# Apify Dataset Quality Profiler (`eager_vitamin/apify-dataset-quality-profiler`) Actor Profile missing fields, nulls, empty strings, JSON types, distinct counts, and duplicate keys in an Apify dataset. - **URL**: https://apify.com/eager\_vitamin/apify-dataset-quality-profiler.md - **Developed by:** [Lau Kuan Ee](https://apify.com/eager_vitamin) (community) - **Categories:** Developer tools - **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/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 ## Apify Dataset Quality Profiler Find structural problems in scraper output before exporting it or sending it downstream. The Actor produces one compact profile row per field, so you can scan missing fields, nulls, empty strings, mixed JSON types, distinct counts, and duplicate keys without downloading the dataset. ### Why this Actor - Works directly with an Apify dataset ID or inline trial records. - Reads private datasets with the run's `APIFY_TOKEN` and never logs or stores that token. - Does not publish raw sample values in profile rows. - Supports nested fields through dot paths. - Caps every run at 100,000 records. ### Input ```json { "datasetId": "YOUR_DATASET_ID", "keyFields": ["id"], "maxItems": 10000, "emptyStringsAreMissing": true } ```` Use `items` instead of `datasetId` for an inline trial. Do not provide both. ### Output The default dataset contains one `field_profile` record per discovered leaf path: ```json { "recordType": "field_profile", "field": "company.city", "records": 1000, "present": 982, "missing": 18, "null": 4, "empty": 7, "distinct": 81, "types": {"null": 4, "string": 978}, "qualityFlags": ["missing_values", "null_values", "empty_strings", "mixed_types"] } ``` `OUTPUT.json` reports item and field counts, duplicate-key counts, and quality-flag totals. Distinct counts are exact within the configured record limit. ### Limits and privacy Objects are followed recursively, while arrays are treated as complete values. The Actor does not replace a data-governance review and does not emit raw example values. Dataset reads use only Apify's Dataset Items API. ### Pricing proposal `$0.01` per field-profile output row plus Apify's required minimum Actor-start event. Final pricing is staged separately in the Apify Console. # Actor input Schema ## `datasetId` (type: `string`): An Apify dataset accessible to this run. Leave empty when using inline items. ## `items` (type: `array`): Optional JSON records for a quick trial. Used when Dataset ID is empty. ## `keyFields` (type: `array`): Optional dot paths that form a composite key, such as id or company.domain. ## `maxItems` (type: `integer`): Hard limit for records loaded and profiled. ## `emptyStringsAreMissing` (type: `boolean`): Include empty strings in the missing-values quality flag. ## Actor input object example ```json { "items": [ { "id": "lead-1", "company": { "name": "Acme", "city": "Singapore" }, "score": "9", "active": true }, { "id": "lead-1", "company": { "name": "Acme", "city": "" }, "score": 9, "active": true }, { "id": "lead-3", "company": { "name": "Beta" }, "score": null } ], "keyFields": [ "id" ], "maxItems": 10000, "emptyStringsAreMissing": true } ``` # 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 = { "items": [ { "id": "lead-1", "company": { "name": "Acme", "city": "Singapore" }, "score": "9", "active": true }, { "id": "lead-1", "company": { "name": "Acme", "city": "" }, "score": 9, "active": true }, { "id": "lead-3", "company": { "name": "Beta" }, "score": null } ] }; // Run the Actor and wait for it to finish const run = await client.actor("eager_vitamin/apify-dataset-quality-profiler").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 = { "items": [ { "id": "lead-1", "company": { "name": "Acme", "city": "Singapore", }, "score": "9", "active": True, }, { "id": "lead-1", "company": { "name": "Acme", "city": "", }, "score": 9, "active": True, }, { "id": "lead-3", "company": { "name": "Beta" }, "score": None, }, ] } # Run the Actor and wait for it to finish run = client.actor("eager_vitamin/apify-dataset-quality-profiler").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 '{ "items": [ { "id": "lead-1", "company": { "name": "Acme", "city": "Singapore" }, "score": "9", "active": true }, { "id": "lead-1", "company": { "name": "Acme", "city": "" }, "score": 9, "active": true }, { "id": "lead-3", "company": { "name": "Beta" }, "score": null } ] }' | apify call eager_vitamin/apify-dataset-quality-profiler --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=eager_vitamin/apify-dataset-quality-profiler", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Apify Dataset Quality Profiler", "description": "Profile missing fields, nulls, empty strings, JSON types, distinct counts, and duplicate keys in an Apify dataset.", "version": "0.1", "x-build-id": "2gWnbHCTUQ05ipMOE" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/eager_vitamin~apify-dataset-quality-profiler/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-eager_vitamin-apify-dataset-quality-profiler", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/eager_vitamin~apify-dataset-quality-profiler/runs": { "post": { "operationId": "runs-sync-eager_vitamin-apify-dataset-quality-profiler", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/eager_vitamin~apify-dataset-quality-profiler/run-sync": { "post": { "operationId": "run-sync-eager_vitamin-apify-dataset-quality-profiler", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": "Dataset ID or name", "type": "string", "description": "An Apify dataset accessible to this run. Leave empty when using inline items." }, "items": { "title": "Inline records", "type": "array", "description": "Optional JSON records for a quick trial. Used when Dataset ID is empty.", "items": { "type": "object" } }, "keyFields": { "title": "Duplicate key fields", "type": "array", "description": "Optional dot paths that form a composite key, such as id or company.domain.", "items": { "type": "string" }, "default": [ "id" ] }, "maxItems": { "title": "Maximum records", "minimum": 1, "maximum": 100000, "type": "integer", "description": "Hard limit for records loaded and profiled.", "default": 10000 }, "emptyStringsAreMissing": { "title": "Flag empty strings as missing", "type": "boolean", "description": "Include empty strings in the missing-values quality flag.", "default": true } } }, "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 } } } } } } } } } } ```