pyveritas

class pyveritas.BooleanRule(field: str)

Bases: Rule

Checks if a field is a boolean.

The field must be a boolean value for the BooleanRule to be valid.

error_message(data: Dict, context: RuleContext = None) → str

Returns an error message if the field is not a boolean.

Args:: data (t.Dict): The data that failed validation. context (RuleContext, optional): Contextual information for the rule. Defaults to None.
Returns:: str: An error message describing the validation failure.

is_valid(data: Dict, context: RuleContext = None) → bool

Checks if the field is a boolean.

Args:: data (t.Dict): The data to validate. context (RuleContext, optional): Contextual information for the rule. Defaults to None.
Returns:: bool: True if the field is a boolean, False otherwise.

class pyveritas.DataContract(rules: List[Rule] = None)

Bases: ABC

Base class for all data contracts.

A data contract defines the structure and constraints for a particular type of data. Subclasses must implement the validate method.

add_rule(rule: Rule)

Adds a rule to the contract.

Args:: rule (Rule): The rule to add.

abstract validate(data: Dict, context: RuleContext = None) → List[str]

Validates the given data against the contract’s rules.

Args:: data (t.Dict): A dictionary containing the data to validate. context (RuleContext, optional): A RuleContext object providing additional

context for the validation. Defaults to None.
Returns:: t.List[str]: A list of error messages. If the list is empty, the data is valid.

class pyveritas.DateTimeFormatRule(field: str, format_string: str)

Bases: DateTimeRule

Checks if a datetime string matches a specified format.

The datetime string must match the specified format for the DateTimeFormatRule to be valid.

error_message(data: Dict, context: RuleContext = None) → str

Returns an error message if the datetime string does not match the specified format.

Args:: data (t.Dict): The data that failed validation. context (RuleContext, optional): Contextual information for the rule. Defaults to None.
Returns:: str: An error message describing the validation failure.

is_valid(data: Dict, context: RuleContext = None) → bool

Checks if the datetime string matches the specified format.

Args:: data (t.Dict): The data to validate. context (RuleContext, optional): Contextual information for the rule. Defaults to None.
Returns:: bool: True if the datetime string matches the specified format, False otherwise.

class pyveritas.JSONRule(field: str)

Bases: Rule

Checks if a field contains valid JSON.

The field must contain a valid JSON string for the JSONRule to be valid.

is_valid(data: Dict, context: RuleContext = None) → bool

Checks if the field contains valid JSON.

Args:: data (t.Dict): The data to validate. context (RuleContext, optional): Contextual information for the rule. Defaults to None.
Returns:: bool: True if the field contains valid JSON, False otherwise.

class pyveritas.NumberRangeRule(field: str, min_value: int | float = None, max_value: int | float = None)

Bases: NumberRule

Checks if a number falls within a specified range (inclusive).

The number must be greater than or equal to min_value and less than or equal to max_value (inclusive).

error_message(data: Dict, context: RuleContext = None) → str

Returns an error message if the number is not within the specified range.

Args:: data (t.Dict): The data that failed validation. context (RuleContext, optional): Contextual information for the rule. Defaults to None.
Returns:: str: An error message describing the validation failure.

is_valid(data: Dict, context: RuleContext = None) → bool

Checks if the number is within the specified range.

Args:: data (t.Dict): The data to validate. context (RuleContext, optional): Contextual information for the rule. Defaults to None.
Returns:: bool: True if the number is within the specified range, False otherwise.

class pyveritas.RequiredRule(field: str)

Bases: Rule

Checks if a field is present in the data.

The field must be present in the data for the RequiredRule to be valid.

error_message(data: Dict, context: RuleContext = None) → str

Returns an error message if the field is not present in the data.

Args:: data (t.Dict): The data that failed validation. context (RuleContext, optional): Contextual information for the rule. Defaults to None.
Returns:: str: An error message describing the validation failure.

is_valid(data: Dict, context: RuleContext = None) → bool

Checks if a field is present in the data.

Args:: data (t.Dict): The data to validate. context (RuleContext, optional): Contextual information for the rule. Defaults to None.
Returns:: bool: True if the field is present in the data, False otherwise.

class pyveritas.Rule

Bases: ABC

Base class for all validation rules.

Rules define a specific validation check. Subclasses must implement the is_valid and error_message methods.

abstract error_message(data: Dict, context: RuleContext = None) → str

Returns an error message if the rule is not valid.

Args:: data (t.Dict): The data that failed validation. context (RuleContext, optional): Contextual information for the rule.

Defaults to None.
Returns:: str: An error message describing the validation failure.

abstract is_valid(data: Dict, context: RuleContext = None) → bool

Checks if the rule is valid for the given data.

Args:: data (t.Dict): The data to validate. context (RuleContext, optional): Contextual information for the rule.

Defaults to None.
Returns:: bool: True if the data is valid, False otherwise.

class pyveritas.RuleContext(data: Dict = {})

Bases: object

Provides context to rules during validation.

Can be extended for application-specific needs.

Attributes:: context (t.Dict, optional): A dictionary containing contextual data. Defaults to {}.

class pyveritas.StringLengthRule(field: str, min_length: int = None, max_length: int = None)

Bases: StringRule

Checks if a string’s length falls within a specified range.

The string length must be greater than or equal to min_length and less than or equal to max_length (inclusive).

error_message(data: Dict, context: RuleContext = None) → str

Returns an error message if the string’s length is not within the specified range.

Args:: data (t.Dict): The data that failed validation. context (RuleContext, optional): Contextual information for the rule. Defaults to None.
Returns:: str: An error message describing the validation failure.

is_valid(data: Dict, context: RuleContext = None) → bool

Checks if the string’s length is within the specified range.

Args:: data (t.Dict): The data to validate. context (RuleContext, optional): Contextual information for the rule. Defaults to None.
Returns:: bool: True if the string’s length is within the specified range, False otherwise.

class pyveritas.StringRegexRule(field: str, regex: str)

Bases: StringRule

Checks if a string matches a specified regular expression.

The string must match the regular expression for the StringRegexRule to be valid.

error_message(data: Dict, context: RuleContext = None) → str

Returns an error message if the string does not match the regular expression.

Args:: data (t.Dict): The data that failed validation. context (RuleContext, optional): Contextual information for the rule. Defaults to None.
Returns:: str: An error message describing the validation failure.

is_valid(data: Dict, context: RuleContext = None) → bool

Checks if the string matches the regular expression.

Args:: data (t.Dict): The data to validate. context (RuleContext, optional): Contextual information for the rule. Defaults to None.
Returns:: bool: True if the string matches the regular expression, False otherwise.

class pyveritas.TestRunner(name: str)

Bases: object

A test runner for DataContracts.

This class is responsible for running test cases and validating data against data contracts.

add(test_case: Dict)

Adds a test case to the suite.

Args:

test_case (t.Dict): A dictionary containing test case details: (description, contract, data, expected_errors)

run()

Runs all test cases in the suite.

For each test case, it dynamically loads the contract class, instantiates it, validates the data against the contract, and prints the results.

summary()

Prints a summary of test results.

This method has been removed and is not used for the “base.py” file has been removed

class pyveritas.UserContract

Bases: DataContract

Example data contract for a User object.

This contract checks that the ‘name’ field is a string with a length between 3 and 20 characters, the ‘email’ field is a valid email address, and the ‘age’ field is a number between 0 and 120.

validate(data: Dict, context: RuleContext = None) → List[str]

Validates the given data against the contract’s rules.

Args:: data (t.Dict): A dictionary containing the data to validate. context (RuleContext, optional): A RuleContext object providing additional

context for the validation. Defaults to None.
Returns:: t.List[str]: A list of error messages. If the list is empty, the data is valid.

class pyveritas.Validator(contract: DataContract)

Bases: object

A simple validator class that validates data against a DataContract.

The Validator takes a DataContract as input and provides methods for validating data against that contract.

is_valid(data: Dict, context: RuleContext = None) → bool

Checks if the given data is valid according to the contract.

Args:: data (t.Dict): The data to validate. context (RuleContext, optional): A RuleContext object providing additional

context for the validation. Defaults to None.
Returns:: bool: True if the data is valid, False otherwise.

validate(data: Dict, context: RuleContext = None) → List[str]

Validates the given data against the contract.

Args:: data (t.Dict): The data to validate. context (RuleContext, optional): A RuleContext object providing additional

context for the validation. Defaults to None.
Returns:: t.List[str]: A list of error messages. If the list is empty, the data is valid.

pyveritas.contracts

class pyveritas.contracts.DataContract(rules: List[Rule] = None)

Bases: ABC

Base class for all data contracts.

A data contract defines the structure and constraints for a particular type of data. Subclasses must implement the validate method.

add_rule(rule: Rule)

Adds a rule to the contract.

Args:: rule (Rule): The rule to add.

abstract validate(data: Dict, context: RuleContext = None) → List[str]

Validates the given data against the contract’s rules.

Args:: data (t.Dict): A dictionary containing the data to validate. context (RuleContext, optional): A RuleContext object providing additional

context for the validation. Defaults to None.
Returns:: t.List[str]: A list of error messages. If the list is empty, the data is valid.

class pyveritas.contracts.UserContract

Bases: DataContract

Example data contract for a User object.

This contract checks that the ‘name’ field is a string with a length between 3 and 20 characters, the ‘email’ field is a valid email address, and the ‘age’ field is a number between 0 and 120.

validate(data: Dict, context: RuleContext = None) → List[str]

Validates the given data against the contract’s rules.

Args:: data (t.Dict): A dictionary containing the data to validate. context (RuleContext, optional): A RuleContext object providing additional

context for the validation. Defaults to None.
Returns:: t.List[str]: A list of error messages. If the list is empty, the data is valid.

pyveritas.rules

class pyveritas.rules.AndRule(rule1: Rule, rule2: Rule)

Bases: Rule

Combines two rules with a logical AND.

The data must be valid according to both rules for the AndRule to be valid.

error_message(data: Dict, context: RuleContext = None) → str

Returns an error message if the data is not valid according to either rule.

Args:: data (t.Dict): The data that failed validation. context (RuleContext, optional): Contextual information for the rules. Defaults to None.
Returns:: str: An error message describing the validation failure.

is_valid(data: Dict, context: RuleContext = None) → bool

Checks if the data is valid according to both rules.

Args:: data (t.Dict): The data to validate. context (RuleContext, optional): Contextual information for the rules. Defaults to None.
Returns:: bool: True if the data is valid according to both rules, False otherwise.

class pyveritas.rules.BooleanRule(field: str)

Bases: Rule

Checks if a field is a boolean.

The field must be a boolean value for the BooleanRule to be valid.

error_message(data: Dict, context: RuleContext = None) → str

Returns an error message if the field is not a boolean.

Args:: data (t.Dict): The data that failed validation. context (RuleContext, optional): Contextual information for the rule. Defaults to None.
Returns:: str: An error message describing the validation failure.

is_valid(data: Dict, context: RuleContext = None) → bool

Checks if the field is a boolean.

Args:: data (t.Dict): The data to validate. context (RuleContext, optional): Contextual information for the rule. Defaults to None.
Returns:: bool: True if the field is a boolean, False otherwise.

class pyveritas.rules.DateTimeFormatRule(field: str, format_string: str)

Bases: DateTimeRule

Checks if a datetime string matches a specified format.

The datetime string must match the specified format for the DateTimeFormatRule to be valid.

error_message(data: Dict, context: RuleContext = None) → str

Returns an error message if the datetime string does not match the specified format.

Args:: data (t.Dict): The data that failed validation. context (RuleContext, optional): Contextual information for the rule. Defaults to None.
Returns:: str: An error message describing the validation failure.

is_valid(data: Dict, context: RuleContext = None) → bool

Checks if the datetime string matches the specified format.

Args:: data (t.Dict): The data to validate. context (RuleContext, optional): Contextual information for the rule. Defaults to None.
Returns:: bool: True if the datetime string matches the specified format, False otherwise.

class pyveritas.rules.DateTimeRule(field: str)

Bases: Rule

Base class for datetime-based rules.

Provides a helper method for retrieving the datetime value from the data.

class pyveritas.rules.EndDateAfterStartDateRule(start_date_field: str, end_date_field: str)

Bases: Rule

Checks if an end date happens after a start date.

The end date must happen after the start date for the EndDateAfterStartDateRule to be valid.

error_message(data: Dict, context: RuleContext = None) → str

Returns an error message if the end date is not after the start date.

Args:: data (t.Dict): The data that failed validation. context (RuleContext, optional): Contextual information for the rule. Defaults to None.
Returns:: str: An error message describing the validation failure.

is_valid(data: Dict, context: RuleContext = None) → bool

Checks if the end date is after the start date in the given data.

Args:: data (t.Dict): The data to validate. context (RuleContext, optional): A RuleContext object providing additional

context for the validation. Defaults to None.
Returns:: bool: True if the end date is after the start date, False otherwise.

class pyveritas.rules.JSONRule(field: str)

Bases: Rule

Checks if a field contains valid JSON.

The field must contain a valid JSON string for the JSONRule to be valid.

is_valid(data: Dict, context: RuleContext = None) → bool

Checks if the field contains valid JSON.

Args:: data (t.Dict): The data to validate. context (RuleContext, optional): Contextual information for the rule. Defaults to None.
Returns:: bool: True if the field contains valid JSON, False otherwise.

class pyveritas.rules.NotRule(rule: Rule)

Bases: Rule

Negates a rule.

The data must not be valid according to the rule for the NotRule to be valid.

error_message(data: Dict, context: RuleContext = None) → str

Returns an error message if the data is valid according to the rule.

Args:: data (t.Dict): The data that passed validation (but shouldn’t have). context (RuleContext, optional): Contextual information for the rule. Defaults to None.
Returns:: str: An error message describing the validation failure (i.e., that the data was unexpectedly valid).

is_valid(data: Dict, context: RuleContext = None) → bool

Checks if the data is not valid according to the rule.

Args:: data (t.Dict): The data to validate. context (RuleContext, optional): Contextual information for the rule. Defaults to None.
Returns:: bool: True if the data is not valid according to the rule, False otherwise.

class pyveritas.rules.NumberRangeRule(field: str, min_value: int | float = None, max_value: int | float = None)

Bases: NumberRule

Checks if a number falls within a specified range (inclusive).

The number must be greater than or equal to min_value and less than or equal to max_value (inclusive).

error_message(data: Dict, context: RuleContext = None) → str

Returns an error message if the number is not within the specified range.

Args:: data (t.Dict): The data that failed validation. context (RuleContext, optional): Contextual information for the rule. Defaults to None.
Returns:: str: An error message describing the validation failure.

is_valid(data: Dict, context: RuleContext = None) → bool

Checks if the number is within the specified range.

Args:: data (t.Dict): The data to validate. context (RuleContext, optional): Contextual information for the rule. Defaults to None.
Returns:: bool: True if the number is within the specified range, False otherwise.

class pyveritas.rules.NumberRule(field: str)

Bases: Rule

Base class for number-based rules.

Provides a helper method for retrieving the number value from the data.

class pyveritas.rules.OrRule(rule1: Rule, rule2: Rule)

Bases: Rule

Combines two rules with a logical OR.

The data must be valid according to at least one of the rules for the OrRule to be valid.

error_message(data: Dict, context: RuleContext = None) → str

Returns an error message if the data is not valid according to either rule.

Args:: data (t.Dict): The data that failed validation. context (RuleContext, optional): Contextual information for the rules. Defaults to None.
Returns:: str: An error message describing the validation failure.

is_valid(data: Dict, context: RuleContext = None) → bool

Checks if the data is valid according to at least one of the rules.

Args:: data (t.Dict): The data to validate. context (RuleContext, optional): Contextual information for the rules. Defaults to None.
Returns:: bool: True if the data is valid according to at least one of the rules, False otherwise.

class pyveritas.rules.RequiredRule(field: str)

Bases: Rule

Checks if a field is present in the data.

The field must be present in the data for the RequiredRule to be valid.

error_message(data: Dict, context: RuleContext = None) → str

Returns an error message if the field is not present in the data.

Args:: data (t.Dict): The data that failed validation. context (RuleContext, optional): Contextual information for the rule. Defaults to None.
Returns:: str: An error message describing the validation failure.

is_valid(data: Dict, context: RuleContext = None) → bool

Checks if a field is present in the data.

Args:: data (t.Dict): The data to validate. context (RuleContext, optional): Contextual information for the rule. Defaults to None.
Returns:: bool: True if the field is present in the data, False otherwise.

class pyveritas.rules.Rule

Bases: ABC

Base class for all validation rules.

Rules define a specific validation check. Subclasses must implement the is_valid and error_message methods.

abstract error_message(data: Dict, context: RuleContext = None) → str

Returns an error message if the rule is not valid.

Args:: data (t.Dict): The data that failed validation. context (RuleContext, optional): Contextual information for the rule.

Defaults to None.
Returns:: str: An error message describing the validation failure.

abstract is_valid(data: Dict, context: RuleContext = None) → bool

Checks if the rule is valid for the given data.

Args:: data (t.Dict): The data to validate. context (RuleContext, optional): Contextual information for the rule.

Defaults to None.
Returns:: bool: True if the data is valid, False otherwise.

class pyveritas.rules.RuleContext(data: Dict = {})

Bases: object

Provides context to rules during validation.

Can be extended for application-specific needs.

Attributes:: context (t.Dict, optional): A dictionary containing contextual data. Defaults to {}.

class pyveritas.rules.StringChoicesRule(field: str, choices: List[str])

Bases: StringRule

Checks if a string is one of a specified set of choices.

The string must be present in the choices list for the StringChoicesRule to be valid.

error_message(data: Dict, context: RuleContext = None) → str

Returns an error message if the string is not one of the specified choices.

Args:: data (t.Dict): The data that failed validation. context (RuleContext, optional): Contextual information for the rule. Defaults to None.
Returns:: str: An error message describing the validation failure.

is_valid(data: Dict, context: RuleContext = None) → bool

Checks if the string is one of the specified choices.

Args:: data (t.Dict): The data to validate. context (RuleContext, optional): Contextual information for the rule. Defaults to None.
Returns:: bool: True if the string is one of the specified choices, False otherwise.

class pyveritas.rules.StringLengthRule(field: str, min_length: int = None, max_length: int = None)

Bases: StringRule

Checks if a string’s length falls within a specified range.

The string length must be greater than or equal to min_length and less than or equal to max_length (inclusive).

error_message(data: Dict, context: RuleContext = None) → str

Returns an error message if the string’s length is not within the specified range.

Args:: data (t.Dict): The data that failed validation. context (RuleContext, optional): Contextual information for the rule. Defaults to None.
Returns:: str: An error message describing the validation failure.

is_valid(data: Dict, context: RuleContext = None) → bool

Checks if the string’s length is within the specified range.

Args:: data (t.Dict): The data to validate. context (RuleContext, optional): Contextual information for the rule. Defaults to None.
Returns:: bool: True if the string’s length is within the specified range, False otherwise.

class pyveritas.rules.StringRegexRule(field: str, regex: str)

Bases: StringRule

Checks if a string matches a specified regular expression.

The string must match the regular expression for the StringRegexRule to be valid.

error_message(data: Dict, context: RuleContext = None) → str

Returns an error message if the string does not match the regular expression.

Args:: data (t.Dict): The data that failed validation. context (RuleContext, optional): Contextual information for the rule. Defaults to None.
Returns:: str: An error message describing the validation failure.

is_valid(data: Dict, context: RuleContext = None) → bool

Checks if the string matches the regular expression.

Args:: data (t.Dict): The data to validate. context (RuleContext, optional): Contextual information for the rule. Defaults to None.
Returns:: bool: True if the string matches the regular expression, False otherwise.

class pyveritas.rules.StringRule(field: str)

Bases: Rule

Base class for string-based rules.

Provides a helper method for retrieving the string value from the data.

class pyveritas.rules.TypeRule(field: str, expected_type: type)

Bases: Rule

Checks if a field is of a specific type.

The field must be of the specified type for the TypeRule to be valid.

error_message(data: Dict, context: RuleContext = None) → str

Returns an error message if the field is not of the specified type.

Args:: data (t.Dict): The data that failed validation. context (RuleContext, optional): Contextual information for the rule. Defaults to None.
Returns:: str: An error message describing the validation failure.

is_valid(data: Dict, context: RuleContext = None) → bool

Checks if the field is of the specified type.

Args:: data (t.Dict): The data to validate. context (RuleContext, optional): Contextual information for the rule. Defaults to None.
Returns:: bool: True if the field is of the specified type, False otherwise.

pyveritas.validator

class pyveritas.validator.Validator(contract: DataContract)

Bases: object

A simple validator class that validates data against a DataContract.

The Validator takes a DataContract as input and provides methods for validating data against that contract.

is_valid(data: Dict, context: RuleContext = None) → bool

Checks if the given data is valid according to the contract.

Args:: data (t.Dict): The data to validate. context (RuleContext, optional): A RuleContext object providing additional

context for the validation. Defaults to None.
Returns:: bool: True if the data is valid, False otherwise.

validate(data: Dict, context: RuleContext = None) → List[str]

Validates the given data against the contract.

Args:: data (t.Dict): The data to validate. context (RuleContext, optional): A RuleContext object providing additional

context for the validation. Defaults to None.
Returns:: t.List[str]: A list of error messages. If the list is empty, the data is valid.

pyveritas.runner

class pyveritas.runner.TestRunner(name: str)

Bases: object

A test runner for DataContracts.

This class is responsible for running test cases and validating data against data contracts.

add(test_case: Dict)

Adds a test case to the suite.

Args:

test_case (t.Dict): A dictionary containing test case details: (description, contract, data, expected_errors)

run()

Runs all test cases in the suite.

For each test case, it dynamically loads the contract class, instantiates it, validates the data against the contract, and prints the results.

summary()

Prints a summary of test results.

This method has been removed and is not used for the “base.py” file has been removed