tagmapper 0.6.4

Python wrapper for SPD tag mapping database

tagmapper-sdk

Python package to get timeseries and constant value mappings for data models from SDP tag mapping library.

It supports SDP defined models for Separators and Wells as well as generic models with or without schema.

Authentication is done using Azure credentials and bearer tokens.

Use

1. See demo. Or try the following simple code.

   from tagmapper import Well
   w = Well("NO 30/6-E-2")  
   

2. Fetching the base view (well_attributes_mapped_to_timeseries_base) from the API:
   Refer to examples/demo_api_func.py:
   Fetch data for all facilities:
   

   from tagmapper.base_model import get_data_base_well
   df = get_data_base_well(limit=100000, offset=0) 
   print(df)
   

   Fetch data for selected facilities:

   from tagmapper.base_model import get_data_base_well
   facility_names = ['STATFJORD B','JOHAN SVERDRUP RP']
   df = get_data_base_well(facility_names, limit=10000, offset=0) # More facilit
   print(df)
   

   3. Getting a generic model with no schema from API:
      See demo. Example usage:

      from tagmapper import Model
      
      # Create a model
      model = Model.get_model(
      model_owner="example_owner",
      model_name="example_model",
      object_name="example_object")
      model.print_report()
      

Installing

Install from pypi using pip.
pip install tagmapper

Developing

Clone repo and run poetry install to install dependencies.

Testing

Run tests and check coverage using pytest-cov poetry run pytest --cov=tagmapper test/ --cov-report html