`pyvaru`
`pyvaru.rules`

Core API¶

class pyvaru.ValidationRule(apply_to: object, label: str, error_message: str = None, stop_if_invalid: bool = False)¶

Base abstract rule class from which concrete ones must inherit from.

Parameters:

apply_to (object) – Value against which the rule is applied (can be any type).
label (str) – Short string describing the field that will be validated (e.g. “phone number”, “user name”...). This string will be used as the key in the ValidationResult error dictionary.
error_message (str) – Custom message that will be used instead of the “default_error_message”.
stop_if_invalid (bool) – True to prevent Validator from processing the rest of the get_rules if the current one is not respected, False (default) to collect all the possible errors.

apply() → bool¶

Abstract method that must be implemented by concrete get_rules in order to return a boolean indicating whether the rule is respected or not.

Returns:	True if the rule is respected, False otherwise
Return type:	bool

default_error_message = 'Data is invalid.'¶: Default error message for the rule (class attribute).

get_error_message() → str¶

Returns the message that will be used by the validator if the rule is not respected. If a custom error message is provided during rule instantiation that one will be used, otherwise the default one.

Returns:	Error message
Return type:	str

class pyvaru.ValidationResult(errors: dict = None)¶

Represents a report of Validator’s validate() call.

Parameters:	errors (dict) – Map containing errors descriptions (if one ore more get_rules are not respected)

annotate_exception(exception: Exception, rule: pyvaru.ValidationRule = None) → None¶

Takes note of an exception occurred during validation. (Typically caused by an invalid attribute/key access inside get_rules() method)

Parameters:	exception (Exception) – Exception catched during validate() phase. rule (ValidationRule) – Validation rule that has generated the exception.
Returns:	None

annotate_rule_violation(rule: pyvaru.ValidationRule) → None¶

Takes note of a rule validation failure by collecting its error message.

Parameters:	rule (ValidationRule) – Rule that failed validation.
Returns:	None

is_successful() → bool¶

Checks that the validation result does not contain errors.

Returns:	True if the validation is successful, False otherwise.
Return type:	bool

exception pyvaru.ValidationException(validation_result: pyvaru.ValidationResult, message: str = 'Data did not validate.')¶

Internal exception used by the library to represent a validation failure when using a Validator as a context processor.

Parameters:	validation_result (ValidationResult) – Validation result returned by validator. message (str) – Error message

with_traceback()¶: Exception.with_traceback(tb) – set self.__traceback__ to tb and return self.

class pyvaru.Validator(data: object)¶

Validate a data model against a list of ValidationRule(s). This class is abstract, concrete validators must inherit from Validator in order to provide a an actual implementation of get_rules().

Parameters:	data (object) – Data model to validate (like a dict or a custom Python object instance).

get_rules() → list¶

Concrete validators must implement this abstract method in order to return a list of ValidationRule(s), that will be used to validate the model.

Returns:	ValidationRule list
Return type:	list

validate() → pyvaru.ValidationResult¶

Apply the configured ValidationRule(s) (in the given order) and return a ValidationResult object.

Returns:	validation result
Return type:	ValidationResult

class pyvaru.JoinType¶: An enumeration.

class pyvaru.RuleGroup(apply_to: object, label: str, rules: list, error_message: str = None, stop_if_invalid: bool = False)¶

Allows the execution of multiple rules sequentially.

Example:

>>> rules = [
>>>    (TypeRule, {'valid_type': list}),
>>>    (MinLengthRule, {'min_length': 1}),
>>>    UniqueItemsRule
>>> ]
>>> group = RuleGroup(apply_to=countries, label='Countries', rules=rules)

Parameters:

apply_to (object) – Value against which the rule is applied (can be any type).
label (str) – Short string describing the field that will be validated (e.g. “phone number”, “user name”...). This string will be used as the key in the ValidationResult error dictionary.
rules (list) – List of rules to execute. The list can contain rule type (ie: FullStringRule, MinValueRule...) or tuples in the format: “(RuleClass, options)” (ie: “(MinLengthRule, {‘min_length’: 1})”)
error_message (str) – Custom message that will be used instead of the “default_error_message”.
stop_if_invalid (bool) – True to prevent Validator from processing the rest of the get_rules if the current one is not respected, False (default) to collect all the possible errors.

exception pyvaru.InvalidRuleGroupException(message: str)¶

Exception raised by RuleGroup if the provided configuration is invalid.

with_traceback()¶: Exception.with_traceback(tb) – set self.__traceback__ to tb and return self.

Generic validation rules¶

class pyvaru.rules.TypeRule(apply_to: object, label: str, valid_type: type, error_message: str = None, stop_if_invalid: bool = False)¶

Ensure that the target value is an instance of the given type.

Parameters:

apply_to (object) – Value against which the rule is applied (can be any type).
label (str) – Short string describing the field that will be validated (e.g. “phone number”, “user name”...). This string will be used as the key in the ValidationResult error dictionary.
valid_type (type) – Valid class
error_message (str) – Custom message that will be used instead of the “default_error_message”.
stop_if_invalid (bool) – True to prevent Validator from processing the rest of the get_rules if the current one is not respected, False (default) to collect all the possible errors.

default_error_message = 'Object is not an instance of the expected type.'¶: Default error message for the rule.

get_error_message() → str¶

Returns the message that will be used by the validator if the rule is not respected. If a custom error message is provided during rule instantiation that one will be used, otherwise the default one.

Returns:	Error message
Return type:	str

class pyvaru.rules.FullStringRule(apply_to: object, label: str, error_message: str = None, stop_if_invalid: bool = False)¶

Ensure that the target value is a non empty string object.

Parameters:

apply_to (object) – Value against which the rule is applied (can be any type).
label (str) – Short string describing the field that will be validated (e.g. “phone number”, “user name”...). This string will be used as the key in the ValidationResult error dictionary.
error_message (str) – Custom message that will be used instead of the “default_error_message”.
stop_if_invalid (bool) – True to prevent Validator from processing the rest of the get_rules if the current one is not respected, False (default) to collect all the possible errors.

default_error_message = 'String is empty.'¶: Default error message for the rule.

get_error_message() → str¶

Returns the message that will be used by the validator if the rule is not respected. If a custom error message is provided during rule instantiation that one will be used, otherwise the default one.

Returns:	Error message
Return type:	str

class pyvaru.rules.ChoiceRule(apply_to: object, label: str, choices: tuple, error_message: str = None, stop_if_invalid: bool = False)¶

Ensure that the target value is contained in a provided list of possible options.

Parameters:

apply_to (object) – Value against which the rule is applied (can be any type).
label (str) – Short string describing the field that will be validated (e.g. “phone number”, “user name”...). This string will be used as the key in the ValidationResult error dictionary.
choices (tuple) – Available options.
error_message (str) – Custom message that will be used instead of the “default_error_message”.
stop_if_invalid (bool) – True to prevent Validator from processing the rest of the get_rules if the current one is not respected, False (default) to collect all the possible errors.

default_error_message = 'Value not found in available choices.'¶: Default error message for the rule.

get_error_message() → str¶

Returns the message that will be used by the validator if the rule is not respected. If a custom error message is provided during rule instantiation that one will be used, otherwise the default one.

Returns:	Error message
Return type:	str

class pyvaru.rules.MinValueRule(apply_to: object, label: str, min_value: float, error_message: str = None, stop_if_invalid: bool = False)¶

Ensure that the target value is >= than the provided reference value.

Parameters:

apply_to (object) – Value against which the rule is applied (can be any type).
label (str) – Short string describing the field that will be validated (e.g. “phone number”, “user name”...). This string will be used as the key in the ValidationResult error dictionary.
min_value (float) – Minimum value allowed.
error_message (str) – Custom message that will be used instead of the “default_error_message”.
stop_if_invalid (bool) – True to prevent Validator from processing the rest of the get_rules if the current one is not respected, False (default) to collect all the possible errors.

default_error_message = 'Value is smaller than expected one.'¶: Default error message for the rule.

get_error_message() → str¶

Returns the message that will be used by the validator if the rule is not respected. If a custom error message is provided during rule instantiation that one will be used, otherwise the default one.

Returns:	Error message
Return type:	str

class pyvaru.rules.MaxValueRule(apply_to: object, label: str, max_value: float, error_message: str = None, stop_if_invalid: bool = False)¶

Ensure that the target value is <= than the provided reference value.

Parameters:

apply_to (object) – Value against which the rule is applied (can be any type).
label (str) – Short string describing the field that will be validated (e.g. “phone number”, “user name”...). This string will be used as the key in the ValidationResult error dictionary.
max_value (float) – Maximum value allowed.
error_message (str) – Custom message that will be used instead of the “default_error_message”.
stop_if_invalid (bool) – True to prevent Validator from processing the rest of the get_rules if the current one is not respected, False (default) to collect all the possible errors.

default_error_message = 'Value is greater than expected one.'¶: Default error message for the rule.

get_error_message() → str¶

Returns the message that will be used by the validator if the rule is not respected. If a custom error message is provided during rule instantiation that one will be used, otherwise the default one.

Returns:	Error message
Return type:	str

class pyvaru.rules.MinLengthRule(apply_to: object, label: str, min_length: int, error_message: str = None, stop_if_invalid: bool = False)¶

Ensure that the target value has a length >= than the provided reference value. This rule can be applied to all python objects supporting len() (strings, lists, tuples, sets, dicts... and even custom types).

Parameters:

apply_to (object) – Value against which the rule is applied (can be any type).
label (str) – Short string describing the field that will be validated (e.g. “phone number”, “user name”...). This string will be used as the key in the ValidationResult error dictionary.
min_length (int) – Minimum length allowed.
error_message (str) – Custom message that will be used instead of the “default_error_message”.
stop_if_invalid (bool) – True to prevent Validator from processing the rest of the get_rules if the current one is not respected, False (default) to collect all the possible errors.

default_error_message = 'Length is smaller than expected one.'¶: Default error message for the rule.

get_error_message() → str¶

Returns the message that will be used by the validator if the rule is not respected. If a custom error message is provided during rule instantiation that one will be used, otherwise the default one.

Returns:	Error message
Return type:	str

class pyvaru.rules.MaxLengthRule(apply_to: object, label: str, max_length: int, error_message: str = None, stop_if_invalid: bool = False)¶

Ensure that the target value has a length <= than the provided reference value. This rule can be applied to all python objects supporting len() (strings, lists, tuples, sets, dicts... and even custom types).

Parameters:

apply_to (object) – Value against which the rule is applied (can be any type).
label (str) – Short string describing the field that will be validated (e.g. “phone number”, “user name”...). This string will be used as the key in the ValidationResult error dictionary.
max_length (int) – Maximum length allowed.
error_message (str) – Custom message that will be used instead of the “default_error_message”.
stop_if_invalid (bool) – True to prevent Validator from processing the rest of the get_rules if the current one is not respected, False (default) to collect all the possible errors.

default_error_message = 'Length is greater than expected one.'¶: Default error message for the rule.

get_error_message() → str¶

Returns the message that will be used by the validator if the rule is not respected. If a custom error message is provided during rule instantiation that one will be used, otherwise the default one.

Returns:	Error message
Return type:	str

class pyvaru.rules.RangeRule(apply_to: object, label: str, valid_range: range, error_message: str = None, stop_if_invalid: bool = False)¶

Ensure that the target value is contained in the provided range.

IMPORTANT: this rule handles python range() objects (and its “step” configuration), so does not support floats as test value (testing for a float will always fail and even for an integer if it doesn’t match the step increment).

For a validation like “value BETWEEN x AND y” use IntervalRule instead!

Parameters:

apply_to (object) – Value against which the rule is applied (can be any type).
label (str) – Short string describing the field that will be validated (e.g. “phone number”, “user name”...). This string will be used as the key in the ValidationResult error dictionary.
valid_range (range) – Allowed range.
error_message (str) – Custom message that will be used instead of the “default_error_message”.
stop_if_invalid (bool) – True to prevent Validator from processing the rest of the get_rules if the current one is not respected, False (default) to collect all the possible errors.

default_error_message = 'Value is out of range.'¶: Default error message for the rule.

get_error_message() → str¶

Returns the message that will be used by the validator if the rule is not respected. If a custom error message is provided during rule instantiation that one will be used, otherwise the default one.

Returns:	Error message
Return type:	str

class pyvaru.rules.IntervalRule(apply_to: object, label: str, interval_from: float, interval_to: float, error_message: str = None, stop_if_invalid: bool = False)¶

Ensure that the target value is contained in the provided interval.

Parameters:

apply_to (object) – Value against which the rule is applied (can be any type).
label (str) – Short string describing the field that will be validated (e.g. “phone number”, “user name”...). This string will be used as the key in the ValidationResult error dictionary.
interval_from (float) – Minimum allowed value.
interval_to (float) – Maximum allowed value.
error_message (str) – Custom message that will be used instead of the “default_error_message”.
stop_if_invalid (bool) – True to prevent Validator from processing the rest of the get_rules if the current one is not respected, False (default) to collect all the possible errors.

default_error_message = 'Value is not in interval.'¶: Default error message for the rule.

get_error_message() → str¶

Returns the message that will be used by the validator if the rule is not respected. If a custom error message is provided during rule instantiation that one will be used, otherwise the default one.

Returns:	Error message
Return type:	str

class pyvaru.rules.PatternRule(apply_to: object, label: str, pattern: str, flags: int = 0, error_message: str = None, stop_if_invalid: bool = False)¶

Ensure that the target string respects the given pattern.

Parameters:

apply_to (object) – Value against which the rule is applied (can be any type).
pattern (str) – Regex used for pattern matching.
flags (int) – Regex flags.
label (str) – Short string describing the field that will be validated (e.g. “phone number”, “user name”...). This string will be used as the key in the ValidationResult error dictionary.
error_message (str) – Custom message that will be used instead of the “default_error_message”.
stop_if_invalid (bool) – True to prevent Validator from processing the rest of the get_rules if the current one is not respected, False (default) to collect all the possible errors.

default_error_message = 'Value does not match expected pattern.'¶: Default error message for the rule.

get_error_message() → str¶

Returns the message that will be used by the validator if the rule is not respected. If a custom error message is provided during rule instantiation that one will be used, otherwise the default one.

Returns:	Error message
Return type:	str

class pyvaru.rules.PastDateRule(apply_to: object, label: str, reference_date: datetime.datetime = None, error_message: str = None, stop_if_invalid: bool = False)¶

Ensure that the target value is a past date.

Parameters:

apply_to (object) – Value against which the rule is applied.
label (str) – Short string describing the field that will be validated (e.g. “phone number”, “user name”...). This string will be used as the key in the ValidationResult error dictionary.
reference_date (datetime) – Date used for time checking (default to datetime.now()).
error_message (str) – Custom message that will be used instead of the “default_error_message”.
stop_if_invalid (bool) – True to prevent Validator from processing the rest of the get_rules if the current one is not respected, False (default) to collect all the possible errors.

default_error_message = 'Not a past date.'¶: Default error message for the rule.

get_error_message() → str¶

Returns the message that will be used by the validator if the rule is not respected. If a custom error message is provided during rule instantiation that one will be used, otherwise the default one.

Returns:	Error message
Return type:	str

class pyvaru.rules.FutureDateRule(apply_to: object, label: str, reference_date: datetime.datetime = None, error_message: str = None, stop_if_invalid: bool = False)¶

Ensure that the target value is a future date.

Parameters:

apply_to (object) – Value against which the rule is applied.
label (str) – Short string describing the field that will be validated (e.g. “phone number”, “user name”...). This string will be used as the key in the ValidationResult error dictionary.
reference_date (datetime) – Date used for time checking (default to datetime.now()).
error_message (str) – Custom message that will be used instead of the “default_error_message”.
stop_if_invalid (bool) – True to prevent Validator from processing the rest of the get_rules if the current one is not respected, False (default) to collect all the possible errors.

default_error_message = 'Not a future date.'¶: Default error message for the rule.

get_error_message() → str¶

Returns the message that will be used by the validator if the rule is not respected. If a custom error message is provided during rule instantiation that one will be used, otherwise the default one.

Returns:	Error message
Return type:	str

class pyvaru.rules.UniqueItemsRule(apply_to: object, label: str, error_message: str = None, stop_if_invalid: bool = False)¶

Ensure that the target list (or iterable) does not contain duplicated items.

Parameters:

apply_to (object) – Value against which the rule is applied (can be any type).
label (str) – Short string describing the field that will be validated (e.g. “phone number”, “user name”...). This string will be used as the key in the ValidationResult error dictionary.
error_message (str) – Custom message that will be used instead of the “default_error_message”.
stop_if_invalid (bool) – True to prevent Validator from processing the rest of the get_rules if the current one is not respected, False (default) to collect all the possible errors.

default_error_message = 'List contains duplicated items.'¶: Default error message for the rule.

get_error_message() → str¶

Returns the message that will be used by the validator if the rule is not respected. If a custom error message is provided during rule instantiation that one will be used, otherwise the default one.

Returns:	Error message
Return type:	str