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csv-test Build Status

A command line application for validating CSV files. Use it for verifying that data files meet defined criteria, like "age is a number and greater than 10" or "email is a valid email address".

It works by looping through each field of each row and testing the data value against a set of rules. It provides a log of any validation errors it finds.

It uses node.js streams so it can work on large files with little memory consumption, tested with a 3,400,256 row CSV file using an average 53mb of memory completing in 1m49.886s.

install

At the command line / terminal, run the following:

npm install -g csv-test

run

Run the csv-test command by passing it a configuration file and a CSV file:

csv-test path/to/config.yml path/to/data.csv

You will see output about your tests that looks like this:

✗ [row 2, field email] `isEmail` failed.
2 rows tested
1 error found

configuration

csv-test runs by testing your CSV against a configuration file. The configuration file support yaml, which is a human-readable data format. Here is an example configuration file:

fields:
  name:
    - isLength:
      - 1
      - 10
  age:
    - isInt:
        max: 90
        min: 10
  email: isEmail

Start your configuration file with a fields key to define the validation settings for each field. Then specify a key for each field you'd like to validate. Fields that do not have rules specified will be skipped.

Field validation settings can take a number of forms. For fields with only one rule, they can be strings, such as age: isInt.

For fields with multiple rules or rules that take named options, use the array form:

age:
  - isNumeric
  - isInt:
      max: 90
      min: 10

Some rules take options as an array, such as isLength. Those rules should list options as an array:

name:
  - isLength:
    - 1
    - 10

Rules that only take one option can be written as follows:

state:
  contains: NJ

The configuration file also supports a settings key at the top level, which will configure how the CSV file should be parsed. For instance, delimiter: ";" tells the parser to parse on semicolons instead of commas. See the node-csv-parse documentation for all available parse options.

validation options

csv-test uses the validator.js library for validating data. Available validation rules include the following:

Validators

  • contains(str, seed) - check if the string contains the seed.
  • equals(str, comparison) - check if the string matches the comparison.
  • isAfter(str [, date]) - check if the string is a date that's after the specified date (defaults to now).
  • isAlpha(str) - check if the string contains only letters (a-zA-Z).
  • isAlphanumeric(str) - check if the string contains only letters and numbers.
  • isAscii(str) - check if the string contains ASCII chars only.
  • isBase64(str) - check if a string is base64 encoded.
  • isBefore(str [, date]) - check if the string is a date that's before the specified date.
  • isBoolean(str) - check if a string is a boolean.
  • isByteLength(str, min [, max]) - check if the string's length (in bytes) falls in a range.
  • isCreditCard(str) - check if the string is a credit card.
  • isCurrency(str, options) - check if the string is a valid currency amount. options is an object which defaults to {symbol: '$', require_symbol: false, allow_space_after_symbol: false, symbol_after_digits: false, allow_negatives: true, parens_for_negatives: false, negative_sign_before_digits: false, negative_sign_after_digits: false, allow_negative_sign_placeholder: false, thousands_separator: ',', decimal_separator: '.', allow_space_after_digits: false }.
  • isDate(str) - check if the string is a date.
  • isDecimal(str) - check if the string represents a decimal number, such as 0.1, .3, 1.1, 1.00003, 4.0, etc.
  • isDivisibleBy(str, number) - check if the string is a number that's divisible by another.
  • isEmail(str [, options]) - check if the string is an email. options is an object which defaults to { allow_display_name: false, allow_utf8_local_part: true, require_tld: true }. If allow_display_name is set to true, the validator will also match Display Name <email-address>. If allow_utf8_local_part is set to false, the validator will not allow any non-English UTF8 character in email address' local part. If require_tld is set to false, e-mail addresses without having TLD in their domain will also be matched.
  • isFQDN(str [, options]) - check if the string is a fully qualified domain name (e.g. domain.com). options is an object which defaults to { require_tld: true, allow_underscores: false, allow_trailing_dot: false }.
  • isFloat(str [, options]) - check if the string is a float. options is an object which can contain the keys min and/or max to validate the float is within boundaries (e.g. { min: 7.22, max: 9.55 }).
  • isFullWidth(str) - check if the string contains any full-width chars.
  • isHalfWidth(str) - check if the string contains any half-width chars.
  • isHexColor(str) - check if the string is a hexadecimal color.
  • isHexadecimal(str) - check if the string is a hexadecimal number.
  • isIP(str [, version]) - check if the string is an IP (version 4 or 6).
  • isISBN(str [, version]) - check if the string is an ISBN (version 10 or 13).
  • isISIN(str) - check if the string is an ISIN (stock/security identifier).
  • isISO8601(str) - check if the string is a valid ISO 8601 date.
  • isIn(str, values) - check if the string is in a array of allowed values.
  • isInt(str [, options]) - check if the string is an integer. options is an object which can contain the keys min and/or max to check the integer is within boundaries (e.g. { min: 10, max: 99 }).
  • isJSON(str) - check if the string is valid JSON (note: uses JSON.parse).
  • isLength(str, min [, max]) - check if the string's length falls in a range. Note: this function takes into account surrogate pairs.
  • isLowercase(str) - check if the string is lowercase.
  • isMobilePhone(str, locale) - check if the string is a mobile phone number, (locale is one of ['zh-CN', 'en-ZA', 'en-AU', 'en-HK', 'pt-PT', 'fr-FR', 'el-GR', 'en-GB', 'en-US', 'en-ZM', 'ru-RU']).
  • isMongoId(str) - check if the string is a valid hex-encoded representation of a MongoDB ObjectId.
  • isMultibyte(str) - check if the string contains one or more multibyte chars.
  • isNull(str) - check if the string is null.
  • isNumeric(str) - check if the string contains only numbers.
  • isSurrogatePair(str) - check if the string contains any surrogate pairs chars.
  • isURL(str [, options]) - check if the string is an URL. options is an object which defaults to { protocols: ['http','https','ftp'], require_tld: true, require_protocol: false, require_valid_protocol: true, allow_underscores: false, host_whitelist: false, host_blacklist: false, allow_trailing_dot: false, allow_protocol_relative_urls: false }.
  • isUUID(str [, version]) - check if the string is a UUID (version 3, 4 or 5).
  • isUppercase(str) - check if the string is uppercase.
  • isVariableWidth(str) - check if the string contains a mixture of full and half-width chars.
  • matches(str, pattern [, modifiers]) - check if string matches the pattern. For example: matches('foo', 'foo', 'i').

source: validator.js documentation

custom validators

You can test against custom validators by defining your own validation functions in a file passed as a third argument: csv-test path/to/config.yml path/to/data.csv path/to/customValidators.js

Your custom validators file should export an object with keys as validator names and values as functions. The functions take the string of the test value as the first argument and any subsequent options specified in the configuration file as additional arguments. They also have the field name, field value, and row for the test set to the context object. Access them in the validation function with this.field, this.value, and this.row.

An example file of custom validators might look like this:

module.exports = {
  startsWith: function(str, seed) {
    return str.indexOf(seed) === 0;
  },
  sumFields: function(str) {
    var cols = Array.prototype.slice.call(arguments);
    cols.shift();
    var sum = cols.reduce(function(memo, col) {
      return memo + +this.row[col];
    }, 0);
    return sum === +str;
  }
};

And these rules would be used in a configuration file like this:

fields:
  id:
    - startsWith: n
    - isLength: 1
  cost: isInt
  fees: isInt
  sum:
    - sumFields:
        - cost
        - fees

public domain

This project is in the worldwide public domain.

This project is in the public domain within the United States, and copyright and related rights in the work worldwide are waived through the CC0 1.0 Universal public domain dedication.

All contributions to this project will be released under the CC0 dedication. By submitting a pull request, you are agreeing to comply with this waiver of copyright interest.