---
title: "CSVToDocument"
id: csvtodocument
slug: "/csvtodocument"
description: "Converts CSV files to documents."
---

# CSVToDocument

Converts CSV files to documents.

<div className="key-value-table">

|  |  |
| --- | --- |
| **Most common position in a pipeline** | Before [PreProcessors](../preprocessors.mdx) , or right at the beginning of an indexing pipeline |
| **Mandatory run variables**            | `sources`: A list of file paths or [ByteStream](../../concepts/data-classes.mdx#bytestream) objects          |
| **Output variables**                   | `documents`: A list of documents                                                                |
| **API reference**                      | [Converters](/reference/converters-api)                                                                |
| **GitHub link**                        | https://github.com/deepset-ai/haystack/blob/main/haystack/components/converters/csv.py        |

</div>

## Overview

`CSVToDocument` converts one or more CSV files into a text document.

The component uses UTF-8 encoding by default, but you may specify a different encoding if needed during initialization.
You can optionally attach metadata to each document with a `meta` parameter when running the component.

## Usage

### On its own

```python
from haystack.components.converters.csv import CSVToDocument

converter = CSVToDocument()
results = converter.run(sources=["sample.csv"], meta={"date_added": datetime.now().isoformat()})
documents = results["documents"]

print(documents[0].content)
## 'col1,col2\now1,row1\nrow2row2\n'
```

### In a pipeline

```python
from haystack import Pipeline
from haystack.document_stores.in_memory import InMemoryDocumentStore
from haystack.components.converters import CSVToDocument
from haystack.components.preprocessors import DocumentCleaner
from haystack.components.preprocessors import DocumentSplitter
from haystack.components.writers import DocumentWriter

document_store = InMemoryDocumentStore()

pipeline = Pipeline()
pipeline.add_component("converter", CSVToDocument())
pipeline.add_component("cleaner", DocumentCleaner())
pipeline.add_component("splitter", DocumentSplitter(split_by="sentence", split_length=5))
pipeline.add_component("writer", DocumentWriter(document_store=document_store))
pipeline.connect("converter", "cleaner")
pipeline.connect("cleaner", "splitter")
pipeline.connect("splitter", "writer")

pipeline.run({"converter": {"sources": file_names}})
```
