# Stock Analyst Ratings - Upgrades, Downgrades, Targets (`michael_b/stock-analyst-ratings`) Actor Daily analyst rating changes across US, UK, and Canadian markets: upgrades, downgrades, price targets, initiations, reiterations. Also per-ticker history with consensus snapshot and per-brokerage feeds with 12-month ROI. Built for AI agents, MCP pipelines, and portfolio monitoring. - **URL**: https://apify.com/michael\_b/stock-analyst-ratings.md - **Developed by:** [Michal Búci](https://apify.com/michael_b) (community) - **Categories:** AI, MCP servers, Automation - **Stats:** 1 total users, 1 monthly users, 0.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $0.40 / 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. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## Stock Analyst Ratings Scraper - Upgrades, Downgrades & Price Targets Get daily **analyst rating changes** for the US, UK, and Canadian markets in a single call. Upgrades, downgrades, initiations, reiterations, and price target moves — all in one structured dataset. Also supports per-ticker rating history with a consensus snapshot and per-brokerage feeds with 12-month ROI. Built for AI agents, MCP pipelines, and portfolio monitoring. ### **What does this actor do?** This actor extracts analyst rating activity from [MarketBeat](https://www.marketbeat.com) and returns it as clean JSON. Three modes, one unified schema: | Mode | How to trigger | Typical output | |---|---|---| | **Daily market feed** | Default (no tickers/brokerages) | ~400 rows/day across US+UK+Canada | | **Ticker history** | Set `tickers` | Last ~15 dated ratings per ticker + consensus snapshot | | **Brokerage feed** | Set `brokerages` | ~100 dated ratings per firm with 12-month ROI | Unlike per-ticker lookup tools, the daily feed gives you a **market-wide view of every analyst action** — no need to query ticker by ticker. ### **Why scrape analyst ratings from MarketBeat?** Analyst upgrades and downgrades move markets. Getting them structured and timely is hard: most sources only offer per-ticker views, paywalled APIs, or stale RSS. MarketBeat aggregates actions from 150+ research firms covering US, UK, and Canadian stocks and exposes them in plain HTML. This actor turns that into structured JSON, ready for LLMs, trading systems, dashboards, or alerting pipelines. ### **How to scrape analyst ratings** 1. Open the [Stock Analyst Ratings Scraper](https://apify.com/michael_b/stock-analyst-ratings) actor page 2. Pick a mode: leave everything blank for the daily feed, add `tickers` for per-ticker history, or add `brokerages` for per-firm feeds 3. Click **Start** 4. Download results as JSON, CSV, or Excel, or read them via the Apify API or MCP ### **Input** | Parameter | Type | Default | Description | |---|---|---|---| | `tickers` | string | — | Comma-separated ticker symbols (e.g. `AAPL, TSLA, NVDA`). Accepts `EXCHANGE:TICKER` to skip exchange lookup (`NASDAQ:AAPL`). Switches to ticker history mode. | | `brokerages` | string | — | Comma-separated brokerage names. Fuzzy-matched against ~150 tracked firms (`JPMorgan`, `Goldman Sachs`, `Citi`). Switches to brokerage mode. | | `market` | string | `all` | Filter the daily feed: `all`, `us` (NYSE/NASDAQ/AMEX), `uk` (LON), `ca` (TSE). Ignored when tickers/brokerages are set. | | `actions` | array | `[]` | Keep only these normalized actions: `upgrade`, `downgrade`, `initiate`, `reiterate`, `target_raised`, `target_lowered`, `target_set`. Empty = keep all. | | `daysBack` | integer | `0` | Keep only ratings within the last N days (ticker/brokerage modes only, daily feed is always today). `0` = no filter. | | `includeConsensus` | boolean | `true` | In ticker mode, attach consensus snapshot (rating, target, breakdown, 1m/3m/1y history) to each row. No extra requests. | | `maxItems` | integer | `0` | Hard cap on rows. `0` = unlimited. | #### Example inputs Daily feed, US-only upgrades and downgrades: ```json { "market": "us", "actions": ["upgrade", "downgrade"] } ```` Ticker history for a portfolio, with consensus: ```json { "tickers": "AAPL, TSLA, NVDA, MSFT", "includeConsensus": true } ``` Recent JPMorgan and Goldman calls: ```json { "brokerages": "JPMorgan, Goldman Sachs", "daysBack": 30 } ``` ### **Output** Every row, regardless of mode, uses this schema. Null fields are omitted from each row (only populated fields are included). ```json { "ticker": "ABNB", "exchange": "NASDAQ", "company": "Airbnb", "action": "upgrade", "brokerage": "Wells Fargo & Company", "analyst": "Ken Gawrelski", "priorRating": "Equal Weight", "newRating": "Overweight", "priorTarget": 136.0, "newTarget": 178.0, "targetCurrency": "USD", "currentPrice": 144.18, "stockPriceChangePct": 1.1, "upsideToTargetPct": 23.45, "ratingId": 2386270, "sourceUrl": "https://www.marketbeat.com/ratings/" } ``` | Field | Type | Description | |---|---|---| | `ticker` | string | Ticker symbol | | `exchange` | string | NYSE, NASDAQ, NYSEAMERICAN, LON, or TSE | | `company` | string | Company name | | `action` | string | Normalized enum: `upgrade`, `downgrade`, `initiate`, `reiterate`, `target_raised`, `target_lowered`, `target_set` | | `brokerage` | string | Research firm / investment bank | | `analyst` | string/null | Individual analyst. `null` when gated behind MarketBeat's paywall. | | `priorRating` | string/null | Rating before this action | | `newRating` | string/null | Rating after this action | | `priorTarget` | number/null | Previous price target in quote currency | | `newTarget` | number/null | New price target in quote currency | | `targetCurrency` | string/null | `USD`, `GBX` (British pence), `CAD`, etc. | | `currentPrice` | number | Stock price at scrape time (daily + brokerage modes) | | `stockPriceChangePct` | number | Intraday percent change of the underlying stock price | | `upsideToTargetPct` | number | Percent upside from current stock price to the new price target | | `ratingDate` | string | ISO `YYYY-MM-DD` date the rating was issued (ticker + brokerage modes only) | | `recommendationRoi12mo` | number | 12-month ROI on this specific recommendation (brokerage mode only) | | `ratingId` | integer | MarketBeat's stable internal ID for this rating. Use as dedup key. | | `sourceUrl` | string | Canonical MarketBeat URL the row was scraped from | | `consensus` | object | Consensus snapshot with 1m/3m/1y history (ticker mode with `includeConsensus`) | #### Consensus object (ticker mode) ```json { "rating": "Moderate Buy", "priceTarget": 303.06, "upsideToTargetPct": 10.94, "breakdown": { "strongBuy": 1, "buy": 22, "hold": 12, "sell": 1 }, "history": { "current": { "target": 303.06, "rating": "Moderate Buy" }, "oneMonthAgo": { "target": 297.58, "rating": "Moderate Buy" }, "threeMonthsAgo": { "target": 281.70, "rating": "Moderate Buy" }, "oneYearAgo": { "target": 236.97, "rating": "Moderate Buy" } } } ``` Useful for detecting whether analysts are getting more bullish or bearish on a name over time — one request, four data points. ### **Use cases** | Use case | Description | Best for | |---|---|---| | **Daily rating digest** | Pull the full market feed on a schedule for downstream filtering and alerting | Portfolio managers, newsletters | | **Portfolio news monitor** | Run in ticker mode each day for a watchlist and flag consensus drift | Retail investors, AI portfolio agents | | **Earnings-week monitoring** | Filter for `upgrade`/`downgrade` in the days after earnings | Event-driven strategies | | **LLM-fed research** | Feed the daily feed into an MCP-enabled agent to summarize market sentiment | ChatGPT, Claude, custom agents | | **Brokerage tracking** | Pull a specific firm's calls with their 12-month ROI to evaluate analyst quality | Quants, research desks | | **Alerting** | Filter `downgrade` or large `target_lowered` moves on a portfolio | Risk-aware traders | | **Historical dataset** | Run daily and store; builds a clean analyst ratings database | Data science / backtest research | ### **How to use with Python** ```python from apify_client import ApifyClient client = ApifyClient("YOUR_APIFY_TOKEN") run = client.actor("michael_b/stock-analyst-ratings").call(run_input={ "market": "us", "actions": ["upgrade", "downgrade"], }) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(f"[{item['ticker']}] {item['brokerage']}: {item['priorRating']} -> {item['newRating']}") ``` ### **How to use with JavaScript** ```javascript import { ApifyClient } from 'apify-client'; const client = new ApifyClient({ token: 'YOUR_APIFY_TOKEN' }); const run = await client.actor('michael_b/stock-analyst-ratings').call({ tickers: 'AAPL, TSLA, NVDA', includeConsensus: true, }); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach(r => console.log(`${r.ticker}: ${r.brokerage} -> ${r.newRating} @ ${r.newTarget}`)); ``` ### **How much does it cost?** Raw HTTP requests with no browser keep costs minimal. Recommended memory: **512 MB**. | Scenario | HTTP requests | Output rows | Typical runtime | |---|---|---|---| | Daily feed | 1 | ~400 | a few seconds | | 10 tickers + consensus | 10 | ~150 + consensus | 10-15 seconds | | 5 brokerages | 6 (+1 index) | ~500 | 10-15 seconds | ### **Automate with Apify** - **Schedule daily** for a rolling ratings archive - **Use with MCP** — fully compatible with Apify's MCP server for Claude, ChatGPT, and custom agents - **Hook into Make, n8n, or Zapier** for no-code alerting - **Export** as JSON, CSV, Excel, or stream to your database via the Apify API ### **FAQ** **Is it legal to scrape MarketBeat?** This actor only accesses publicly available pages. No private data is read, no authentication is bypassed, and every row links back to the source URL on marketbeat.com. **How often is the data updated?** Live on every run. MarketBeat updates the main feed continuously through the trading day. **Why is `analyst` sometimes null?** MarketBeat gates individual analyst names behind their All Access subscription on the main feed. Ticker history and brokerage pages tend to include analysts more consistently. **Why is `ratingDate` null on the daily feed?** The main feed table doesn't show per-row dates, every row on it is from today. If you need exact timestamps, use ticker or brokerage mode. **How do I dedup across runs?** Use `ratingId`. It's MarketBeat's stable internal identifier for each rating and won't collide between runs. **Why doesn't ticker mode show a current price?** The per-ticker forecast page doesn't include intraday quote data. The daily feed does. Combine modes if you need both. **How are brokerage names matched?** Fuzzy match against MarketBeat's directory (`/ratings/by-issuer/`). `JPMorgan`, `JP Morgan`, and `J.P. Morgan` all resolve. If no match is found, the actor logs a warning and skips that name. **Is Canada supported?** Partially. The main feed includes Toronto (TSE) rows. Filter with `market: "ca"`. MarketBeat's dedicated Canadian endpoint redirects back to the main feed — we handle that automatically. ### **Support** Questions, feature requests, or bugs? Open an issue in the [Issues tab](https://apify.com/michael_b/stock-analyst-ratings/issues). # Actor input Schema ## `tickers` (type: `string`): Comma-separated ticker symbols to pull rating history for. When set, the actor switches to ticker history mode and returns the last ~15 dated ratings per ticker plus optional consensus block. Example: AAPL, TSLA, NVDA. Leave blank to scrape the daily market feed. If a ticker is ambiguous across markets, prefix it with its exchange (e.g. NASDAQ:AAPL, LON:ABF, TSE:ABX). ## `brokerages` (type: `string`): Comma-separated brokerage names to pull recent ratings per firm. Fuzzy-matched against MarketBeat's 300+ tracked issuers (e.g. "JPMorgan", "Goldman Sachs", "Citi"). When set, the actor switches to brokerage mode and returns ~100 dated ratings per brokerage with 12-month ROI. ## `market` (type: `string`): Filter the daily feed by market. 'all' returns everything (US + UK + Canada). Ignored when tickers or brokerages are set. ## `actions` (type: `array`): Keep only ratings matching these action types. Leave empty to include all actions. ## `daysBack` (type: `integer`): Keep only ratings within the last N days. Applies to ticker and brokerage modes where rating dates are available. Ignored for the daily feed (always today). Set to 0 to disable. ## `includeConsensus` (type: `boolean`): In ticker mode, attach a consensus block (average rating, price target, breakdown, trend over 1m/3m/1yr) per ticker. Adds no extra requests - data is parsed from the same page. ## `maxItems` (type: `integer`): Hard cap on total rating rows returned across all modes. Set to 0 for no limit. ## Actor input object example ```json { "market": "all", "actions": [], "daysBack": 0, "includeConsensus": true, "maxItems": 0 } ``` # Actor output Schema ## `results` (type: `string`): Dataset of analyst rating rows with normalized fields: ticker, exchange, company, action, brokerage, analyst, prior/new rating, prior/new price target, current price, upside pct, optional rating date, detail ID for dedup, and source URL. # 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 = {}; // Run the Actor and wait for it to finish const run = await client.actor("michael_b/stock-analyst-ratings").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 = {} # Run the Actor and wait for it to finish run = client.actor("michael_b/stock-analyst-ratings").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 '{}' | apify call michael_b/stock-analyst-ratings --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=michael_b/stock-analyst-ratings", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Stock Analyst Ratings - Upgrades, Downgrades, Targets", "description": "Daily analyst rating changes across US, UK, and Canadian markets: upgrades, downgrades, price targets, initiations, reiterations. Also per-ticker history with consensus snapshot and per-brokerage feeds with 12-month ROI. Built for AI agents, MCP pipelines, and portfolio monitoring.", "version": "0.1", "x-build-id": "HVfq0Ep6fLict7rwQ" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/michael_b~stock-analyst-ratings/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-michael_b-stock-analyst-ratings", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/michael_b~stock-analyst-ratings/runs": { "post": { "operationId": "runs-sync-michael_b-stock-analyst-ratings", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/michael_b~stock-analyst-ratings/run-sync": { "post": { "operationId": "run-sync-michael_b-stock-analyst-ratings", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "tickers": { "title": "Tickers (optional)", "type": "string", "description": "Comma-separated ticker symbols to pull rating history for. When set, the actor switches to ticker history mode and returns the last ~15 dated ratings per ticker plus optional consensus block. Example: AAPL, TSLA, NVDA. Leave blank to scrape the daily market feed. If a ticker is ambiguous across markets, prefix it with its exchange (e.g. NASDAQ:AAPL, LON:ABF, TSE:ABX)." }, "brokerages": { "title": "Brokerages (optional)", "type": "string", "description": "Comma-separated brokerage names to pull recent ratings per firm. Fuzzy-matched against MarketBeat's 300+ tracked issuers (e.g. \"JPMorgan\", \"Goldman Sachs\", \"Citi\"). When set, the actor switches to brokerage mode and returns ~100 dated ratings per brokerage with 12-month ROI." }, "market": { "title": "Market Filter", "enum": [ "all", "us", "uk", "ca" ], "type": "string", "description": "Filter the daily feed by market. 'all' returns everything (US + UK + Canada). Ignored when tickers or brokerages are set.", "default": "all" }, "actions": { "title": "Action Types", "uniqueItems": true, "type": "array", "description": "Keep only ratings matching these action types. Leave empty to include all actions.", "items": { "type": "string", "enum": [ "upgrade", "downgrade", "initiate", "reiterate", "target_raised", "target_lowered", "target_set" ] }, "default": [] }, "daysBack": { "title": "Days Back", "minimum": 0, "type": "integer", "description": "Keep only ratings within the last N days. Applies to ticker and brokerage modes where rating dates are available. Ignored for the daily feed (always today). Set to 0 to disable.", "default": 0 }, "includeConsensus": { "title": "Include Consensus Snapshot (ticker mode)", "type": "boolean", "description": "In ticker mode, attach a consensus block (average rating, price target, breakdown, trend over 1m/3m/1yr) per ticker. Adds no extra requests - data is parsed from the same page.", "default": true }, "maxItems": { "title": "Max Items", "minimum": 0, "type": "integer", "description": "Hard cap on total rating rows returned across all modes. Set to 0 for no limit.", "default": 0 } } }, "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 } } } } } } } } } } ```