sm_data_ml_utils 1.0.5

Common Python tools and utilities for ML work

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 data-ml-utils --upgrade

Documentation

Head over to https://data-ml-utils.readthedocs.io/en/latest/index.html# to read our library documentation

Feature

Pyathena client initialisation

Almost one liner

import os
from 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

Visit link

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