User Guide¶
Users fill the web form with necessary information, however, they often make mistakes. This is where form validation comes into play. The goal of validation is to ensure that the user provided necessary and properly formatted information needed to successfully complete an operation.
Validator¶
Validator
is a container of validation
rules that all together provide object validation. You instantiate
Validator
and supply it a map
between attribute names being validated and list of rules. Here is an example:
credential_validator = Validator({
'username': [required, length(max=10)],
'password': [required, length(min=8, max=12)]
})
Validator
in no way tied to object
and/or class being validated, instead the only requirement is existance of
attributes being validated.
Validator
supports
__getitem__
interface, so is applicable to dict
like objects:
user = {'username': '', 'password': ''}
errors = {}
succeed = credential_validator.validate(user, errors)
Method validate
returns True
only in case all validation rules succeed
otherwise False
.
errors
dictionary contains all errors reported during validation. Key
corresponds to attribute name being checked, while value is a list of errors.
If you need validation check all rules for failed attribute, you need set
stop
attribute to False
(default is to stop on first error):
succeed = credential_validator.validate(user, errors, stop=False)
Nested Validator¶
Validator
can be nested into some
other validator, so ultimately can form any hierarchically complex structure.
This can be useful for composite objects, e.g. Registration
model can
aggregate Credential
model. While each model has own validation,
registration model can nest the validator for the credential model:
class Registration(object):
def __init__(self):
self.credential = Credential()
registration_validator = Validator({
'credential': credential_validator
})
Internationalization¶
Validator
supports the python standard
gettext
module. You need to pass gettext
translations as a argument
to validate
method. Here is an example:
from gettext import NullTranslations
translations = NullTranslations()
succeed = credential_validator.validate(
user,
errors,
translations=translations)
Thread Safety¶
Validator does not alter its state once initialized. It is guaranteed to be thread safe.
Validation Rules¶
Validation rules prevent bad data from being processed. A validation rule is a
criterion used in the process of data validation. Rules support simple types
attributes as well as list typ attributes, e.g. iterator
rule can apply
a number of other rules to each item in the list.
There are a number of validation rules already defined.
required
. Any value evaluated to booleanTrue
passes this rule. Also take a look at therequired_but_missing
list. SeeRequiredRule
.not_none
. None value will not pass this rule. SeeNotNoneRule
.missing
,empty
. Any value evaluated to booleanFalse
passes this rule. Also take a look at therequired_but_missing
list. SeeRequiredRule
.length
. Result of python functionlen()
must fall within a range defined by this rule. Supported range attributes include:min
,max
. SeeLengthRule
.compare
. Compares attribute being validated with some other attribute value. Supported comparison operations include:equal
,not_equal
. SeeCompareRule
.predicate
,model_predicate
. Fails if predicate returns booleanFalse
. Predicate is any callable that accepts a model and returns a boolean. It is useful for custom rules, e.g. a number of days between two model properties must not exceed a certain value, etc. SeePredicateRule
.must
,value_predicate
. Fails if predicate returns booleanFalse
. Predicate is any callable that accepts a value and returns a boolean. It is useful for custom rule applicable to multiple attributes of model. SeeValuePredicateRule
.regex
. Search for regular expression pattern. Initialized withregex
as a regular expression pattern or a pre-compiled regular expression. Supportsnegated
argument. SeeRegexRule
.slug
. Ensures only letters, numbers, underscores or hyphens. SeeSlugRule
.email
. Ensures a valid email. SeeEmailRule
.scientific
. Ensures a valid scientific string input. SeeScientificRule
.base64
. Ensures a valid base64 string input (supports alternative alphabet for+
and/
characters). SeeBase64Rule
.urlsafe_base64
. Ensures a valid base64 string input using an alphabet, which substitutes-
instead of+
and_
instead of/
in the standard Base64 alphabet. The input can still contain=
. SeeURLSafeBase64Rule
.range
. Ensures value is in range defined by this rule. Works with any numbers including int, float, decimal, etc. Supported range attributes include:min
,max
. SeeRangeRule
.and_
. Applies allrules
regardless of validation result. SeeAndRule
.or_
. Succeeds if at least one rule inrules
succeed. Failed rule results are not added unless they all fail. SeeOrRule
.iterator
. Appliesrules
to each item in value. Iterates over each rule and checks whenever any item in value fails. Designed to work with iteratable attributes: list, tuple, etc. SeeIteratorRule
.one_of
. Value must match at least one element fromitems
. Checks whenever value belongs toitems
. SeeOneOfRule
.relative_date
,relative_utcdate
,relative_tzdate
,relative_datetime
,relative_utcdatetime
,relative_tzdatetime
. Check if value is in relative date/datetime range per local, UTC or tz time. SeeRelativeDateDeltaRule
,RelativeUTCDateDeltaRule
,RelativeTZDateDeltaRule
andRelativeDateTimeDeltaRule
,RelativeUTCDateTimeDeltaRule
,RelativeTZDateTimeDeltaRule
.relative_timestamp
,relative_unixtime
. Check if value is in relative unix timestamp range. SeeRelativeUnixTimeDeltaRule
.adapter
,int_adapter
. Adapts a value according to converter. This is useful when you need to keep string input in model but validate as an integer. SeeAdapterRule
,IntAdapterRule
.ignore
. The idea behind this rule is to be able to substitute any validation rule by this one that always succeeds. SeeIgnoreRule
.
Custom Message¶
You are able to customize the error message by using message_template
argument
during rule declaration:
credential_validator = Validator({
'username': [required(message_template='Required field')]
})
Every rule supports message_template
argument during rule declaration.
gettext
utilities¶
Please remember to add msgid
/msgstr
of customized validation error to
po
file. You can extract gettext messages by:
$ xgettext --join-existing --sort-by-file --omit-header \
-o i18n/translations.po src/*.py
Compile po files:
$ msgfmt -v translations.po -o translations.mo
Custom Rules¶
It is easy to provide your own validation rule. The rule is any callable with the following contract:
def check(self, value, name, model, result, gettext):
Here is a description of each attribute:
value
- value that is currently validated.name
- name of attribute.model
- object being validated.result
- a dictionary that accepts validation errors.gettext
- a function used to provide i18n support.
Validation Mixin¶
ValidationMixin
provides a sort of
contextual integration with third party modules. Specifically this mixin
requires two attributes: errors
and translations
. Once these two
attributes provided, validation can be simplified. Let’s review it by example:
user_validator = Validator({
'name': [required]
})
We defined user_validator
. Now here is our integration in some service:
class MyService(ValidationMixin):
def __init__(self):
self.errors = {}
self.translations = {'validation': None}
def signin(self, user):
succeed = self.validate(user, user_validator)
...
self.error('Unauthorized')
return False
If the signin
operation fails the client can request all validation errors
from errors
attribute. Note that general error message (‘Unauthorized’)
is stored under __ERROR__
key. Thus it can be used to display general
information to the end user.
Model Update¶
Web form submit is a dictionary where key is the name of the input element being submitted and value is a list. That list can have just a single value for elements like input or several values that depict user choice.
try_update_model()
method is provided to
try update any given object with values submitted by web form.
The convention used by try_update_model()
method is requirement for the model to be properly initialized with default
values, e.g. integer attributes must default to some integer value, etc.
List of supported value_providers
:
try:
return date(*strptime(value, fmt)[:3])
except ValueError:
continue
raise ValueError()
else:
return None
def time_value_provider(value, gettext):
"""Converts ``value`` to ``datetime.time``."""
Example of domain model initialized with defaults:
class Credential(object):
def __init__(self):
self.username = ''
self.password = ''
Values submitted by web form:
values = {'username': [''], 'password': ['']}
Typical use case as follows:
from wheezy.validation.model import try_update_model
credential = Credential()
errors = {}
succeed = try_update_model(credential, values, errors)
errors
dictionary contains all errors reported during model update. Key
corresponds to attribute being updated, while value is a list of errors.
Numbers¶
Number value providers (
int_value_provider()
,
decimal_value_provider()
,
float_value_provider()
) supports thousands
separator as well as decimal separator. Take a look at the validation.po
file.
Date and Time¶
Date and time value providers (
date_value_provider()
,
time_value_provider()
,
datetime_value_provider()
) support a number
of formats. Generally there is a default format and fallback formats. It tries
the default format and if it fails tries fallback formats. Take a look at
the validation.po
file for a list of supported formats.
Please note that datetime_value_provider()
falls back to date_value_provider()
in case
none of its own formats matched. Empty value is converted to minimal value
for date/time.
Lists¶
try_update_model()
method supports list
attributes. Note that existing model list is used (it is not overwritten).
>>> class User(object):
... def __init__(self):
... self.prefs = []
... self.prefs2 = [0]
>>> user = User()
>>> values = {'prefs': ['1', '2'], 'prefs2': ['1', '2']}
>>> results = {}
>>> try_update_model(user, values, results)
True
>>> user.prefs
['1', '2']
>>> user.prefs2
[1, 2]
Note that the type of the first element in the list selects value_provider for all elements in the list.
Custom Value Providers¶
Value provider is any callable of the following contract:
def my_value_provider(str_value, gettext):
return parsed_value
You can add your value provider to defaults:
from wheezy.validation.model import value_providers
value_providers['my_type'] = my_value_provider