Ctrl+K

IDE’s (interactive development environments)

IDE’s (interactive development environments)#

This section will provide you with information on the recommended IDE’s to use with the Python and R programming languages. Here we will cover their installation, setup and basic use.

Python#

Visual Studio Code#

VS Code is a robust IDE for working in Python. It has a wide variety of extensions that support python programming and integration with other languages and tools.

Installation#

The easiest way to install VS Code is directly from the website https://code.visualstudio.com/Download

Setup#

When you start using VS Code you will want to install some core extensions for working with Python. These are:

  • Python (which should also install Pylance)

  • Jupyter (which will install several related Jupyter extensions)

Basic usage#

  • Start by opening the folder for the project you are working on. This might be a git repo or an empty project folder

  • Setup a virtual environment. Virtual environments make it easier to manage the package dependencies for a project during development and deployment

  • To initialise a new virtual environment:

    1. Ensure you have opened the project folder you are working on. The virtual environment data (.venv) will be stored here

    2. Open a new terminal in VS Code by going to the tool bar at the top, clicking on ‘Terminal’, then selecting ‘New Terminal’ from the dropdown. This will open a new terminal at the bottom of the window

    3. Open the command palette by pressing cmd + shift + P

    4. The command palette will open at the top of the window

    5. Start typing ‘Python: Create Environment’ and select this option

    6. From the dropdown select the environment type venv

    7. Select a Python interpreter version

    8. You will see in the terminal that the current location is preceded by (.venv)

  • To initialise an existing virtual environment

    1. Open the project folder (likely a git repo you have cloned)

    2. Open a new terminal in VS Code by going to the tool bar at the top, clicking on ‘Terminal’, then selecting ‘New Terminal’ from the dropdown. This will open a new terminal at the bottom of the window

    3. In the terminal type source 'name_of_virtual_environment'/bin/activate the name of the virtual environment will likely be venv unless otherwise specified

    4. Open the command palette by pressing cmd + shift + P

    5. The command palette will open at the top of the window

    6. Start typing ‘Python: Select Interpreter’ and select this option

    7. From the dropdown select the Python interpreter specified in the virtual environment. This can be found in the ‘name_of_virtual_environment’/bin folder

  • Installing packages in your virtual environment

    • To install new packages to your virtual environment simply go to the terminal and type pip install ‘package_name’

    • The package name to be used at installation can easily be found by googling something like ‘Python pip install pandas’

    • You can also specifiy a specific version of a package if necessary otherwise the latest stable version compatible with you version of Python should be installed

Resources#

VS Code Python tutorial https://code.visualstudio.com/docs/python/python-tutorial

R#

R base and R Studio#

Installation#

To you R with R Studio, you need to first install R base then install R Studio. R Studio will then automatically locate R base if installed in this order.

Setup#

R Studio should work straight out of the box. It has a built in package manager function that allows you to easily install packages such as shiny, tidyverse, psych, dplyr, ggplot etc.

Basic usage#

The main thing to note when using R is to ensure that you set your working directory. This is done using the setwd() function or can be manually set within the IDE in the file explorer.

Resources#

Contents