A prototype CLI tool to transform YANG models into Pydantic datastructures that can be initialized with config values and serialized into RESTCONF payloads.
Check out the documentation https://pydantify.github.io/pydantify/
Prerequisites:
- Python 3.10
- pip
Installing from PYPI:
pip install pydantifyInstalling from local folder:
pip install .Example:
pydantify -i ./models_dir -o ./output_dir -t interfaces/ethernet model.yangTransforms the /interfaces/ethernet node and its children (located in model.yang) into a Python script located in ./output_dir. Imports of definitions found in ./models_dir are included if relevant to the specified model and node.
Command syntax:
pydantify [-h] [-v] [-V] [-S] [-i INPUT_DIR] [-o OUTPUT_DIR] [-t TRIM_PATH] input_file
positional arguments:
input_file The YANG file containing the entrypoint to the model to evaluate.
options:
-h, --help show this help message and exit
-v, --verbose Enables debug output
-V, --include-verification
Adds validation code, as well as the relevant YANG files, to the output model.
-S, --standalone Generated output model has no dependency on Pydantify.
All required code is copied into the output model.
-i INPUT_DIR, --input-dir INPUT_DIR, --path INPUT_DIR
The directory that contains the YANG input model.
Defaults to the input file's folder.
-o OUTPUT_DIR, --output-dir OUTPUT_DIR
The directory that should be used to store the output model. Defaults to "$CWD/out".
-f OUTPUT_FILE, --output-file OUTPUT_FILE
The name of the output file. Defaults to "out.py".
-t TRIM_PATH, --trim-path TRIM_PATH
Get only the specified branch of the whole tree.
-j, --json-schema Output JSON schema instead of Pydantic models.
-d, --data-type {config,state}
Limit output to config or state only. Default is config and state combined.
NOTE: All unknown arguments will be passed to Pyang as-is and without guarantees.- Visual Studio Code
- Python 3.10
- PDM package manager
Note: instructions with the same indentation are alternatives to eachother.
- Install
- dependencies through pdm (
pdm installin project root)- into the local
__pypackages__folder- to run your project as a python module
- locally (
python -m pydantify) - in a docker container (see Dockerfile)
- locally (
- to be accessed by your IDE for intellisense (see .vscode/settings.json)
- to be accessed by your debug launch configuration (see .vscode/launch.json)
- to run your project as a python module
- into the local
- project through pip (see guide for users)
- dependencies through pdm (
- Build
- through pdm (
pdm build)- into the local
distfolder- to be published on pypi
- through twine (
twine upload dist/*)
- through twine (
- to be published on pypi
- into the local
- through pdm (
- Dejan Jovicic and Dominic Walther, who laid the foundations of pydantify