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Query and Ingestion Client for Azure using Python

Project description

Getting started

kustopy is a Python SDK for Azure Data Explorer (Kusto).

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Installation and Import

pip install kustopy
from kustopy import KustoPyClient as kpc

Client setup

# Get login credentials from Azure Vault
client_id = dbutils.secrets.get(scope="ce5", key="adxClientId")
client_secret = dbutils.secrets.get(scope="ce5", key="adxClientSecret")
tenant_id = dbutils.secrets.get(scope="ce5", key="adxTenantId")

# Set up the query client
kusto_client = kpc.Client(cluster='https://sample.kusto.windows.net/',
                          database='confidential-satanalytics-sample',
                          client_id=client_id,
                          client_secret=client_secret,
                          tenant_id=tenant_id,
                          truncation=False)

Queries

# Get list of all tables available in database
kusto_client.get_table_names()
# Write kusto queries to get data into pandas dataframe
kusto_client.query_to_df(user_input='SampleTable | take 100 | where fruit=="apple"')

Ingestions

# Drop table from the database
kusto_client.drop_table(tablename='SampleTable')
# Write pandas dataframe to the database. If the table exists you will get an Error.
kusto_client.write_table(dataframe=df, tablename='SampleTable')
# Write pandas dataframe to the database. If the table exists it will be replaced.
kusto_client.write_replace_table(dataframe=df, tablename='SampleTable')

If you want to append data to an existing table, we recommend querying the table to a pandas dataframe using .query_to_df(), doing the transformations within pandas and use .write_replace_table() to overwrite the existing table in the database. This gives you full access to the powerful functions of pandas.

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