# USDA Food Price Outlook Revision Monitor (`aether_studio/usda-food-price-outlook-revision-monitor`) Actor Compares the newest two official USDA Food Price Outlook releases and reports revisions to consumer or producer food-price forecast intervals by category. - **URL**: https://apify.com/aether\_studio/usda-food-price-outlook-revision-monitor.md - **Developed by:** [AetherPromptStudio](https://apify.com/aether_studio) (community) - **Categories:** Automation, Other - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $1.00 / 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/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 ## USDA Food Price Outlook Revision Monitor Convert the U.S. Department of Agriculture Economic Research Service's monthly Food Price Outlook releases into analysis-ready forecast revisions. Choose the Consumer Price Index series for retail food categories or the Producer Price Index series for selected farm and wholesale categories. The Actor compares the newest two releases and returns changes to each category's forecast midpoint and prediction-interval bounds. ### Common uses - Grocery, restaurant, and food-service planning - CPG and procurement monitoring - Food-inflation research and journalism - Automated alerts when official forecasts are materially revised ### Output Each record contains the category, year being forecast, current and previous release months, lower/midpoint/upper forecasts, revision amounts in percentage points, a stable series key, official source links, retrieval time, and limitations. ### Source and limitations Data comes directly from the official USDA ERS Food Price Outlook historical CPI and PPI forecast CSV files. Values are forecasts and prediction intervals, not guaranteed price changes. Releases may be revised; category definitions and methods may change. Results are not procurement, pricing, investment, or financial advice. This independent product is not affiliated with or endorsed by USDA. # Actor input Schema ## `seriesType` (type: `string`): Consumer Price Index forecasts cover retail food prices; Producer Price Index forecasts cover selected farm and wholesale categories. ## `categoryContains` (type: `string`): Case-insensitive food-category filter. Leave empty for all. ## `targetYears` (type: `array`): Optional list of four-digit target years. Leave empty for all target years in the newest release. ## `minMidpointRevision` (type: `number`): Minimum absolute change in forecast midpoint, measured in percentage points. ## `maxResults` (type: `integer`): Maximum number of revised category-year series written to the dataset. ## Actor input object example ```json { "seriesType": "CPI", "categoryContains": "", "targetYears": [], "minMidpointRevision": 0.1, "maxResults": 50 } ```` # Actor output Schema ## `results` (type: `string`): No description ## `summary` (type: `string`): No description # 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 = { "seriesType": "CPI", "categoryContains": "", "targetYears": [], "minMidpointRevision": 0.1, "maxResults": 50 }; // Run the Actor and wait for it to finish const run = await client.actor("aether_studio/usda-food-price-outlook-revision-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 = { "seriesType": "CPI", "categoryContains": "", "targetYears": [], "minMidpointRevision": 0.1, "maxResults": 50, } # Run the Actor and wait for it to finish run = client.actor("aether_studio/usda-food-price-outlook-revision-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 '{ "seriesType": "CPI", "categoryContains": "", "targetYears": [], "minMidpointRevision": 0.1, "maxResults": 50 }' | apify call aether_studio/usda-food-price-outlook-revision-monitor --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=aether_studio/usda-food-price-outlook-revision-monitor", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "USDA Food Price Outlook Revision Monitor", "description": "Compares the newest two official USDA Food Price Outlook releases and reports revisions to consumer or producer food-price forecast intervals by category.", "version": "0.1", "x-build-id": "LvoAP5wzMUgtI4ALC" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/aether_studio~usda-food-price-outlook-revision-monitor/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-aether_studio-usda-food-price-outlook-revision-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/aether_studio~usda-food-price-outlook-revision-monitor/runs": { "post": { "operationId": "runs-sync-aether_studio-usda-food-price-outlook-revision-monitor", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/aether_studio~usda-food-price-outlook-revision-monitor/run-sync": { "post": { "operationId": "run-sync-aether_studio-usda-food-price-outlook-revision-monitor", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "properties": { "seriesType": { "title": "Forecast Series", "enum": [ "CPI", "PPI" ], "type": "string", "description": "Consumer Price Index forecasts cover retail food prices; Producer Price Index forecasts cover selected farm and wholesale categories.", "default": "CPI" }, "categoryContains": { "title": "Category Contains", "type": "string", "description": "Case-insensitive food-category filter. Leave empty for all.", "default": "" }, "targetYears": { "title": "Years Being Forecast", "type": "array", "description": "Optional list of four-digit target years. Leave empty for all target years in the newest release.", "default": [], "items": { "type": "string" } }, "minMidpointRevision": { "title": "Minimum Midpoint Revision", "minimum": 0, "maximum": 100, "type": "number", "description": "Minimum absolute change in forecast midpoint, measured in percentage points.", "default": 0 }, "maxResults": { "title": "Maximum Results", "minimum": 1, "maximum": 1000, "type": "integer", "description": "Maximum number of revised category-year series written to the dataset.", "default": 200 } } }, "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 } } } } } } } } } } ```