Skip to main content

Azure Data Explorer (Kusto) dialect for SQLAlchemy

Project description

Azure Data Explorer (Kusto) dialect for SQLAlchemy

pypi

sqlalchemy-kusto implements a DBAPI (PEP-249) and SQLAlchemy dialect that enables SQL query execution via SQLAlchemy.

Current project includes support for two dialects: SQL dialect and KQL dialect.

SQL dialect

Current implementation has full support for SQL queries. But pay your attention that Kusto implementation of T-SQL has not full coverage; check the list of known issues.

KQL dialect

KQL dialect still in progress. Please, use it on your own risk for now.

Notice that implemented Kusto dialects don't support DDL statements and inserts, deletes, updates.

Installation

pip install sqlalchemy-kusto

Library usage

Using DBAPI

from sqlalchemy_kusto import connect

connection = connect(
        cluster=kusto_url,
        database=database_name,
        msi=False,
        user_msi=None,
        azure_ad_client_id=kusto_client_id,
        azure_ad_client_secret=kusto_client_secret,
        azure_ad_tenant_id=kusto_tenant_id,
        dev_mode=False
)

result = connection.execute(f"select 1").fetchall()

Using SQLAlchemy raw sql

from sqlalchemy.engine import create_engine

engine = create_engine(
    f"kustosql+{kusto_url}/{database_name}?"
    f"msi=False&azure_ad_client_id={kusto_client_id}&"
    f"azure_ad_client_secret={kusto_client_secret}&"
    f"azure_ad_tenant_id={kusto_tenant_id}&"
    f"dev_mode=False"
)
engine.connect()
cursor = engine.execute(f"select top 1")
data_rows = cursor.fetchall()

Using SQLAlchemy

from sqlalchemy import create_engine, MetaData, Table, Column, String, Integer

engine = create_engine(
    f"kustosql+{kusto_url}/{database_name}?"
    f"msi=False&azure_ad_client_id={kusto_client_id}&"
    f"azure_ad_client_secret={kusto_client_secret}&"
    f"azure_ad_tenant_id={kusto_tenant_id}"
)

my_table = Table(
        "MyTable",
        MetaData(),
        Column("Id", Integer),
        Column("Text", String),
)

query = my_table.select().limit(5)

engine.connect()
cursor = engine.execute(query)
print([row for row in cursor])

Using with Apache Superset

Apache Superset starting from version 1.5 also supports Kusto database engine spec.
When connecting to a new data source you may choose a data source type either KustoSQL or KustoKQL depending on the dialect you want to use.

There are following connection string formats:

# KustoSQL
kustosql+https://<CLUSTER_URL>/<DATABASE>?azure_ad_client_id=<CLIENT_ID>&azure_ad_client_secret=<CLIENT_SECRET>&azure_ad_tenant_id=<TENANT_ID>&msi=False

# KustoKQL
kustokql+https://<CLUSTER_URL>/<DATABASE>?azure_ad_client_id=<CLIENT_ID>&azure_ad_client_secret=<CLIENT_SECRET>&azure_ad_tenant_id=<TENANT_ID>&msi=False

Important notice on package version compatibility.
Apache Superset stable releases 1.5 and 2.0 dependent on sqlalchemy==1.3.24. If you want to use sqlalchemy-kusto with these versions you need to install version 1.* of the package.

Current master branch of the apache/superset dependent on sqlalchemy==1.4.36. If you want to use sqlalchemy-kusto with the latest unstable version of apache/superset, you need to install version 2.* of the package.

Contributing

Please see the CONTRIBUTING.md for development setup and contributing process guidelines.


Issue in Apache Superset repository that inspired current solution.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

sqlalchemy_kusto-3.0.0.tar.gz (20.9 kB view details)

Uploaded Source

Built Distribution

sqlalchemy_kusto-3.0.0-py3-none-any.whl (19.4 kB view details)

Uploaded Python 3

File details

Details for the file sqlalchemy_kusto-3.0.0.tar.gz.

File metadata

  • Download URL: sqlalchemy_kusto-3.0.0.tar.gz
  • Upload date:
  • Size: 20.9 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.0.1 CPython/3.10.15

File hashes

Hashes for sqlalchemy_kusto-3.0.0.tar.gz
Algorithm Hash digest
SHA256 4eee4ff4f5f466afc734c6047db447615e3cad8bd374d75c365c81ea8ac25e13
MD5 94c1e0203fdd533ae3456940c7cf7d35
BLAKE2b-256 822fc068ec5bba11de5d74c4f8434319d390d97cefbfeffa6d00fcf5af0ac417

See more details on using hashes here.

File details

Details for the file sqlalchemy_kusto-3.0.0-py3-none-any.whl.

File metadata

File hashes

Hashes for sqlalchemy_kusto-3.0.0-py3-none-any.whl
Algorithm Hash digest
SHA256 009309ea1e544c0b6921637ef9debae52c1a1c9c4f8313700cf7d85096219db5
MD5 e24f6a10a66c6d0179dc18355c3a3301
BLAKE2b-256 7e0ec037ee7042b19062a7bc409bc74eae6092c46b2557b6351ca7032295ef9d

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page