Introduction

Welcome to the BK7084-Computational Simulation. This is a tutorial to help you setup the Python programming environment so that you can jump right into the practical courses.

Coding Environment Setup

Install a Python interpreter

To run a Python program, you need something called an interpreter. This is a piece of software that runs each command in your code. Python is pre-installed on macOS and Linux, while Windows users must manually install it. You can have multiple installations of Python on the same machine, just like you can have different versions of Microsoft Office or Adobe Photoshop. To manage all these installations and make sure we use the right one, we’ll use the Python environment manager Anaconda to install Python.

Install mini-anaconda

Windows

  1. download the latest Miniconda installer for Windows 64-bit from

https://docs.conda.io/en/latest/miniconda.html#latest-miniconda-installer-links.

  1. Double-click the .exe file you just downloaded.
  2. Follow the instructions on the screen. If you are unsure about any setting, accept the defaults. You can always change them later. When the installation is complete, launch the Anaconda Prompt from the Start menu.
  3. To test your installation. Run the conda list command from your Anaconda prompt. A list of installed packages appears if it has been installed correctly.

macOS

  1. Download the latest version of Miniconda that matches your computer’s processor (Intel or Apple M1) from

https://docs.conda.io/en/latest/miniconda.html#latest-miniconda-installer-links.

  1. Double-click the downloaded installer and then follow the instructions on the screen.
  2. Test your installation. Open up Terminal on your Mac (you can search for the app in Spotlight by pressing command + spacebar), type in conda and press Enter. You should see instructions for Conda in your terminal window.

Linux

Enter your terminal, then follow the steps:

  1. Download the latest shell script 
    wget -c https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh
  2. Run the installation script then follow the instructions on the screen 
    sh ./Miniconda3-latest-Linux-x86_64.sh
  3. To test your installation. In your terminal, run the command conda list. A list of installed packages appears if it has been installed correctly.

Create a new Python environment

We can manage Python installations by setting up an environment. An environment contains the Python interpreter and some other necessary Python packages. Once an environment is activated, anytime you run Python, it will be the version that is installed in that environment with the packages that were installed in that environment.

Inside of your Anaconda Prompt (on Windows) or Terminal (macOS, Linux) run the following command:

conda create --name compsim python=3.9

This will create a environment named as compsim. Of course you can name it whatever you want. Later we will install some packages inside of this environment. Right after the creation, you can activate this environment use

conda activate compsim

To test if everything works well, type in python and press enter in the command prompt/terminal. You should be able to see a python interpreter popped up:

(compsim) ~/00_introduction > python
Python 3.9.15 (main, Nov 1 2022, 14:18:21) [GCC 12.2.0] on linux
Type "help", "copyright", "credits", or "license" for more information.
>>>

Install Visual Studio Code and the Python Extension

Visual Studio Code

Go to https://code.visualstudio.com/Download and download the corresponding installer for your system.

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Once the Visual Studio Code editor is installed, install the Python extension. Open your Visual Studio Code, and search python in Extensions tab.

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Start VS Code in a project folder

Create an empty folder called hello, and open the folder from VS Code: Menu > File > Open Folder…

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From the File Explorer toolbar, select the New File button on the hello folder:

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Name the file hello.py, and it automatically opens in the editor:

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Enter the following source code in hello.py:

print("Hello World")

Before we run it, we need to select a Python interpreter: within VSCode, open the Command Palette (Ctrl+Shift+P), and then type Python: Select Interpreter command to search, then select the command. The command presents a list of available interpreters that VS Code can find automatically, you should be able to see bk7084-env, the environment we just created. Click to choose it. If you don’t see the name bk7084-env, close VS Code, open Ananconda-Prompt then run command

conda activate compsim

and reopen the VS Code, you should now be able to choose the environment that we created.

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Now you can run the script by simply click the Run Python File in Terminal play button in the top-right side of the editor.

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The button opens terminal panel in which your Python interpreter is automatically activated, then runs python hello.py.

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As you can see, the Hello World is successfully printed on the screen in terminal.

Assignments Setup

To get your assignments, click the Download assignments button at the top of the page or go to https://github.com/bk7084/assignments, click Code then Download ZIP.

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Extract the zip file to your preferred location. Open the folder 00_introduction in VS Code, then open the file intro.py. You can try to run the file by clicking the Run Python File on top-right. Your terminal probably gives the following error: ModuleNotFoundError: No module named ’bk7084’

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So, what exactly is a Python module? Simply put, a module is a python file that contains definitions of functions, classes, and variables. In our case, it means that we need to install this module or package named bk7084.

Open Anaconda-Prompt, then activate compsim using

conda activate compsim

type the following command to install the missing bk7084 module

pip install bk7084

pip is the standard package manager for Python. It allows you to install and manage additional packages that are not part of the Python standard library.

Once the installation is finished, try again to run the intro.py, you should have a window with a brownish triangle drawn above like this:

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Congratulations! You now have a Python environment with necessary packages to run all the exercises. Now finish exercises inside intro.py.