xml-to-pydantic xml-to-pydantic is a library for Python to convert XML or HTML to pydantic models. This can be used to: Parse and validate a scraped HTML page into a python object Parse and validate an XML response from an XML-based API Parse and validate data stored in XML format (Please note that this project is not affiliated in any way with the great team at pydantic.) pydantic is a Python library for data validation, applying type hints / annotations. It enables the creation of easy or complex data validation rules for processing external data. That data usually comes in JSON format or from a Python dictionary. But to process and validate HTML or XML into pydantic models would then require two steps: convert the HTML or XML to a Python dictionary, then convert to the pydantic model. This libary provides a convenient way to combine those steps. Note: if you are using this library to parse external, uncontrolled HTML or XML, you should be aware of possible attack vectors through XML: [https://github.com/tiran/defusedxml]. This library uses lxml under the hood. Installation Use pip, or your favorite Python package manager (pipenv, poetry, pdm, ...): bash pip install xml-to-pydantic Usage The HTML or XML data is extracted using XPath. For simple documents, the XPath can be calcualted from the model: ```py from xml_to_pydantic import ConfigDict, XmlBaseModel html_bytes = b""" My page title Header Paragraph1 Paragraph2 Paragraph3 """ class MainContent(XmlBaseModel): model_config = ConfigDict(xpath_root="/html/body/main") p: list[str] result = MainContent.model_validate_html(html_bytes) print(result) > p=['Paragraph1', 'Paragraph2', 'Paragraph3'] ``` ```py from xml_to_pydantic import XmlBaseModel xml_bytes = b""" 4.53 3.25 """ class MyModel(XmlBaseModel): element: list[float] model = MyModel.model_validate_xml(xml_bytes) print(model) > element=[4.53, 3.25] ``` However, for more complicated XML, this one-to-one correspondance may not be convenient, and a better approach is supplying the xpath directly (similar to how pydantic allows specifying an alias for a field): ```py from xml_to_pydantic import XmlBaseModel, XmlField xml_bytes = b""" 4.53 Link """ class MyModel(XmlBaseModel): number: float = XmlField(xpath="./element/text()") href: str = XmlField(xpath="./a/@href") model = MyModel.model_validate_xml(xml_bytes) print(model) > number=4.53 href='https://example.com' ``` The parsing can also deal with nested models and lists: ```py from xml_to_pydantic import XmlBaseModel, XmlField xml_bytes = b""" value1 value2 value3 value11 """ class NextLevel(XmlBaseModel): level2: list[str] = XmlField(xpath="./level2/text()") class MyModel(XmlBaseModel): next_level: NextLevel = XmlField(xpath="./level1") level_11: list[str] = XmlField(xpath="./level11/text()") model = MyModel.model_validate_xml(xml_bytes) print(model) > next_level=NextLevel(level2=['value1', 'value2', 'value3']) level_11=['value11'] ``` Development Prerequisites: Any Python 3.8 through 3.12 poetry for dependency management git make (to use the helper scripts in the Makefile) Autoformatting can be applied by running bash make lintable Before commiting, remember to run bash make lint make test
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Latest version: 0.2 Released: 2024-06-11