Common Python tools and utilities for Hipages ML work
Project description
data-ml-utils
A utility python package that covers the common libraries we use.
Installation
This is an open source library hosted on pypi. Run the following command to install the library.
pip install hip-data-ml-utils --upgrade
Documentation
Head over to https://hip-data-ml-utils.readthedocs.io/en/latest/index.html# to read our library documentation
Feature
Pyathena client initialisation
Almost one liner
import os
from hip_data_ml_utils.pyathena_client.client import PyAthenaClient
os.environ["AWS_ACCESS_KEY_ID"] = "xxx"
os.environ["AWS_SECRET_ACCESS_KEY"] = "xxx" # pragma: allowlist secret
os.environ["S3_BUCKET"] = "xxx"
pyathena_client = PyAthenaClient()
Pyathena query
Almost one liner
query = """
SELECT
*
FROM
dev.example_pyathena_client_table
LIMIT 10
"""
df_raw = pyathena_client.query_as_pandas(final_query=query)
MLflow utils
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More to Come
- You suggest, raise a feature request issue and we will review!
Tutorials
Pyathena
There is a jupyter notebook to show how to use the package utility package for pyathena
: notebook
MLflow utils
There is a jupyter notebook to show how to use the package utility package for mlflow_databricks
: notebook
Project details
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