# CSV Cleaner (`urban_souffle/mf-201-csv-cleaner`) Actor

Parse CSV text safely, normalize cells, and return structured JSON rows for APIs, automation, ETL pipelines, and data processing workflows.

- **URL**: https://apify.com/urban\_souffle/mf-201-csv-cleaner.md
- **Developed by:** [Luca Gallifuoco](https://apify.com/urban_souffle) (community)
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $0.40 / 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?

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 Cleaner

Parse CSV text safely, normalize cells, and return structured JSON rows without external network access.

### What this Actor does

- Parse quoted CSV cells including embedded delimiters
- Auto-detect comma, semicolon, or tab delimiters
- Trim cells and skip empty rows

### Input

`csvText` contains CSV with a header row. Choose delimiter detection and cleaning options.

#### Example input

```json
{
  "csvText": "name,city\n Alice , Naples \nBob,Rome",
  "delimiter": "auto",
  "trimStrings": true,
  "skipEmptyRows": true
}
```

### Output

One dataset item per parsed row with `rowNumber` and `data`.

Results are written to the default Apify dataset and can be consumed from the Console, API, Make, Zapier, or other automation workflows.

### Common use cases

- Convert CSV exports to JSON
- Prepare spreadsheet exports for APIs
- Clean CSV data before automation

### Pricing

This Actor is designed for transparent pay-per-event pricing. Check the current Apify Store pricing before running it.

### Limitations

- First non-empty row is treated as the header
- No automatic number/date type inference
- Input is provided as text, not fetched from a URL

### Privacy and safety

- Input data is processed deterministically.
- No credentials are embedded in the Actor source.
- This utility does not require external website access.
- Review sensitive or regulated data handling requirements before processing such data.

# Actor input Schema

## `csvText` (type: `string`):

CSV content including a header row.

## `delimiter` (type: `string`):

Delimiter

## `trimStrings` (type: `boolean`):

Trim cells

## `skipEmptyRows` (type: `boolean`):

Skip empty rows

## Actor input object example

```json
{
  "csvText": "name,city\n Alice , Naples \nBob,Rome",
  "delimiter": "auto",
  "trimStrings": true,
  "skipEmptyRows": true
}
```

# Actor output Schema

## `results` (type: `string`):

Items written to the default dataset.

# 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 = {
    "csvText": `name,city
 Alice , Naples 
Bob,Rome`
};

// Run the Actor and wait for it to finish
const run = await client.actor("urban_souffle/mf-201-csv-cleaner").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 = { "csvText": """name,city
 Alice , Naples 
Bob,Rome""" }

# Run the Actor and wait for it to finish
run = client.actor("urban_souffle/mf-201-csv-cleaner").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 '{
  "csvText": "name,city\\n Alice , Naples \\nBob,Rome"
}' |
apify call urban_souffle/mf-201-csv-cleaner --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,urban_souffle/mf-201-csv-cleaner"
        }
    }
}
```

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/8V2u99n2c3fZ2JluM/builds/L1mbcxTgjG3mmEitk/openapi.json