012", "developers": ["Valve"], "publishers": ["Valve"], "genres": ["Action", "Free To Play"], "platforms": { "windows": true, "mac": false, "linux": true }, "recommendationsTotal": 4000000, "sourceSearchTerm": "counter strike", "scrapedAt": "2026-07-01T00:00:00.000Z" } ``` ### How to run 1. Open the actor on Apify. 2. Enter one or more search terms or Steam app IDs. 3. Set `maxItems` to control run size. 4. Choose country and language. 5. Enable optional enrichment if needed. 6. Start the run. 7. Download the dataset as JSON, CSV, Excel, XML, or HTML. ### Tips for best results - Start with a small `maxItems` value to confirm your query. - Use app IDs for precise tracking. - Use search terms for discovery workflows. - Use the same `country` for price comparisons over time. - Disable screenshots for leaner exports. - Enable review summaries only when review counts are important. ### Integrations You can connect results to: - Google Sheets for price monitoring. - Airtable for game catalog operations. - BigQuery or Snowflake for analytics. - Zapier or Make for alerts. - Your backend through the Apify API. - Apify webhooks for scheduled catalog snapshots. ### API usage with Node.js ```js import { ApifyClient } from 'apify-client'; const client = new ApifyClient({ token: process.env.APIFY_TOKEN }); const run = await client.actor('fetch_cat/steam-store-games-scraper').call({ searchTerms: ['counter strike'], maxItems: 10, country: 'US', language: 'english' }); const { items } = await client.dataset(run.defaultDatasetId).listItems(); console.log(items); ``` ### API usage with Python ```python from apify_client import ApifyClient import os client = ApifyClient(os.environ['APIFY_TOKEN']) run = client.actor('fetch_cat/steam-store-games-scraper').call(run_input={ 'appIds': ['730', '570', '440'], 'maxItems': 3, }) items = client.dataset(run['defaultDatasetId']).list_items().items print(items) ``` ### API usage with cURL ```bash curl "https://api.apify.com/v2/acts/fetch_cat~steam-store-games-scraper/runs?token=$APIFY_TOKEN" \ -H 'Content-Type: application/json' \ -d '{"searchTerms":["strategy"],"maxItems":10,"country":"US"}' ``` ### MCP and AI agents Use the official Apify MCP server to call this Actor from compatible AI tools. The default server can search and run Actors; the focused URL exposes only this Actor. MCP URL pattern: ```text https://mcp.apify.com?tools=fetch_cat/steam-store-games-scraper ``` Claude Code setup command: ```bash claude mcp add apify https://mcp.apify.com?tools=fetch_cat/steam-store-games-scraper ``` Claude Desktop JSON config example: ```json { "mcpServers": { "apify-steam-store-games": { "url": "https://mcp.apify.com?tools=fetch_cat/steam-store-games-scraper" } } } ``` Example prompts: - "Find 20 Steam games for the query survival crafting and summarize pricing." - "Extract metadata for Steam app IDs 730, 570, and 440." - "Compare discounts for Steam strategy games in the US store." ### Scheduling Run this actor daily, weekly, or monthly to monitor changing Steam prices and discounts. Scheduled runs work well for watchlists of app IDs. For keyword discovery, keep `maxItems` bounded so snapshots remain comparable over time. ### Limitations - Steam may omit fields for some apps. - Mature or age-gated titles may return limited metadata. - Pricing depends on the selected country. - Recommendation and review fields are aggregate public signals, not full review text. - Full Steam review scraping is a separate workflow. ### Troubleshooting #### Why did I get fewer games than `maxItems`? The search term may have fewer unique public Store results, or duplicate app IDs may have been removed. Try a broader search term or add direct app IDs. #### Why is price empty? Some apps are free, unreleased, unavailable in the selected country, or missing price metadata. Check `isFree`, `comingSoon`, and `priceFormatted`. #### Why are review fields empty? Enable `includeReviewsSummary` to fetch public review summary counts. Some apps may still not have enough review data. ### Legality and ethical use This actor extracts publicly available Steam Store metadata. Use the data responsibly, respect Steam's terms, and avoid excessive run sizes. Do not use the actor to collect private account data. ### Related actors - [Steam Reviews Scraper](https://apify.com/fetch_cat/steam-reviews-scraper) ### Changelog - 2026-07-04 - Feature: Launched Steam Store Games Scraper on Apify Store (APIA-1222) - This actor is now publicly available at https://apify.com/fetch\_cat/steam-store-games-scraper. #### 0.1 Initial version with search terms, app IDs, localized prices, core metadata, optional screenshots, DLC IDs, and optional review summaries. ### Support If a run fails, returns no data, or a field looks wrong, open an issue from the Actor page. Please include the Apify run ID or run URL, input JSON, one example public URL, query, or input item, what you expected, and what the dataset returned. Small reproducible inputs make parsing or site-layout issues much faster to fix. ### FAQ #### Can I scrape by app ID only? Yes. Provide `appIds` and leave `searchTerms` empty. #### Can I search multiple keywords? Yes. Add multiple strings to `searchTerms`. #### Can I get CSV output? Yes. Apify datasets can be exported as CSV, JSON, Excel, XML, RSS, or HTML. #### Does it use my Steam account? No. It works with public Steam Store data only. #### Can I scrape all of Steam? Use bounded runs and scheduled snapshots. Very broad full-catalog extraction should be split into controlled batches. #### Does it include full user reviews? No. This actor focuses on catalog metadata. Use a dedicated Steam reviews actor for full review text. #### Can I track discounts over time? Yes. Schedule app ID watchlist runs and compare `price`, `initialPrice`, and `discountPercent` across datasets. #### Can I localize prices? Yes. Set the `country` input to a two-letter country code. #### Can I localize text? Yes. Set the `language` input to a Steam-supported language value. #### Are screenshots included by default? No. Enable `includeScreenshots` when you need image URLs. #### Are DLC IDs included by default? No. Enable `includeDlc` when DLC relationships are important. #### Is this a browser scraper? No user action is required. The actor runs automatically in Apify and returns structured results. ### Version notes This first release is optimized for dependable catalog metadata and price tracking. Future versions may add richer search filters, top seller modes, and named datasets if additional entity types are introduced. # Actor input Schema ## `searchTerms` (type: `array`): Steam Store search keywords. Each term is searched until maxItems is reached. ## `appIds` (type: `array`): Known Steam app IDs to extract directly, for example 730 for Counter-Strike 2. ## `maxItems` (type: `integer`): Maximum number of unique Steam game records to save. ## `country` (type: `string`): Two-letter country code used by Steam for localized prices, for example US, GB, DE, JP. ## `language` (type: `string`): Steam language code for localized text fields. ## `includeDescriptions` (type: `boolean`): Include short description and official website when available. ## `includeScreenshots` (type: `boolean`): Include screenshot URLs from Steam app details. ## `includeDlc` (type: `boolean`): Include DLC app IDs listed on the game detail response. ## `includeReviewsSummary` (type: `boolean`): Fetch public review summary counts from Steam appreviews for each app. Adds one lightweight request per game. ## Actor input object example ```json { "searchTerms": [ "counter strike" ], "appIds": [ "730", "570", "440" ], "maxItems": 10, "country": "US", "language": "english", "includeDescriptions": true, "includeScreenshots": false, "includeDlc": false, "includeReviewsSummary": false } ``` # Actor output Schema ## `overview` (type: `string`): No description # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "searchTerms": [ "counter strike" ], "appIds": [ "730", "570", "440" ] }; // Run the Actor and wait for it to finish const run = await client.actor("fetch_cat/steam-store-games-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 = { "searchTerms": ["counter strike"], "appIds": [ "730", "570", "440", ], } # Run the Actor and wait for it to finish run = client.actor("fetch_cat/steam-store-games-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 '{ "searchTerms": [ "counter strike" ], "appIds": [ "730", "570", "440" ] }' | apify call fetch_cat/steam-store-games-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=fetch_cat/steam-store-games-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Steam Store Games Scraper", "description": "Extract Steam Store game metadata, localized prices, discounts, genres, platforms, release dates, images, recommendations, and review summaries.", "version": "0.1", "x-build-id": "7f7OPrxp4CkdVoVjB" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/fetch_cat~steam-store-games-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-fetch_cat-steam-store-games-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/fetch_cat~steam-store-games-scraper/runs": { "post": { "operationId": "runs-sync-fetch_cat-steam-store-games-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/fetch_cat~steam-store-games-scraper/run-sync": { "post": { "operationId": "run-sync-fetch_cat-steam-store-games-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": { "searchTerms": { "title": "Search terms", "type": "array", "description": "Steam Store search keywords. Each term is searched until maxItems is reached.", "items": { "type": "string" } }, "appIds": { "title": "Steam app IDs", "type": "array", "description": "Known Steam app IDs to extract directly, for example 730 for Counter-Strike 2.", "items": { "type": "string" } }, "maxItems": { "title": "Maximum games", "minimum": 1, "maximum": 10000, "type": "integer", "description": "Maximum number of unique Steam game records to save.", "default": 10 }, "country": { "title": "Country code", "minLength": 2, "maxLength": 2, "type": "string", "description": "Two-letter country code used by Steam for localized prices, for example US, GB, DE, JP.", "default": "US" }, "language": { "title": "Language", "type": "string", "description": "Steam language code for localized text fields.", "default": "english" }, "includeDescriptions": { "title": "Include descriptions and website", "type": "boolean", "description": "Include short description and official website when available.", "default": true }, "includeScreenshots": { "title": "Include screenshots", "type": "boolean", "description": "Include screenshot URLs from Steam app details.", "default": false }, "includeDlc": { "title": "Include DLC app IDs", "type": "boolean", "description": "Include DLC app IDs listed on the game detail response.", "default": false }, "includeReviewsSummary": { "title": "Include review summary", "type": "boolean", "description": "Fetch public review summary counts from Steam appreviews for each app. Adds one lightweight request per game.", "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 } } } } } } } } } } ```