CSVParse
CSV Processor – Parse
Summary (SEO Meta Description):
The CSV Processor’s Parse action in WeHub converts CSV text into structured workflow objects.
Configure delimiter, schema, and truncation for reliable data ingestion.
Overview
The Parse action reads CSV-formatted text and transforms it into structured objects (arrays of records).
This enables workflows to process data from spreadsheets, reports, or system exports.
With schema validation and optional truncation, parsed CSV data can be normalized before further processing.
⚙️ Configuration Options
| Field | Type | Description |
|---|---|---|
| Label | String | Custom name for the node (e.g., "Parse Payroll CSV"). |
| Delimiter | String | Character used to separate values (e.g., ,, ;, \t). |
| Truncate Field | Boolean | Toggle to shorten large values in parsed records. |
| Schema | Schema | Optional schema to validate the parsed CSV structure. |
💡 Example Use Cases
- Healthcare → Parse CSV exports of patient appointments into structured workflow data.
- Finance → Process bank transaction CSV files into normalized JSON for reporting.
- Ops → Import roster or HR data from system-generated CSV extracts.
FAQ
Q: Does it support headers?
A: Yes, column names from the first row can be mapped automatically if schema is applied.
Q: What happens if a row has missing values?
A: Missing values are parsed as empty strings unless schema rules handle them.
Q: Can I parse very large CSV files?
A: Yes, but consider chunking large files or enabling truncation for oversized fields.
Keywords: WeHub CSV Processor, Parse CSV, CSV ingestion, delimiter, structured data