# How Step Functions parses input CSV files
<a name="example-csv-parse-dist-map"></a>

**Managing state and transforming data**  
Learn about [Passing data between states with variables](workflow-variables.md) and [Transforming data with JSONata](transforming-data.md).

Step Functions parses text delimited files based on the following rules:
+ The delimiter that separates fields is specified by `CSVDelimiter` in *ReaderConfig*. The delimiter defaults to `COMMA`.
+ Newlines are a delimiter that separates **records**.
+ Fields are treated as strings. For data type conversions, use the `States.StringToJson` intrinsic function in [ItemSelector (Map)](input-output-itemselector.md).
+ Double quotation marks (" ") are not required to enclose strings. However, strings that are enclosed by double quotation marks can contain commas and newlines without acting as record delimiters.
+ You can preserve double quotes by repeating them.
+ Backslashes (\$1) are another way to escape special characters. Backslashes only work with other backslashes, double quotation marks, and the configured field separator such as comma or pipe. A backslash followed by any other character is silently removed.
+ You can preserve backslashes by repeating them. For example: 

  ```
  path,size
  C:\\Program Files\\MyApp.exe,6534512
  ```
+ Backslashes that escape double quotation marks (`\"`), only work when included in pairs, so we recommend escaping double quotation marks by repeating them: `""`.
+ If the number of fields in a row is **less** than the number of fields in the header, Step Functions provides **empty strings** for the missing values.
+ If the number of fields in a row is **more** than the number of fields in the header, Step Functions **skips** the additional fields.

**Example of parsing an input CSV file**  
Say that you have provided a CSV file named `myCSVInput.csv` that contains one row as input. Then, you've stored this file in an Amazon S3 bucket that's named `amzn-s3-demo-bucket`. The CSV file is as follows.

```
abc,123,"This string contains commas, a double quotation marks (""), and a newline (
)",{""MyKey"":""MyValue""},"[1,2,3]"
```

The following state machine reads this CSV file and uses [ItemSelector (Map)](input-output-itemselector.md) to convert the data types of some of the fields.

```
{
  "StartAt": "Map",
  "States": {
    "Map": {
      "Type": "Map",
      "ItemProcessor": {
        "ProcessorConfig": {
          "Mode": "DISTRIBUTED",
          "ExecutionType": "STANDARD"
        },
        "StartAt": "Pass",
        "States": {
          "Pass": {
            "Type": "Pass",
            "End": true
          }
        }
      },
      "End": true,
      "Label": "Map",
      "MaxConcurrency": 1000,
      "ItemReader": {
        "Resource": "arn:aws:states:::s3:getObject",
        "ReaderConfig": {
          "InputType": "CSV",
          "CSVHeaderLocation": "GIVEN",
          "CSVHeaders": [
            "MyLetters",
            "MyNumbers",
            "MyString",
            "MyObject",
            "MyArray"
          ]
        },
        "Parameters": {
          "Bucket": "amzn-s3-demo-bucket",
          "Key": "myCSVInput.csv"
        }
      },
      "ItemSelector": {
        "MyLetters.$": "$$.Map.Item.Value.MyLetters",
        "MyNumbers.$": "States.StringToJson($$.Map.Item.Value.MyNumbers)",
        "MyString.$": "$$.Map.Item.Value.MyString",
        "MyObject.$": "States.StringToJson($$.Map.Item.Value.MyObject)",
        "MyArray.$": "States.StringToJson($$.Map.Item.Value.MyArray)"
      }
    }
  }
}
```

When you run this state machine, it produces the following output.

```
[
  {
    "MyNumbers": 123,
    "MyObject": {
      "MyKey": "MyValue"
    },
    "MyString": "This string contains commas, a double quote (\"), and a newline (\n)",
    "MyLetters": "abc",
    "MyArray": [
      1,
      2,
      3
    ]
  }
]
```