Getting Started with Python in Visual Studio Code textbook (2023)

In this tutorial, you'll use Python 3 to create a simple "Hello World" Python application in Visual Studio Code. ThroughPython-extension, turn your VS code into a great, lightweight Python editor.

In this tutorial, you'll learn about VS Code for Python development, specifically how to edit, run, and debug code with the following tasks:

• Write, run, and debug a "Hello World" application in Python
• Learn how to install packages by creating Python virtual environments
• Write a simple Python script to plot numbers in VS Code

This tutorial is not intended to teach you Python itself. Once you learn the basics of VS Code, you can do anything fromprogramming instructions at python.orgunder VS Code for an introduction to the language.

If you have problems, you can search the page for an answer or ask a questionPython Extensions Discussions Questions and Answers.

Requirements

To successfully complete this tutorial, you must first set up your Python development environment. Specifically, this guide requires:

• Python 3
• Code VS
• Python extension of VS code

Install Visual Studio Code and the Python extension

1. If you haven't already, install itCode VS.

2. Then installPython extension for VS Codefrom the Visual Studio Marketplace. For more information about installing extensions, seeexpansion market. The name of the Python extensionPythonand is published by Microsoft.

Install the Python interpreter

With the Python extension, you must install the Python interpreter. Choosing a translator depends on your specific needs, but here are some guidelines.

ramen

installPython used python.org. You can usually useDownload Pythonbutton that appears first on the page to download the latest version.

Remark: If you don't have administrative access, an additional option to install Python on Windows is to use the Microsoft Store. The Microsoft Store offers installationssupported versions of python.

For more information about using Python on Windows, seeUsing Python on Windows at Python.org

Mac operating system

Installing Python on macOS is not supported. Instead, a package management system such asCook yourselfit is recommended. Use to install Python with Homebrew on macOSbrew install python3u de Terminal-prompt.

RemarkOn macOS, make sure the VS Code installation location is included in the PATH environment variable. Seethese installation instructionsFor more information.

Linux

The built-in installation of Python 3 on Linux works fine, but to install other Python packages, you'll need to install themPipzget-pip.py.

other options

• Data science: If your primary purpose of using Python is Data Science, consider downloading sHe liked it. Anaconda provides not only a Python interpreter, but also many useful data science libraries and tools.

• Windows Subsystem for Linux: If you use Windows and need a Linux environment to work with Python,Windows Subsystem for Linux(WSL) is the option for you. If you choose this option, you will also want to installWSL-extension. For more information on using WSL with VS Code, seeVS remote code developmentor try toRad the WSL Tutorialwhich walks you through configuring WSL, installing Python, and creating a Hello World application that runs on WSL.

Check your Python installation

To verify that Python has been successfully installed on your computer, run one of the following commands (depending on your operating system):

• Linux/macOS: open a terminal window and type the following command:

  python3 --version

• Windows: Open a command prompt and run the following command:

  (Video) Learn Python 3: Visual Studio Code for Beginners

  py-3--version

If the installation was successful, the launch window should show the installed version of Python.

RemarkYou can usepy-0command in VS Code's integrated terminal to view the versions of python installed on your computer. The default interpreter is marked with an asterisk (*).

Run VS Code in the workspace folder

Running VS code in a folder makes that folder your "workspace". VS Code stores settings specific to this workspace.vscode/settings.jsonwhich are independent of globally saved user settings.

Using the command line or terminal, create an empty directory called "hello", navigate to it, and open VS Code (to code) in this folder (.) by entering the following commands:

hello thereCDHelloto code.

Remark: If you're using Anaconda, make sure you're using Anaconda's command line.

Alternatively, you can launch VS Code from the operating system's user interface and then use itFile > Open Folderto open the project folder.

Select the Python interpreter

Python is an interpreted language. So to run python code and get python intellisense, you need to tell VS Code which interpreter to use.

From VS Code, select the Python 3 interpreter by opening the fileCommand palette(⇧⌘str(Windows, LinuxCtrl+Shift+P)), start typingPython: Choose an interpretersearch, and then select a command. You can also use the so-calledSelect the Python environmentoption in the status bar, if available (it may also already show the selected translator):

The command presents a list of available interpreters that VS Code can find automatically, including virtual environments. If you don't see the translator you want, take a lookSet up Python environments.

Remark: When using the Anaconda distribution, the correct interpreter must have a suffix("osnova": conda), For examplePython 3.7.3 64-bitni ("base":conda).

Interpreter selection determines which interpreter the Python extension will use for that workspace.

Remark: If you select an interpreter without an open workspace folder, VS codepython.defaultInterpreterŚcieżkainstead of at the user scope which is generally set by the default VS code interpreter. The user setting ensures that you always have a default interpreter for python projects. Workspace settings allow you to override user settings.

Create a Python Hello World source code file

Select the file from the Explorer toolbarnew filebutton onHelloduration:

Give the file a namehoi.pyand it will automatically open in the editor:

door.pyfile, you tell VS Code to interpret that file as a Python content evaluator with a Python extension and interpreter of your choice.

Remark: The File Explorer toolbar also lets you create folders in your workspace to better organize your code. You can useNew cardbutton to quickly create a folder.

Now that you have the code file in your workspace, enter the following source codehoi.py:

message ="Hello World"to print(message)

When you start writingto print, notice howIntelliSensepresents auto-completion options.

IntelliSense and auto-completion work with standard Python modules and other packages installed in the chosen Python interpreter environment. It also provides completions of methods available for object types. For example becausemessagevariable contains a string, IntelliSense provides string methods as you typemessage:

You can experiment a bit more with IntelliSense, but then undo the changesmessagevariable ito printcall and save the file (⌘S(Windows, LinuxCtrl+S)).

For more information on editing, styling, and refactoring, seeEdit the code. The Python extension also has full support forfight.

Start Hello World

It is easy to usehoi.pywith Python. Just clickRun the python file in the terminalthe play button in the upper right corner of the editor.

The button opens a terminal panel where the Python interpreter is automatically activated and then startedpython3 halo.py(macOS/Linux) lubpython halo.py(Ramen):

There are three other ways to run Python code in VS Code:

• Right-click anywhere in the editor window and selectRun the python file in the terminal(which automatically saves the file):

  

• Select one or more lines, then pressShift+Enteror right-click and selectExecute the selection/rule in python terminal. This command is useful for testing only part of a file.

• From the command palette (⇧⌘str(Windows, LinuxCtrl+Shift+P)), ChoosePython: Run REPLcommand to open a terminal REPL for the currently selected python interpreter. In the REPL, you can then enter and execute lines of code one by one.

Configure and run the debugger

Now let's try to debug our simple Hello World program.

First set a breakpoint on line 2hoi.pyplacing the cursor onto printcall and pressF9. Or just click on the left pane of the editor, next to the line numbers. When a breakpoint is set, a red circle appears in the margin.

Then press to run the debuggerF5. Since this is the first time you are debugging this file, a configuration menu opens from the command palette where you can select the type of configuration to debug for the open file.

Remark: VS Code uses JSON files for all its various configurations;run.jsonis the default name of the debug configuration file.

These different configurations are fully explained inDebugging configurations; just choose nowpython zaliha, which is a configuration that executes the current file displayed in the editor using the currently selected Python interpreter.

You can also start the debugger by clicking the down arrow next to the run button in the editor and selectingDebug python file in terminal.

The debugger stops at the first line of the file breakpoint. The current row is marked with a yellow arrow in the left margin. If you are researchingLocalthe variables window at this point will now see definedmessagethe variable appears in theLocalglas.

The Debug toolbar appears at the top with the following commands from left to right: continue (F5), krok nad (F10), Enter (F11), Exit (⇧F11(Windows, LinuxShift+F11)), restart (⇧⌘F5(Windows, LinuxCtrl+Shift+F5)), and stand (⇧F5(Windows, LinuxShift+F5)).

The status bar also changes color (orange in many themes) to indicate that you are in debug mode. ThePython Debug consoleit also automatically appears in the lower right pane to display the commands that are executed along with the program output.

To continue running the program, select Continue on the Debug toolbar (F5). The debugger runs the program to the end.

AdviceDebug information can also be viewed by hovering over code such as variables. In case ofmessage, when you hover over a variable, a string of characters is displayedHello worldin the box above the variable.

You can also work with u variablesDebug console(If you don't see it, select itDebug consolein the lower right of the VS Code or select it...menu.) Then try entering the following lines one by one, w>query at the bottom of the console:

messagemsg.capital()msg.split()

Choose blueBuckle upagain on the toolbar (or press F5) to run the program to the end. "Hello World" appears in thePython Debug consoleif you go back to it and VS Code exits debug mode after the program exits.

If you restart the debugger, the debugger stops at the first breakpoint.

To stop the program before it finishes, use the red square stop button on the debug toolbar (⇧F5(Windows, LinuxShift+F5)) or usedStart > Stop met foutopsporingmenu command.

See for detailsDebugging configurations, which contains notes on using a particular Python interpreter for debugging.

Tip: Use points to log in instead of printing statements: Developers often make source code clutteredto printinstructions for quickly viewing variables without going through each line of code in the debugger. In VS Code you can use this insteadPoints to apply. A log point is similar to a breakpoint, except that it logs a message to the console and does not stop the program. For more information seePoints to applyin the main VS Code Debugging article.

Install and use packages

Now let's look at an example that is a little more interesting. In Python, packages are a way to get any number of usable code libraries, usually from themPyPI. In this example, usematplotlibandnumberpackages for creating graphical charts, as is often the case in data science. (Notice thismatplotlibcannot display graphs during operationWindows Subsystem for Linuxbecause it doesn't have the necessary UI support).

Back totrackerview (top left icon showing files), create a new file namedstandard graph.pyand paste the following source code:

importmatplotlib.pyplotHowpltimportnumberHownpx = np.linspatie(0,20,100)# Create a list of evenly spaced numbers in a rangeplt.plot(x, np.sin(x))# Draw the sine of each point xplt.show()# View the chart

Advice: If you enter the above code manually, the autocompletes can be renamed after thisHowkeywords when pressedA nurseat the end of the line. Enter a space to avoid thisA nurse.

Then try running the file in the debugger using the "Python: current file" configuration, as described in the last section.

Unless you are using the Anaconda distro or have it pre-installedmatplotlibpackage, you should see a message,"ModuleNotFoundError: No module named 'matplotlib'"". Such a message means that the requested package is not available on your system.

installmatplotlibpackage (which also installsnumberas a dependency), stop the debugger and use the command palette to launch itTerminal: Create a new terminal(⌃⇧`(Windows, LinuxCtrl+Shift+`)). This command opens a command prompt for the selected interpreter.

A best practice among Python developers is to avoid installing packages in the global interpreter environment. Use project-specific insteadvirtual environmentwhich contains a copy of the global interpreter. Once this environment is activated, all installed packages are isolated from other environments. This isolation reduces many of the complications that can arise from conflicting package versions. to createvirtual environmentand install the required packages, enter the following commands appropriate for your operating system:

Remark: For additional information on virtual environments, seeEnvironment.

1. Create a virtual environment using the Create Environment command

   From within VS Code, you can create non-global environments with Venv or Anaconda by opening the command palette (⇧⌘str(Windows, LinuxCtrl+Shift+P)), start typingPython: Creating an environmentsearch, and then select a command. You can also callPython: Creating an environmentcommand on the Getting Started with Python page.

   The command presents a list of environment types, Venv or Conda. Select in this exampleVenv.

   

   The command then lists the compilers that can be used in the project.

   

   After selecting the desired interpreter, a notification shows the progress of environment creation and an environment folder appears in your workspace.

   

   The command also installs the necessary packages described in the requirements/dependencies file, such asrequirements.txt,pyproject.toml, Lubenvironment.yml, in the project folder.

   Remark: If you want to create an environment manually or encounter an error while creating an environment, please visit the pageEnvironmentkant.

2. Make sure the new environment is selected using the filePython: Choose an interpreterfrom regulationCommand palette.

   

3. Install the packages

   # Do not use with Anaconda distributions as they already include matplotlib.# Mac operating systempython3 -m pip instalater matplotlib# Windows (may require booting)py -m pip install matplotlib#Linux (Debian)apt-get install python3-tkpython3 -m pip instalater matplotlib

4. Now run the program again (with or without the debugger) and after a few moments a graph window will appear with the result:

   

5. When you're done, typedeactivatein the terminal window to deactivate the virtual environment.

For more examples of creating and activating a virtual environment and installing packages, seeThe Django GuideandBottle guide.

Next steps

You can configure VS Code to use any installed Python environment, including virtual and conda environments. You can also use a separate debugging environment. See for detailsEnvironment.

Follow one of the to learn more about Pythonprogramming lessonslisted on python.org in the context of VS Code.

Check out the following tutorials to learn how to develop web applications using the Django and Flask frameworks:

• Using Django in Visual Studio Code
• Using Flask in Visual Studio Code

So there's a lot more to explore in Python in Visual Studio Code:

• Python profile template- Make new onesprofilewith a select set of extensions, settings and code snippets
• Edit the code- Learn about auto-completion, IntelliSense, formatting and refactoring in Python.
• fight- Activate, configure and deploy various python linters.
• Debugowanie- Learn to debug Python both locally and remotely.
• Test- Set up test environments and discover, run and debug tests.
• Item reference- Explore the full range of Python-related settings in VS Code.
• Implementirajte Python u Azure App Service
• Deploy Python in containerized applications

20.01.2023