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Project description
Snowpark Session Util
A simple utility for spark and mlflow session objects
Setup
Quick Install
python -m pip install snowpark_session
Build from source
Clone the repository
git clone https://github.com/Broomva/snowpark_session.git
Install the package
cd snowpark_session && make install
Build manually
After cloning, create a virtual environment
conda create -n snowpark_session python=3.8
conda activate snowpark_session
conda install snowflake-snowpark-python pandas
Install the requirements
pip install -r requirements.txt
Run the python installation
python setup.py install
Usage
The deployment requires a .env file created under local folder:
touch .env
It should have a schema like this:
snowflake_account=''
snowflake_user=''
snowflake_password=''
snowflake_user_role=''
snowflake_warehouse=''
snowflake_database=''
snowflake_schema=''
# Optional
azureml_experiment_name=''
azureml_experiment_id=''
azureml_subscription_id=''
azureml_resource_group=''
azureml_workspace_name=''
import snowpark_session as ss
# Create a Spark session
spark = ss.SnowparkSession().get_session()
# Connect to MLFLow Artifact Server
mlflow_session = ss.AzureMLFlowSession().get_session()
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