Python is a highly versatile programming language, making it suitable for diverse domains such as web development, data analysis, and machine learning. One very important strength of Python is its extensive library support, which allow you to add a broad spectrum of additional functionalities for your code.
Moreover, Python can be used to interface with other software tools like Touch Designer, Unreal Engine, and Unity.
Miniforge, a distribution of Conda, serves as a comprehensive package manager and environment management system, simplifying package installation and dependency management. Its utility lies in the ability to manage separate Python environments for different projects. This in turn prevents issues from arising if different projects require different versions of Python or different versions of the same library. Another advantage of using environments is that they can easily be deleted once a project has been completed, which allows us to keep our core Python installation "clean" from add-ons that are no longer needed. Follow the steps below to install Miniforge on your system.
-
Navigate to the Miniforge GitHub page.
-
Download the Windows installer and run the setup file.
-
Choose "Run anyway" if a Windows Defender message appears.
-
Opt for the default installation options until the Advanced Installation Options menu.
-
In the Advanced Installation Options menu, select "Register Miniforge3 as my default Python 3.10."
-
Click Install.
Upon completion of the installation, you should be able to access a program called "Miniforge prompt." Open the prompt and enter either conda or mamba to confirm their functionality on your system.
Entering python --version should indicate that Python 3.10 is now part of your base environment. You will learn more about this later.
For macOS, you can install Miniforge using a script or through Homebrew.
- Visit the Miniforge GitHub page.
- Download the appropriate macOS script for your system.
- Open the terminal in the script download path.
- Execute the command
chmod +x Miniforge3-MacOSX-x86_64.shorchmod +x Miniforge3-MacOSX-arm64.shbased on the install script downloaded. - Run the script by entering
./Miniforge3-MacOSX-x86_64.shor./Miniforge3-MacOSX-arm64.shin the terminal depending on your install script and press enter. - Accept the license terms when prompted by entering yes.
- Confirm the install location by pressing enter when prompted.
- Enter yes when prompted to initialise Miniforge3 by running conda init.
In a terminal, enter the following command:
brew install miniforgeVerify the macOS installation by opening a new terminal and typing either conda or mamba.
Entering python --version should indicate that Python 3.10 is now part of your base environment. You will learn more about this later.
This guide introduces Python programming through the use of Visual Studio Code (VS Code), a versatile Integrated Development Environment (IDE) developed by Microsoft. IDEs offer a number of useful features for development, such as debugging, testing, Version Control software integration, and auto-completion. In time you'll find such tools will greatly enhance your productivity and will enable you to spot problems earlier. A stitch in time saves nine.
To install VS Code, download the appropriate setup file for your system from here and go through the setup steps. Alternatively, if you are on a UAL machine, you can use Self-Service if VS Code is not already installed.
With VS Code installed, we will now need to make it recognise our Conda/Mamba location. To do this, you must first make sure that VS Code has the Python Extension installed. This may be downloaded by following this link.
Now go into your Settings in VS Code by clicking on the cog icon in the bottom-left and then clicking on Settings.
Type "Conda" in the search to bring up the option for the Conda path.
Now you need to give it the path of either your Conda or Mamba installation. Both are fine. The steps to do this will vary depending on your system.
Open the Miniforge Prompt and type where conda or where mamba. Copy and paste the first path into the Conda Path field in the VS Code settings. Close the Settings tab.
In a terminal type whereis conda or whereis mamba. Copy and paste the output into the Conda Path field in the VS Code settings. Close the Settings tab.
Now that VS Code can see your Conda/Mamba installation, we can use its base environment as our interpreter for Python projects.
To do this we press Ctrl + Shift + P (Windows) or Command + Shift + P (Mac) to bring up VS Code's Command Palette.
Type in "Select Interpreter" and you should see the option of choosing a Python interpreter.
Clicking this will lead to a drop-down option of possible Python interpreters for our Python files. Select the base Conda/Mamba interpreter. This one will say "Conda" on the right.
Now any Python file run within VS Code will make use of the base Conda/Mamba environment by default. We will want to change this later on, but for now this works.
And here are the full steps in a gif.
When creating a new Python project, it is a good idea to create a separate environment for it. An environment is like a specialised Python installation that has all the libraries needed for a particular project. As you work with Python more, you will find that different projects require different libraries. Creating separate Python environments helps keep things tidy.
To create an environment, we give the following command:
Conda:
conda create -n <env-name>
Mamba:
mamba create -n <env-name>
By default, this will create an environment with the same Python version as your base environment.
Creating a new environment with a specific version of Python can be done with the following command:
Conda:
conda create -n <env-name> python=X.X
Mamba:
mamba create -n <env-name> python=X.X
To activate an environment we then use the following command:
Conda:
conda activate <env-name>
Mamba:
mamba activate <env-name>
When an environment has been activated, using the python command will cause that particular environment's version of python to be used rather than that of the base environment.
Using the deactivate command then allows you to return to the base environment:
Conda:
conda deactivate
Mamba:
mamba deactivate
In many cases, a library can be installed through Mamba or Conda. This can be achieved with the following command:
Conda:
conda install <library-name>
Mamba:
mamba install <library-name>
Alternatively, a library can also be installed with pip. This will also install the library to the environment.
pip install <library-name>
Python can be run in the terminal. This can be useful if you want to do something simple, like checking if a library you've installed is working.
We can also use Python scripts. These are files that end in the .py extension. Below is an example of a basic Python script being executed.
Notebooks are another way of using Python. The notebook for the Introduction to Python workshop can be found here.
- Python is a versatile programming language.
- To effectively manage diverse Python project requirements, we employ virtual environments.
- Conda and Mamba facilitate quick creation of virtual environments and library installations.
- IDEs provide comprehensive tools and features to streamline and facilitate the entire software development process, including code writing, debugging, and project management.
- Python can be used in the terminal, in Python script files, or in notebooks.