pyva 0.4.1

Simple and flexible python data validation library

Python data validation library

Table of Contents

• Introduction
• Installation
• Usage
  • Basic Usage
• Available rules
  • required
  • required_with
  • required_with_all
  • required_without
  • required_without_all
  • required_if
  • required_unless
  • present
  • email
  • url
  • ip
  • ipv4
  • ipv6
  • re (regex)
  • size
  • numeric
  • integer
  • string
  • list
  • dict
  • between
  • in
  • nullable
  • min
  • max
  • gt
  • gte
  • lt
  • lte
• Retrieving data
• Extending Validator
  • Custom Validation using callback
  • Custom Validation using RuleContract
• Examples
• Credits
• License

Introduction

piva is a simple and powerful library for data validation

from pyva import Validator

validation = Validator(
    {
        'name': 'John',
        'age': 25
    },
    {
        'name':'required',
        'age':' required|min:18'
    }
)

if validation.passes():
    # do something cool

Installation

pip install pyva

Usage

Basic Usage

from pyva import Validator

data = {
    'user': {
        'name': 'John',
        'email': '[e-mail]',
        'age': 25
    }
}

rules = {
    'user': 'required|dict',
    'user.name': 'required|min:3|max:16', # must be at least 3 chars and not more than 16 (16 included )
    'user.email': 'required',
    'user.age': 'required|min:18|max:100',
}

v = Validator(data, rules)

if v.passes():
    validated_data = v.validated()
    print(validated_data)

# or check if it fails
if v.fails():
    print(v.failed_rules)


# You can use list of rules

rules = {
        'user.age': ['required', 'min:18', 'max:100'],
}
v = Validator(data, rules)


# event more, you can make rule params as a list
rules = {
      'user.age': [
        'required',
        ['min', 18], # first item of list must be rule, rest are params
        ['max', 100] # 'max:100' this both are same
      ],
}

Available Rules

required

The field under validation must be present in the input data and not empty. A field is considered "empty" if one of the following conditions are true:

• The value is None.
• The value is an empty string.
• The value is an empty list,dict... or object that implements __len__ method and len(obj) < 1.

required_with:foo,bar,...

The field under validation must be present and not empty only if any of the other specified fields are present and not empty.

required_with_all:foo,bar,...

The field under validation must be present and not empty only if all of the other specified fields are present and not empty.

required_without:foo,bar,...

The field under validation must be present and not empty only when any of the other specified fields are empty or not present.

required_without_all:foo,bar,...

The field under validation must be present and not empty only when all of the other specified fields are empty or not present.

required_if:anotherfield,value,...

The field under validation must be present and not empty if the anotherfield field is equal to any value.

If you would like to construct more complex condition see custom rules

required_unless:anotherfield,value,...

The field under validation must be present and not empty unless the anotherfield field is equal to any value.

present

The field under validation must be present in the input data but can be empty.

email

The field under validation must be formatted as an email address

check some valid/invalid email examples

if this does not fit to your requirements check extending validator section

url

The field under validation must be a valid URL.

ip

The field under validation must be an IP address.

ipv4

The field under validation must be an IPv4 address.

ipv6

The field under validation must be an IPv6 address.

re:pattern

The field under validation must match the given regular expression.

Note

When using the re patterns, it may be necessary to specify rules in a list instead of using | delimiters, especially if the regular expression contains a | character.

size:value

The field under validation must have a size matching the given value.

• For string data, value corresponds to the number of characters.
• For numeric data, value corresponds to a given integer value
• For list,dict,tuple..., size corresponds to the len of the obj

numeric

The field under validation must be instance of numbers.Number or numeric string (strings like '5.6' considered as numeric).

integer

The field under validation must be an integer.

string

The field under validation must be a string.

list

The field under validation must be instance of list.

dict

The field under validation must be instance of dict.

between:min,max

The field under validation must have a size between the given min and max. Strings, numerics, list, dict... are evaluated in the same fashion as the size rule.

in:foo,bar,...

The field under validation must be included in the given list of values.

nullable

The field under validation may be None.

min:value

The field under validation must have a minimum value.

max:value

The field under validation must be less than or equal to a maximum value.

The field under validation must be instance of dict.

gt:other_field

The field under validation must be greater than the given field. The two fields must be of the same type.

gte:other_field

The field under validation must be greater than or equal to the given field. The two fields must be of the same type.

lt:other_field

The field under validation must be less than the given field. The two fields must be of the same type.

lte:other_field

The field under validation must be less than or equal to the given field. The two fields must be of the same type.

Retrieving data

To retrieve the validated input data call validated() method

from pyva import Validator

data = {
    'user': {
            'name': 'John',
            'age': 28
        }
}

rules = {
    'user': 'dict',
    'user.name': 'required|min:3',
    'user.age': 'required|min:18|max:100',
}

validation = Validator(data, rules)
if validation.passes():
    print(validation.validated())  # get validated data

Extending Validator

Custom Validation using callback:

from pyva import Validator

def is_odd(attribute, value, fail):
    
    if value % 2 != 1:
        fail("{} must be odd ".format(attribute))
        
data = {
    'length': 20
}

rules = {
    'length': ['required', is_odd] 
}

v = Validator(data, rules)

print(v.passes())

# or check if it fails
if v.fails():
    print(v.failed_rules) # length must be odd

What if you want more powerful validation, well then check Custom Validation using RuleContract

Custom Validation using RuleContract

For this you need to import RuleContract. Your class must implement passes() method and return True or False

from pyva import RuleContract
from pyva import Validator

# your class must implement passes() method

class EndsWith(RuleContract):

    def __init__(self, end_string):
        self.end_string = end_string

    def passes(self, attribute, value):
        return value.endswith(self.end_string)

    def message(self, attribute, value):
        return "{} must end with '{}'".format(attribute, self.end_string)


data = {
    'company_name': 'Accme company'
}

rules = {
    'company_name': [
        'required',
        'string',
        EndsWith('company')
    ]
}

v = Validator(data, rules)
print(v.passes())

Credits

• Inspired by Laravel's validation syntax

License

Licensed under the MIT license.