coltypes

Coltypes (also written coltypes or col_types) is a concept used in data processing to specify the data types of columns in a tabular dataset or database table. It provides a schema that governs how values in each column are interpreted, stored, and validated.

In practice, coltypes are supplied as either a mapping from column names to types or as a positional list that corresponds to the column order. Some systems allow nullability flags, indicating whether a column can contain missing values. Example: coltypes = {'id': 'integer', 'name': 'string', 'birth_date': 'date', 'active': 'boolean'} or coltypes = ['INTEGER', 'VARCHAR(100)', 'DATE', 'BOOLEAN'].

Common type categories include integers, floats, strings, booleans, dates and times, decimals, and categorical types. Some implementations support specialized types such as timestamps with time zones, arrays, or user-defined enums. Type names may be library-specific or aligned to standard SQL types.

Coltypes are often used at data ingestion to enforce a schema, or during ETL pipelines to coerce values into the declared types. If a value cannot be converted, processors may raise an error, skip the row, or emit a warning. Some systems also infer coltypes from data when not provided, which can be faster but less reliable.

Design considerations include performance of type coercion, compatibility across languages, handling of missing values, and evolution of schemas. Clear coltype definitions help data validation, reproducibility, and interoperability between tools and storage systems.

See also: schema, data type, type inference, ETL.