# Scraped Dataset QA Preflight (`checksmithcats/scraped-dataset-qa-preflight`) Actor A quick QA pass for scraper output before client handoff, CRM import, or scheduled pipeline use. Checks sampled rows for field gaps, duplicates, type shifts, and sensitive-pattern counts. - **URL**: https://apify.com/checksmithcats/scraped-dataset-qa-preflight.md - **Developed by:** [Checksmith Cats](https://apify.com/checksmithcats) (community) - **Categories:** Automation, Developer tools - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $0.50 / report generated This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage. 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 ## Scraped Dataset QA Preflight Scraped Dataset QA Preflight checks sampled scraper output before delivery or downstream import. It focuses on source-specific, machine-detectable signals: missing fields, duplicate key rows, format-looking problems, mixed value types, sensitive-looking pattern counts, and lightweight schema contract mismatches. It can read a dataset ID, resolve an Actor run ID to its default dataset, or analyze submitted JSON/CSV data. API tokens and raw row values are not stored in the report or Evidence Pack. ### Presets - `googleMaps`: name, address, phone, website, place URL, category, and hours signals - `leadList`: email, company, person, phone, domain, and source URL signals - `socialProfile`: username, profile URL, follower/post counts, bio, and external URL signals - `generic`: field profile, duplicates, formats, sensitive-pattern preview, and optional contract checks ### Boundaries This is a sampled dataset-output preflight. It does not independently check source pages, confirm complete crawl coverage, repair scraper output, judge legal suitability, validate live email inboxes, or predict downstream outcomes. ### Billing Recommended launch pricing: - `scraped-dataset-qa-report-generated`: USD 0.50 per generated QA report - `scraped-dataset-row-sampled`: USD 0.01 per sampled row Invalid input and dataset load/inspect failures are not charged. ### Related check If the same scraper runs repeatedly, use [Dataset Drift Monitor](https://apify.com/checksmithcats/dataset-drift-monitor?utm_source=apify&utm_medium=actor_referral&utm_campaign=dataset_qa_to_drift) to compare the current aggregate dataset shape with its latest compact baseline. ### Local Example ```bash PYTHONPATH=src python -m scraped_dataset_qa_preflight.cli examples/sample-input.json --json report.json --md report.md ```` # Actor input Schema ## `datasetId` (type: `string`): Dataset ID to read via the Apify API. ## `runId` (type: `string`): Actor run ID. The preflight resolves its default dataset ID. ## `apiToken` (type: `string`): Optional token for private datasets or runs. Sent in the Authorization header only and not stored in reports. ## `items` (type: `array`): Optional inline array of item objects. Use this when not reading from Apify API. ## `dataJson` (type: `string`): Optional JSON array, or an object with an items array. ## `csvText` (type: `string`): Optional CSV with a header row. Values are summarized as aggregate QA signals. ## `preset` (type: `string`): Source-specific field expectations and default duplicate keys. ## `keyFields` (type: `array`): Optional fields used to count duplicate row groups. Preset defaults are used when empty. ## `schemaContractJson` (type: `string`): Optional lightweight JSON Schema object. The preflight checks required fields and simple property types. ## `sampleLimit` (type: `integer`): Maximum number of rows to sample from the current dataset. Keep the default small for scheduled or exploratory runs. ## `missingRateWarning` (type: `number`): Warn when an observed field is empty or missing in at least this share of sampled rows. ## Actor input object example ```json { "preset": "generic", "sampleLimit": 200, "missingRateWarning": 0.3 } ``` # Actor output Schema ## `results` (type: `string`): No description ## `report` (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 = {}; // Run the Actor and wait for it to finish const run = await client.actor("checksmithcats/scraped-dataset-qa-preflight").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("checksmithcats/scraped-dataset-qa-preflight").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 checksmithcats/scraped-dataset-qa-preflight --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=checksmithcats/scraped-dataset-qa-preflight", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Scraped Dataset QA Preflight", "description": "A quick QA pass for scraper output before client handoff, CRM import, or scheduled pipeline use. Checks sampled rows for field gaps, duplicates, type shifts, and sensitive-pattern counts.", "version": "0.1", "x-build-id": "Te0WsDz4YvZeQYW5l" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/checksmithcats~scraped-dataset-qa-preflight/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-checksmithcats-scraped-dataset-qa-preflight", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/checksmithcats~scraped-dataset-qa-preflight/runs": { "post": { "operationId": "runs-sync-checksmithcats-scraped-dataset-qa-preflight", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/checksmithcats~scraped-dataset-qa-preflight/run-sync": { "post": { "operationId": "run-sync-checksmithcats-scraped-dataset-qa-preflight", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "datasetId": { "title": "Apify dataset ID", "type": "string", "description": "Dataset ID to read via the Apify API." }, "runId": { "title": "Apify run ID", "type": "string", "description": "Actor run ID. The preflight resolves its default dataset ID." }, "apiToken": { "title": "Apify API token", "type": "string", "description": "Optional token for private datasets or runs. Sent in the Authorization header only and not stored in reports." }, "items": { "title": "Submitted JSON items", "type": "array", "description": "Optional inline array of item objects. Use this when not reading from Apify API.", "items": { "type": "object" } }, "dataJson": { "title": "Submitted JSON text", "type": "string", "description": "Optional JSON array, or an object with an items array." }, "csvText": { "title": "Submitted CSV text", "type": "string", "description": "Optional CSV with a header row. Values are summarized as aggregate QA signals." }, "preset": { "title": "Preset", "enum": [ "googleMaps", "leadList", "socialProfile", "generic" ], "type": "string", "description": "Source-specific field expectations and default duplicate keys.", "default": "generic" }, "keyFields": { "title": "Duplicate key fields", "maxItems": 12, "type": "array", "description": "Optional fields used to count duplicate row groups. Preset defaults are used when empty.", "items": { "type": "string" } }, "schemaContractJson": { "title": "Schema contract JSON", "type": "string", "description": "Optional lightweight JSON Schema object. The preflight checks required fields and simple property types." }, "sampleLimit": { "title": "Sample limit", "minimum": 1, "maximum": 5000, "type": "integer", "description": "Maximum number of rows to sample from the current dataset. Keep the default small for scheduled or exploratory runs.", "default": 200 }, "missingRateWarning": { "title": "Missing-rate warning threshold", "minimum": 0.01, "maximum": 1, "type": "number", "description": "Warn when an observed field is empty or missing in at least this share of sampled rows.", "default": 0.3 } } }, "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 } } } } } } } } } } ```