CSV Parser
In this article
Overview
You can use this Snap to read CSV binary data from its input view, parse it, and then write it to its output view as CSV document data.
Snap Type
CSV Parser is a PARSE-type Snap that reads the binary data from the input view, parses, and writes to the output view.
Prerequisites
None.
Support for Ultra Pipelines
Works in Ultra Pipelines.
Limitations and Known Issues
None.
Snap Views
Type | Format | Number of Views | Examples of Upstream and Downstream Snaps | Description |
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Input | Binary
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| This Snap has at most two binary input views, where it gets the CSV binary data to be parsed. If there are two input views, it gets the CSV binary data to be parsed from the first input view and the CSV metadata from the second input view. The metadata should be a CSV format with two lines of CSV data: the first line is the CSV header, the second, data types. Supported data types are 'string', 'integer', 'float' and 'boolean'. If 'string' is a default data type, empty data type fields are considered to be 'string' type. An example of CSV metadata is: Last name,First name,age,commute_km,isDriving string, ,integer,float,boolean |
Output | Document |
| Document | This Snap has exactly one document output view, where it provides the CSV document data stream. |
Error | Error handling is a generic way to handle errors without losing data or failing the Snap execution. You can handle the errors that the Snap might encounter while running the Pipeline by choosing one of the following options from the When errors occur list under the Views tab are:
Learn more about Error handling in Pipelines. |
Snap Settings
Asterisk (*): Indicates a mandatory field.
Suggestion icon (): Indicates a list that is dynamically populated based on the configuration.
Expression icon (): Indicates the value is an expression (if enabled) or a static value (if disabled). Learn more about Using Expressions in SnapLogic.
Add icon (): Indicates that you can add fields in the fieldset.
Remove icon (): Indicates that you can remove fields from the fieldset.
Field Name | Field Type | Description | |
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Label* Default Value: CSV Parser | String | Specify the name for the Snap. You can modify this to be more specific, especially if you have more than one of the same Snap in your Pipeline.
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Quote character Default Value: “ | Character | Specify the character to be used for a quote. As of 4.3.2, this property can be an expression, which is evaluated with the values from the Pipeline parameters. Only a single character is allowed as a quote character. | |
Delimiter* Default value:
| String/Expression | Specify the string or the character to be used as a delimiter in formatting the delimited data. Any combination of characters may be used, adhering to the following guidelines. The input must be submitted with any control characters escaped. For example, When using a single backslash ( | |
Escape character Default value: \ | Character | Specify the escape character that is to be used when parsing rows. Only single characters are supported. As of 4.3.2, this property can be an expression, which is evaluated with the values from the pipeline parameters. Leave this property empty if no escape character is used in the input CSV data. | |
Skip lines* Default value: 0 | Integer/Expression | Specify the number of lines that are to be skipped in the input data before the Snap starts parsing it. This example explains how to skip lines. | |
Contains header Default value: Selected | Checkbox | Select the checkbox to specify if the input data contains the CSV header or not. | |
Column names | Use this fieldset to specify the column header names, which is a composite table property. | ||
Header | String | Specify the list of headers that are to be used as a CSV header in case you deselect the Contains header property.
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Validate headers Default value: Deselected | Checkbox | Select the checkbox to specify if the headers from the input data should be validated against the Column names table property or not. If this option is selected, the Snap throws an exception when they do not match exactly. | |
Header size error policy Default value: Both | Dropdown list | Select an option to define how to handle errors for records that do not match the header columns in the CSV file. This error condition occurs if the input document has fewer or additional columns that do not match with the header columns. The available options are:
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Character set Default value: Auto BOM detect. | Dropdown list | Select an option to specify the character set in which input CSV data is encoded. The available options are:
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Ignore empty data Default value: Selected | Checkbox | Select this checkbox to send the document to error view if the input is empty. If you do not select this checkbox, then it produces an empty output document when the input CSV data is empty (both an empty binary stream and a binary stream with CSV headers only). This feature may be useful if the downstream Snaps should be executed whether the input CSV data is empty or not. | |
Preserve Surrounding Spaces Default value: Deselected | Checkbox | Select this checkbox to preserve the surrounding spaces for the values that are non-quoted.
For example, if you are using data with a delimiter as follows:
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Snap Execution Default Value: Validate & Execute | Dropdown list | Select one of the three modes in which the Snap executes. Available options are:
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Examples
Skip lines from input data
The following example pipeline demonstrates how to skip lines from the input data (CSV) and parse the remaining data.
Configure the File Reader Snap to pass CSV file as input.
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Configure the CSV Parser Snap to skip two lines (value from the upstream Snap via expression enabler) while parsing the CSV data.
On validation, the CSV Parser Snap skips two lines from the input and parses the remaining data.
Using the CSV Parser Snap Schema Capability
One of the features in the CSV Parser which customers sometimes request is the ability to define the fields (and their data types) for incoming CSV files. This is made easy by adding a second input view to the CSV Parser Snap, and providing the definition of the fields, and their data types in the flow.
For example, if you have input data in the CSV file as follows, with no header line:
Then, you can create a definition of the CSV data in another CSV file as follows:
Note the data types are optional, and defined on the second line of the input file. The parser supports the use of 'string', 'integer', 'float' and 'boolean' types. String is the default data type, any empty data type fields are considered to be strings.
The configuration of the pipeline for this use is as follows:
where the Read Snaps are File Readers.
The CSV Parser is configured as follows: | Views is configured as follows: |
The resulting data in the SnapLogic pipeline data flow looks like this: |