pyPrediktorMapClient

Helper functions for Prediktor Map Services

Helper functions for communicating with Prediktors OPC UA ModelIndex REST-API and OPC UA Values REST-API. Typically used for data anlytics purposes, you'll find Jypiter Notebooks with examples in the notebooks folder.

Install is primarily done through PyPi with pip install pyPrediktorMapClient. If you want to contribute or need run the Jupyter Notebooks in the notebooks folder locally, please clone this repository.

To use after install

Example:

from pyprediktormapclient.model_index import ModelIndex
from pyprediktormapclient.opc_ua import OPC_UA

model = ModelIndex(url=your_model_index_url)
tsdata = OPC_UA(rest_url=your_opcua_rest_url, opcua_url=your_opcua_server_uri)

obj_types = model.get_object_types()

Further information, documentation and module reference on the documentation site and check out the jypiter notebooks in the notebooks folder.

Setup to Install

1. First clone the repository and navigate to the main folder of repository.

git clone [email protected]:PrediktorAS/pyPrediktorMapClient.git

2. Create Virtual environment

python3 -m venv .venv
source .venv/bin/activate

3. Install dependencies As this is a python package, dependencies are in setyp.py (actually in setup.cfg, as this is a pyScaffold project). Requirements.txt will perform the correct installation and add a couple of additional packages

pip install -r requirements.txt

4. Run tests

tox

5. Do your changes Add whatever you need and create PRs to be approved
6. Build

tox -e build

7. Publish to PyPi test and live

tox -e publish
tox -e publish -- --repository pypi