LIVR.Validator - Lightweight validator supporting Language Independent Validation Rules Specification (LIVR)
Python 2 and 3 compatible
Common usage:
from LIVR import Validator
Validator.Validator.set_default_auto_trim(True)
validator = Validator.Validator({
'name': 'required',
'email': [ 'required', 'email' ],
'gender': { 'one_of' : ['male', 'female'] },
'phone': { 'max_length' : 10 },
'password': [ 'required', {'min_length' : 10} ],
'password2': { 'equal_to_field' : 'password' }
})
valid_data = validator.validate(user_data)
if valid_data:
save_user_data(valid_data)
else:
some_error_handler(validator.get_errors())
You can use filters separately or can combine them with validation:
validator = Validator.Validator({
'email': [ 'required', 'trim', 'email', 'to_lc' ]
})
Feel free to register your own rules:
validator = Validator.Validator({
'password': ['required', 'strong_password']
})
class StrongPassword(object):
def __init__(self, *args):
pass
def __call__(self, value, unuse, *args):
value == None or value == '':
return
if len(value) < 6:
return 'WEAK_PASSWORD'
validator.register_rules({ 'strong_password': StrongPassword})
Also you can use aliases for some case, but you must ensure that in aliase dict present required kyes 'rules' and 'name':
validator = Validator.Validator({
'password': ['required', 'strong_password']
})
validator.register_aliased_rule({
'name': 'strong_password',
'rules': {'min_length' : 9},
'error': 'WEAK_PASSWORD'
})
See http://livr-spec.org for detailed documentation and list of supported rules.
Features:
- Rules are declarative and language independent
- Any number of rules for each field
- Return together errors for all fields
- Excludes all fields that do not have validation rules described
- Has possibility to validatate complex hierarchical structures
- Easy to describe and undersand rules
- Returns understandable error codes(not error messages)
- Easy to add own rules
- Rules are be able to change results output ("trim", "nested_object", for example)
- Multipurpose (user input validation, configs validation, contracts programming etc)
Install LIVR from PyPI using PIP:
sudo pip install LIVR
Contructor creates validator objects. livr - validations rules. Rules description is available here - https://github.com/koorchik/LIVR
- is_auto_trim - asks validator to trim all values before validation. Output will be also trimmed.
- if is_auto_trim is undefined(or None) than default_auto_trim value will be used.
rule_builder - is a function reference which will be called for building single rule validator.
class MyRule(object):
def __init__(self, *args):
rule_builders = args[0]
# rule_builders - are rules from original validator
# to allow you create new validator with all supported rules
# validator = Validator(livr)
# validator.register_rules(rule_builders)
# validator.prepare()
def __call__(self, value, all_values, output_array):
if not_valid:
return "SOME_ERROR_CODE"
else:
# some usefull code
Validator.Validator.register_default_rules( {"my_rule": MyRule} )
Then you can use "my_rule" for validation:
{
'name1': 'my_rule', # Call without parameters
'name2': { 'my_rule': arg1 }, # Call with one parameter.
'name3': { 'my_rule': [arg1] }, # Call with one parameter.
'name4': { 'my_rule': [ arg1, arg2, arg3 ] } # Call with many parameters.
}
Here is "max_number" implementation:
class MaxNumber(object):
def __init__(self, *args):
self._max_number = float(args[1])
def __call__(self, number, unuse, unuse_):
# We do not validate empty fields. We have "required" rule for this purpose
if number == None or number == '':
return
#return error message
if float(number) > self._max_number:
return 'TOO_HIGH'
Validator.Validator.register_default_rules({ "max_number": MaxNumber })
All rules for the validator are equal. It does not distinguish "required", "list_of_different_objects" and "trim" rules. So, you can extend validator with any rules you like.
returns object containing all default rule_builders for the validator. You can register new rule or update existing one with "register_rules" method.
Enables or disables automatic trim for input data. If is on then every new validator instance will have auto trim option enabled
Validates user input. On success returns valid_data (contains only data that has described validation rules). On error return false.
valida_data = validator.validate(input)
if valida_data:
#use valida_data
else:
errors = validator.get_errors()
Returns errors object.
{
"field1": "ERROR_CODE",
"field2": "ERROR_CODE",
...
}
For example:
{
"country": "NOT_ALLOWED_VALUE",
"zip": "NOT_POSITIVE_INTEGER",
"street": "REQUIRED",
"building": "NOT_POSITIVE_INTEGER"
}
rule_builder - is a function reference which will be called for building single rule validator.
See "Validator.Validator.register_default_rules" for rules examples.
returns object containing all rule_builders for the validator. You can register new rule or update existing one with "register_rules" method.
alias - is a composite validation rule.
See "Validator.Validator.register_aliased_rule" for rules examples.
koorchik (Viktor Turskyi), asholok (Ihor Kolosha)
Please report any bugs or feature requests to Github https://github.com/asholok/python-validator-livr
Copyright 2012 Viktor Turskyi.
This program is free software, you can redistribute it and/or modify it under the terms of the the Artistic License (2.0). You may obtain a copy of the full license at:
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