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 3.10.3.

   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.

   

2. Enter the commands below.

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

   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. Again, use the pip or pip3 command that returns a version 3.4 or greater of Python.

   On Linux or Mac, 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
   

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

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

   Shell (Microsoft Windows)

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   cd %IQDIR17%\SDK\Python
   python setup.py install
   

   Shell (Linux)

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   cd $IQDIR17/sdk/python
   python setup.py install
   

   This should create additional build directories in the current folder.

2. On Microsoft Windows, create a user environment variable named SQLANY_API_DLL and set it to %IQDIR17%\Bin64\dbcapi.dll.

   

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.

   Shell (Microsoft Windows)

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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.

   Shell (Linux)

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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:

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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 HOTEL.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. Replace the host value.

4. 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 or 2 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.

   Shell (Microsoft Windows)

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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.

   Shell (Linux)

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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_Trial')
   
   #If no errors, print connected
   print('connected')
   
   curs = conn.cursor()
   sql_command = "select TITLE, FIRSTNAME, NAME from HOTEL.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. 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.