validify 0.0.15

validify is a rule-based validation module for assessing the structure of an xml tree, built on top of the lxml library. It currently covers a subset of the XML Schema 1.1 Definition.

validify is a rule-based validation module for assessing the structure of an xml tree, written in Python and built on top of the lxml library. It currently covers a subset of the XML Schema 1.1 Definition.

Requirements

• Python 3.5+
• lxml
• loguru

Installation

The validify module can be found on PyPI. It can be installed by using pip:

pip install validify

Dependencies will be automatically fetched by pip.

Basic usage

import validify
validation_result = validify.validate(input_file="validify/test.xml", input_elementtree=None, xmlns_def=None, validation_rules=None, message_lang=None, log_to_console=True, log_debug=False)

Parameters

• input_file (default: None): path to xml file which should be validated.
• input_elementtree (default: None): an etree.ElementTree object (parameter 'input_elementtree') can also be passed, instead of an input file string.
• xmlns_def (default: None): a namespace definition can be supplied as a python dictionary object ({None: "default_namespace", "namespace_prefix": "another_namespace"}}).
• validation_rules (default: None): a python dictionary object containing the validation rules (see "Defining validation rules" below for an example.). An example rules dictionary is used if no value is supplied here.
• message_lang (default: de): language for validation message strings. Supported values are en and de.
• log_to_console (default: True): if True, validation and status messages are logged to console. If false, validation messages are only added to the results dict returned by validfy.
• log_debug (default: False): if True, debug status messages are logged to console.

One of the paramaters input_file or input_elementtree should be passed for the library to produce validation results.

Defining validation rules

Validation rules are defined in a dictionary object (JSON-like structure):

validation_rules = {}

validation_rules["element"] = []
ruleset = {}

ruleset["element_content_optional"] = False
ruleset["element_children_optional"] = False
ruleset["optional_attributes"] = ["valid_optional_attribute_01", "valid_optional_attribute_02"]
ruleset["obligatory_attributes"] = ["obligatory_attribute_01", "obligatory_attribute_02"]
ruleset["optional_subelements"] = ["optional_subelement_01", "optional_subelement_02"]
ruleset["obligatory_subelements"] = ["obligatory_subelement_01", "obligatory_subelement_02"]
ruleset["max_occurence"] = 2
ruleset["text_character_content_allowed"] = True
ruleset["tail_character_content_allowed"] = False

ruleset["allowed_values"] = ["valid_value_01", "valid_value_02"]
ruleset["allowed_patterns"] = ["^test-\d{4}$", "^test-\d{3}$"]
ruleset["allowed_datatypes"] = []
ruleset["attribute_def"] = []
ruleset["attribute_def"].append({"attribute_name": "valid_optional_attribute_01", "allowed_values": ["valid_value_01", "valid_value_02"],
                                 "allowed_patterns": ["^test-\d{4}$", "^test-\d{3}$"]})
ruleset["attribute_def"].append(
    {"attribute_name": "obligatory_attribute_01", "allowed_values": ["valid_value_01", "valid_value_02"],
     "allowed_patterns": []})


ruleset["rule_conditions"] = []
ruleset["rule_conditions"].append(
    {"text_values": ["valid_text_value"],
     "attribute_def": [{"attribute_name": "valid_attribute_name", "allowed_values": ["valid_value"]},
                       {"attribute_name": "another_valid_attribute_name", "allowed_values": ["valid_value"]}],
     "reference_elements": [{"element_name": "reference_element", "attribute_def": [{"attribute_name": "reference_test", "allowed_values": ["valid_value"]}],"preceding_elements": 1}]})


validation_rules["element"].append(ruleset)

Each element can be provided with one or more rulesets. The rule_conditions definiton can be used when the ruleset should only be applied if the validated element contains the defined attribute(s) and attribute value(s). Besides the validated element, a reference element can also be defined and checked for attribute values. Currently, it must be a parent element of the validated element (parent level defined by preceding_elements).

Validation output

validify.validate returns a list containing the validation messages as dictionaries:

[{'message_id': '0001', 'message_text ': 'Element example_element does not contain any subelements, although one or more subelements are expected.', 'element_name': '{namespace}example_element', 'local_name': 'example_element', 'element_sourceline': '23'}]

XML Schema feature coverage

For now, a small subset of the XML Schema features is provided:

• Test if a ruleset applies by checking a reference element's text and attribute values
• Define if element childen and content are optional
• Define optional and obligatory attributes
• Define optional and obligatory subelements
• Define maximum occurence of an element
• Define if character content is allowed
• Define an element's allowed values (~ xs:enumeration)
• Define an element's allowed patterns (~ xs:pattern)
• Define an attribute's allowed values and patterns

This module is currently used for validating data deliveries in the EAD XML application profile, which are processed for ingesting in the metadata portals Deutsche Digitale Bibliothek and Archivportal-D. Therefore, supported features currently are nowhere near those provided by the XML Schema standard. Feature support is supposed to be gradually expanded, however.

The following features are planned for a future release:

• checking max/min text and attribute values
• validating string length
• support for pre-defined data types (i.e. xs:ID, xs:NMTOKEN)
• rule conditions: direct support for XPath and lxml's itersiblings and iterancestors methods.

Development status

This package is in an early development stage. It should already work reliably for intended use cases, but documentation and stability of API are still lacking.