# CSV Column Type Validator
Validate CSV columns against declared types like int, float, bool, date, and enum, with row/line reports for every offending cell.
## Run it
- **CLI:** `gizza tool csv-column-type-validator "name,age,score,active,joined,plan
Ada,34,9.5,true,2021-06-01,pro
Bo,twelve,8,yes,2021/06/02,gold" 'types=age:int, score:float, active:bool, joined:date, plan:enum(free|pro)'`
- **Web:** https://gizza.ai/tools/csv-column-type-validator/
- **Agents:** machine-readable descriptor (parameters JSON Schema) at https://gizza.ai/tools/csv-column-type-validator/tool.json
## Inputs
- `data` — CSV data _(field)_
- `types` — Column types _(field)_
- `header` — First row is a header _(field)_
- `delimiter` — Delimiter _(field)_
- `date_format` — Date format _(field)_
- `empty_ok` — Allow blank cells _(field)_
- `max_issues` — Max issues to list _(field)_
- `format` — Output format _(field)_
## Output
- Validation report (text)
## Query parameters
Open the tool pre-filled and auto-run via URL:
- `data` — CSV data
- `types` — Column types
- `header` — First row is a header
- `delimiter` — Delimiter
- `date_format` — Date format
- `empty_ok` — Allow blank cells
- `max_issues` — Max issues to list
- `format` — Output format
Example: `https://gizza.ai/tools/csv-column-type-validator/?data=name%2Cage%2Cscore%2Cactive%2Cjoined%2Cplan%0AAda%2C34%2C9.5%2Ctrue%2C2021-06-01%2Cpro%0ABo%2Ctwelve%2C8%2Cyes%2C2021%2F06%2F02%2Cgold&types=age%3Aint%2C%20score%3Afloat%2C%20active%3Abool%2C%20joined%3Adate%2C%20plan%3Aenum%28free%7Cpro%29&header=true&delimiter=auto&date_format=iso&empty_ok=true&max_issues=50&format=text`
---
## About this tool
**CSV Column Type Validator** checks selected CSV columns against a small declared schema and reports every cell that does not match. It is useful before importing spreadsheets, partner exports, or analytics feeds into a stricter system.
Declare types with a comma- or newline-separated list such as:
```text
age:int, score:float, active:bool, joined:date, plan:enum(free|pro)
```
Then paste CSV data. With a header row enabled, declarations use header names. With **First row is a header** disabled, declarations use 1-based column indexes such as `2:int, 3:enum(free|pro)`.
### Worked example
Input data:
```csv
name,age,score,active,joined,plan
Ada,34,9.5,true,2021-06-01,pro
Bo,twelve,8,yes,2021/06/02,gold
```
Types:
```text
age:int, score:float, active:bool, joined:date, plan:enum(free|pro)
```
The report marks the CSV invalid and lists three offending cells: row 2 `age` is not an integer, row 2 `joined` is not an ISO date, and row 2 `plan` is outside the allowed enum values.
### Supported checks
- **int** — signed whole numbers like `42` or `-7`.
- **float** — decimal or scientific notation like `3.14`, `.5`, `2.`, or `1e6`.
- **bool** — `true/false`, `1/0`, `yes/no`, `t/f`, `y/n` (case-insensitive).
- **date** — controlled by Date format: ISO `YYYY-MM-DD`, US `MM/DD/YYYY`, EU `DD/MM/YYYY`, or any of those.
- **enum(a|b|c)** — exact allowed values; enum matching is case-sensitive after trimming whitespace.
### Limits and edge cases
The parser handles quoted fields, doubled quotes, delimiters inside quotes, quoted newlines, and blank physical lines. It auto-detects comma, tab, semicolon, and pipe delimiters from the first non-blank line. It does not perform regex validation, min/max numeric ranges, email/phone/postal checks, type coercion, or automatic fixing; it is a report-only type checker.
CLI example:
```bash
gizza tool csv-column-type-validator data="name,age
Ada,34
Bo,x" types="age:int" header=true delimiter=comma date_format=iso empty_ok=true max_issues=50 format=text
```
## FAQ
How do I validate a CSV without headers?
Turn off **First row is a header**, then refer to columns by 1-based index in the type declaration. For example, `2:int, 3:enum(free|pro)` validates the second column as an integer and the third column against the two enum values.
What happens when I declare a column that is not in the CSV?
The result is invalid even if no cell-level type errors are found. Unknown declared columns usually mean a misspelled header, a delimiter mismatch, or a headerless file being checked with header mode still enabled.
Are empty cells valid?
By default, yes: blank checked cells are allowed. Disable **Allow blank cells** to make every checked cell required; blank values will then be reported as `empty cell (required)`.
Can this validate emails, phone numbers, regexes, or numeric ranges?
No. This tool focuses on coarse column types: integer, float, boolean, date, and enum. Use dedicated validators for business-specific formats, or pre-clean the CSV before running this type check.
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