# FTA Transit Safety Rate & Change Monitor (`aether_studio/fta-transit-safety-change-monitor`) Actor Compares the latest two validated FTA National Transit Database safety months by agency, mode, and service type, including events and per-million-trip rates. - **URL**: https://apify.com/aether\_studio/fta-transit-safety-change-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 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 ## FTA Transit Safety Rate & Change Monitor Turn the official Federal Transit Administration National Transit Database Monthly Modal Time Series into current safety changes by agency, mode, and type of service. The Actor compares each series' newest two validated months, returns total-event changes and component totals, and normalizes event counts per million passenger trips. A minimum-ridership filter reduces unstable rates caused by very small denominators. ### Common uses - Transit agency safety and oversight dashboards - Insurance and transit-consulting research - Public-policy and academic analysis - Reproducible monthly monitoring for journalists ### Output Each record contains agency and FTA identifiers, comparison months, ridership, total events and change, per-million-trip rates and change, collisions, fatalities, injuries, assaults on transit workers, stable keys, official provenance, retrieval time, and limitations. ### Source and limitations Data comes directly from the official FTA NTD **Monthly Modal Time Series** dataset. FTA safety data are validated with a reporting lag and may be revised. Historical reporting thresholds and definitions have changed. Month-to-month differences do not establish causation, comparative agency safety, or future risk and are not operational or safety advice. This independent product is not affiliated with or endorsed by FTA. # Actor input Schema ## `agencyContains` (type: `string`): Case-insensitive agency-name filter. Leave empty for all. ## `modes` (type: `array`): Examples: MB for motor bus, HR for heavy rail, CR for commuter rail. Leave empty for all. ## `minRidership` (type: `integer`): Require at least this many trips in both months to reduce unstable rates from very small denominators. ## `minAbsoluteEventDelta` (type: `integer`): Exclude series whose change in total events is smaller than this value. ## `maxAgeDays` (type: `integer`): Exclude series whose newest validated safety month is older than this many days. ## `maxResults` (type: `integer`): Maximum number of changed agency-mode series written to the dataset. ## Actor input object example ```json { "agencyContains": "", "modes": [], "minRidership": 10000, "minAbsoluteEventDelta": 2, "maxAgeDays": 240, "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 = { "agencyContains": "", "modes": [], "minRidership": 10000, "minAbsoluteEventDelta": 2, "maxAgeDays": 240, "maxResults": 50 }; // Run the Actor and wait for it to finish const run = await client.actor("aether_studio/fta-transit-safety-change-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 = { "agencyContains": "", "modes": [], "minRidership": 10000, "minAbsoluteEventDelta": 2, "maxAgeDays": 240, "maxResults": 50, } # Run the Actor and wait for it to finish run = client.actor("aether_studio/fta-transit-safety-change-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 '{ "agencyContains": "", "modes": [], "minRidership": 10000, "minAbsoluteEventDelta": 2, "maxAgeDays": 240, "maxResults": 50 }' | apify call aether_studio/fta-transit-safety-change-monitor --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=aether_studio/fta-transit-safety-change-monitor", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "FTA Transit Safety Rate & Change Monitor", "description": "Compares the latest two validated FTA National Transit Database safety months by agency, mode, and service type, including events and per-million-trip rates.", "version": "0.1", "x-build-id": "pMBTxe5faegokoxL7" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/aether_studio~fta-transit-safety-change-monitor/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-aether_studio-fta-transit-safety-change-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/aether_studio~fta-transit-safety-change-monitor/runs": { "post": { "operationId": "runs-sync-aether_studio-fta-transit-safety-change-monitor", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/aether_studio~fta-transit-safety-change-monitor/run-sync": { "post": { "operationId": "run-sync-aether_studio-fta-transit-safety-change-monitor", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "agencyContains": { "title": "Agency Contains", "type": "string", "description": "Case-insensitive agency-name filter. Leave empty for all.", "default": "" }, "modes": { "title": "FTA Mode Codes", "type": "array", "description": "Examples: MB for motor bus, HR for heavy rail, CR for commuter rail. Leave empty for all.", "default": [], "items": { "type": "string" } }, "minRidership": { "title": "Minimum Monthly Ridership", "minimum": 0, "maximum": 1000000000, "type": "integer", "description": "Require at least this many trips in both months to reduce unstable rates from very small denominators.", "default": 1000 }, "minAbsoluteEventDelta": { "title": "Minimum Absolute Event Change", "minimum": 0, "maximum": 1000000, "type": "integer", "description": "Exclude series whose change in total events is smaller than this value.", "default": 1 }, "maxAgeDays": { "title": "Maximum Data Age", "minimum": 30, "maximum": 1095, "type": "integer", "description": "Exclude series whose newest validated safety month is older than this many days.", "default": 240 }, "maxResults": { "title": "Maximum Results", "minimum": 1, "maximum": 1000, "type": "integer", "description": "Maximum number of changed agency-mode 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 } } } } } } } } } } ```