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Project description
mlplatformutils
mlplatformutils for observability
Structure
.
|-- LICENSE.txt
|-- README.rst
|-- setup.cfg
|-- setup.py
|-- src
| |-- mlplatformutils
| | |-- __init__.py
| | |-- core
| | |-- |-- __init__.py
| | |-- |-- sparkutils.py
| | |-- |-- platformutils.py
| | |-- |-- pandasutils.py
| | |-- |-- lineagegraph.py
| | |-- |-- app_insights_logger.py
|-- tests
| |-- __init__.py
| |-- core
| |-- |--__init__.py
| |-- |-- sparkutils.py
| |-- |-- platformutils.py
| |-- |-- pandasutils.py
| |-- |-- lineagegraph.py
| |-- |-- app_insights_logger.py
Instructions
install twine - twine is a utility package that is used for publishing Python packages on PyPI
python -m pip install twine
Build Package - create the source distribution of the package
python setup.py sdist
Upload Package to PyPI
**python -m twine upload dist/ ***
Description
app_insights_logger - Constains telemetrylogger Class with Functions to Manage and Log Telemetry into Azure Application Insights lineagegraph - Contains LineageGraph Class with functions to manage Graph on Azure Cosmos DB enabled with Gremlin
platformutils - Contains platform utility functions to check, install depedencies, check Azure ML Compute
- is_package_installed
- install_pip
- get_environment
- set_environment
- assert_amlcompute
- read_setup_ini
sparkutils - Contains functions to read data from sources such as (Azure Data Lake Gen2, Azure Data Explorer (Kusto), Azure Sql Server) and write (Azure Data Lake Gen2)while ensuring integrated Lineage Graph Logging.
- read_from_adls_gen2
- write_to_adls_gen2
- read_from_kusto
- read_from_azsql
pandasutils - Contains functions to read data from Azure Data Lake Gen2 (from Delta Format or Parquet Format) into Pandas Dataframe without Spark while ensuring integrated Lineage Graph Logging.
- read_from_delta_as_pandas
- read_from_parquet_as_pandas
Examples
from mlplatformutils.core.platformutils import is_package_installed
print(is_package_installed("pandas"))
from mlplatformutils.core.app_insights_logger import telemetrylogger
from mlplatformutils.core.lineagegraph import LineageGraph
from mlplatformutils.core.sparkutils import write_to_adls_gen2, read_from_adls_gen2
import mlplatformutils.core.platformutils as mlpu
mlpu.version
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