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A simple library for validating data contained in CSV files or similar row-oriented data sources.

Project description

This module provides some simple utilities for validating data contained in CSV files, or other similar data sources.

The source code for this module lives at:

Please report any bugs or feature requests via the issue tracker there.


This module is registered with the Python package index, so you can do:

$ easy_install csvvalidator

… or download from and install in the usual way:

$ python install

If you want the bleeding edge, clone the source code repository:

$ git clone git://
$ cd csvvalidator
$ python install


The CSVValidator class is the foundation for all validator objects that are capable of validating CSV data.

You can use the CSVValidator class to dynamically construct a validator, e.g.:

import sys
import csv
from csvvalidator import *

field_names = (

validator = CSVValidator(field_names)

# basic header and record length checks
validator.add_header_check('EX1', 'bad header')
validator.add_record_length_check('EX2', 'unexpected record length')

# some simple value checks
validator.add_value_check('study_id', int,
                          'EX3', 'study id must be an integer')
validator.add_value_check('patient_id', int,
                          'EX4', 'patient id must be an integer')
validator.add_value_check('gender', enumeration('M', 'F'),
                          'EX5', 'invalid gender')
validator.add_value_check('age_years', number_range_inclusive(0, 120, int),
                          'EX6', 'invalid age in years')
validator.add_value_check('date_inclusion', datetime_string('%Y-%m-%d'),
                          'EX7', 'invalid date')

# a more complicated record check
def check_age_variables(r):
    age_years = int(r['age_years'])
    age_months = int(r['age_months'])
    valid = (age_months >= age_years * 12 and
             age_months % age_years < 12)
    if not valid:
        raise RecordError('EX8', 'invalid age variables')

# validate the data and write problems to stdout
data = csv.reader('/path/to/data.csv', delimiter='\t')
problems = validator.validate(data)
write_problems(problems, sys.stdout)

For more complex use cases you can also sub-class CSVValidator to define re-usable validator classes for specific data sources.

For a complete account of all of the functionality available from this module, see the and modules in the source code repository.


Note that the csvvalidator module is intended to be used in combination with the standard Python csv module. The csvvalidator module will not validate the syntax of a CSV file. Rather, the csvvalidator module can be used to validate any source of row-oriented data, such as is provided by a csv.reader object.

I.e., if you want to validate data from a CSV file, you have to first construct a CSV reader using the standard Python csv module, specifying the appropriate dialect, and then pass the CSV reader as the source of data to either the CSVValidator.validate or the CSVValidator.ivalidate method.

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