To access the Python shell run the command: $ python3.11įrom here, you can run your Python code. You can also consider installing the Tkinter Python Library as shown $ sudo apt install python3.11-tk $ sudo apt install python3.11-devĪlso, consider installing the standard library `dbm.gnu` module $ sudo apt install python3.11-gdbmĪnd lastly, feel free to install the Python venv module that allows you to create virtual environments. To confirm that Python3.11 is installed, run the command: $ python3.11 -versionĪdditionally, there are some useful packages that supplement the default Python installation that you might consider installing.Ĭonsider installing development headers for building and compiling C extensions as follows. $ sudo apt updateįinally, use the APT command to install Python 3.11as shown. Next, update the package lists to sync your system with the newly added deadsnakes PPA. To continue adding the PPA, proceed and hit ENTER. $ sudo add-apt-repository ppa:deadsnakes/ppa So, proceed with the addition of the deadsnakes PPA. To successfully install Ubuntu, we need to add the deadsnakes PPA which provides the most recent versions of Python such as Python 3.7 and 3.8 for Ubuntu 18.04 and Python 3.9 to Python 3.11 For both Ubuntu 18.04 and Ubuntu 20.04. Once the software-properties-common package is in place, let’s head over to the next step. $ sudo apt install software-properties-common This provides an abstraction of APT repositories and provides some useful scripts that help you manage software applications from third-party vendors such as PPAs. Next, install the software-properties-common package. But first, refresh the Ubuntu package lists as follows. In this guide, we will walk you through the installation of Python 3.11 on Ubuntu 20.04 Step 1: Update the system & Install dependenciesĪs we set sail, the first step is to install dependencies that will be required during the installation of Python 3.11. Python 3.11 was released a few months ago this year, October, 2022 and provides a wide array of improvements such as faster speed of execution, better error diagnostics, and improved modules to mention just a few. It’s used in a wide selection of areas including data science, machine learning, rapid prototyping, and creating web applications. Python is regarded as one of most popular, multi-purpose and beginner-friendly programming languages.
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