Configuring the Python Machine Learning Client for SAP HANA

To effectively work with classification models in SAP HANA, you will need the following prerequisites:

• Instance of SAP HANA Cloud with ScriptServer (APL, PAL enabled)
• Python hana-ml package 2.21.24062800, other packages and dependencies installed
• Basic Structured Query Language (SQL) knowledge is highly desirable

Before implementing classification models in SAP HANA, it is essential to set up the required environment. This includes installing the necessary Python libraries, establishing a connection to SAP HANA Cloud, and configuring authentication settings to ensure seamless integration and secure access to machine learning functions.

The following cell loads/imports diverse modules needed for the current Demo. As you may know a module can be considered to be the same as a code library.

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import hana_ml
print(hana_ml.__version__)

2.20.24042601

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#importing other packages used
import pandas as pd
import matplotlib.pyplot as plt
import time
import numpy as np
import os
import time
import json
from hana_ml.visualizers.unified_report import UnifiedReport
from hana_ml.algorithms.pal.unified_classification import UnifiedClassification
from hana_ml.algorithms.pal.partition import train_test_val_split

%matplotlib inline

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from hana_ml import dataframe

address = "b8xxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx.hana.prod-eu10.hanacloud.ondemand.com"
port = 443
user = 'ML_DEMO'

conn = dataframe.ConnectionContext(address, port, user, encrypt=True, sslValidateCertificate=False)

# Control connection
print(conn.connection.isconnected())
print(conn.hana_version())