# Steam Community Discussions Scraper (`automation-lab/steam-community-discussions-scraper`) Actor Extract public Steam discussion topics, posts, replies, authors, timestamps, awards, and thread status for community monitoring. - **URL**: https://apify.com/automation-lab/steam-community-discussions-scraper.md - **Developed by:** [Stas Persiianenko](https://apify.com/automation-lab) (community) - **Categories:** Social media - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing Pay per event 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/docs.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python/docs.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/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 Community Discussions Scraper Extract public Steam Community discussion topics, original posts, and replies into structured records for support research, community monitoring, sentiment analysis, and RAG workflows. Use a Steam app ID for broad game-forum coverage or provide exact category and thread URLs for focused collection. Export the resulting dataset as JSON, CSV, Excel, XML, or RSS, or send it directly to your automation stack. ### What does Steam Community Discussions Scraper do? Steam Community Discussions Scraper turns public, server-rendered Steam forum pages into analysis-ready topic and post records. It can: - discover discussions for one or more Steam games - collect topic titles, IDs, URLs, reply counts, awards, and status flags - expand discovered threads into original posts and ordered replies - preserve displayed author names and public profile URLs - return Steam timestamps in Unix and ISO 8601 formats - scrape a known category or thread directly - run in topic-only mode for inexpensive recurring monitoring The Actor accesses anonymous public pages only. It does not sign in, post, vote, subscribe, or retrieve private content. ### Who is it for? ๐ŸŽฎ **Game studios and publishers** can identify recurring bugs, feature requests, balance complaints, and player questions. ๐ŸŽง **Community and support teams** can route new conversations into triage queues and measure which topics attract the most replies. ๐Ÿ“Š **Market researchers** can compare public player conversations across games and follow shifts around launches or updates. ๐Ÿค– **Data and AI teams** can build sentiment classifiers, searchable archives, RAG collections, and alerting pipelines from structured forum text. ๐Ÿ›ก๏ธ **Trust and safety analysts** can review publicly visible conversation patterns while retaining canonical evidence URLs. ### Why use this Actor? Steam forum pages are designed for people, not repeatable data workflows. This Actor handles discovery, pagination, parsing, normalization, deduplication, and dataset storage for you. Benefits include: - **Auditable records:** every topic and post links to its public Steam thread. - **Stable identifiers:** Steam topic and post IDs support downstream deduplication. - **Predictable scope:** separate topic and post limits keep output volume controlled. - **Flexible depth:** collect summaries frequently, then expand only conversations that matter. - **Automation-ready output:** consume results through exports, the Apify API, webhooks, schedules, or integrations. ### What data can I extract? | Field | Description | |---|---| | `recordType` | `topic` summary or `post` content record | | `appId` | Steam application ID | | `categoryId` | Discussion category ID when available | | `topicId` | Stable Steam forum topic ID | | `postId` | Stable original-post or reply ID | | `title` | Discussion title | | `threadUrl` | Canonical public thread URL | | `authorName` | Displayed Steam Community author name | | `authorUrl` | Public author profile URL when available | | `body` | Normalized post text | | `timestamp` | ISO 8601 publication timestamp | | `timestampUnix` | Steam Unix timestamp | | `replyOrder` | Position of a post in its conversation | | `replyCount` | Number of replies shown for a topic | | `awardCount` | Number of displayed community awards | | `isPinned` | Whether the topic is pinned | | `isLocked` | Whether the topic is locked | | `scrapedAt` | ISO 8601 collection time | Optional values that Steam does not expose are returned as `null`; the Actor does not invent missing data. ### How to scrape Steam Community discussions 1. Open **Steam Community Discussions Scraper** in the Apify Store. 2. Click **Try for free** to open the Actor input page. 3. Enter one or more Steam app IDs, such as `730` for Counter-Strike 2, or add public discussion/thread URLs. 4. Choose whether to enable **Extract thread posts**. Disable it when topic summaries are sufficient. 5. Set **Maximum topics** and **Maximum posts** to control the dataset size and cost. 6. Leave proxy use disabled for a small first run; enable Apify Proxy only if your larger workload needs it. 7. Click **Start** and wait for the run to finish. 8. Open the **Dataset** tab to review, filter, export, or integrate the records. For recurring monitoring, save the input as an Apify task and attach a schedule after confirming the first result set. ### Input The Actor accepts these fields: | Input | Type | Purpose | |---|---|---| | `appIds` | string array | Numeric Steam app IDs to monitor | | `startUrls` | request list | Public category indexes or individual thread URLs | | `expandThreads` | boolean | Extract original posts and replies when `true` | | `maxTopics` | integer | Maximum topic summaries discovered across category pages | | `maxPosts` | integer | Maximum post records extracted across threads | | `proxyConfiguration` | object | Optional Apify Proxy configuration | You may combine app IDs and URLs in one run. Limits apply across the complete run rather than independently to every source. ### Input examples #### Low-cost topic discovery ```json { "appIds": ["730"], "expandThreads": false, "maxTopics": 25, "maxPosts": 1 } ```` #### Collect topics and replies ```json { "appIds": ["570"], "expandThreads": true, "maxTopics": 20, "maxPosts": 100 } ``` #### Extract a known public thread ```json { "startUrls": [ { "url": "https://steamcommunity.com/app/730/discussions/0/" } ], "expandThreads": true, "maxTopics": 10, "maxPosts": 50 } ``` ### Output example ```json { "recordType": "post", "appId": "730", "categoryId": "0", "topicId": "example-topic-id", "postId": "example-post-id", "title": "Example discussion title", "threadUrl": "https://steamcommunity.com/app/730/discussions/0/example-topic-id/", "authorName": "Community member", "authorUrl": "https://steamcommunity.com/profiles/example", "body": "Public discussion text appears here.", "timestamp": "2026-07-12T12:00:00.000Z", "timestampUnix": 1783857600, "replyOrder": 0, "replyCount": null, "awardCount": null, "isPinned": false, "isLocked": false, "scrapedAt": "2026-07-12T12:05:00.000Z" } ``` Topic rows and post rows share one dataset and are distinguished by `recordType`. ### How much does it cost to scrape Steam Community discussions? Pricing consists of a **$0.005 run start** plus a charge for each topic or post saved to the dataset. Per-item prices decrease with the Apify subscription tier: | Tier | Price per saved topic or post | |---|---:| | FREE | $0.000035889 | | BRONZE | $0.000031208 | | SILVER | $0.000024342 | | GOLD | $0.000018725 | | PLATINUM | $0.000012483 | | DIAMOND | $0.000010000 | Concrete examples, excluding any platform compute usage included by your Apify plan: - **100 records on FREE:** $0.005 start + $0.0035889 = about **$0.0086**. - **1,000 records on BRONZE:** $0.005 start + $0.031208 = about **$0.0362**. - **10,000 records on DIAMOND:** $0.005 start + $0.10 = about **$0.105**. Only records successfully saved are item events. Your exact total depends on output volume and your active Apify tier. Use topic-only mode and conservative limits when validating a new workflow. ### Topic-only monitoring workflow Set `expandThreads` to `false` when you need discovery rather than full conversation text. 1. Schedule a modest topic-only task. 2. Store `topicId` as the stable deduplication key. 3. Compare `replyCount`, `awardCount`, `isPinned`, and `isLocked` between runs. 4. Send newly discovered or fast-growing `threadUrl` values to a second deep-extraction task. 5. Alert the relevant support or community team. This two-stage design reduces unnecessary requests and output events. ### Full-thread research workflow Use exact thread URLs or enable thread expansion when post text and reply order matter. - Preserve `recordType + topicId + postId` as a compound key. - Sort post rows by `replyOrder` before conversation analysis. - Keep `threadUrl` with derived labels so analysts can audit the original source. - Use `timestamp` for BI tools and `timestampUnix` for numeric comparisons. - Track `scrapedAt` separately from publication time. ### Integrations Connect the Actor to specific downstream workflows: - **Google Sheets:** append newly discovered topics for community managers to review and assign. - **Slack or Microsoft Teams:** use an Apify webhook plus Make or Zapier to alert on high-reply or newly pinned discussions. - **Airtable:** maintain a support-research backlog keyed by `topicId` and update reply counts on each scheduled run. - **BigQuery, Snowflake, or PostgreSQL:** load normalized records for trend dashboards and cross-game analysis. - **Amazon S3 or Google Cloud Storage:** archive periodic exports for reproducible research. - **LLM and RAG pipelines:** chunk `body`, retain `threadUrl` as citation metadata, and filter retrieval by `appId`. - **Sentiment services:** classify each post, then aggregate labels by game, topic, or release window. Apify schedules provide recurring runs; webhooks can start the integration only after a run succeeds. ### API usage #### Node.js ```javascript import { ApifyClient } from 'apify-client'; const client = new ApifyClient({ token: process.env.APIFY_TOKEN }); const run = await client.actor('automation-lab/steam-community-discussions-scraper').call({ appIds: ['730'], maxTopics: 20, maxPosts: 100, expandThreads: true, }); const { items } = await client.dataset(run.defaultDatasetId).listItems(); ``` #### Python ```python from apify_client import ApifyClient client = ApifyClient('YOUR_APIFY_TOKEN') run = client.actor('automation-lab/steam-community-discussions-scraper').call( run_input={ 'appIds': ['730'], 'maxTopics': 20, 'maxPosts': 100, 'expandThreads': True, } ) items = client.dataset(run['defaultDatasetId']).list_items().items ``` #### cURL ```bash curl -X POST \ 'https://api.apify.com/v2/acts/automation-lab~steam-community-discussions-scraper/runs?token=YOUR_APIFY_TOKEN' \ -H 'Content-Type: application/json' \ -d '{"appIds":["730"],"maxTopics":20,"maxPosts":100,"expandThreads":true}' ``` ### MCP for Claude Add the hosted Apify MCP server in Claude Code: ```bash claude mcp add --transport http apify \ 'https://mcp.apify.com/?tools=automation-lab/steam-community-discussions-scraper' ``` Claude Desktop configuration: ```json { "mcpServers": { "apify": { "url": "https://mcp.apify.com/?tools=automation-lab/steam-community-discussions-scraper" } } } ``` Example prompts: - โ€œFind newly active Counter-Strike 2 bug discussions and summarize the recurring issues.โ€ - โ€œExtract this public Steam thread and return the replies in chronological order.โ€ - โ€œCompare topic engagement for these Steam app IDs and cite the source threads.โ€ ### Data quality and deduplication Steam IDs are stored as strings to avoid numeric precision loss. Topic records use `topicId`; post records contain both `topicId` and `postId`. For repeat runs, deduplicate with: ```text recordType + topicId + postId ``` For topic rows without a post ID, use `recordType + topicId`. Text is whitespace-normalized while preserving readable content. Canonical URLs make every record traceable to its public source. ### Performance tips - Start with one app ID and the low prefilled limits. - Disable thread expansion for frequent discovery jobs. - Use direct thread URLs when the conversations are already known. - Increase `maxTopics` and `maxPosts` gradually after reviewing output. - Enable Apify Proxy only when sustained workloads require it. - Schedule larger crawls less frequently and deduplicate downstream. - Keep output limits aligned with what your integration can process. ### Limitations - Deleted, moderated, private, age-gated, or login-only content is unavailable. - Steam may change page markup or throttle sustained traffic. - Display names can change and should not be treated as verified identities. - Some optional metadata is absent from particular categories or posts. - Results reflect what the public page exposes at scrape time and are not a complete historical archive. - One dataset contains both topic and post entity types; use `recordType` when filtering. ### Troubleshooting **A public URL returns no records. What should I check?** Confirm it is a `steamcommunity.com/app/.../discussions/...` category or thread URL, opens without login, and has not been removed. Then inspect the run log for a response or parsing error. **My scheduled crawl receives throttling responses. What should I do?** Reduce limits or frequency first. For sustained collection, enable Apify Proxy and keep the workload conservative rather than retrying aggressively. **Why does a topic have no reply rows?** The topic may contain only its original post, thread expansion may be disabled, the global post limit may have been reached, or moderated content may expose less text than the index indicates. **Why are some fields `null`?** Steam does not display every field on every page. The Actor returns `null` rather than fabricating unavailable values. ### Legality and responsible use The Actor reads public pages without logging in. Use it only for a lawful purpose, respect Steam's terms and reasonable request rates, and process usernames and post text according to applicable privacy and data-protection rules. Do not use forum data to harass people, infer sensitive traits, or make unsupported consequential decisions. Retain source links and apply human review where context matters. ### Related scrapers These Automation Labs actors support adjacent Steam research workflows: - [Steam Game Reviews Scraper](https://apify.com/automation-lab/steam-game-reviews-scraper) โ€” collect public game reviews and ratings for sentiment analysis. - [Steam Workshop Scraper](https://apify.com/automation-lab/steam-workshop-scraper) โ€” extract Workshop mods and community-created item metadata. - [Steam Curator Reviews Scraper](https://apify.com/automation-lab/steam-curator-reviews-scraper) โ€” gather curator recommendations and review text. - [Steam Scraper](https://apify.com/automation-lab/steam-scraper) โ€” collect broader Steam store and game metadata. Choose this Discussions Scraper when the required dataset is forum topics, original posts, and replies rather than store, review, curator, or Workshop records. ### FAQ **Does it require a Steam account?** No. It reads only pages available anonymously. **Can I monitor several games in one run?** Yes. Add multiple strings to `appIds`; the topic and post limits apply across the whole run. **Can I collect only topic summaries?** Yes. Set `expandThreads` to `false`. **Can I scrape one exact conversation?** Yes. Add its public thread URL to `startUrls` and enable thread expansion. **Are timestamps normalized?** Yes. Available Steam timestamps are returned as both Unix values and ISO 8601 strings. **Can I export the output?** Yes. Apify datasets support JSON, CSV, Excel, XML, RSS, and API access. ### Support For reproducible help, include the public app ID or discussion URL, sanitized input, run ID, and a description of the unexpected output. Never share Steam credentials; this Actor does not need them. # Actor input Schema ## `appIds` (type: `array`): Numeric app IDs, such as 730 for Counter-Strike 2. ## `startUrls` (type: `array`): Steam Community category indexes or individual public threads. ## `expandThreads` (type: `boolean`): Turn off for a lower-cost topic monitoring run. ## `maxTopics` (type: `integer`): Maximum topic records discovered from category pages. ## `maxPosts` (type: `integer`): Maximum original posts and replies extracted across threads. ## `proxyConfiguration` (type: `object`): Optional Apify Proxy settings for larger monitoring runs. ## Actor input object example ```json { "appIds": [ "730" ], "expandThreads": true, "maxTopics": 10, "maxPosts": 20, "proxyConfiguration": { "useApifyProxy": 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 = { "appIds": [ "730" ], "expandThreads": true, "maxTopics": 10, "maxPosts": 20, "proxyConfiguration": { "useApifyProxy": false } }; // Run the Actor and wait for it to finish const run = await client.actor("automation-lab/steam-community-discussions-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`๐Ÿ’พ 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); }); // ๐Ÿ“š Want to learn more ๐Ÿ“–? Go to โ†’ 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 = { "appIds": ["730"], "expandThreads": True, "maxTopics": 10, "maxPosts": 20, "proxyConfiguration": { "useApifyProxy": False }, } # Run the Actor and wait for it to finish run = client.actor("automation-lab/steam-community-discussions-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("๐Ÿ’พ Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # ๐Ÿ“š Want to learn more ๐Ÿ“–? Go to โ†’ https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "appIds": [ "730" ], "expandThreads": true, "maxTopics": 10, "maxPosts": 20, "proxyConfiguration": { "useApifyProxy": false } }' | apify call automation-lab/steam-community-discussions-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=automation-lab/steam-community-discussions-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Steam Community Discussions Scraper", "description": "Extract public Steam discussion topics, posts, replies, authors, timestamps, awards, and thread status for community monitoring.", "version": "0.1", "x-build-id": "E5Ohsgp2nZcCZQGJz" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/automation-lab~steam-community-discussions-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-automation-lab-steam-community-discussions-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/automation-lab~steam-community-discussions-scraper/runs": { "post": { "operationId": "runs-sync-automation-lab-steam-community-discussions-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/automation-lab~steam-community-discussions-scraper/run-sync": { "post": { "operationId": "run-sync-automation-lab-steam-community-discussions-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "appIds": { "title": "Steam app IDs", "type": "array", "description": "Numeric app IDs, such as 730 for Counter-Strike 2.", "items": { "type": "string" } }, "startUrls": { "title": "Discussion or thread URLs", "type": "array", "description": "Steam Community category indexes or individual public threads.", "items": { "type": "object", "required": [ "url" ], "properties": { "url": { "type": "string", "title": "URL of a web page", "format": "uri" } } } }, "expandThreads": { "title": "Extract thread posts", "type": "boolean", "description": "Turn off for a lower-cost topic monitoring run.", "default": true }, "maxTopics": { "title": "Maximum topics", "minimum": 1, "maximum": 5000, "type": "integer", "description": "Maximum topic records discovered from category pages.", "default": 25 }, "maxPosts": { "title": "Maximum posts", "minimum": 1, "maximum": 10000, "type": "integer", "description": "Maximum original posts and replies extracted across threads.", "default": 100 }, "proxyConfiguration": { "title": "Proxy configuration", "type": "object", "description": "Optional Apify Proxy settings for larger monitoring runs." } } }, "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 } } } } } } } } } } ```