TSV Validator

The TSV Validator analyzes tab-delimited data to verify structural integrity and row-level validity without transforming the data.
It accepts a raw TSV string or streaming input and confirms that header presence (when supplied) matches the schema, that each row contains the expected number of fields, and that optional type and range checks pass. It detects malformed lines, missing values in required columns, and improper quoting that can cause split or merge errors during downstream processing. The tool is designed for datasets used in data ingestion pipelines, analytics, and reporting workflows.
When a schema is supplied, the tool validates each column type (string, integer, float, date), enforces required fields, allowed value sets, and basic format rules. If no schema is provided, structural checks (column count and header presence) remain active. It reports per-row issues with precise column indexes and sample values, and it can detect duplicate rows or inconsistent delimiters within a file. Advanced users can enable streaming validation to handle multi-GB TSV files without loading the entire dataset into memory.
Core value lies in enabling reliable data intake: teams can quantify data quality, locate problematic rows quickly, and generate exportable summaries for audits. Unique differentiators include schema-driven validation, robust delimiter handling with tab defaults and explicit delimiter support, and streaming support for large TSV files.