Predictive Hacks

How to Access Snowpark with OKTA via Jupyter Notebook

Currently, Snowpark API supports only Python 3.8. We can create a virtual environment with Python 3.8 using conda and installing the numpy and pandas packages by typing:

conda create --name py38_env --override-channels -c python=3.8 numpy pandas

Then, we should activate the py38_env and install the following packages:

conda install snowflake-snowpark-python
conda install snowflake-snowpark-python pandas
pip install notebook

Note that there is a known issue with running Snowpark Python on Apple M1 chips due to memory handling in pyOpenSSL. The error message displayed is, “Cannot allocate write+execute memory for ffi.callback()”.

As a workaround, set up a virtual environment that uses x86 Python using these commands:

CONDA_SUBDIR=osx-64 conda create -n snowpark python=3.8 numpy pandas --override-channels -c
conda activate snowpark
conda config --env --set subdir osx-64

Access Snowpark with OKTA via Jupyter Notebook

Within the “py38_env” virtual environment, we can type to start the Jupyter Notebook

jupyter notebook

Once we open the Jupyter Notebook we can type:

from snowflake.snowpark import Session

connection_parameters = {
    "authenticator" : 'https://<company_domain>',
    "account":'<your account>',
    "role" : 'SYSADMIN'
new_session = Session.builder.configs(connection_parameters).create() 
# we get: <snowflake.snowpark.session.Session at 0x25f127ff530>

new_session.sql("SELECT count(*) FROM test_table").collect()
#we get [Row(COUNT(*)=229)]

#close the session

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