Yangson is a Python 3 library that offers programmers tools for working with configuration and other data modelled with the YANG data modelling language. Yangson supports only the JSON data encoding as defined in [RFC7951].
The Yangson package also provides a simple Command-Line Utility.
Instance data are internally represented as a persistent data structure. This makes the code thread-safe, and also allows for copying and updating data trees in a space-efficient way.
Parser and evaluator for XPath 1.0 expressions [XPath] and extensions defined for YANG 1.1 (new XPath functions, default namespace, and others).
Complete validation of instance data against the data model.
Support for RESTCONF data resources [RFC8040] (timestamps and entity-tags) and resource identifiers.
Support for NETCONF Access Control Module (NACM) [RFC6536].
The Yangson package is available from PyPI and can be installed using the pip package manager as follows:
python -m pip install yangson
Naming of YANG Modules
module-or-submodule-name ['@' revision-date] '.yang'
For a (sub)module without a revision statement, the
revision-date part must be omitted, otherwise it may or may not be
present. Either way, the module name and revision declared in the YANG
library must match the corresponding statements in the (sub)module text
Yangson is currently able to parse only the compact syntax of YANG files. Modules written in the alternative XML format (YIN) can be converted to the compact syntax by using the XSLT stylesheet yin2yang.xsl that can be obtained from the YIN Tools project.
This documentation uses doctest snippets rather heavily. For this purpose, each Python module uses a specific example data model and/or JSON instance document that have to be loaded first. Python statements that do so are also included as doctest snippets. Other obvious steps, such as necessary Python module imports, are not shown.
The example YANG modules, YANG library specifications and instance
documents are included with Yangson documentation, in subdirectories
examples directory. All the examples are also listed in
Example Data Models and Instances.
Doctest snippets embedded in the documentation can also be used as a
test suite. To run all Python code contained in those snippets and
obtain a summary of the results per Python module, use the following
command from the
$ make doctest