# CSV Anti-Join Finder (`junipr/csv-anti-join-finder`) Actor

Find rows in one CSV that do not have matching keys in another CSV, with support for composite keys, normalization rules, duplicate diagnostics, and left-only/right-only export reports.

- **URL**: https://apify.com/junipr/csv-anti-join-finder.md
- **Developed by:** [junipr](https://apify.com/junipr) (community)
- **Categories:** Developer tools
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $3.90 / 1,000 row checkeds

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.

- **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

## CSV Anti-Join Finder

### Store Positioning

**Store title:** CSV Anti-Join Finder

**Short description:** Find rows in one CSV that do not have matching keys in another CSV, with support for composite keys, normalization rules, duplicate diagnostics, and left-only/right-only export reports.

**SEO title:** CSV Anti-Join Finder — data QA, validation, and cleanup utility

**SEO description:** Find rows in one CSV that do not have matching keys in another CSV, with support for composite keys, normalization rules, duplicate diagnostics, and left-only/right-only export reports. Use it to validate rows, schemas, duplicates, field quality, and delivery-readiness before handing data to clients or automations.

**Categories:** DEVELOPER\_TOOLS

**Keywords:** csv, anti, join, finder, csv qa, data/schema qa utility

### Pay-Per-Event Pricing

This actor uses pay-per-event pricing. Event prices include Apify platform usage; users are not expected to pay a separate platform-usage pass-through charge for the configured pricing model.

- Tier: U2 — Data/schema QA utility
- Primary event: `row-checked` at $0.00390 base
- Default max charge: $5.00
- Store discounts: FREE/BRONZE base, SILVER discounted, GOLD deepest approved discount

Event set:

- `actor-start`: base $0.00500, GOLD $0.00400. CSV Anti Join Finder: charged when actor start is completed. The price includes Apify platform usage; no separate usage pass-through is intended.
- `row-checked`: base $0.00390, GOLD $0.00312. CSV Anti Join Finder: charged when row checked is completed. The price includes Apify platform usage; no separate usage pass-through is intended.
- `issue-detected`: base $0.00372, GOLD $0.00298. CSV Anti Join Finder: charged when issue detected is completed. The price includes Apify platform usage; no separate usage pass-through is intended.
- `qa-report-generated`: base $0.05000, GOLD $0.04000. CSV Anti Join Finder: charged when qa report generated is completed. The price includes Apify platform usage; no separate usage pass-through is intended.

### Public Task Concepts

- Audit CSV Anti-Join controls on a capped public sample
- Find high-priority CSV Anti-Join issues before release
- Validate CSV Anti-Join evidence from supplied pages
- Prioritize CSV Anti-Join fixes with severity and proof
- Export CSV Anti-Join QA rows for client review

Finds left-only and right-only CSV rows by normalized single or composite keys, emitting source row indexes, key hashes, duplicate diagnostics, and reconciliation recommendations.

### Inputs

- `leftCsvUrl`
- `rightCsvUrl`
- `leftCsvText`
- `rightCsvText`
- `leftKeyColumns`
- `rightKeyColumns`
- `antiJoinMode`
- `normalizationRules`
- `includeSourceRows`
- `includeMatchedSummary`
- `maxRows`
- `sampleLimit`
- `timeoutMs`
- `maxChargeUsd`

### Public source provenance

The starter input uses https://raw.githubusercontent.com/datasets/country-list/master/data.csv compared with https://raw.githubusercontent.com/datasets/country-codes/master/data/country-codes.csv using ISO alpha-2 codes. The checked-in bounded snapshot keeps exact runs deterministic and avoids sending credentials or private data. Live URL inputs remain available when a current network check is required.

### Outputs

Dataset fields: `side`, `rowIndex`, `keyColumns`, `keyValue`, `normalizedKey`, `keyHash`, `antiJoinReason`, `matchCountOtherSide`, `duplicateCountSameSide`, `sourceRow`, `warning`, `recommendation`.

Reports: `csv-anti-join-report.md`, `left-only-rows.csv`, `right-only-rows.csv`, `anti-join-match-summary.json`, `key-normalization-log.csv`.

Use small capped runs first; live network checks should stay bounded and avoid secrets in inputs.

Live and local execution use the same pay-per-event billing guard: the actor-start event is accepted before analysis, each paid row is charged before dataset output, reports are charged before key-value-store output, and `maxChargeUsd` stops gracefully without leaking unpaid artifacts.

# Actor input Schema

## `leftCsvUrl` (type: `string`):

Public left CSV URL to fetch or inspect for CSV Anti-Join Finder.

## `rightCsvUrl` (type: `string`):

Public right CSV URL to fetch or inspect for CSV Anti-Join Finder.

## `leftCsvText` (type: `string`):

Supplied left CSV text to analyze directly.

## `rightCsvText` (type: `string`):

Supplied right CSV text to analyze directly.

## `leftKeyColumns` (type: `array`):

Left Key Columns controls CSV Anti-Join Finder processing for the supplied inputs; keep values conservative for first runs.

## `rightKeyColumns` (type: `array`):

Right Key Columns controls CSV Anti-Join Finder processing for the supplied inputs; keep values conservative for first runs.

## `antiJoinMode` (type: `string`):

Anti Join Mode controlling how CSV Anti-Join Finder processes the supplied inputs.

## `normalizationRules` (type: `object`):

Rules used by CSV Anti-Join Finder to classify findings and recommendations.

## `includeSourceRows` (type: `boolean`):

Include source rows in output rows or reports when available.

## `includeMatchedSummary` (type: `boolean`):

Include matched summary in output rows or reports when available.

## `maxRows` (type: `number`):

Maximum rows to process in one run; keep defaults low for safe first runs.

## `sampleLimit` (type: `number`):

Sample Limit controls CSV Anti-Join Finder processing for the supplied inputs; keep values conservative for first runs.

## `timeoutMs` (type: `number`):

Maximum time in milliseconds allowed for the CSV Anti-Join Finder operation before it is treated as timed out.

## `maxChargeUsd` (type: `number`):

Maximum estimated PPE charge allowed for the run before the actor stops gracefully.

## Actor input object example

```json
{
  "leftCsvUrl": "",
  "rightCsvUrl": "",
  "leftCsvText": "Name,Code\nAfghanistan,AF\nAlbania,AL\nAlgeria,DZ\nAmerican Samoa,AS\nAndorra,AD\n",
  "rightCsvText": "official_name_en,ISO3166-1-Alpha-2\nAfghanistan,AF\nAlbania,AL\nAlgeria,DZ\nÅland Islands,AX\n",
  "leftKeyColumns": [
    "Code"
  ],
  "rightKeyColumns": [
    "ISO3166-1-Alpha-2"
  ],
  "antiJoinMode": "both",
  "normalizationRules": {
    "trim": true,
    "case": "lower",
    "numeric": true
  },
  "includeSourceRows": true,
  "includeMatchedSummary": true,
  "maxRows": 10,
  "sampleLimit": 10,
  "timeoutMs": 5000,
  "maxChargeUsd": 1
}
```

# 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("junipr/csv-anti-join-finder").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("junipr/csv-anti-join-finder").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 '{}' |
apify call junipr/csv-anti-join-finder --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,junipr/csv-anti-join-finder"
        }
    }
}

```

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/5EwR4FUxniukjg4Q4/builds/92RZh820Njev6oPDi/openapi.json