01. Convert CSV to JSON

Read a semicolon-delimited sales file, preserve column names and produce JSON for the next integration.

Task and prerequisites

Read a semicolon-delimited sales file, preserve column names and produce JSON for the next integration.

This example uses demonstration data and settings. Validate the expected result in your own environment before connecting production destinations. Identifiers demo_* are illustrative: select your own training connections or sources in the editor. The JSON below shows the block and connection structure, not a ready-to-transfer flow archive.

Training input data

sales.csv

Order;Product;Qty
O-001;Tea;2
O-002;Coffee;3

Blocks, connections and exact settings

01. Convert CSV to JSON. Example 01 topology: 2 blocks, 1 connection. Node identifiers and ports from the configured graph are preserved. — **Flow diagram 01**
Example 01 topology: 2 blocks, 1 connection. Node identifiers and ports from the configured graph are preserved.

Add the listed blocks in the designer, open each block's properties and set these values. Names demo_* identify training sources and connections.

Block	Setting
1 File `src`	Role: `source` Source: `demo_sales` Read settings: Sheet: `CSV` Range: `A1:C3` First row is the header: `так` Delimiter: `;`
2 Data export `out`	Format: `json` File name: `sales_json` Purpose: `download` Delimiter: `;` Time zone: `Europe/Kyiv`

Port connections

src out → out in

Complete graph configuration as JSON

{
  "version": 3,
  "nodes": [
    {
      "id": "src",
      "type": "file",
      "label": "src",
      "config": {
        "role": "source",
        "source_id": "demo_sales",
        "options": {
          "sheet": "CSV",
          "range": "A1:C3",
          "header": true,
          "delimiter": ";"
        }
      }
    },
    {
      "id": "out",
      "type": "export",
      "label": "out",
      "config": {
        "format": "json",
        "filename": "sales_json",
        "destination": "download",
        "delimiter": ";",
        "timezone": "Europe/Kyiv"
      }
    }
  ],
  "edges": [
    {
      "source": "src",
      "target": "out",
      "source_port": "out",
      "target_port": "in"
    }
  ]
}

Expected result

Order	Product	Qty
O-001	Tea	2
O-002	Coffee	3

File sales_json.json contains two records. CSV does not specify data types: add an explicit conversion to guarantee a numeric Qty type.

Run and verify

Upload sales.csv in “Sources” and select it in the src block.
Check that range A1:C3 includes the header and two rows. Save the flow.
Run the flow, open the export result and compare the two Order/Product pairs and Qty values.

Common errors

If all data lands in one column, the wrong delimiter is selected.
If you see a technical column name instead of Order, enable header.
Do not specify A1:C2: the second record would fall outside the range.