CSV Schema 验证器

How to use

1. Paste your CSV text (or drag-drop a .csv file) into the input area. The first row must be headers.
2. Enter a JSON Table Schema in the schema box — list each column with its type and whether it's required.
3. Click Validate. Each error shows the row number, column name, and what was wrong. A passing CSV shows "✓ Valid".

Related data tools

• JSON Schema Validator
• CSV Merger
• CSV Splitter
• JSON ↔ CSV Converter
• YAML Validator

Common use cases

• Validate CSV before API import
• Check column data types

常见问题

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.