Quick CSV Viewer

Quick CSV Viewer is a VS Code extension that opens .csv files in a readonly, tabular custom editor designed to stay responsive with large comma-delimited files.

You can also use it in IDEs that are based on VS Code (such as Cursor).

To install it, simply search its name "Quick CSV Viewer" in the "Extensions" side panel of VS Code (or Cursor, etc.).

It is hosted both on VS Code marketplace and Open VSX:

• Visual Studio Marketplace: https://marketplace.visualstudio.com/items?itemName=jsh9.quick-csv-viewer
• Open VSX: https://open-vsx.org/extension/jsh9/quick-csv-viewer

• Very fast file loading: render the top X rows instead of the whole file.
• Readonly viewing: prevent accidental changes to precious data files.
• Intuitive UI: toggle cell wrapping, adjust column widths, and inspect CSV files in a clean table view.

Open any .csv file in VS Code and Quick CSV Viewer opens it with the custom viewer by default.

Git staged and unstaged CSV diffs stay in VS Code's native diff editor.

You can also run Quick CSV Viewer: Open in Quick CSV Viewer from the command palette, the editor title menu, or the Explorer context menu for a .csv file.

Use Ctrl+F on Windows/Linux or Cmd+F on macOS to search text in the rendered viewer contents. In indexed virtual views, Find searches the rows currently rendered by the viewport plus the viewer's small overscan buffer; scroll to search another range.

• quickCsvViewer.maxRows: number of data rows to show. Default is 20.
• quickCsvViewer.maxRows: 0: index the full file and render visible rows on demand.
• The info bar Show [input] rows control updates quickCsvViewer.maxRows globally when you press Enter or leave the field.
• quickCsvViewer.firstRowIsHeader: treat the first CSV record as headers. Default is true.
• The info bar Header row control updates quickCsvViewer.firstRowIsHeader globally.
• quickCsvViewer.wrapCellContents: wrap table cell contents. Default is true.
• The info bar Wrap cells control updates quickCsvViewer.wrapCellContents globally.

When quickCsvViewer.firstRowIsHeader is enabled, Quick CSV Viewer renders the first CSV record as the frozen table header and shows it with row index 0. Data rows start at row index 1.

When quickCsvViewer.firstRowIsHeader is disabled, Quick CSV Viewer does not freeze a top header row. The first CSV record is rendered as row index 1.

The row-index column is always frozen on the left side of the table.

Columns size themselves from the CSV rows already loaded into the viewer. In indexed mode, that means the visible row range plus the header fields. Drag a column boundary in the header, or in the generated width-control row when header mode is off, to resize a column until the viewer is closed or reloaded.

When quickCsvViewer.maxRows is 0 or a large positive preview count, Quick CSV Viewer does not send the whole file to the webview. It builds a byte-offset record index with progress, then the webview requests only the visible row range while scrolling. This keeps DOM size bounded for very large files.

View raw opens the file in VS Code's default text editor. The extension's top info bar is not available there, but you can return to the viewer with Open in Quick CSV Viewer from the editor title, Explorer context menu, or command palette.

npm install
npm test
npm run format

npm install installs Husky hooks automatically. The pre-commit hook runs npm test. Prettier formats the project with an 80-column print width, and npm test checks formatting before compiling and running the test suite.

Use VS Code's extension host launch flow to test the viewer manually with the small and large files in sample-data/.

The Run Extension launch configuration opens generated files from sample-data/ through the internal quickCsvViewer.openSampleFiles command. These .csv files are local-only test fixtures and are ignored by Git. Generate two small fixtures and three 500 MB+ fixtures with:

python3 sample-data/generate_large_csv.py

For a faster smoke test, lower the target size of each large file:

QUICK_CSV_BIG_SIZE_MB=5 python3 sample-data/generate_large_csv.py