An overview of IKATS global architecture is available here
This component, developed in python, is the core of IKATS python part. It is directly used by algorithms implementations to access data to compute (read/write). It is composed of:
- a RESTful API to access to the data model (datasets, functional identifiers, metadata, tables, time series, process data) through ikats-datamodel component
- an execution engine for IKATS algorithms
- an access to algorithms catalog
Some examples of use of IKATS API:
from ikats.core.resource.api import IkatsApi
# retrieving metadata for a list of tsuid
meta_list = IkatsApi.md.read(tsuid_list)
# Creating new reference in database for new timeseries
IkatsApi.ts.create_ref(func_id)
# Importing time series data in database
IkatsApi.ts.create(fid=fid, data=data, generate_metadata=True, sparkified=True)
# Retrieve imported number of points from database
qual_nb_points = IkatsApi.ts.nb_points(tsuid=tsuid)
# Inherit metadat from parent
IkatsApi.ts.inherit(tsuid, tsuid_origin)