CSV File Validator

CSVLint compared with online CSV validators and Frictionless
CSVLint (csvlint.io)	Online CSV validators (typical)	Frictionless
Validation scope: The service checks CSV files against RFC 4180 and the CSV on the Web (CSVW) specification. It reports errors such as inconsistent row lengths and malformed delimiters, and warnings for best-practice issues such as incorrect character encoding.	Validation scope: Typically a syntax linter. The ExtendsClass validator, one member checked, finds syntax errors, lets you set the separator (comma, tab, semicolon or pipe), the quote character and the escape character, and has an optional column count check against the first row.	Validation scope: Frictionless validates data tables, resources and datasets. Its reports flag issues such as blank or duplicate headers, missing cells, blank rows and extra cells, and custom checks and formats can be added.
Schema support: Validation can be driven by a schema in JSON Table Schema form, which enforces data types, mandatory fields and value patterns.	Schema support: The ExtendsClass page does not mention schema validation, so the check stays at the level of file structure.	Schema support: The framework is built on the Frictionless Data Specifications and describes tabular data as well as validating it.
Reporting: Findings are separated into errors for structural problems and warnings for best-practice violations.		Reporting: Validation produces a unified report, with many options to customise the process.
Openness and platform: A hosted web service described as free to use.	Openness and platform: The ExtendsClass tool is a free online toolbox that states advertising is its only resource. No privacy statement was found on the page.	Openness and platform: An open-source Python framework under the MIT licence. Version 4.17.5 dates from September 2021, and a newer 5.x release exists on PyPI.

CSVLint compared with online CSV validators and Frictionless

CSVLint (csvlint.io)

Online CSV validators (typical)

Frictionless

Validation scope: The service checks CSV files against RFC 4180 and the CSV on the Web (CSVW) specification. It reports errors such as inconsistent row lengths and malformed delimiters, and warnings for best-practice issues such as incorrect character encoding.

Validation scope: Typically a syntax linter. The ExtendsClass validator, one member checked, finds syntax errors, lets you set the separator (comma, tab, semicolon or pipe), the quote character and the escape character, and has an optional column count check against the first row.

Validation scope: Frictionless validates data tables, resources and datasets. Its reports flag issues such as blank or duplicate headers, missing cells, blank rows and extra cells, and custom checks and formats can be added.

Schema support: Validation can be driven by a schema in JSON Table Schema form, which enforces data types, mandatory fields and value patterns.

Schema support: The ExtendsClass page does not mention schema validation, so the check stays at the level of file structure.

Schema support: The framework is built on the Frictionless Data Specifications and describes tabular data as well as validating it.

Reporting: Findings are separated into errors for structural problems and warnings for best-practice violations.

Reporting: Validation produces a unified report, with many options to customise the process.

Openness and platform: A hosted web service described as free to use.

Openness and platform: The ExtendsClass tool is a free online toolbox that states advertising is its only resource. No privacy statement was found on the page.

Openness and platform: An open-source Python framework under the MIT licence. Version 4.17.5 dates from September 2021, and a newer 5.x release exists on PyPI.