# MusicBrainz Scraper (`solidcode/musicbrainz-org-scraper`) Actor \[💰 $0.55 / 1K] Extract music metadata from MusicBrainz. Search or look up artists, albums, recordings, labels, works, places and events by name, URL, or MusicBrainz ID. Get types, countries, dates, genres, tags, ratings, aliases and official links. - **URL**: https://apify.com/solidcode/musicbrainz-org-scraper.md - **Developed by:** [SolidCode](https://apify.com/solidcode) (community) - **Categories:** Developer tools, Other - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $0.55 / 1,000 results 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 web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows. 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 ## MusicBrainz Scraper Pull structured music metadata from MusicBrainz at scale — artists, albums, recordings, labels, works, and more, complete with stable MusicBrainz IDs, community genres and ratings, ISRC and ISWC codes, and official streaming and social links. Search by keyword or look up exact entities by link or ID, then export clean rows to JSON, CSV, or Excel. Built for music-app developers, catalog and rights teams, and researchers who need canonical music data without hand-querying an open encyclopedia one page at a time. ### Why This Scraper? - **All 11 MusicBrainz entity types in one actor** — artists/bands, albums (release groups), releases, recordings (tracks), labels, works (compositions), areas, places, events, series, and instruments. Search or look up any of them. - **Two ways in: keyword search or direct MBID/URL lookup** — run fuzzy keyword searches across millions of entities, or paste a MusicBrainz page link or MusicBrainz ID (MBID) to pull one exact record with zero ambiguity. - **Community genres and tags with vote counts** — every result can carry crowd-curated genres and folksonomy tags plus the number of community votes behind each, sorted most-voted first. - **Community star ratings with vote counts** — the 0–5 rating and how many people voted, on every entity type that supports it. - **Official links from the relationship graph** — homepage, streaming (Spotify, Apple Music, and more), social media, Discogs, and Wikidata URLs pulled straight from each entity's relationships. - **ISRC, ISWC, and barcode identifiers** — recording ISRCs, work ISWCs, and release barcodes surface on the row for rights matching and catalog reconciliation. - **Stable MBID and canonical URL on every row** — each result carries its permanent 36-character MusicBrainz Identifier and musicbrainz.org page URL, so you can join, dedupe, and re-fetch reliably across runs. - **Uncapped pagination** — reaches far past MusicBrainz's 100-per-page ceiling, up to 50,000 matching entities per search term. - **Batch many terms and links in one run** — pass a list of search terms and a list of entity links together; each term produces its own result set. ### Use Cases **Music Data & Catalog Enrichment** - Match an internal track catalog to canonical MBIDs, ISRCs, and first-release dates - Fill gaps with artist countries, formation dates, sort names, and aliases - Deduplicate artist and release records against MusicBrainz's permanent IDs - Attach community genres and tags to catalog entries for richer browse and search **Media & Streaming Apps** - Power artist, album, and track pages with clean, structured metadata - Pull homepage, streaming, and social URLs to link out from your app - Show track lengths, release dates, and credited-artist strings on player screens - Surface alternate names and spellings so search matches more of your users **Rights, Licensing & Label Operations** - Resolve ISRCs and ISWCs for rights matching and royalty workflows - Look up label rosters and release barcodes for catalog audits - Cross-reference Discogs and Wikidata IDs pulled from relationship links - Reconcile release editions (specific pressings) against canonical MBIDs **Research & Musicology** - Build datasets of artists, works, and recordings for academic study - Trace an artist's aliases and name variants across languages - Map places (studios, venues) and events (concerts, festivals) for music-history projects - Analyze genre and tag distributions across thousands of releases **Data Journalism & Analytics** - Rank artists or labels by community rating and vote count - Chart releases by year, country, or genre - Fact-check discographic details against a community-maintained source - Build "most-tagged genre" or "highest-rated album" leaderboards ### Getting Started #### Simple Artist Search The simplest possible run — one band, 25 results: ```json { "searchQueries": ["Radiohead"], "entityType": "artist", "maxResults": 25 } ```` #### Album Search with Genres and Ratings Search for albums (release groups) and enrich each with community genres, tags, and star ratings: ```json { "searchQueries": ["Abbey Road", "OK Computer"], "entityType": "release-group", "includeTags": true, "includeRatings": true, "maxResults": 50 } ``` #### Direct Lookup by Link or ID (All Enrichment On) Fetch exact entities by MusicBrainz URL or bare MBID, with genres, ratings, and links all turned on: ```json { "entityUrls": [ "https://musicbrainz.org/artist/a74b1b7f-71a5-4011-9441-d0b5e4122711", "5b11f4ce-a62d-471e-81fc-a69a8278c7da" ], "entityType": "artist", "includeTags": true, "includeRatings": true, "includeRelationships": true } ``` ### Input Reference #### What to Fetch At least one of `searchQueries` or `entityUrls` is needed — you can use both in the same run. | Parameter | Type | Default | Description | |-----------|------|---------|-------------| | `searchQueries` | string\[] | `["Radiohead"]` | Search terms to find music entities, e.g. "Radiohead", "Abbey Road", or "Blue Note". Each term produces its own set of results. | | `entityType` | select | `Artist / Band` | What kind of entity your search terms should match: Artist / Band, Album (Release Group), Release (Specific Edition), Recording (Track), Label, Work (Composition), Area, Place, Event, Series, or Instrument. | | `entityUrls` | string\[] | `[]` | MusicBrainz page links (e.g. `https://musicbrainz.org/artist/a74b1b7f-...`) or bare MusicBrainz IDs to fetch those exact entities. A bare ID is treated as the entity type selected above. | #### Results | Parameter | Type | Default | Description | |-----------|------|---------|-------------| | `maxResults` | integer | `100` | Maximum results per search term. Set to `0` for all available results, up to a safety limit of 50,000 per term. | #### Extra Details Each toggle fetches a bit more per result, which adds runtime. All off with a keyword search returns search fields only. | Parameter | Type | Default | Description | |-----------|------|---------|-------------| | `includeTags` | boolean | `true` | Add community-curated genres and tags with their vote counts to each result. | | `includeRatings` | boolean | `false` | Add the community star rating (0–5) and number of votes to each result. | | `includeRelationships` | boolean | `false` | Add related links — official website, streaming, social media, Discogs, Wikidata — and connections to other entities such as band members or labels. | ### Output Each result is one flat row. Empty fields are omitted, so the fields present depend on the entity type and which enrichment toggles are on. Here is a representative artist result with all enrichment enabled: ```json { "entityType": "artist", "mbid": "a74b1b7f-71a5-4011-9441-d0b5e4122711", "name": "Radiohead", "sortName": "Radiohead", "disambiguation": "English rock band", "type": "Group", "score": 100, "country": "GB", "area": "United Kingdom", "beginDate": "1991", "aliases": ["On a Friday"], "tags": [ { "name": "rock", "count": 12 }, { "name": "alternative rock", "count": 9 } ], "genres": [ { "name": "art rock", "count": 7 } ], "rating": 4.5, "ratingVotes": 128, "relationships": [ { "type": "official homepage", "url": "https://www.radiohead.com/", "target": "url" }, { "type": "streaming", "url": "https://open.spotify.com/artist/4Z8W4fKeB5YxbusRsdQVPb", "target": "url" } ], "musicBrainzUrl": "https://musicbrainz.org/artist/a74b1b7f-71a5-4011-9441-d0b5e4122711", "searchQuery": "Radiohead", "scrapedAt": "2026-07-24T14:30:00Z" } ``` #### Core Fields | Field | Type | Description | |-------|------|-------------| | `entityType` | string | Which of the 11 entity types this row is (`artist`, `release-group`, `recording`, ...) | | `mbid` | string | Permanent MusicBrainz Identifier (36-character UUID) for this entity | | `name` | string | Display name or title of the entity | | `sortName` | string | Sortable form of the name (e.g. "Beatles, The") | | `disambiguation` | string | Short note distinguishing same-named entities | | `type` | string | Entity sub-type (e.g. Group / Person for artists, Album / Single for albums) | | `score` | number | Search relevance score, 0–100 (search results only) | | `musicBrainzUrl` | string | Canonical musicbrainz.org page URL | | `searchQuery` | string | The search term that produced this row (search results only) | | `scrapedAt` | string | ISO timestamp of extraction | #### Details, Dates & Identifiers | Field | Type | Description | |-------|------|-------------| | `country` | string | ISO country code | | `area` | string | Associated area name — country, region, or city | | `beginDate` | string | Start date — formation, birth, or founding | | `endDate` | string | End date — dissolution or death, when applicable | | `firstReleaseDate` | string | First release date (albums / release groups) | | `date` | string | Release or event date | | `artistCredit` | string | Credited-artist string with join phrases preserved | | `length` | number | Track length in milliseconds (recordings) | | `lengthFormatted` | string | Track length as `m:ss` | | `barcode` | string | Release barcode (UPC / EAN) | | `trackCount` | number | Number of tracks on a release | | `isrcs` | string\[] | Recording ISRC codes | | `iswcs` | string\[] | Work ISWC codes | | `aliases` | string\[] | Alternate names and spellings | #### Genres & Tags Populated when **Include Genres & Tags** is on. | Field | Type | Description | |-------|------|-------------| | `tags` | object\[] | Community tags as `{name, count}`, sorted by vote count | | `genres` | object\[] | Community genres as `{name, count}`, sorted by vote count | #### Ratings Populated when **Include Ratings** is on. | Field | Type | Description | |-------|------|-------------| | `rating` | number | Community star rating, 0–5 | | `ratingVotes` | number | Number of community votes behind the rating | #### Links & Relationships Populated when **Include Links & Relationships** is on. | Field | Type | Description | |-------|------|-------------| | `relationships` | object\[] | Related URLs as `{type, url, target}` — homepage, streaming, social, Discogs, Wikidata | ### Tips for Best Results - **Pick the right entity type.** Your search terms only match the type you select — choose "Album (Release Group)" for records, "Recording (Track)" for individual tracks, and "Label" for imprints. A wrong type quietly returns the wrong kind of match. - **Use direct link/ID lookup for exact entities.** When you already know the entity, paste its MusicBrainz link or MBID into Entity Links or IDs. It fetches that exact record instead of a fuzzy keyword guess — ideal for enriching a known list of MBIDs. - **Keep enrichment focused.** Each of Genres & Tags, Ratings, and Links adds one extra lookup per result, so a large run with all three on does far more work than a plain search. Narrow your result count when you turn them on. Recording ISRCs specifically only populate when at least one enrichment toggle is on. - **Sharpen searches with field syntax.** MusicBrainz search accepts Lucene-style terms like `artist:Radiohead AND country:GB`, or wrap a phrase in quotes (`"Abbey Road"`) for exact matches — far more precise than a bare keyword. - **Sort your dataset by `score`.** Every search row carries a 0–100 relevance score; sort by it to float the best matches to the top before you filter. - **Set Max Results to 0 for everything.** A single term can pull up to 50,000 matching entities — so use a specific query to get the right 50,000, not the broadest possible net. - **Series and Instruments carry no ratings.** Those two entity types don't support community ratings; every other type does, so don't expect a `rating` field on them. ### Pricing **From $0.55 per 1,000 results** — flat pay-per-result pricing for canonical music metadata, with genres, ratings, and links bundled at no extra charge. Bronze, Silver, and Gold subscribers pay progressively less; the table below shows total cost at each discount tier. | Results | No discount | Bronze | Silver | Gold | |---------|-------------|--------|--------|------| | 100 | $0.066 | $0.062 | $0.058 | $0.055 | | 1,000 | $0.66 | $0.62 | $0.58 | $0.55 | | 10,000 | $6.60 | $6.20 | $5.80 | $5.50 | | 100,000 | $66.00 | $62.00 | $58.00 | $55.00 | A "result" is any entity row in the output dataset — one per search hit or per looked-up entity. **No compute or time-based charges — you pay per result, plus a small fixed per-run start fee.** ### Integrations Export data in JSON, CSV, Excel, XML, or RSS. Connect to 1,500+ apps via: - **Zapier** / **Make** / **n8n** — Workflow automation - **Google Sheets** — Direct spreadsheet export - **Slack** / **Email** — Notifications on new results - **Webhooks** — Trigger custom APIs on run completion - **Apify API** — Full programmatic access ### Legal & Ethical Use This actor reads publicly available metadata from MusicBrainz, whose core data is released into the public domain (CC0) while some supplementary content carries a Creative Commons license. Please respect MusicBrainz's terms of use and attribution guidelines when redistributing data, and use the actor at a courteous request rate. You are responsible for complying with applicable laws and for using extracted data ethically — not for spam, harassment, or any illegal purpose. # Actor input Schema ## `searchQueries` (type: `array`): Search terms to find music entities, e.g. 'Radiohead', 'Abbey Road', or 'Blue Note'. Each term produces its own set of results. Leave empty if you only want to look up specific entities below. ## `entityType` (type: `string`): What kind of music entity your search terms should match. ## `entityUrls` (type: `array`): Paste MusicBrainz page links (e.g. 'https://musicbrainz.org/artist/a74b1b7f-71a5-4011-9441-d0b5e4122711') or MusicBrainz IDs to fetch those exact entities. Bare IDs are treated as the entity type selected above. ## `maxResults` (type: `integer`): Maximum number of results to return for each search term. Set to 0 for all available results (up to a safety limit of 50,000 per term). ## `includeTags` (type: `boolean`): Add community-curated genres and tags with their vote counts to each result. ## `includeRatings` (type: `boolean`): Add the community star rating (0–5) and number of votes to each result. ## `includeRelationships` (type: `boolean`): Add related links (official website, streaming, social media, Discogs, Wikidata) and connections to other entities such as band members or labels. ## Actor input object example ```json { "searchQueries": [ "Radiohead" ], "entityType": "artist", "entityUrls": [], "maxResults": 100, "includeTags": true } ``` # Actor output Schema ## `overview` (type: `string`): Table of extracted MusicBrainz entities with key fields. # 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 = { "searchQueries": [ "Radiohead" ], "entityType": "artist", "entityUrls": [], "maxResults": 100, "includeTags": true, "includeRatings": false, "includeRelationships": false }; // Run the Actor and wait for it to finish const run = await client.actor("solidcode/musicbrainz-org-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 = { "searchQueries": ["Radiohead"], "entityType": "artist", "entityUrls": [], "maxResults": 100, "includeTags": True, "includeRatings": False, "includeRelationships": False, } # Run the Actor and wait for it to finish run = client.actor("solidcode/musicbrainz-org-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 '{ "searchQueries": [ "Radiohead" ], "entityType": "artist", "entityUrls": [], "maxResults": 100, "includeTags": true, "includeRatings": false, "includeRelationships": false }' | apify call solidcode/musicbrainz-org-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=solidcode/musicbrainz-org-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "MusicBrainz Scraper", "description": "[💰 $0.55 / 1K] Extract music metadata from MusicBrainz. Search or look up artists, albums, recordings, labels, works, places and events by name, URL, or MusicBrainz ID. Get types, countries, dates, genres, tags, ratings, aliases and official links.", "version": "1.0", "x-build-id": "uwbswow11w6gZVj4H" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/solidcode~musicbrainz-org-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-solidcode-musicbrainz-org-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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/solidcode~musicbrainz-org-scraper/runs": { "post": { "operationId": "runs-sync-solidcode-musicbrainz-org-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/solidcode~musicbrainz-org-scraper/run-sync": { "post": { "operationId": "run-sync-solidcode-musicbrainz-org-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": { "searchQueries": { "title": "Search Queries", "type": "array", "description": "Search terms to find music entities, e.g. 'Radiohead', 'Abbey Road', or 'Blue Note'. Each term produces its own set of results. Leave empty if you only want to look up specific entities below.", "items": { "type": "string" } }, "entityType": { "title": "Entity Type", "enum": [ "artist", "release-group", "release", "recording", "label", "work", "area", "place", "event", "series", "instrument" ], "type": "string", "description": "What kind of music entity your search terms should match." }, "entityUrls": { "title": "Entity Links or IDs", "type": "array", "description": "Paste MusicBrainz page links (e.g. 'https://musicbrainz.org/artist/a74b1b7f-71a5-4011-9441-d0b5e4122711') or MusicBrainz IDs to fetch those exact entities. Bare IDs are treated as the entity type selected above.", "items": { "type": "string" } }, "maxResults": { "title": "Max Results per Query", "minimum": 0, "type": "integer", "description": "Maximum number of results to return for each search term. Set to 0 for all available results (up to a safety limit of 50,000 per term)." }, "includeTags": { "title": "Include Genres & Tags", "type": "boolean", "description": "Add community-curated genres and tags with their vote counts to each result." }, "includeRatings": { "title": "Include Ratings", "type": "boolean", "description": "Add the community star rating (0–5) and number of votes to each result." }, "includeRelationships": { "title": "Include Links & Relationships", "type": "boolean", "description": "Add related links (official website, streaming, social media, Discogs, Wikidata) and connections to other entities such as band members or labels." } } }, "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 } } } } } } } } } } ```