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azure-kusto-python/azure-kusto-ingest
mayamarom10 f90f2d258b
Fix json 401 error (#545)
* Updated handle_http_error to handle 401 errors and check if json is empty don't parse

* black

* black

* response.content -> response.text

* added UT

* changed PermissionError to KustoServiceError

* check exception error message

* deleted e2e test
2024-08-26 15:12:47 +03:00
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azure Bump 2024-06-19 10:21:57 +03:00
tests Fix json 401 error (#545) 2024-08-26 15:12:47 +03:00
MANIFEST.in
README.rst
azure-kusto-ingest.iml Changed dataframe_from_result_table function (#538) 2024-06-17 09:59:54 +03:00
setup.cfg
setup.py
tox.ini

README.rst

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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>`_.