# Chicago Restaurant Inspections (`deepztack/chicago-restaurant-inspections`) Actor Get fresh Chicago restaurant health inspection results (Pass/Fail) from the official city open-data API, with business name, facility type, risk level, address, and date. - **URL**: https://apify.com/deepztack/chicago-restaurant-inspections.md - **Developed by:** [deepztack](https://apify.com/deepztack) (community) - **Categories:** Business, Marketing - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing Pay per usage This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-usage ## 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 ## Chicago Restaurant Inspections Get fresh Chicago restaurant health inspection results from the official City of Chicago open-data API, including business name, facility type, risk level, inspection date, address, and Pass/Fail result. ### What this Actor does This Actor queries Chicago's official Socrata dataset for food inspections and returns clean records with: - inspection ID and business name, - facility type and risk level, - inspection date, type, and result (Pass/Fail/Conditions), - address and geolocation, - source link, - simplified result category. Official source: - `https://data.cityofchicago.org/resource/4ijn-s7e5.json` ### Who it is for - restaurant owners and managers tracking their compliance record, - food industry researchers analyzing health trends, - health compliance consultants, - commercial brokers assessing areas by restaurant quality. ### Input ```json { "startDate": "2026-06-01", "endDate": "2026-07-04", "results": ["Fail", "Pass w/ Conditions"], "facilityTypes": ["Restaurant"], "maxItems": 100 } ```` All filters are optional except `maxItems`. ### Output example ```json { "inspectionId": "2639280", "businessName": "TEST RESTAURANT INC", "facilityType": "Restaurant", "risk": "Risk 1 (High)", "address": "100 N STATE ST", "city": "CHICAGO", "inspectionDate": "2026-07-01", "inspectionType": "Canvass", "result": "Pass", "resultType": "pass", "latitude": 41.8827, "longitude": -87.6278, "sourceUrl": "https://data.cityofchicago.org/Food-Health/Food-Inspections/4ijn-s7e5/2639280", "scrapedAt": "2026-07-04T12:00:00+00:00" } ``` ### Result types - `pass`: Pass - `fail`: Fail - `conditional`: Pass w/ Conditions - `other`: Business Not Located, No Entry, Not Ready, Out of Business - `unknown`: missing result ### Responsible use This Actor uses public food inspection data from the City of Chicago. Use the output responsibly and in accordance with applicable laws. ### Limitations - Not affiliated with or endorsed by the City of Chicago. - Dataset fields depend on the official source and may be blank for some records. - Result categories are simplified from the source; always verify results against the source URL. ### Development ```bash python3 -m pytest tests/test_chicago_inspections.py -q npx apify-cli run ``` ### Changelog - v0.1.0 — Initial Chicago restaurant inspection extraction from official Socrata API. # Actor input Schema ## `startDate` (type: `string`): Only include inspections on or after this date (YYYY-MM-DD). ## `endDate` (type: `string`): Only include inspections on or before this date (YYYY-MM-DD). ## `results` (type: `array`): Filter by inspection result. Leave empty for all results. ## `facilityTypes` (type: `array`): Filter by facility type, for example Restaurant, School, Grocery Store. ## `riskLevels` (type: `array`): Filter by risk level: Risk 1 (High), Risk 2 (Medium), Risk 3 (Low). ## `minLatitude` (type: `number`): Southern boundary for geographic filter. ## `maxLatitude` (type: `number`): Northern boundary for geographic filter. ## `minLongitude` (type: `number`): Western boundary for geographic filter. ## `maxLongitude` (type: `number`): Eastern boundary for geographic filter. ## `maxItems` (type: `integer`): Maximum number of inspection records to return. Capped at 10000. ## Actor input object example ```json { "results": [ "Fail", "Pass w/ Conditions" ], "maxItems": 100 } ``` # Actor output Schema ## `results` (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 = { "results": [ "Fail", "Pass w/ Conditions" ], "maxItems": 100 }; // Run the Actor and wait for it to finish const run = await client.actor("deepztack/chicago-restaurant-inspections").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 = { "results": [ "Fail", "Pass w/ Conditions", ], "maxItems": 100, } # Run the Actor and wait for it to finish run = client.actor("deepztack/chicago-restaurant-inspections").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 '{ "results": [ "Fail", "Pass w/ Conditions" ], "maxItems": 100 }' | apify call deepztack/chicago-restaurant-inspections --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=deepztack/chicago-restaurant-inspections", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Chicago Restaurant Inspections", "description": "Get fresh Chicago restaurant health inspection results (Pass/Fail) from the official city open-data API, with business name, facility type, risk level, address, and date.", "version": "0.1", "x-build-id": "LBN6B6JJ601khdEom" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/deepztack~chicago-restaurant-inspections/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-deepztack-chicago-restaurant-inspections", "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/deepztack~chicago-restaurant-inspections/runs": { "post": { "operationId": "runs-sync-deepztack-chicago-restaurant-inspections", "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/deepztack~chicago-restaurant-inspections/run-sync": { "post": { "operationId": "run-sync-deepztack-chicago-restaurant-inspections", "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": [ "maxItems" ], "properties": { "startDate": { "title": "Start date", "type": "string", "description": "Only include inspections on or after this date (YYYY-MM-DD)." }, "endDate": { "title": "End date", "type": "string", "description": "Only include inspections on or before this date (YYYY-MM-DD)." }, "results": { "title": "Results", "type": "array", "description": "Filter by inspection result. Leave empty for all results.", "items": { "type": "string" } }, "facilityTypes": { "title": "Facility types", "type": "array", "description": "Filter by facility type, for example Restaurant, School, Grocery Store.", "items": { "type": "string" } }, "riskLevels": { "title": "Risk levels", "type": "array", "description": "Filter by risk level: Risk 1 (High), Risk 2 (Medium), Risk 3 (Low).", "items": { "type": "string" } }, "minLatitude": { "title": "Min latitude", "type": "number", "description": "Southern boundary for geographic filter." }, "maxLatitude": { "title": "Max latitude", "type": "number", "description": "Northern boundary for geographic filter." }, "minLongitude": { "title": "Min longitude", "type": "number", "description": "Western boundary for geographic filter." }, "maxLongitude": { "title": "Max longitude", "type": "number", "description": "Eastern boundary for geographic filter." }, "maxItems": { "title": "Maximum records", "minimum": 1, "maximum": 10000, "type": "integer", "description": "Maximum number of inspection records to return. Capped at 10000." } } }, "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 } } } } } } } } } } ```