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Feature

Inline Data Editing

Fix typos without re-uploading the file.

Click a cell, edit it, save. Add new rows. Delete old ones. Your API reflects the change on the next request — no re-uploading, no exporting and re-importing.

What it does

Inline Data Editing turns the dataset detail page into a lightweight admin interface. Every row in your CSV is editable directly from the browser. Add new records with a form, delete rows with a click, or update existing values in place. Edits are persisted to the same dynamic table the API reads from, so the very next API request reflects your change.

How it works

  1. 1

    Open the dataset detail page

    Navigate to any of your datasets from the dashboard. Rows render in a familiar table view.

  2. 2

    Click a cell to edit it

    Cells become editable inputs in place. Hit Enter or click away to save.

  3. 3

    Add or delete rows

    Use the 'Add row' button to insert a new record, or the row menu to delete an existing one. Confirmation prompts protect against accidents.

  4. 4

    Your API stays in sync

    The next request to /api/v1/datasets/:id/records returns the updated data — no cache to bust, no redeploy.

See it in action

text
Dashboard → Dataset: customers
┌──────┬───────┬────────────┐
│ name │ age   │ city       │
├──────┼───────┼────────────┤
│ Alice│  32   │ Portland   │  ← click to edit
│ Bob  │  28   │ Portland   │
│ Carol│  41   │ Portland   │
└──────┴───────┴────────────┘
        [+ Add row]

Why it matters

  • No re-upload cycle

    Stop downloading the CSV, fixing it in Excel, and re-uploading. Edit in place and move on.

  • Safe column-by-column edits

    Edits respect the detected column type, so you can't accidentally turn a number column into a string.

  • Live API

    There's no delay between editing and the API reflecting the change. The dashboard and the API read from the same source.

The problem it solves

Re-uploading a CSV every time you fix a typo is the kind of friction that makes you stop fixing typos. Inline editing turns the dataset into something you can actually maintain instead of something you only ever bulk-load.

Common use cases

  • Fixing typos and stale values without leaving the app

  • Curating a small dataset that's edited more often than it's bulk-loaded

  • Letting a non-technical teammate maintain the data behind your API

  • Quickly seeding test data for a frontend you're building

Try Inline Data Editing for yourself

Create a free csv-api account, upload a file, and see your API live in under a minute.

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