# Resy Availability & Scarcity Monitor (`zhorex/resy-availability-monitor`) Actor Forward-dated restaurant reservation availability from Resy: slot counts, prime-time counts, first and last seating, seating types, sold-out flags. Delta mode returns only what moved. Read-only: books nothing, no account, no personal data. - **URL**: https://apify.com/zhorex/resy-availability-monitor.md - **Developed by:** [Sami](https://apify.com/zhorex) (community) - **Categories:** Travel, E-commerce - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $5.00 / 1,000 venue-date availability rows 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 ## Resy Availability & Scarcity Monitor — Restaurant Reservation Data by Date (2026) Turn restaurant reservation availability into a dataset. For every venue, date and party size you ask for, you get the **number of bookable slots, how many of them fall in the prime dinner window, the first and last seating, the seating types on offer, and whether it is sold out**. Turn on delta mode and a daily schedule returns only what *moved* — sold out, reopened, prime window emptied. No login. No API key to obtain. No browser. Clean JSON / CSV / Excel, billed per row you actually receive. > **Read-only by design.** This Actor books nothing, creates no account, holds no table, resells no reservation and collects no personal data. It reads the same public availability any diner sees on the site. ### How to build a comp set in 3 steps 1. **Scan a metro once.** Mode `metro_scan` with `metros: ["new-york"]` returns venues with their `venueId` and `urlSlug`. 2. **Watch your comp set.** Mode `venue_watch` with those ids, your date window and the party sizes you care about. Each venue-date is one small request (~34 KB, ~0.2 s). 3. **Schedule it with `deltaMode: true`** and you have a scarcity feed instead of a nightly re-read. ### What makes a row useful Every other actor on this surface returns a venue list. This one returns **the availability shape of a night**, which is what a revenue manager or an analyst actually reads: | Field | Why it matters | |---|---| | `totalSlots` | How much inventory is genuinely bookable for that date and party size | | `primeSlots` + `primeWindow` | Slots between **18:30 and 20:59**. A 16:00 seating and a 19:30 seating are not the same product, and averaging them hides the signal | | `fullyBooked` / `primeFullyBooked` | Sold out overall, or prime-time gone while off-peak tables remain — the earliest sign of real demand | | `earliestSeating` / `latestSeating` | Service window, and how it stretches or contracts by season | | `seatingTypes` | Dining Room / Bar / High Top / Lounge — which inventory the venue is actually releasing | | `maxTableQuantity` | Largest table on offer, i.e. group capacity | | `rating`, `totalRatings`, `cuisine`, `priceRange`, `neighborhood` | Segment any of the above by quality, cuisine, price band or district | ### Example row ```json { "venueId": 87134, "venueName": "Mudville", "urlSlug": "mudville", "cuisine": "American", "priceRange": 2, "neighborhood": "Tribeca", "city": "New York", "date": "2026-08-04", "partySize": 2, "totalSlots": 144, "primeSlots": 30, "primeWindow": "18:30-20:59", "earliestSeating": "11:30", "latestSeating": "23:15", "seatingTypes": ["Dining Room", "High Top", "Lounge"], "maxTableQuantity": 45, "fullyBooked": false, "primeFullyBooked": false, "rating": 4.6158, "totalRatings": 2841, "scrapedAt": "2026-07-25T20:10:00Z" } ```` ### Delta mode — a cron that bills for movement With `deltaMode: true`, the first run sets a baseline and later runs return only cells that changed: | `changeType` | Meaning | |---|---| | `new` | Venue-date cell seen for the first time | | `sold_out` | Had slots, now has none | | `reopened` | Was full, now has slots — a cancellation wave | | `prime_sold_out` | Prime window emptied while off-peak tables remain | | `availability_up` / `availability_down` | Slot count moved beyond the noise floor (2 slots), with `slotChange` and `primeSlotChange` | | `disappeared` | Cell was tracked and the venue is absent from a scope this run swept | Each change carries `previousTotalSlots` and `previousPrimeSlots`, so the row explains itself without a join. Unchanged cells are **not returned and not charged**. **And this is the part that cannot be bought later:** nobody can retro-fetch how full a restaurant was last Tuesday — not this Actor, not a competitor who starts next month. A scarcity history exists only from the day your schedule starts. ```json { "mode": "venue_watch", "venueIds": ["6194", "87134"], "startDaysAhead": 1, "horizonDays": 30, "partySizes": ["2", "4"], "deltaMode": true, "deltaStateKey": "nyc-compset" } ``` ### Who this is for | Buyer | Use | |---|---| | **Restaurant groups and revenue managers** | Watch the comp set's forward calendar; see the night your rival's prime window empties, and whether yours follows | | **Hospitality consultancies** | Demand curves by neighbourhood, cuisine and price band, built from bookable inventory rather than surveys | | **Consumer and real-estate analysts** | Dining scarcity as a neighbourhood-level demand proxy — restaurant availability leads foot traffic | | **Event, travel and concierge operations** | Which venues still have prime tables across a date range, at a glance | | **Data teams building city panels** | A normalised venue-date-party grid ready to join with weather, events or transaction data | ### Sizing your run (and your bill) Rows = **venues × dates × party sizes**, one request each. | Setup | Requests | Rows | At $0.005/row | |---|---|---|---| | Comp set: 20 venues × 14 dates × 1 party size | 280 | 280 | $1.40 | | Comp set: 40 venues × 30 dates × 2 party sizes | 2,400 | 2,400 | $12 | | Metro discovery: 1 metro × 3 dates, 200 venues deep | ~6 | ~600 | $3 | | Daily cron **with delta** on 40 venues × 30 dates | 1,200/day | only what moved | typically a small fraction | A single run is capped at 3,000 requests so a typo cannot launch a runaway sweep. `dateStepDays: 7` keeps the weekday fixed, which is both cheaper and more readable as a trend. ### Pricing | Event | Price | What it is | |---|---|---| | `venue-date-row` | **$0.005** | One venue priced for one date and party size, full field set | | `availability-change` | **$0.015** | One cell that moved in delta mode, with its previous counts | Cells that fail to fetch are pushed as error records with the reason — **and are never charged**. ### Limitations, stated plainly - **Resy is US-centric.** New York, Miami, Chicago, San Francisco, Boston and Washington DC carry real depth. London and Toronto returned almost nothing when tested, and non-US coordinates generally return an empty venue list. If you need European dining data, this is not the right tool. - **Availability is not the same as demand.** A venue with no slots may be sold out, may have closed for a private event, or may simply not have released inventory yet. `totalSlots` is what is bookable, and that is what the row claims — nothing more. - **No history before your first run.** Reservation availability cannot be backfilled by anyone. - **This reads an internal client API**, not a documented product. It is stable in practice and the Actor re-reads the client key at runtime so a rotation self-heals, but an undocumented endpoint can change without notice. If it does, open an issue and it gets fixed. - **Prime window is fixed at 18:30-20:59 local.** If your market's prime hours differ, use `earliestSeating` / `latestSeating` and the raw counts. ### FAQ **Do I need a proxy?** No. Verified with 12 rapid consecutive requests from a plain datacenter IP: 12 successes, no throttling, no challenge. **Does this book tables or hold reservations?** No. It performs read-only availability lookups. It cannot book, cancel, hold or transfer a reservation, and it never signs in. **Why is my first delta run large?** It is the baseline. From the second run on you only get movement. **How do I find venue ids?** Run `metro_scan` once — every row carries `venueId` and `urlSlug`. **Can I track large-party availability?** Yes, that is what `partySizes` is for. A table for 6 is far scarcer than a table for 2, and each size is its own row. ### Other scrapers by Zhorex - [Hostelworld Rate & Availability Monitor](https://apify.com/zhorex/hostelworld-rate-monitor) — the same delta-monitor pattern for accommodation rates by date - [Booking.com Reviews Scraper](https://apify.com/zhorex/booking-reviews-scraper) — guest reviews with delta mode for new-review monitoring ### Legal This Actor reads publicly visible commercial availability: venue names, bookable time slots, seating types, ratings and neighbourhoods. It collects no personal data, creates no accounts, makes no bookings and does not facilitate reservation resale. Respect the platform's terms and applicable law in your jurisdiction, and use the data for analysis rather than redistribution. # Actor input Schema ## `mode` (type: `string`): 'Watch venues' is the comp-set product: give it venue ids and it prices each one across your date window — one small, fast request per venue-date. 'Scan metro' sweeps a whole city by coordinates to discover venues and their ids, then you feed the ones you care about into watch mode. ## `metros` (type: `array`): City slugs to sweep. Available: new-york, los-angeles, chicago, san-francisco, miami, boston, washington-dc, austin, seattle, denver, atlanta, philadelphia, dallas, houston, las-vegas, new-orleans, nashville, san-diego, toronto, london. Resy's depth is US-centric — New York, Miami, Chicago, San Francisco, Boston and Washington DC carry hundreds of venues; London and Toronto are thin. ## `venueIds` (type: `array`): Resy venue ids for your comp set. Run 'Scan metro' once and take the venueId column — every row carries it, along with the venue's url slug. Each venue-date is a single ~34 KB request, so a 40-venue comp set across 30 dates is 1,200 fast requests. ## `startDaysAhead` (type: `integer`): Where the window starts. 1 = tomorrow. Tonight's availability behaves differently from forward dates, so comp-set work usually starts at 1. ## `horizonDays` (type: `integer`): How many dates to price from the first one. 14 gives a fortnight; 30 a month. Rows = venues x dates x party sizes, one request each. ## `dateStepDays` (type: `integer`): 1 = every date. 7 = the same weekday each week, which is the cheap way to watch a long season — Saturday scarcity is a different signal from Tuesday scarcity, so keeping the weekday fixed makes the trend readable. ## `partySizes` (type: `array`): Availability is quoted per party size, and a table for 2 is a completely different scarcity picture from a table for 6. Add every size your analysis needs — each one multiplies rows. ## `metroPageSize` (type: `integer`): Page size for a metro sweep. Keep it at 100 or below: the response carries roughly 80 KB per venue, so an uncapped New York request is around 180 MB — almost all of it images the Actor discards. ## `metroMaxVenues` (type: `integer`): How deep to paginate a metro. New York has thousands of venues; 200 gets you the well-known ones, 1,000+ approaches full coverage at proportional cost. ## `deltaMode` (type: `boolean`): Turn this on for a scheduled monitor. The first run records a baseline; every later run returns and bills ONLY cells that changed — sold out, reopened after being full, prime window emptied, or slot count shifted beyond the noise floor — with the previous counts attached. Unchanged cells are never charged. This is also the only way to build a scarcity history: nobody, including this Actor, can retro-fetch how full a restaurant was last Tuesday. ## `deltaStateKey` (type: `string`): Names an independent delta stream so several monitors don't collide (e.g. 'nyc-compset' vs 'miami-season'). Only used when Delta mode is on. ## `latitude` (type: `string`): Sweep a point that isn't in the metro list. Pair with longitude. Resy's radius covers a real metro — a New York sweep reaches ~19 miles out. ## `longitude` (type: `string`): Sweep a point that isn't in the metro list. Pair with latitude. ## `proxyConfiguration` (type: `object`): Not needed: this data is served to ordinary datacenter IPs and 12 rapid consecutive requests returned 12 successes with no throttling. Leave it off unless you specifically want your traffic routed — turning it on costs proxy usage without improving results. ## Actor input object example ```json { "mode": "metro_scan", "metros": [ "new-york", "miami" ], "venueIds": [ "6194", "87134" ], "startDaysAhead": 1, "horizonDays": 14, "dateStepDays": 1, "partySizes": [ "2", "4", "6" ], "metroPageSize": 100, "metroMaxVenues": 200, "deltaMode": false, "deltaStateKey": "default", "proxyConfiguration": { "useApifyProxy": 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 = { "mode": "metro_scan", "metros": [ "new-york" ], "startDaysAhead": 1, "horizonDays": 14, "dateStepDays": 1, "partySizes": [ "2" ], "metroPageSize": 100, "metroMaxVenues": 200, "deltaStateKey": "default" }; // Run the Actor and wait for it to finish const run = await client.actor("zhorex/resy-availability-monitor").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 = { "mode": "metro_scan", "metros": ["new-york"], "startDaysAhead": 1, "horizonDays": 14, "dateStepDays": 1, "partySizes": ["2"], "metroPageSize": 100, "metroMaxVenues": 200, "deltaStateKey": "default", } # Run the Actor and wait for it to finish run = client.actor("zhorex/resy-availability-monitor").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 '{ "mode": "metro_scan", "metros": [ "new-york" ], "startDaysAhead": 1, "horizonDays": 14, "dateStepDays": 1, "partySizes": [ "2" ], "metroPageSize": 100, "metroMaxVenues": 200, "deltaStateKey": "default" }' | apify call zhorex/resy-availability-monitor --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=zhorex/resy-availability-monitor", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Resy Availability & Scarcity Monitor", "description": "Forward-dated restaurant reservation availability from Resy: slot counts, prime-time counts, first and last seating, seating types, sold-out flags. Delta mode returns only what moved. Read-only: books nothing, no account, no personal data.", "version": "0.1", "x-build-id": "g1duWPt5babZ3Xk1u" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/zhorex~resy-availability-monitor/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-zhorex-resy-availability-monitor", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/zhorex~resy-availability-monitor/runs": { "post": { "operationId": "runs-sync-zhorex-resy-availability-monitor", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/zhorex~resy-availability-monitor/run-sync": { "post": { "operationId": "run-sync-zhorex-resy-availability-monitor", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "mode" ], "properties": { "mode": { "title": "Mode", "enum": [ "venue_watch", "metro_scan" ], "type": "string", "description": "'Watch venues' is the comp-set product: give it venue ids and it prices each one across your date window — one small, fast request per venue-date. 'Scan metro' sweeps a whole city by coordinates to discover venues and their ids, then you feed the ones you care about into watch mode.", "default": "metro_scan" }, "metros": { "title": "Metros (scan mode)", "type": "array", "description": "City slugs to sweep. Available: new-york, los-angeles, chicago, san-francisco, miami, boston, washington-dc, austin, seattle, denver, atlanta, philadelphia, dallas, houston, las-vegas, new-orleans, nashville, san-diego, toronto, london. Resy's depth is US-centric — New York, Miami, Chicago, San Francisco, Boston and Washington DC carry hundreds of venues; London and Toronto are thin.", "items": { "type": "string" } }, "venueIds": { "title": "Venue IDs (watch mode)", "type": "array", "description": "Resy venue ids for your comp set. Run 'Scan metro' once and take the venueId column — every row carries it, along with the venue's url slug. Each venue-date is a single ~34 KB request, so a 40-venue comp set across 30 dates is 1,200 fast requests.", "items": { "type": "string" } }, "startDaysAhead": { "title": "First date (days from today)", "minimum": 0, "maximum": 365, "type": "integer", "description": "Where the window starts. 1 = tomorrow. Tonight's availability behaves differently from forward dates, so comp-set work usually starts at 1.", "default": 1 }, "horizonDays": { "title": "Horizon (number of dates)", "minimum": 1, "maximum": 365, "type": "integer", "description": "How many dates to price from the first one. 14 gives a fortnight; 30 a month. Rows = venues x dates x party sizes, one request each.", "default": 14 }, "dateStepDays": { "title": "Date step", "minimum": 1, "maximum": 30, "type": "integer", "description": "1 = every date. 7 = the same weekday each week, which is the cheap way to watch a long season — Saturday scarcity is a different signal from Tuesday scarcity, so keeping the weekday fixed makes the trend readable.", "default": 1 }, "partySizes": { "title": "Party sizes", "type": "array", "description": "Availability is quoted per party size, and a table for 2 is a completely different scarcity picture from a table for 6. Add every size your analysis needs — each one multiplies rows.", "items": { "type": "string" }, "default": [ "2" ] }, "metroPageSize": { "title": "Venues per request (scan mode)", "minimum": 1, "maximum": 400, "type": "integer", "description": "Page size for a metro sweep. Keep it at 100 or below: the response carries roughly 80 KB per venue, so an uncapped New York request is around 180 MB — almost all of it images the Actor discards.", "default": 100 }, "metroMaxVenues": { "title": "Max venues per metro-date (scan mode)", "minimum": 1, "maximum": 4000, "type": "integer", "description": "How deep to paginate a metro. New York has thousands of venues; 200 gets you the well-known ones, 1,000+ approaches full coverage at proportional cost.", "default": 200 }, "deltaMode": { "title": "Delta mode — only availability that MOVED", "type": "boolean", "description": "Turn this on for a scheduled monitor. The first run records a baseline; every later run returns and bills ONLY cells that changed — sold out, reopened after being full, prime window emptied, or slot count shifted beyond the noise floor — with the previous counts attached. Unchanged cells are never charged. This is also the only way to build a scarcity history: nobody, including this Actor, can retro-fetch how full a restaurant was last Tuesday.", "default": false }, "deltaStateKey": { "title": "Delta stream name", "type": "string", "description": "Names an independent delta stream so several monitors don't collide (e.g. 'nyc-compset' vs 'miami-season'). Only used when Delta mode is on.", "default": "default" }, "latitude": { "title": "Custom latitude (optional)", "type": "string", "description": "Sweep a point that isn't in the metro list. Pair with longitude. Resy's radius covers a real metro — a New York sweep reaches ~19 miles out." }, "longitude": { "title": "Custom longitude (optional)", "type": "string", "description": "Sweep a point that isn't in the metro list. Pair with latitude." }, "proxyConfiguration": { "title": "Proxy (optional — not required)", "type": "object", "description": "Not needed: this data is served to ordinary datacenter IPs and 12 rapid consecutive requests returned 12 successes with no throttling. Leave it off unless you specifically want your traffic routed — turning it on costs proxy usage without improving results.", "default": { "useApifyProxy": 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 } } } } } } } } } } ```