# Dataset Drift Monitor (`checksmithcats/dataset-drift-monitor`) Actor

Scheduled scraper ran successfully, but did the output quietly change? Compare the current dataset shape with the latest baseline for count, field, missing-rate, and type-distribution drift.

- **URL**: https://apify.com/checksmithcats/dataset-drift-monitor.md
- **Developed by:** [Checksmith Cats](https://apify.com/checksmithcats) (community)
- **Categories:** Developer tools, Automation
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $0.60 / 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 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.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — 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

## Dataset Drift Monitor

Dataset Drift Monitor compares the current shape of a scraper dataset with the latest compact baseline for the same identity. It is for scraper operators who need to catch quiet output changes such as sudden row-count drops, missing fields, removed fields, or type changes.

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, Evidence Pack, or drift state.

### What It Checks

- Record count drop versus the previous compact baseline
- Field additions and removals
- Field missing-rate increases
- Field type-distribution shifts
- First-run baseline creation

### Boundaries

This is an aggregate output-shape monitor. It does not independently check source pages, prove scraper correctness, repair missing records, judge legality, or promise alert coverage. It records what changed in the sampled dataset output.

### Billing

Recommended launch pricing:

- `dataset-drift-report-generated`: USD 0.60 per generated drift report
- `dataset-row-sampled`: USD 0.01 per sampled row

Invalid input and dataset load/compare failures are not charged.

### Local Example

```bash
PYTHONPATH=src python -m apify_dataset_drift_monitor.cli examples/sample-input.json --json report.json --md report.md
```

# Actor input Schema

## `datasetId` (type: `string`):

Dataset ID to read through the platform API.

## `runId` (type: `string`):

Actor run ID. The monitor 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 or state.

## `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 analyzed only as aggregate shape signals.

## `baselineKey` (type: `string`):

Stable identity used for repeated comparisons. Required for submitted data and recommended for runId-based checks.

## `sampleLimit` (type: `integer`):

Maximum number of rows to sample from the current dataset. Keep the default small for scheduled runs.

## `countDropRatio` (type: `number`):

Warn when record count drops by at least this ratio compared with the latest baseline.

## `missingRateDelta` (type: `number`):

Warn when a field's missing rate increases by at least this absolute amount.

## `typeShiftDelta` (type: `number`):

Warn when a field's observed type distribution moves by at least this amount.

## `stateStoreName` (type: `string`):

Key-value store name for the latest compact baseline snapshot.

## Actor input object example

```json
{
  "sampleLimit": 200,
  "countDropRatio": 0.25,
  "missingRateDelta": 0.2,
  "typeShiftDelta": 0.5,
  "stateStoreName": "dataset-drift-monitor-state"
}
```

# 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 '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {};

// Run the Actor and wait for it to finish
const run = await client.actor("checksmithcats/dataset-drift-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 '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {}

# Run the Actor and wait for it to finish
run = client.actor("checksmithcats/dataset-drift-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 '{}' |
apify call checksmithcats/dataset-drift-monitor --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "command": "npx",
            "args": [
                "mcp-remote",
                "https://mcp.apify.com/?tools=checksmithcats/dataset-drift-monitor",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

```

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/Hfls840fa54XhH7Lh/builds/VlPIaK6n8jL0xatNV/openapi.json