Free Online CSV Validator

import pandas as pd

def validate_csv_structure(file_path: str, delimiter: str = ",") -> dict:
    """
    Validate a CSV file before data processing using pandas,
    catching standard parsing exceptions and checking column integrity.
    """
    report = {"valid": False, "errors": [], "warnings": [], "shape": None}

    try:
        # 1. Attempt standard read. Raises ParserError on corrupt quotes or ragged lines.
        df = pd.read_csv(
            file_path,
            sep=delimiter,
            engine="c",  # fast C engine enforces strict column counts
        )
        report["shape"] = df.shape

        # 2. Check for empty DataFrame
        if df.empty:
            report["warnings"].append("File parsed successfully but contains no data rows.")

        # 3. Check for duplicate column headers
        duplicates = df.columns[df.columns.duplicated()].tolist()
        if duplicates:
            report["warnings"].append(f"Duplicate column headers found: {duplicates}")

        # 4. Check for unnamed / empty column headers
        unnamed = [col for col in df.columns if str(col).startswith("Unnamed:")]
        if unnamed:
            report["warnings"].append(f"Empty or missing column headers: {unnamed}")

        report["valid"] = len(report["errors"]) == 0
        return report

    except pd.errors.EmptyDataError:
        report["errors"].append("EmptyDataError: File contains 0 bytes or only blank lines.")
        return report
    except pd.errors.ParserError as e:
        report["errors"].append(f"ParserError: {e}")
        return report
    except UnicodeDecodeError as e:
        report["errors"].append(f"UnicodeDecodeError: File encoding mismatch ({e}). Try encoding='utf-8-sig'.")
        return report
    except Exception as e:
        report["errors"].append(f"Unexpected error: {type(e).__name__}: {e}")
        return report

# Example usage:
# result = validate_csv_structure("customers.csv")
# print(result)