# Earnings Scraper Pro (`xtech/earnings-scraper-pro`) Actor Bulk earnings calendar scraper for stock symbols. Get upcoming earnings dates, EPS estimates, earnings history, UTC‑normalized events, and alerts for earnings week and recent beat/miss trends. - **URL**: https://apify.com/xtech/earnings-scraper-pro.md - **Developed by:** [Xtech](https://apify.com/xtech) (community) - **Categories:** Developer tools, Automation, Other - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 1 bookmarks - **User rating**: No ratings yet ## Pricing $23.00/month + usage To use this Actor, you pay a monthly rental fee to the developer. The rent is subtracted from your prepaid usage every month after the free trial period.You also pay for the Apify platform usage, which gets cheaper the higher Apify subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#rental-actors ## 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 ## Earnings Calendar Scraper 📆 Bulk scraper focused on earnings-related data. It collects earnings calendars, upcoming earnings dates, and earnings history, then normalizes event times to UTC when possible and generates lightweight alerts. ### ✅ What You Get - **Earnings calendar**: Raw calendar fields from the provider. - **Upcoming earnings dates**: Structured rows of scheduled earnings dates. - **Earnings history**: Historical EPS data when available. - **Normalized events**: Standardized event types with UTC conversion when possible. - **Alerts**: “Earnings week” flags and surprise/beat‑miss trend summary. ### 📦 Output Structure (per symbol) ```json { "symbol": "AAPL", "scraped_at": "2026-01-30T12:00:00+00:00", "earnings": { "calendar_raw": {"Earnings Date": ["2026-02-01T00:00:00-05:00"]}, "calendar_events": [ { "type": "earnings_date", "source": "calendar", "source_field": "Earnings Date", "date": "2026-02-01T00:00:00-05:00", "date_utc": "2026-02-01T05:00:00+00:00", "date_utc_assumed": false } ], "earnings_dates_request": {"limit": 12, "offset": 0}, "earnings_dates": [ {"Earnings Date": "2026-02-01T00:00:00-05:00", "EPS Estimate": 2.10} ], "earnings_dates_events": [ { "type": "earnings_date", "source": "earnings_dates", "source_field": "Earnings Date", "date": "2026-02-01T00:00:00-05:00", "date_utc": "2026-02-01T05:00:00+00:00", "date_utc_assumed": false } ], "earnings_history": [ {"quarter": "2025-11-01T00:00:00-04:00", "epsActual": 2.22, "epsEstimate": 2.10} ], "events": [ { "type": "earnings_date", "source": "calendar", "source_field": "Earnings Date", "date": "2026-02-01T00:00:00-05:00", "date_utc": "2026-02-01T05:00:00+00:00", "date_utc_assumed": false } ], "alerts": { "earnings_week": { "window_days": 7, "count": 1, "has_upcoming": true, "upcoming": [ { "date": "2026-02-01T00:00:00-05:00", "date_utc": "2026-02-01T05:00:00+00:00", "date_utc_assumed": false, "source": "calendar", "source_field": "Earnings Date" } ] }, "surprise": { "latest": {"value": 5.7, "unit": "percent", "based_on": "actual_minus_estimate"}, "previous": {"value": 3.2, "unit": "percent", "based_on": "surprise_pct"}, "change": 2.5 }, "beat_miss_trend_last_4": ["beat", "beat", "miss", "beat"] } } } ```` Notes: - `date_utc_assumed: true` means the provider supplied a date without timezone; the scraper assumed UTC for comparison. - Missing data is expected (availability can vary by ticker). ### ⚙️ Input ```json { "symbols": ["AAPL", "MSFT", "TSLA"], "earnings_dates_limit": 12, "earnings_dates_offset": 0, "earnings_alert_window_days": 7 } ``` #### Parameters - **symbols**: List of stock symbols (or comma‑separated string). - **earnings\_dates\_limit**: Max rows for earnings dates. Default `12`. - **earnings\_dates\_offset**: Offset for earnings dates. Default `0`. - **earnings\_alert\_window\_days**: Window for “earnings week” alerts. Default `7` days. Ready to monitor earnings? Click “Try for free” to start. # Actor input Schema ## `symbols` (type: `array`): Enter one or more stock symbols (e.g., AAPL, MSFT, BTC-USD). You can also pass a comma-separated string. ## `earnings_dates_limit` (type: `integer`): Maximum number of rows to return for earnings dates. ## `earnings_dates_offset` (type: `integer`): Offset for earnings dates (useful for pagination). ## `earnings_alert_window_days` (type: `integer`): How many days ahead to flag upcoming earnings dates. ## Actor input object example ```json { "symbols": [ "AAPL", "MSFT", "TSLA" ], "earnings_dates_limit": 12, "earnings_dates_offset": 0, "earnings_alert_window_days": 7 } ``` # 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 = { "symbols": [ "AAPL", "MSFT", "TSLA" ] }; // Run the Actor and wait for it to finish const run = await client.actor("xtech/earnings-scraper-pro").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 = { "symbols": [ "AAPL", "MSFT", "TSLA", ] } # Run the Actor and wait for it to finish run = client.actor("xtech/earnings-scraper-pro").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 '{ "symbols": [ "AAPL", "MSFT", "TSLA" ] }' | apify call xtech/earnings-scraper-pro --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=xtech/earnings-scraper-pro", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Earnings Scraper Pro", "description": "Bulk earnings calendar scraper for stock symbols. Get upcoming earnings dates, EPS estimates, earnings history, UTC‑normalized events, and alerts for earnings week and recent beat/miss trends.", "version": "1.0", "x-build-id": "GbGExVAKfivekZofc" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/xtech~earnings-scraper-pro/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-xtech-earnings-scraper-pro", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/xtech~earnings-scraper-pro/runs": { "post": { "operationId": "runs-sync-xtech-earnings-scraper-pro", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/xtech~earnings-scraper-pro/run-sync": { "post": { "operationId": "run-sync-xtech-earnings-scraper-pro", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "symbols" ], "properties": { "symbols": { "title": "Stock Symbols", "minItems": 1, "uniqueItems": true, "type": "array", "description": "Enter one or more stock symbols (e.g., AAPL, MSFT, BTC-USD). You can also pass a comma-separated string.", "items": { "type": "string" } }, "earnings_dates_limit": { "title": "Earnings Dates Limit", "minimum": 1, "type": "integer", "description": "Maximum number of rows to return for earnings dates.", "default": 12 }, "earnings_dates_offset": { "title": "Earnings Dates Offset", "minimum": 0, "type": "integer", "description": "Offset for earnings dates (useful for pagination).", "default": 0 }, "earnings_alert_window_days": { "title": "Earnings Alert Window (days)", "minimum": 1, "type": "integer", "description": "How many days ahead to flag upcoming earnings dates.", "default": 7 } } }, "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 } } } } } } } } } } ```