# Actor Pricing Simulator (`junipr/actor-pricing-simulator`) Actor Estimate Apify actor PPE pricing, break-even points, margins, and profit risk from run-cost assumptions. - **URL**: https://apify.com/junipr/actor-pricing-simulator.md - **Developed by:** [junipr](https://apify.com/junipr) (community) - **Categories:** Developer tools - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $6.50 / 1,000 operation testeds This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. 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 ## Actor Pricing Simulator ### Store Positioning **Store title:** Actor Pricing Simulator **Short description:** Estimate Apify actor PPE pricing, break-even points, margins, and profit risk from run-cost assumptions. **SEO title:** Actor Pricing Simulator — API, schema, and developer QA **SEO description:** Estimate Apify actor PPE pricing, break-even points, margins, and profit risk from run-cost assumptions. Use it to catch contract drift, schema mistakes, unsafe endpoint assumptions, and developer-tool quality issues before release. **Categories:** DEVELOPER_TOOLS **Keywords:** actor, pricing, simulator, apify actor, pricing audit, api testing, api/developer qa ### Fixed-Inclusive PPE Pricing This actor uses pay-per-event pricing. Event prices include Apify platform usage; users are not expected to pay a separate platform-usage pass-through charge for the configured pricing model. - Tier: A1 — API/developer QA - Primary event: `operation-tested` at $0.00650 base - Default max charge: $10.00 - Store discounts: FREE/BRONZE base, SILVER discounted, GOLD deepest approved discount Event set: - `actor-start`: base $0.00500, GOLD $0.00400. Actor Pricing Simulator: charged when actor start is completed. The price includes Apify platform usage; no separate usage pass-through is intended. - `operation-tested`: base $0.00650, GOLD $0.00520. Actor Pricing Simulator: charged when operation tested is completed. The price includes Apify platform usage; no separate usage pass-through is intended. - `contract-rule-checked`: base $0.00390, GOLD $0.00312. Actor Pricing Simulator: charged when contract rule checked is completed. The price includes Apify platform usage; no separate usage pass-through is intended. - `report-generated`: base $0.05000, GOLD $0.04000. Actor Pricing Simulator: charged when report generated is completed. The price includes Apify platform usage; no separate usage pass-through is intended. ### Public Task Concepts - Build an Actor Pricing stakeholder brief from source rows - Prioritize Actor Pricing findings with evidence and confidence - Summarize Actor Pricing metrics into recommended actions - Prepare an Actor Pricing source table with uncertainty notes - Export Actor Pricing decision rows for review Estimate Apify actor pay-per-event pricing, break-even points, expected margins, and profit risk before publishing or promoting an actor. ### What This Actor Does Actor Pricing Simulator models Apify marketplace fees, primary PPE events, fixed run-start/report events, platform usage cost, pass-through assumptions, and target margin. It returns one dataset row per scenario and optional key-value-store reports for quick pricing review. It is designed for creator operations, portfolio audits, and pre-publish checks where a bad price can turn a working actor into a loss-making actor. ### What This Actor Does Not Do - It does not change live Apify pricing. - It does not publish actors. - It does not fetch private earnings, billing, or customer-plan data from Apify. - It does not guarantee revenue, rankings, or profitability. - It is not financial advice; it is a deterministic calculator based on the assumptions you provide. ### Best Use Cases - Check whether a browser, proxy, OCR, or file-conversion actor can absorb owner-paid platform usage. - Find the break-even PPE event price for a scraper before it goes public. - Compare usage-included pricing against platform usage pass-through. - Triage a portfolio and identify actors likely to lose money. - Prepare exact pricing notes before a Console/API pricing update. ### Input Fields - `scenarios`: Pricing scenarios to simulate. Each scenario can include `actorSlug`, `eventName`, `eventPriceUsd`, `itemsPerRun`, `platformUsageCostPerRunUsd`, fixed start/report event prices, pass-through mode, and target margin. - `apifyFeePct`: Marketplace fee percentage deducted from event revenue. The default is `20`. - `defaultTargetGrossMarginPct`: Target margin used when a scenario does not provide one. The default is `60`. - `includeSensitivity`: Add price sensitivity points at 75%, 100%, 125%, and 150% of the provided event price. - `includeReport`: Write `PRICING_SIMULATIONS.json`, `PRICING_SUMMARY.json`, and `PRICING_REPORT.md` to the key-value store. - `maxScenarios`: Maximum scenarios to process. The default is `100`; the hard cap is `1000`. - `maxChargeUsd`: Hard run-level PPE cap. Defaults to `$10`; the actor stops before paid work or withholds uncharged reports when the next event would exceed it. - `debug`: Enable extra troubleshooting logs. The default input includes one browser/proxy-heavy example and one cheap utility example so a zero-config run demonstrates meaningful output quickly. ### Example Input ```json { "scenarios": [ { "actorSlug": "example-browser-scraper", "eventName": "item-scraped", "eventPriceUsd": 0.012, "itemsPerRun": 100, "platformUsageCostPerRunUsd": 0.65, "fixedStartEventPriceUsd": 0.025, "reportEventPriceUsd": 0.05, "passThroughUsageToUser": false, "targetGrossMarginPct": 60 } ], "apifyFeePct": 20, "includeSensitivity": true, "includeReport": true, "maxScenarios": 10 } ```` ### Output Fields Each dataset item represents one pricing scenario: - `scenarioId`: Stable scenario hash. - `actorSlug` and `eventName`: Actor/scenario label and primary PPE event. - `status`: Scenario processing status. Current value is `simulated`. - `eventPriceUsd`: Proposed primary event price. - `itemsPerRun`: Assumed billable primary events per run. - `platformUsageCostPerRunUsd`: Estimated platform/proxy/browser cost per run. - `passThroughUsageToUser`: Whether platform usage is assumed paid by the user. - `grossRevenueUsd`: Event revenue before Apify fee. - `netEventRevenueUsd`: Event revenue after marketplace fee. - `ownerUsageCostUsd`: Platform usage cost absorbed by the actor owner. - `netProfitUsd`: Net event revenue minus owner usage cost. - `grossMarginPct`: Net profit divided by net event revenue. - `breakEvenEventPriceUsd`: Primary event price needed to break even. - `targetMarginEventPriceUsd`: Primary event price needed for the target margin. - `riskLevel`: `low`, `medium`, `high`, or `loss`. - `recommendation`: Plain-language action based on the simulated risk. - `issues`: Structured pricing issues such as underpriced events or high usage-cost share. - `sensitivity`: Optional price sensitivity points. - `processedAt`: ISO timestamp for the simulation. The key-value store also contains: - `PRICING_SIMULATIONS.json`: Full scenario array. - `PRICING_SUMMARY.json`: Run-level counts and totals. - `PRICING_REPORT.md`: Human-readable summary report. ### Example Output ```json { "actorSlug": "example-browser-scraper", "eventName": "item-scraped", "status": "simulated", "eventPriceUsd": 0.012, "itemsPerRun": 100, "platformUsageCostPerRunUsd": 0.65, "passThroughUsageToUser": false, "grossRevenueUsd": 1.275, "netEventRevenueUsd": 1.02, "ownerUsageCostUsd": 0.65, "netProfitUsd": 0.37, "grossMarginPct": 36.27, "breakEvenEventPriceUsd": 0.007375, "targetMarginEventPriceUsd": 0.019563, "riskLevel": "medium", "recommendation": "Pricing is viable but below target margin. Consider testing $0.0196 per event." } ``` ### Cost-Control Tips - Start with 1-10 scenarios. - Use measured run cost from small Apify runs when available. - For browser, proxy, OCR, video, or large-crawl actors, test both owner-paid usage and pass-through scenarios. - Treat default free-plan runs as a separate profitability question because event revenue and platform usage handling can differ by user plan. ### Public Task Examples This actor includes five prepared task concepts: - Browser scraper PPE margin check. - Utility actor break-even check. - Pass-through comparison. - Price increase target model. - Portfolio pricing triage sample. ### FAQ #### Does this update my live Apify pricing? No. It only calculates recommendations. Apply pricing changes separately through the Apify Console/API after reviewing the output. #### What cost should I put in `platformUsageCostPerRunUsd`? Use a measured small run when possible. If you only have estimates, enter a conservative high estimate and compare the sensitivity output. #### Why does the actor include Apify fee? Gross event revenue is not the same as owner revenue. The simulation defaults to a 20% marketplace fee, so net event revenue is 80% of configured event revenue before owner-paid platform usage. #### Are diagnostics billed as dataset rows? ### Troubleshooting - `Primary event price is missing or zero`: Set `eventPriceUsd` for each scenario. - `Owner-paid usage cost exceeds net event revenue`: Raise the event price, lower run cost, reduce run size, or enable usage pass-through. - Results look too optimistic: Increase `platformUsageCostPerRunUsd` and use the measured cost from a realistic smoke run. - Too many scenarios: Lower `maxScenarios` or split the portfolio into smaller runs. ### Limitations - This actor uses user-provided assumptions; it cannot see private Apify earnings or exact free-plan versus paid-plan user mix. - It models linear primary-event volume and fixed run/report events, not every possible pricing structure. - It does not account for refunds, coupons, exchange-rate effects, or conversion changes from price increases. ### Source And Safety Notes This actor does not scrape websites or process personal data. It only computes pricing math from the scenario values supplied by the user. ### Changelog - `1.0.0`: Initial production build with break-even math, target-margin pricing, risk classification, sensitivity output, KVS summaries, PPE billing, examples, and fixture tests. # Actor input Schema ## `scenarios` (type: `array`): Actor pricing and cost scenarios to simulate. ## `apifyFeePct` (type: `number`): Marketplace fee percentage deducted from event revenue before platform usage cost. ## `defaultTargetGrossMarginPct` (type: `number`): Target gross margin used when a scenario does not provide one. ## `includeSensitivity` (type: `boolean`): Include price/cost sensitivity points for each scenario. ## `maxItems` (type: `integer`): Alias for Max Targets/Maximum Records used by the Junipr actor baseline. When both are provided, actor-specific limits still apply. ## `includeReport` (type: `boolean`): Write summary JSON and Markdown report artifacts to the key-value store. ## `maxScenarios` (type: `integer`): Maximum scenarios to simulate. ## `maxChargeUsd` (type: `number`): Hard local spending cap for actor-start, per-item, and report events. The actor stops before work or withholds uncharged output when the next event would exceed this amount. ## `dryRun` (type: `boolean`): Validate input and write a dry-run summary without PPE charges or dataset output. ## `debug` (type: `boolean`): Enable debug logs. ## Actor input object example ```json { "scenarios": [ { "actorSlug": "example-browser-scraper", "eventName": "item-scraped", "eventPriceUsd": 0.012, "itemsPerRun": 100, "platformUsageCostPerRunUsd": 0.65, "fixedStartEventPriceUsd": 0.025, "reportEventPriceUsd": 0.05, "passThroughUsageToUser": false, "targetGrossMarginPct": 60 }, { "actorSlug": "cheap-cleaner", "eventName": "item-processed", "eventPriceUsd": 0.00195, "itemsPerRun": 500, "platformUsageCostPerRunUsd": 0.02, "fixedStartEventPriceUsd": 0.001, "reportEventPriceUsd": 0.01, "passThroughUsageToUser": false, "targetGrossMarginPct": 60 } ], "apifyFeePct": 20, "defaultTargetGrossMarginPct": 60, "includeSensitivity": true, "maxItems": 100, "includeReport": true, "maxScenarios": 100, "maxChargeUsd": 10, "dryRun": false, "debug": false } ``` # Actor output Schema ## `results` (type: `string`): Each dataset row is one actor pricing scenario with revenue, cost, margin, risk, and recommendation fields. ## `pricingSimulationsJson` (type: `string`): Full JSON array of pricing scenario results. ## `summaryJson` (type: `string`): Run-level risk counts and projected profit totals. ## `summaryReport` (type: `string`): Markdown report describing the pricing simulation results. # 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 = { "scenarios": [ { "actorSlug": "example-browser-scraper", "eventName": "item-scraped", "eventPriceUsd": 0.012, "itemsPerRun": 100, "platformUsageCostPerRunUsd": 0.65, "fixedStartEventPriceUsd": 0.025, "reportEventPriceUsd": 0.05, "passThroughUsageToUser": false, "targetGrossMarginPct": 60 }, { "actorSlug": "cheap-cleaner", "eventName": "item-processed", "eventPriceUsd": 0.00195, "itemsPerRun": 500, "platformUsageCostPerRunUsd": 0.02, "fixedStartEventPriceUsd": 0.001, "reportEventPriceUsd": 0.01, "passThroughUsageToUser": false, "targetGrossMarginPct": 60 } ] }; // Run the Actor and wait for it to finish const run = await client.actor("junipr/actor-pricing-simulator").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 = { "scenarios": [ { "actorSlug": "example-browser-scraper", "eventName": "item-scraped", "eventPriceUsd": 0.012, "itemsPerRun": 100, "platformUsageCostPerRunUsd": 0.65, "fixedStartEventPriceUsd": 0.025, "reportEventPriceUsd": 0.05, "passThroughUsageToUser": False, "targetGrossMarginPct": 60, }, { "actorSlug": "cheap-cleaner", "eventName": "item-processed", "eventPriceUsd": 0.00195, "itemsPerRun": 500, "platformUsageCostPerRunUsd": 0.02, "fixedStartEventPriceUsd": 0.001, "reportEventPriceUsd": 0.01, "passThroughUsageToUser": False, "targetGrossMarginPct": 60, }, ] } # Run the Actor and wait for it to finish run = client.actor("junipr/actor-pricing-simulator").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 '{ "scenarios": [ { "actorSlug": "example-browser-scraper", "eventName": "item-scraped", "eventPriceUsd": 0.012, "itemsPerRun": 100, "platformUsageCostPerRunUsd": 0.65, "fixedStartEventPriceUsd": 0.025, "reportEventPriceUsd": 0.05, "passThroughUsageToUser": false, "targetGrossMarginPct": 60 }, { "actorSlug": "cheap-cleaner", "eventName": "item-processed", "eventPriceUsd": 0.00195, "itemsPerRun": 500, "platformUsageCostPerRunUsd": 0.02, "fixedStartEventPriceUsd": 0.001, "reportEventPriceUsd": 0.01, "passThroughUsageToUser": false, "targetGrossMarginPct": 60 } ] }' | apify call junipr/actor-pricing-simulator --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=junipr/actor-pricing-simulator", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Actor Pricing Simulator", "description": "Estimate Apify actor PPE pricing, break-even points, margins, and profit risk from run-cost assumptions.", "version": "1.0", "x-build-id": "3xMDxaaPOsZ1bhIWl" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/junipr~actor-pricing-simulator/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-junipr-actor-pricing-simulator", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/junipr~actor-pricing-simulator/runs": { "post": { "operationId": "runs-sync-junipr-actor-pricing-simulator", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/junipr~actor-pricing-simulator/run-sync": { "post": { "operationId": "run-sync-junipr-actor-pricing-simulator", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "scenarios": { "title": "Pricing Scenarios", "type": "array", "description": "Actor pricing and cost scenarios to simulate.", "items": { "type": "object" }, "default": [ { "actorSlug": "example-browser-scraper", "eventName": "item-scraped", "eventPriceUsd": 0.012, "itemsPerRun": 100, "platformUsageCostPerRunUsd": 0.65, "fixedStartEventPriceUsd": 0.025, "reportEventPriceUsd": 0.05, "passThroughUsageToUser": false, "targetGrossMarginPct": 60, "notes": "Browser or proxy-heavy scraper with owner-paid platform usage." }, { "actorSlug": "cheap-cleaner", "eventName": "item-processed", "eventPriceUsd": 0.00195, "itemsPerRun": 500, "platformUsageCostPerRunUsd": 0.02, "fixedStartEventPriceUsd": 0.001, "reportEventPriceUsd": 0.01, "passThroughUsageToUser": false, "targetGrossMarginPct": 60, "notes": "Bounded utility actor with low compute cost and no proxy requirement." } ] }, "apifyFeePct": { "title": "Apify Fee Percent", "minimum": 0, "maximum": 80, "type": "number", "description": "Marketplace fee percentage deducted from event revenue before platform usage cost.", "default": 20 }, "defaultTargetGrossMarginPct": { "title": "Default Target Gross Margin Percent", "minimum": 0, "maximum": 95, "type": "number", "description": "Target gross margin used when a scenario does not provide one.", "default": 60 }, "includeSensitivity": { "title": "Include Sensitivity", "type": "boolean", "description": "Include price/cost sensitivity points for each scenario.", "default": true }, "maxItems": { "title": "Max Items", "minimum": 1, "maximum": 1000, "type": "integer", "description": "Alias for Max Targets/Maximum Records used by the Junipr actor baseline. When both are provided, actor-specific limits still apply.", "default": 100 }, "includeReport": { "title": "Include Report Artifacts", "type": "boolean", "description": "Write summary JSON and Markdown report artifacts to the key-value store.", "default": true }, "maxScenarios": { "title": "Max Scenarios", "minimum": 1, "maximum": 1000, "type": "integer", "description": "Maximum scenarios to simulate.", "default": 100 }, "maxChargeUsd": { "title": "Maximum Charge (USD)", "minimum": 0, "maximum": 1000, "type": "number", "description": "Hard local spending cap for actor-start, per-item, and report events. The actor stops before work or withholds uncharged output when the next event would exceed this amount.", "default": 10 }, "dryRun": { "title": "Dry Run", "type": "boolean", "description": "Validate input and write a dry-run summary without PPE charges or dataset output.", "default": false }, "debug": { "title": "Debug Logs", "type": "boolean", "description": "Enable debug logs.", "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 } } } } } } } } } } ```