Connect to Data Lake Relational Engine Using Python Drivers

The first step is to check if Python and pip are installed.

1. Enter the commands below.

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   python --version
   python3 --version

   If Python is installed, the command will return a value such as Python 3.13.0

   In some Linux distributions, ‘python’ refers to Python 2, while ‘python3’ refers to Python 3. However, as Python 2 is now obsolete, ‘python’ may refer to Python 3 instead. It may also be referred to by its specific version such as python3.13.

   If Python is not installed, it can be downloaded from Python downloads.

   On Microsoft Windows, check the box that says Add Python 3.x to PATH as shown below to ensure that the interpreter will be placed in your path. The Microsoft Windows command prompt or shell will need to be reopened after Python is installed to pick up the path to python.

   

   On OpenSUSE Tumbleweed, yast can be used to install python313. Once it has been installed its version can be seen with the below command.

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   python3.13 --version

2. Enter the commands below.

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   pip --version
   pip3 --version
   pip install --upgrade pip

   If you encounter issues with user permissions, run command prompt as an administrator and try again.

   The standard package installer for Python is pip. The following commands will check the version of pip and attempt to upgrade it to the latest available version.

   On Linux, if you encounter permission issues, one way to solve the issue is to use sudo before the command.

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   On Linux, if Python is installed but pip is not, it can be installed on openSUSE using Zypper as shown below.

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   zypper install python3-pip

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The sqlanydb package is the python driver for the data lake Relational Engine and is available as part of the data lake Relational Engine install and is available at PyPI.

1. Navigate to your Data Lake Client installation folder and enter the following command to install the python driver named sqlanydb.

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   cd %HDL_CLIENT_HOME%\SDK\Python
   pip install sqlanydb-1.0.14.tar.gz

   On Linux the rest of the steps will be executed in a virtual environment.

   First make a project folder, and create a virtual environment inside it. To do so, open the terminal app, write the following command, and hit return, here pyvenv is the name of the folder that you wish to create the virtual environment in.

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   mkdir $HOME/pyvenv

   Now, use the venv command to create a virtual environment inside the given folder, here python-virtualenv is the name of the virtual environment that is to be created.

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   cd $HOME/pyvenv
   python3 -m venv pyvenv/python-virtualenv

   We now activate the virtual environment, which we will use to complete the rest of the steps for linux based systems.

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   source pyvenv/python-virtualenv/bin/activate

   A successful activation looks like this:-

   

   Now install the driver named ‘sqlanydb’.

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   cd $HDL_CLIENT_HOME/sdk/python
   pip install sqlanydb-1.0.14.tar.gz

1. In a shell, create a folder named python-sqlanydb, enter the newly created directory, and open a file name pythonQuery.py in an editor.

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   mkdir %HOMEPATH%\DataLakeClientsTutorial\python-sqlanydb
   cd %HOMEPATH%\DataLakeClientsTutorial\python-sqlanydb
   notepad pythonQuery.py

   Substitute pico below for your preferred text editor.

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   mkdir -p $HOME/DataLakeClientsTutorial/python-sqlanydb
   cd $HOME/DataLakeClientsTutorial/python-sqlanydb
   pico pythonQuery.py

2. Copy the following code into pythonQuery.py. Replace the host value.

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   #Import your dependencies
   import sqlanydb
   
   #Initialize your connection
   conn = sqlanydb.connect(uid='USER1', pwd='Password1', host='XX.iq.hdl.trial-us10.hanacloud.ondemand.com:443',enc='TLS{tls_type=rsa;direct=yes}')
   
   #If no errors, print connected
   print('connected')
   
   curs = conn.cursor()
   sql_command = "select TITLE, FIRSTNAME, NAME from HOTELS.CUSTOMER;"
   curs.execute(sql_command)
   rows = curs.fetchall()
   for row in rows:
       for col in row:
           print ("%s" % col, end=" ")
       print ("  ")
   
   curs.close()
   conn.close()

3. Save and close pythonQuery.py. Run the app. Make sure your data lake Relational Engine is running before executing the app.

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   python pythonQuery.py

   

For further information on the Python Driver, visit Python and Database Access.

This is an alternate method of connecting to a data lake Relation Engine from a Python app. The Python ODBC bridge is an open source Python module available on PyPI. The performance characteristics between the two drivers may vary depending on the use case.

1. Ensure that you have created a connection to the data lake Relational Engine using ODBC as shown in step 1 (Windows) or 2 (Linux) of the Connect to Data Lake Relational Engine Using the ODBC Driver tutorial.

2. The repository that contains Python packages is PyPI and includes a package for the pyodbc driver.

   

3. Install pyodbc

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   pip install pyodbc

   If this command fails on Microsoft Windows with an error “Microsoft Visual C++ 14.0 is required”, additional details can be found at Unable to install pyodbc using python 3.10 in windows 10 and Release python 3.10 win wheels for pyodbc.

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   If this command fails on Linux, you may need to install gcc-c++, python3-devel, and unixodbc-dev.

1. In a shell, create a folder named python-pyodbc, enter the newly created directory, and open a file name pythonQuery.py in an editor.

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   mkdir %HOMEPATH%\DataLakeClientsTutorial\python-pyodbc
   cd %HOMEPATH%\DataLakeClientsTutorial\python-pyodbc
   notepad pythonQuery.py

   Substitute pico below for your preferred text editor.

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   mkdir -p $HOME/DataLakeClientsTutorial/python-pyodbc
   cd $HOME/DataLakeClientsTutorial/python-pyodbc
   pico pythonQuery.py

2. Copy the following code into pythonQuery.py.

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   #Import your dependencies
   import pyodbc
   
   #Initialize your connection
   conn = pyodbc.connect(uid='USER1',pwd='Password1',dsn='HC_DL')
   
   #If no errors, print connected
   print('connected')
   
   curs = conn.cursor()
   sql_command = "select TITLE, FIRSTNAME, NAME from HOTELS.CUSTOMER;"
   curs.execute(sql_command)
   rows = curs.fetchall()
   for row in rows:
       for col in row:
           print ("%s" % col, end= " ")
       print ("  ")
   
   curs.close()
   conn.close()

   Save and close pythongQuery.py.

3. The dsn value refers to the data source name in the Microsoft Windows ODBC Administrator or the Linux .odbc.ini file.

   

   or

   

4. Run the app.

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   python pythonQuery.py

   On some Linux distributions, python refers to a 2.x version of Python. If so, replace python with python3.

   

The code in pythonQuery.py uses PEP 249 – Python Database API Specification, which defines a set of methods that provide a consistent database interface, independent of the actual database being used.

Visual Studio Code provides plugins for Python and can be used to debug an application.

1. If you have not already done so, download Visual Studio Code.

2. If you have not already done so, in Visual Studio Code, choose File | Add Folder to Workspace, and then add the DataLakeClientsTutorial folder.

   

3. Open the file pythonQuery.py.

   

   Visual Studio Code will recognize the py file extension and will suggest installing the Python extension. Click Install.

4. Place a breakpoint on line the line for row in rows:.

5. Select Run | Start Debugging | Python File Debug the currently active Python file.

   Notice that the program stops running at the breakpoint that was set.

   Observe the variable values in the leftmost pane. Step through code.

   

Congratulations! You have now created and debugged a Python application that connects to and queries a data lake Relational Engine database.