Metadata
Metadata queries provide contextual information for time series measurements and include information such as names, descriptions and units of measure.
Prerequisites
Ensure you have installed the RTDIP SDK as specified in the Getting Started section.
This example is using DefaultAuth() and DatabricksSQLConnection() to authenticate and connect. You can find other ways to authenticate here. The alternative built in connection methods are either by PYODBCSQLConnection(), TURBODBCSQLConnection() or SparkConnection().
Parameters
Name | Type | Description |
---|---|---|
tag_names | (optional, list) | Either pass a list of tagname/tagnames ["tag_1", "tag_2"] or leave the list blank [] or leave the parameter out completely |
Example
from rtdip_sdk.authentication.azure import DefaultAuth
from rtdip_sdk.connectors import DatabricksSQLConnection
from rtdip_sdk.queries import TimeSeriesQueryBuilder
auth = DefaultAuth().authenticate()
token = auth.get_token("2ff814a6-3304-4ab8-85cb-cd0e6f879c1d/.default").token
connection = DatabricksSQLConnection("{server_hostname}", "{http_path}", token)
data = (
TimeSeriesQueryBuilder()
.connect(connection)
.source("{tablename_or_path}")
.metadata(
tagname_filter=["{tag_name_1}", "{tag_name_2}"],
)
)
print(data)