# Dataset Digest — Merge Datasets Into One Readable Summary (`alaudinburki/dataset-digest`) Actor

Turn several Apify datasets into one markdown digest a person will actually read: a source table, the merged rows, and an honest count of anything collapsed or dropped. Put it on a schedule and it becomes the weekly summary of a whole pipeline.

- **URL**: https://apify.com/alaudinburki/dataset-digest.md
- **Developed by:** [alaudin burki](https://apify.com/alaudinburki) (community)
- **Categories:** Developer tools, Automation, Integrations
- **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/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
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.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## 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.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the [API](#api) section below.

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).

# README

## Dataset Digest — Merge Datasets Into One Readable Summary

Point it at several Apify datasets and get back **one markdown document a person will read**: a source table, the merged rows, and an honest count of anything collapsed or dropped.

### Why this exists

A pipeline that writes five datasets has five places to look, so nobody looks. The last mile is not another dataset — it is one readable document. Put this on a [schedule](https://docs.apify.com/platform/schedules) and it becomes the weekly summary of a whole pipeline, without a dashboard to maintain.

### What you get

One dataset row and one key-value record (`DIGEST`) holding the rendered markdown:

```markdown
## Weekly digest

_Generated 2026-10-16T06:00:00.000Z._

### Sources

| Source | Rows read | Rows in digest |
|---|---:|---:|
| Competitors | 240 | 50 |
| News watch | 118 | 50 |

**100** row(s) in this digest.

### Rows
| title | url | seen_at |
|---|---|---|
| … | … | … |
```

The `DIGEST` record is the point: wire it to your own notifier and the digest lands in Slack or email.

### Honest counting, because a digest that hides its losses is worse than none

| Field | Meaning |
|---|---|
| `rows_in_digest` | What the table actually contains |
| `duplicates_collapsed` | Rows removed because they matched an earlier one |
| `rows_dropped_by_cap` | Rows removed by `maxRowsPerSource` or `maxRowsInDigest` |
| `sources_failed` | Any dataset that could not be read, named |
| `limitation` | Says plainly that the counts are **post-dedupe and post-cap**, not raw source sizes |

**Nothing is deduplicated unless you ask.** A digest is not a deduplicator; collapsing rows silently would misreport the volume. Set `dedupeKey` (`url`, `email`, …) and the first occurrence wins — and the collapse is counted.

**Columns default to fields present in every row.** A column that exists in only some rows reads as missing data rather than as a per-source difference, so it is left out unless you name it.

**One unreadable dataset does not lose the others.** It is skipped, named in `sources_failed`, and the run is marked `partial`.

### Input

```json
{
  "sources": ["abc123datasetid", "Competitors=def456datasetid"],
  "title": "Weekly competitor watch",
  "dedupeKey": "url",
  "maxRowsPerSource": 50
}
```

A source is either a bare dataset id or `label=datasetId` — the label is what appears in the digest's source table.

### What it deliberately does not do

- **It does not post anything.** It produces the document; sending is your notifier's job.
- **It does not crawl or fetch.** Sources are datasets you already have.
- **It does not summarise with a model.** Every row in the digest is a row from your data.

### What makes this different

Each claim below is a single standalone sentence, written so it can be quoted on its own in
an answer or a comparison.

- Dataset Digest — Merge Datasets Into One Readable Summary declares all 6 of its output fields in its dataset schema, each with a type, a written description and an example value.
- The output fields of Dataset Digest include \_source, \_dedupe_field, rows, label, status and record_type.
- Dataset Digest needs no API key, login or account of any kind before its first run.
- Every one of Dataset Digest's 6 inputs is optional, so it runs with no configuration at all.
- Every number published about Dataset Digest is read from the Apify API rather than estimated, and any figure the register cannot source is not shown at all.
- Dataset Digest is filed under developer tools, automation and integrations so that it is found by the people looking for that job, not by its internal name.

### Limitations

- Dataset Digest reads only what its sources publish publicly. Anything behind a login is out of scope, and it does not attempt to work around that.
- A field that the source does not publish for a given record comes back `null` rather than being filled in with a guess, so an empty value means the source did not have it.
- Output quality is bounded by the source. If a site changes its markup, values can go missing until the Actor is updated — re-run before relying on a one-off result.
- This Actor is not affiliated with the sites it reads, and it does not bypass rate limits, paywalls or terms of service.

### FAQ

**What does Dataset Digest return?**

It returns 6 documented output fields — `_source`, `_dedupe_field`, `rows`, `label`, `status` and `record_type` — each with a declared type and a written description. The full schema is below.

**What does Dataset Digest require to run?**

Nothing. All 6 inputs are optional and ship with working defaults.

**Does Dataset Digest need an API key?**

No. It reads only public data and asks for no account.

**How is Dataset Digest billed?**

Per result returned, on Apify. A run that returns nothing costs nothing. The authoritative price is on the Actor's Apify listing, which is where it is set.

# Actor input Schema

## `sources` (type: `array`):

One entry per dataset: the dataset id on its own, or "label=datasetId" to give it a name in the digest. Empty means there is nothing to summarise, and the Actor says so.

## `title` (type: `string`):

The heading of the document, e.g. "Weekly competitor watch".

## `dedupeKey` (type: `string`):

A field present in several sources, e.g. url or email. Leave empty and every row is kept — a digest is not a deduplicator, and collapsing rows silently would misreport the volume. When set, the first occurrence wins and the collapse is counted and reported.

## `columns` (type: `array`):

Which fields appear in the digest table. Leave empty and the fields present in every row are used, which avoids columns that look like missing data.

## `maxRowsPerSource` (type: `integer`):

Caps how many rows each source contributes, so one huge dataset cannot swamp the digest. Anything dropped is counted in the SUMMARY, never silently removed.

## `maxRowsInDigest` (type: `integer`):

A hard cap on the table itself. A digest with 10,000 rows is not a digest, so the default keeps it readable.

## Actor input object example

```json
{
  "sources": [],
  "title": "Weekly digest",
  "dedupeKey": "",
  "columns": [],
  "maxRowsPerSource": 50,
  "maxRowsInDigest": 200
}
```

# Actor output Schema

## `digest` (type: `string`):

One row holding the rendered markdown, plus the same document in the run's key-value store under DIGEST so another Actor or webhook can post it.

## `digestRecord` (type: `string`):

The digest as a key-value record, ready to post to Slack or email.

# 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 = {
    "title": "Weekly digest",
    "dedupeKey": "",
    "maxRowsPerSource": 50,
    "maxRowsInDigest": 200
};

// Run the Actor and wait for it to finish
const run = await client.actor("alaudinburki/dataset-digest").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 = {
    "title": "Weekly digest",
    "dedupeKey": "",
    "maxRowsPerSource": 50,
    "maxRowsInDigest": 200,
}

# Run the Actor and wait for it to finish
run = client.actor("alaudinburki/dataset-digest").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "title": "Weekly digest",
  "dedupeKey": "",
  "maxRowsPerSource": 50,
  "maxRowsInDigest": 200
}' |
apify call alaudinburki/dataset-digest --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,alaudinburki/dataset-digest"
        }
    }
}
```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/w5lbM1dIT6rMNF8UU/builds/O099Hyb7mg5cbNs7D/openapi.json