Metadata-Version: 2.1
Name: azure-kusto-ingest
Version: 3.1.0
Summary: Kusto Ingest Client
Home-page: https://github.com/Azure/azure-kusto-python
Author: Microsoft Corporation
Author-email: kustalk@microsoft.com
License: MIT
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: License :: OSI Approved :: MIT License
Requires-Dist: azure-kusto-data (==3.1.0)
Requires-Dist: azure-storage-blob (<13,>=12)
Requires-Dist: azure-storage-queue (<13,>=12)
Provides-Extra: aio
Provides-Extra: pandas
Requires-Dist: pandas ; extra == 'pandas'

Microsoft Azure Kusto Ingest Library for Python
===============================================

.. code-block:: python

    from azure.kusto.data import KustoConnectionStringBuilder, DataFormat
    from azure.kusto.ingest import QueuedIngestClient, IngestionProperties, FileDescriptor, BlobDescriptor

    ingestion_props = IngestionProperties(database="{database_name}", table="{table_name}", data_format=DataFormat.CSV)
    client = QueuedIngestClient(KustoConnectionStringBuilder.with_interactive_login("https://ingest-{cluster_name}.kusto.windows.net"))

    file_descriptor = FileDescriptor("{filename}.csv", 15360)  # in this example, the raw (uncompressed) size of the data is 15KB (15360 bytes)
    client.ingest_from_file(file_descriptor, ingestion_properties=ingestion_props)
    client.ingest_from_file("{filename}.csv", ingestion_properties=ingestion_props)

    blob_descriptor = BlobDescriptor("https://{path_to_blob}.csv.gz?sas", 51200)  # in this example, the raw (uncompressed) size of the data is 50KB (52100 bytes)
    client.ingest_from_blob(blob_descriptor, ingestion_properties=ingestion_props)


Overview
--------

*Kusto Python Ingest Client* Library provides the capability to ingest data into Kusto clusters using Python.
It is Python 3.x compatible and supports data types through familiar Python DB API interface.

It's possible to use the library, for instance, from `Jupyter Notebooks <http://jupyter.org/>`_ which are attached to Spark clusters,
including, but not exclusively, `Azure Databricks <https://azure.microsoft.com/en-us/services/databricks>`_ instances.

* `How to install the package <https://github.com/Azure/azure-kusto-python#install>`_.

* `Data ingest sample <https://github.com/Azure/azure-kusto-python/blob/master/azure-kusto-ingest/tests/sample.py>`_.

* `GitHub Repository <https://github.com/Azure/azure-kusto-python/tree/master/azure-kusto-data>`_.


