CSV Schema Validator Online
Validate a CSV file against a JSON Table Schema in your browser — check column types, required fields, and regex patterns without uploading your data.
100% client-side · no upload · no tracking
100% in your browser. Your file never leaves your device.
Frictionless Data JSON Table Schema — types: string, number, integer, boolean, date
Paste your CSV above, add a schema below, then click Validate.
How to use
- Paste your CSV text (or drag-drop a .csv file) into the input area. The first row must be headers.
- Enter a JSON Table Schema in the schema box — list each column with its type and whether it's required.
- Click Validate. Each error shows the row number, column name, and what was wrong. A passing CSV shows "✓ Valid".
Related data tools
Common use cases
Frequently Asked Questions
- Does my CSV data leave my device?
- No. All validation runs entirely in your browser using JavaScript. Your CSV file and schema are never uploaded to any server.
- What schema format does this tool accept?
- The tool accepts JSON Table Schema (Frictionless Data spec). Define column names, types (string, number, integer, boolean, date), and mark required fields. A minimal schema looks like: {"fields":[{"name":"id","type":"integer"},{"name":"email","type":"string"}]}.
- Is there a file size limit?
- There is no hard server-side limit because processing is client-side. In practice, files up to ~50 MB validate comfortably in modern browsers. Very large files (>100 MB) may be slow depending on device RAM.
- Which column types are supported?
- Supported types are: string, number, integer, boolean, and date (YYYY-MM-DD). The "required" flag checks that the field is present and non-empty in every row.
- Can I validate per-column values with a regex pattern?
- Yes. Add a "pattern" property to any field definition, e.g. {"name":"postal","type":"string","pattern":"^\\d{5}$"}. Rows where that column does not match the pattern are reported as errors.
Last updated: By jarvisbox