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Converts data between structured formats (JSON, CSV, YAML, TOML, XML) with schema mapping and validation
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| name | data-transformer |
| description | Converts data between structured formats (JSON, CSV, YAML, TOML, XML) with schema mapping and validation |
| version | 1.0.0 |
| author | go-on-team |
| tags | ["data","conversion","json","csv","yaml","toml","xml","etl"] |
| min_go_on_version | 1.0.0 |
Converts structured data between common serialization formats (JSON, CSV, YAML, TOML, XML) with optional field mapping, type coercion, filtering, sorting, and validation. Supports nested flattening, array expansion, and custom delimiter configuration.
| Parameter | Type | Description |
|---|---|---|
input | string | Source data as a string |
input_format | string | Input format: json, csv, yaml, toml, xml |
output_format | string | Output format: json, csv, yaml, toml, xml |
field_mapping | object | Optional: map of {source_field: target_field} renames |
filter | string | Optional: filter expression (e.g. age > 18) |
pretty | boolean | Optional: pretty-print output (default: true) |
{
"input": "name,age,email\nAlice,30,alice@example.com\nBob,25,bob@example.com\nCharlie,35,charlie@example.com",
"input_format": "csv",
"output_format": "json",
"pretty": true
}
Example output:
[
{ "name": "Alice", "age": 30, "email": "alice@example.com" },
{ "name": "Bob", "age": 25, "email": "bob@example.com" },
{ "name": "Charlie", "age": 35, "email": "charlie@example.com" }
]
Input (JSON with nested address object) → output (flat CSV with address.street, address.city columns):
{
"input": "[{\"name\":\"Alice\",\"address\":{\"street\":\"123 Main\",\"city\":\"Springfield\"}}]",
"input_format": "json",
"output_format": "csv",
"field_mapping": { "address.street": "street", "address.city": "city" }
}