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How to Install PIP in Visual Studio Code | PIP in VSCode (2023)

Download and install the Python workload

Complete the following steps to download and install the Python workload.

  1. Download and run the latest Visual Studio Installer for Windows. Python support is present in release 15.2 and later. If you have Visual Studio installed already, open Visual Studio and run the installer by selecting Tools > Get Tools and Features.

    Tip

    The Community edition is for individual developers, classroom learning, academic research, and open source development. For other uses, install Visual Studio Professional or Visual Studio Enterprise.

  2. The installer provides a list of workloads that are groups of related options for specific development areas. For Python, select the Python development workload and select Install:

    Python installation options Description Python distributions Choose any combination of Python distribution that you plan to work with. Common options include 32-bit and 64-bit variants of Python 2, Python 3, Miniconda, Anaconda 2, and Anaconda 3. Each option includes the distribution’s interpreter, runtime, and libraries. Anaconda, specifically, is an open data science platform that includes a wide range of preinstalled packages. Visual Studio automatically detects existing Python installations. For more information, see The Python Environments window. Also, if a newer version of Python is available than the version shown in the installer, you can install the new version separately and Visual Studio detects it. Cookiecutter template support Install the Cookiecutter graphical UI to discover templates, input template options, and create projects and files. For more information, see Use the Cookiecutter extension. Python web support Install tools for web development including HTML, CSS, and JavaScript editing support, along with templates for projects using the Bottle, Flask, and Django frameworks. For more information, see Python web project templates. Python native development tools Install the C++ compiler and other necessary components to develop native extensions for Python. For more information, see Create a C++ extension for Python. Also install the Desktop development with C++ workload for full C++ support.

    By default, the Python workload installs for all users on a computer under:

    %ProgramFiles%\Microsoft Visual Studio\

    \

    Common7\IDE\Extensions\Microsoft\Python

    where

    is 2022 and

    is Community, Professional, or Enterprise.

    %ProgramFiles(x86)%\Microsoft Visual Studio\

    \

    Common7\IDE\Extensions\Microsoft\Python

    where

    is 2019 or 2017 and

    is Community, Professional, or Enterprise.

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Install Python support in Visual Studio

Python support is available only on Visual Studio for Windows. On Mac and Linux, Python support is available through Visual Studio Code.

How to Install PIP in Visual Studio Code | PIP in VSCode (2023)
How to Install PIP in Visual Studio Code | PIP in VSCode (2023)

Generate the requirements.txt file

If all the necessary Python packages for your project are already installed in an environment, you can generate the requirements.txt file in Visual Studio.

  1. In Solution Explorer, expand your project, and then expand the Python Environments node.

  2. Locate the environment node for which you want to generate the requirements file. Right-click the node, and select Generate requirements.txt.

Manually install package dependencies

If pip doesn’t install a package dependency defined in your requirements.txt file, the entire installation fails.

You have two options to address this issue:

  • Manually edit the requirements.txt file to exclude the failed package, and then rerun the installation process.

  • Use pip command options to refer to an installable version of the package.

Update the requirements file with pip wheel

If you use the

pip wheel

command to compile a dependency, you can add the

--find-links

option to your requirements.txt file.

  1. Call the


    pip wheel

    command to compile the list of required dependencies:

    pip wheel azure

    The output shows the wheels built for the collected packages:


    Downloading/unpacking azure Running setup.py (path:C:\Project\env\build\azure\setup.py) egg_info for package azure Building wheels for collected packages: azure Running setup.py bdist_wheel for azure Destination directory: c:\project\wheelhouse Successfully built azure Cleaning up...

  2. Append the


    find-links

    and

    no-index

    options, along with the package version requirement to your requirements.txt file:

    type requirements.txt --find-links wheelhouse --no-index azure==0.8.0

  3. Run the pip install process with your updated requirements file:


    pip install -r requirements.txt -v

    The output tracks progress for the installation process:


    Downloading/unpacking azure==0.8.0 (from -r requirements.txt (line 3)) Local files found: C:/Project/wheelhouse/azure-0.8.0-py3-none-any.whl Installing collected packages: azure Successfully installed azure Cleaning up... Removing temporary dir C:\Project\env\build...

How to install Python Libraries in Visual Studio Code
How to install Python Libraries in Visual Studio Code

Download and install the Python workload

Complete the following steps to download and install the Python workload.

  1. Download and run the latest Visual Studio Installer for Windows. Python support is present in release 15.2 and later. If you have Visual Studio installed already, open Visual Studio and run the installer by selecting Tools > Get Tools and Features.

    Tip

    The Community edition is for individual developers, classroom learning, academic research, and open source development. For other uses, install Visual Studio Professional or Visual Studio Enterprise.

  2. The installer provides a list of workloads that are groups of related options for specific development areas. For Python, select the Python development workload and select Install:

    Python installation options Description Python distributions Choose any combination of Python distribution that you plan to work with. Common options include 32-bit and 64-bit variants of Python 2, Python 3, Miniconda, Anaconda 2, and Anaconda 3. Each option includes the distribution’s interpreter, runtime, and libraries. Anaconda, specifically, is an open data science platform that includes a wide range of preinstalled packages. Visual Studio automatically detects existing Python installations. For more information, see The Python Environments window. Also, if a newer version of Python is available than the version shown in the installer, you can install the new version separately and Visual Studio detects it. Cookiecutter template support Install the Cookiecutter graphical UI to discover templates, input template options, and create projects and files. For more information, see Use the Cookiecutter extension. Python web support Install tools for web development including HTML, CSS, and JavaScript editing support, along with templates for projects using the Bottle, Flask, and Django frameworks. For more information, see Python web project templates. Python native development tools Install the C++ compiler and other necessary components to develop native extensions for Python. For more information, see Create a C++ extension for Python. Also install the Desktop development with C++ workload for full C++ support.

    By default, the Python workload installs for all users on a computer under:

    %ProgramFiles%\Microsoft Visual Studio\

    \

    Common7\IDE\Extensions\Microsoft\Python

    where

    is 2022 and

    is Community, Professional, or Enterprise.

    %ProgramFiles(x86)%\Microsoft Visual Studio\

    \

    Common7\IDE\Extensions\Microsoft\Python

    where

    is 2019 or 2017 and

    is Community, Professional, or Enterprise.

Test your install

Quickly check your installation of Python support:

  1. Launch Visual Studio.

  2. Select Alt + I to open the Python Interactive window.

  3. In the window, enter the statement


    2+2

    .

    The statement output

    displays in the window. If you don’t see the correct output, recheck your steps.

Using Microsoft Visual Studio to Import Python Libraries
Using Microsoft Visual Studio to Import Python Libraries

Install a Python interpreter

Along with the Python extension, you need to install a Python interpreter. Which interpreter you use is dependent on your specific needs, but some guidance is provided below.

Windows

Install Python from python.org. Use the Download Python button that appears first on the page to download the latest version.

Note: If you don’t have admin access, an additional option for installing Python on Windows is to use the Microsoft Store. The Microsoft Store provides installs of supported Python versions.

For additional information about using Python on Windows, see Using Python on Windows at Python.org

macOS

The system install of Python on macOS is not supported. Instead, a package management system like Homebrew is recommended. To install Python using Homebrew on macOS use

brew install python3

at the Terminal prompt.

Note: On macOS, make sure the location of your VS Code installation is included in your PATH environment variable. See these setup instructions for more information.

Linux

The built-in Python 3 installation on Linux works well, but to install other Python packages you must install

pip

with get-pip.py.

Other options

  • Data Science: If your primary purpose for using Python is Data Science, then you might consider a download from Anaconda. Anaconda provides not just a Python interpreter, but many useful libraries and tools for data science.

  • Windows Subsystem for Linux: If you are working on Windows and want a Linux environment for working with Python, the Windows Subsystem for Linux (WSL) is an option for you. If you choose this option, you’ll also want to install the WSL extension. For more information about using WSL with VS Code, see VS Code Remote Development or try the Working in WSL tutorial, which will walk you through setting up WSL, installing Python, and creating a Hello World application running in WSL.

Note: To verify that you’ve installed Python successfully on your machine, 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:


py -3 --version

If the installation was successful, the output window should show the version of Python that you installed. Alternatively, you can use the


py -0

command in the VS Code integrated terminal to view the versions of python installed on your machine. The default interpreter is identified by an asterisk (*).

Create a virtual environment

A best practice among Python developers is to use a project-specific

virtual environment

. Once you activate that environment, any packages you then install are isolated from other environments, including the global interpreter environment, reducing many complications that can arise from conflicting package versions. You can create non-global environments in VS Code using Venv or Anaconda with Python: Create Environment.

Open the Command Palette (⇧⌘P (Windows, Linux Ctrl+Shift+P)), start typing the Python: Create Environment command to search, and then select the command.

The command presents a list of environment types, Venv or Conda. For this example, select Venv.

The command then presents a list of interpreters that can be used for your project. Select the interpreter you installed at the beginning of the tutorial.

After selecting the interpreter, a notification will show the progress of the environment creation and the environment folder (

/.venv

) will appear in your workspace.

Ensure your new environment is selected by using the Python: Select Interpreter command from the Command Palette.

Note: For additional information about virtual environments, or if you run into an error in the environment creation process, see Environments.

How to Install PIP in Python 3.10 | PIP Install in Python (Easy Method)
How to Install PIP in Python 3.10 | PIP Install in Python (Easy Method)

Test your install

Quickly check your installation of Python support:

  1. Launch Visual Studio.

  2. Select Alt + I to open the Python Interactive window.

  3. In the window, enter the statement


    2+2

    .

    The statement output

    displays in the window. If you don’t see the correct output, recheck your steps.

Install packages using the Python Environments window

  1. From the Python Environments window, select the default environment for new Python projects and choose the Packages tab. You’ll then see a list of packages that are currently installed in the environment.

  2. Install


    matplotlib

    by entering its name into the search field and then selecting the Run command: pip install matplotlib option. Running the command will install

    matplotlib

    , and any packages it depends on (in this case that includes

    numpy

    ).

  3. Choose the Packages tab.

  4. Consent to elevation if prompted to do so.

  5. After the package is installed, it appears in the Python Environments window. The X to the right of the package uninstalls it.

  6. Consent to elevation if prompted to do so.

  7. After the package installs, it appears in the Python Environments window. The X to the right of the package uninstalls it.

    Note

    A small progress bar might appear underneath the environment to indicate that Visual Studio is building its IntelliSense database for the newly-installed package. The IntelliSense tab also shows more detailed information. Be aware that until that database is complete, IntelliSense features like auto-completion and syntax checking won’t be active in the editor for that package.

    Visual Studio 2017 version 15.6 and later uses a different and faster method for working with IntelliSense, and displays a message to that effect on the IntelliSense tab.

How To Install & Use/Import Python Packages in Visual Studio Code (2022)
How To Install & Use/Import Python Packages in Visual Studio Code (2022)

Prerequisites

  • Visual Studio installed with support for Python workloads. For more information, see Install Python support in Visual Studio.

  • A requirements file. You can use an existing requirements file or generate a file as described in this article.

Technically, any filename can be used to track requirements. However, Visual Studio provides specific support for the requirements file named “requirements.txt.” You can use the

-r

argument when you install a package to specify your preferred name for the file.

Next steps

To learn how to build web apps with popular Python web frameworks, see the following tutorials:

There is then much more to explore with Python in Visual Studio Code:

  • Python profile template – Create a new profile with a curated set of extensions, settings, and snippets
  • Editing code – Learn about autocomplete, IntelliSense, formatting, and refactoring for Python.
  • Linting – Enable, configure, and apply a variety of Python linters.
  • Debugging – Learn to debug Python both locally and remotely.
  • Testing – Configure test environments and discover, run, and debug tests.
  • Settings reference – Explore the full range of Python-related settings in VS Code.
  • Deploy Python to Azure App Service
  • Deploy Python to Container Apps

Manage required Python packages with requirements.txt

If you share your Python project with others, or use a build system to produce your Python application, you need to specify any required external packages. When you plan to copy your project to other locations where you need to restore an environment, you also need to define the required dependent packages.

The recommended approach for specifying external dependent Python packages is to use a requirements file (readthedocs.org). This file contains a list of pip commands that install any required versions of dependent packages for your project. The most common command is

pip freeze > requirements.txt

. This command records your environment’s current package list into the requirements.txt file.

A requirements file contains precise versions of all installed packages. You can use requirements files to freeze the requirements of an environment. By using precise package versions, you can easily reproduce your environment on another computer. The requirements files include packages even if they’re installed with a version range, as a dependency of another package, or with an installer other than pip.

Microsoft visual Studio 2019 || Python with Visual studio || Visual Studio installation
Microsoft visual Studio 2019 || Python with Visual studio || Visual Studio installation

Create a Python source code file

From the File Explorer toolbar, select the New File button on the

hello

folder:

Name the file

hello.py

, and VS Code will automatically open it in the editor:

By using the

.py

file extension, you tell VS Code to interpret this file as a Python program, so that it evaluates the contents with the Python extension and the selected interpreter.

Note: The File Explorer toolbar also allows you to create folders within your workspace to better organize your code. You can use the New folder button to quickly create a folder.

Now that you have a code file in your Workspace, enter the following source code in

hello.py

:


msg = "Roll a dice" print(msg)

When you start typing

IntelliSense and auto-completions work for standard Python modules as well as other packages you’ve installed into the environment of the selected Python interpreter. It also provides completions for methods available on object types. For example, because the

msg

variable contains a string, IntelliSense provides string methods when you type

msg.

:

Finally, save the file (⌘S (Windows, Linux Ctrl+S)). At this point, you’re ready to run your first Python file in VS Code.

For full details on editing, formatting, and refactoring, see Editing code. The Python extension also has full support for Linting.

Install dependencies listed in requirements.txt

If you load a project that has a requirements.txt file, you can install all the package dependencies listed in the file.

  1. In Solution Explorer, expand the project, and then expand the Python Environments node.

  2. Locate the environment node that you want to install the packages for. Right-click the node, and select Install from requirements.txt.

  3. You can monitor the package installation process in the Output window:

    The output lists any required packages that are installed, along with any updates required for affected pip commands and the availability of newer pip versions.

How To Pip Install Visual Studio Code Tutorial
How To Pip Install Visual Studio Code Tutorial

Set a working directory

By default, Visual Studio runs a Python project opened as a folder in the root of that same folder. The code in your project, however, might assume that Python is being run in a subfolder. For example, now suppose you open the root folder of the pythonkoans repository and there is a subfolder called python3 where _contemplate-koans.py exists. You set the python3/contemplate-koans.py file as startup item. If you then run the code, you would see an error that the koans.txt file can’t be found. This error happens because contemplate-koans.py assumes that Python is being run in the python3 folder rather than the repository root.

In such cases, you must also add a line to the launch configuration JSON file to specify the working directory:

  1. Right-click the Python (.py) startup file in Solution Explorer and select Debug and Launch Settings.

  2. In the Select debugger dialog box that appears, select Default and then choose Select.

    Note

    If you don’t see Default as a choice, be sure that you chose a Python .py file when selecting the Debug and Launch Settings command. Visual Studio uses the file type to determine which debugger options to display.

  3. Visual Studio opens a file named launch.vs.json, which is located in the hidden


    .vs

    folder. This file describes the debugging context for the project. To specify a working directory, add a value for

    "workingDirectory"

    , as in

    "workingDirectory": "python3"

    for python-koans example:

    { "version": "0.2.1", "defaults": {}, "configurations": [ { "type": "python", "interpreter": "(default)", "interpreterArguments": "", "scriptArguments": "", "env": {}, "nativeDebug": false, "webBrowserUrl": "", "project": "contemplate_koans.py", "projectTarget": "", "name": "contemplate_koans.py", "workingDirectory": "python3" } ] }

  4. Save the file and launch the program again, which now runs in the specified folder.

By default, Visual Studio runs a Python project opened as a folder in the root of that same folder. The code in your project, however, might assume that Python is being run in a subfolder. For example, now suppose you open the root folder of the pythonkoans repository and there is a subfolder called python3 where _contemplate-koans.py exists. You set the python3/contemplate-koans.py file as startup item. If you then run the code, you would see an error that the koans.txt file can’t be found. This error happens because contemplate-koans.py assumes that Python is being run in the python3 folder rather than the repository root.

In such cases, you must also add a line to the launch configuration JSON file to specify the working directory:

  1. Right-click the Python (.py) startup file in Solution Explorer and select Add Debug Configuration.

  2. In the Select debugger dialog box that appears, select Default and then choose Select.

    Note

    If you don’t see Default as a choice, be sure that you chose a Python .py file when selecting the Add Debug Configuration command. Visual Studio uses the file type to determine which debugger options to display.

  3. Visual Studio opens a file named launch.vs.json, which is located in the hidden


    .vs

    folder. This file describes the debugging context for the project. To specify a working directory, add a value for

    "workingDirectory"

    , as in

    "workingDirectory": "python3"

    for python-koans example:

    { "version": "0.2.1", "defaults": {}, "configurations": [ { "type": "python", "interpreter": "(default)", "interpreterArguments": "", "scriptArguments": "", "env": {}, "nativeDebug": false, "webBrowserUrl": "", "project": "contemplate_koans.py", "projectTarget": "", "name": "contemplate_koans.py", "workingDirectory": "python3" } ] }

  4. Save the file and launch the program again, which now runs in the specified folder.

Install and use packages

Let’s build upon the previous example by using packages.

In Python, packages are how you obtain any number of useful code libraries, typically from PyPI, that provide additional functionality to your program. For this example, you use the

numpy

package to generate a random number.

Return to the Explorer view (the top-most icon on the left side, which shows files), open

hello.py

, and paste in the following source code:


import numpy as np msg = "Roll a dice" print(msg) print(np.random.randint(1,9))

Tip: If you enter the above code by hand, you may find that auto-completions change the names after the


as

keywords when you press Enter at the end of a line. To avoid this, type a space, then Enter.

Next, run the file in the debugger using the “Python: Current file” configuration as described in the last section.

You should see the message, “ModuleNotFoundError: No module named ‘numpy'”. This message indicates that the required package isn’t available in your interpreter. If you’re using an Anaconda distribution or have previously installed the

numpy

package you may not see this message.

To install the

numpy

package, stop the debugger and use the Command Palette to run Terminal: Create New Terminal (⌃⇧` (Windows, Linux Ctrl+Shift+`)). This command opens a command prompt for your selected interpreter.

To install the required packages in your virtual environment, enter the following commands as appropriate for your operating system:

  1. Install the packages


    # Don't use with Anaconda distributions because they include matplotlib already. # macOS python3 -m pip install numpy # Windows (may require elevation) py -m pip install numpy # Linux (Debian) apt-get install python3-tk python3 -m pip install numpy

  2. Now, rerun the program, with or without the debugger, to view the output!

Congrats on completing the Python tutorial! During the course of this tutorial, you learned how to create a Python project, create a virtual environment, run and debug your Python code, and install Python packages. Explore additional resources to learn how to get the most out of Python in Visual Studio Code!

Hướng dẫn cài đặt Python trên visual Studio - Robot cho mọi người
Hướng dẫn cài đặt Python trên visual Studio – Robot cho mọi người

Phản hồi

Gửi và xem ý kiến phản hồi dành cho

Getting Started with Python in VS Code

In this tutorial, you will learn how to use Python 3 in Visual Studio Code to create, run, and debug a Python “Roll a dice” application, work with virtual environments, use packages, and more! By using the Python extension, you turn VS Code into a great, lightweight Python editor.

If you are new to programming, check out the Visual Studio Code for Education – Introduction to Python course. This course offers a comprehensive introduction to Python, featuring structured modules in a ready-to-code browser-based development environment.

To gain a deeper understanding of the Python language, you can explore any of the programming tutorials listed on python.org within the context of VS Code.

For a Data Science focused tutorial with Python, check out our Data Science section.

Download and install the Python workload

Complete the following steps to download and install the Python workload.

  1. Download and run the latest Visual Studio Installer for Windows. Python support is present in release 15.2 and later. If you have Visual Studio installed already, open Visual Studio and run the installer by selecting Tools > Get Tools and Features.

    Tip

    The Community edition is for individual developers, classroom learning, academic research, and open source development. For other uses, install Visual Studio Professional or Visual Studio Enterprise.

  2. The installer provides a list of workloads that are groups of related options for specific development areas. For Python, select the Python development workload and select Install:

    Python installation options Description Python distributions Choose any combination of Python distribution that you plan to work with. Common options include 32-bit and 64-bit variants of Python 2, Python 3, Miniconda, Anaconda 2, and Anaconda 3. Each option includes the distribution’s interpreter, runtime, and libraries. Anaconda, specifically, is an open data science platform that includes a wide range of preinstalled packages. Visual Studio automatically detects existing Python installations. For more information, see The Python Environments window. Also, if a newer version of Python is available than the version shown in the installer, you can install the new version separately and Visual Studio detects it. Cookiecutter template support Install the Cookiecutter graphical UI to discover templates, input template options, and create projects and files. For more information, see Use the Cookiecutter extension. Python web support Install tools for web development including HTML, CSS, and JavaScript editing support, along with templates for projects using the Bottle, Flask, and Django frameworks. For more information, see Python web project templates. Python native development tools Install the C++ compiler and other necessary components to develop native extensions for Python. For more information, see Create a C++ extension for Python. Also install the Desktop development with C++ workload for full C++ support.

    By default, the Python workload installs for all users on a computer under:

    %ProgramFiles%\Microsoft Visual Studio\

    \

    Common7\IDE\Extensions\Microsoft\Python

    where

    is 2022 and

    is Community, Professional, or Enterprise.

    %ProgramFiles(x86)%\Microsoft Visual Studio\

    \

    Common7\IDE\Extensions\Microsoft\Python

    where

    is 2019 or 2017 and

    is Community, Professional, or Enterprise.

How to Install Python Packages in Visual Studio Code (2023)
How to Install Python Packages in Visual Studio Code (2023)

Install packages using the Python Environments window

  1. From the Python Environments window, select the default environment for new Python projects and choose the Packages tab. You’ll then see a list of packages that are currently installed in the environment.

  2. Install


    matplotlib

    by entering its name into the search field and then selecting the Run command: pip install matplotlib option. Running the command will install

    matplotlib

    , and any packages it depends on (in this case that includes

    numpy

    ).

  3. Choose the Packages tab.

  4. Consent to elevation if prompted to do so.

  5. After the package is installed, it appears in the Python Environments window. The X to the right of the package uninstalls it.

  6. Consent to elevation if prompted to do so.

  7. After the package installs, it appears in the Python Environments window. The X to the right of the package uninstalls it.

    Note

    A small progress bar might appear underneath the environment to indicate that Visual Studio is building its IntelliSense database for the newly-installed package. The IntelliSense tab also shows more detailed information. Be aware that until that database is complete, IntelliSense features like auto-completion and syntax checking won’t be active in the editor for that package.

    Visual Studio 2017 version 15.6 and later uses a different and faster method for working with IntelliSense, and displays a message to that effect on the IntelliSense tab.

Feedback

Submit and view feedback for

Quickstart: Open and run Python code in a folder

Once you’ve installed Python support in Visual Studio 2019, it’s easy to run existing Python code in Visual Studio 2019 without creating a Visual Studio project.

Once you’ve installed Python support in Visual Studio 2022, it’s easy to run existing Python code in Visual Studio 2022 without creating a Visual Studio project.

Note

Visual Studio 2017 and earlier require you to create a Visual Studio project to run Python code, which you can easily do using a built-in project template. See Quickstart: Create a Python project from existing code.

  1. For this walkthrough, you can use any folder with Python code that you like. To follow along with the example shown here, clone the gregmalcolm/python_koans GitHub repository to your computer using the command


    git clone https://github.com/gregmalcolm/python_koans

    in an appropriate folder.

  2. Launch Visual Studio 2019 and in the start window, select Open at the bottom of the Get started column. Alternately, if you already have Visual Studio running, select the File > Open > Folder command instead.

  3. Navigate to the folder containing your Python code, then choose Select Folder. If you’re using the python_koans code, make sure to select the


    python3

    folder within the clone folder.

  4. Visual Studio displays the folder in Solution Explorer in what’s called Folder View. You can expand and collapse folders using the arrows on the left edges of the folder names:

  5. When opening a Python folder, Visual Studio creates several hidden folders to manage settings related to the project. To see these folders (and any other hidden files and folders, such as the


    .git

    folder), select the Show All Files toolbar button:

  6. To run the code, you first need to identify the startup or primary program file. In the example shown here, select the startup file contemplate-koans.py, right-click that file and select Set as Startup Item.

    Important

    If your startup item is not located in the root of the folder you opened, you must also add a line to the launch configuration JSON file as described in the section, Set a working directory.

  7. Run the code by pressing Ctrl+F5 or selecting Debug > Start without Debugging. You can also select the toolbar button that shows the startup item with a play button, which runs code in the Visual Studio debugger. In all cases, Visual Studio detects that your startup item is a Python file, so it automatically runs the code in the default Python environment. (That environment is shown to the right of the startup item on the toolbar.)

  8. The program’s output appears in a separate command window:

  9. To run the code in a different environment, select that environment from the drop-down control on the toolbar, then launch the startup item again.

  10. To close the folder in Visual Studio, select the File > Close folder menu command.

  1. For this walkthrough, you can use any folder with Python code that you like. To follow along with the example shown here, clone the gregmalcolm/python_koans GitHub repository to your computer using the command


    git clone https://github.com/gregmalcolm/python_koans

    in an appropriate folder.

  2. Launch Visual Studio 2022 and in the start window, select Open at the bottom of the Get started column. Alternately, if you already have Visual Studio running, select the File > Open > Folder command instead.

  3. Navigate to the folder containing your Python code, then choose Select Folder.

  4. Visual Studio displays the folder in Solution Explorer in what’s called Folder View. You can expand and collapse folders using the arrows on the left edges of the folder names:

  5. When opening a Python folder, Visual Studio creates several hidden folders to manage settings related to the project. To see these folders (and any other hidden files and folders, such as the


    .git

    folder), select the Show All Files toolbar button:

  6. To run the code, you first need to identify the startup or primary program file. In the example shown here, the startup file contemplate-koans.py. Right-click that file and select Set as Startup Item.

    Important

    If your startup item is not located in the root of the folder you opened, you must also add a line to the launch configuration JSON file as described in the section, Set a working directory.

  7. Run the code by pressing Ctrl+F5 or selecting Debug > Start without Debugging. You can also select the toolbar button that shows the startup item with a play button, which runs code in the Visual Studio debugger. In all cases, Visual Studio detects that your startup item is a Python file, so it automatically runs the code in the default Python environment. (That environment is shown to the right of the startup item on the toolbar.)

  8. The program’s output appears in a separate command window:

  9. To run the code in a different environment, select that environment from the drop-down control on the toolbar, then launch the startup item again.

  10. To close the folder in Visual Studio, select the File > Close folder menu command.

How to Install PIP in Python 3.12 - Windows 10/11 (2023)
How to Install PIP in Python 3.12 – Windows 10/11 (2023)

Start VS Code in a workspace folder

By starting VS Code in a folder, that folder becomes your “workspace”.

Using a command prompt or terminal, create an empty folder called “hello”, navigate into it, and open VS Code (

code

) in that folder () by entering the following commands:


mkdir hello cd hello code .

Note: If you’re using an Anaconda distribution, be sure to use an Anaconda command prompt.

Alternately, you can create a folder through the operating system UI, then use VS Code’s File > Open Folder to open the project folder.

View environments

  1. Select the View > Other Windows > Python Environments menu command. The Python Environments window opens as a peer to Solution Explorer and shows the different environments available to you. The list shows both environments that you installed using the Visual Studio installer and environments you installed separately. That includes global, virtual, and conda environments. The environment in bold is the default environment that’s used for new projects. For more information about working with environments, see How to create and manage Python environments in Visual Studio environments.

    Note

    You can also use the Ctrl+K, Ctrl+` keyboard shortcut to open the Python Environments window from the Solution Explorer window. If the shortcut doesn’t work and you can’t find the Python Environments window in the menu, it’s possible that you haven’t installed the Python workload. See How to install Python support in Visual Studio on Windows for guidance about how to install Python.

    With a Python project open, you can open the Python Environments window from Solution Explorer. Right-click Python Environments and select View All Python Environments.

  2. Now, create a new project with File > New > Project, selecting the Python Application template.

  3. In the code file that appears, paste the following code, which creates a cosine wave like the previous tutorial steps, only this time plotted graphically. You can also use the project you previously created and replace the code.


    from math import radians import numpy as np # installed with matplotlib import matplotlib.pyplot as plt def main(): x = np.arange(0, radians(1800), radians(12)) plt.plot(x, np.cos(x), 'b') plt.show() main()

  4. In the editor window, hover over the


    numpy

    and

    matplotlib

    import statements. You’ll notice that they aren’t resolved. To resolve the import statements, install the packages to the default global environment.

  5. When you look at the editor window, notice that when you hover over the


    numpy

    and

    matplotlib

    import statements that they aren’t resolved. The reason is the packages haven’t been installed to the default global environment.

    For example, select Open interactive window and an Interactive window for that specific environment appears in Visual Studio.

  6. Use the drop-down list below the list of environments to switch to the Packages tab.The Packages tab lists all packages that are currently installed in the environment.

How To Install Python Pip? | Install Pip On Windows | Python Training | Edureka
How To Install Python Pip? | Install Pip On Windows | Python Training | Edureka

Run Python code

Click the Run Python File in Terminal play button in the top-right side of the editor.

The button opens a terminal panel in which your Python interpreter is automatically activated, then runs

python3 hello.py

(macOS/Linux) or

python hello.py

(Windows):

There are three other ways you can run Python code within VS Code:

  1. Right-click anywhere in the editor window and select Run > Python File in Terminal (which saves the file automatically):

  2. Select one or more lines, then press Shift+Enter or right-click and select Run Selection/Line in Python Terminal. This command is convenient for testing just a part of a file.

  3. From the Command Palette (⇧⌘P (Windows, Linux Ctrl+Shift+P)), select the Python: Start REPL command to open a REPL terminal for the currently selected Python interpreter. In the REPL, you can then enter and run lines of code one at a time.

Congrats, you just ran your first Python code in Visual Studio Code!

Feedback

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I’m collaborating with some fellow students to build a python app, and was hoping to use the ‘training wheels’ of Visual Studio intelli-sense. They use python on mac and linux, so ideally our source control repo would consist of just

*.py

source files that we wrote, and a

requirements.txt

export of pip dependancies (using the

pip freeze

method).

I would love to be able to create a new Visual Studio project, then be able to run the following commands (for instance) within that project:


pip install boto pip install fabric pip install cuisine pip freeze > requirements.txt

And after that, be able to write some code that references these libraries and be able to run it from within Visual Studio.

Is there any way to do this? Is Python within Visual Studio even able to handle modules in the format they are available within pip, or do all python libraries used in VS have to have been pre-compiled for Windows?

Install Python support in Visual Studio

Python support is available only on Visual Studio for Windows. On Mac and Linux, Python support is available through Visual Studio Code.

como INSTALAR PIP en visual studio code 🚀
como INSTALAR PIP en visual studio code 🚀

Refresh or add entries to an existing requirements.txt file

If the requirements.txt file already exists, Visual Studio displays a prompt with several options:

  • Replace entire file: Overwrite all items, comments, and options defined in the requirements.text file.
  • Refresh existing entries: Update the version specifiers in the requirements.text file to match the currently installed version.
  • Update and add entries: Refresh existing requirements in the requirements.text file, and append all new package requirements to the end of the file.

Visual Studio runs

pip

to detect the current package requirements for the environment, and then updates your requirements.txt file based on your selection.

View environments

  1. Select the View > Other Windows > Python Environments menu command. The Python Environments window opens as a peer to Solution Explorer and shows the different environments available to you. The list shows both environments that you installed using the Visual Studio installer and environments you installed separately. That includes global, virtual, and conda environments. The environment in bold is the default environment that’s used for new projects. For more information about working with environments, see How to create and manage Python environments in Visual Studio environments.

    Note

    You can also use the Ctrl+K, Ctrl+` keyboard shortcut to open the Python Environments window from the Solution Explorer window. If the shortcut doesn’t work and you can’t find the Python Environments window in the menu, it’s possible that you haven’t installed the Python workload. See How to install Python support in Visual Studio on Windows for guidance about how to install Python.

    With a Python project open, you can open the Python Environments window from Solution Explorer. Right-click Python Environments and select View All Python Environments.

  2. Now, create a new project with File > New > Project, selecting the Python Application template.

  3. In the code file that appears, paste the following code, which creates a cosine wave like the previous tutorial steps, only this time plotted graphically. You can also use the project you previously created and replace the code.


    from math import radians import numpy as np # installed with matplotlib import matplotlib.pyplot as plt def main(): x = np.arange(0, radians(1800), radians(12)) plt.plot(x, np.cos(x), 'b') plt.show() main()

  4. In the editor window, hover over the


    numpy

    and

    matplotlib

    import statements. You’ll notice that they aren’t resolved. To resolve the import statements, install the packages to the default global environment.

  5. When you look at the editor window, notice that when you hover over the


    numpy

    and

    matplotlib

    import statements that they aren’t resolved. The reason is the packages haven’t been installed to the default global environment.

    For example, select Open interactive window and an Interactive window for that specific environment appears in Visual Studio.

  6. Use the drop-down list below the list of environments to switch to the Packages tab.The Packages tab lists all packages that are currently installed in the environment.

You MUST WATCH THIS before installing PYTHON. PLEASE DON'T MAKE this MISTAKE.
You MUST WATCH THIS before installing PYTHON. PLEASE DON’T MAKE this MISTAKE.

Test your install

Quickly check your installation of Python support:

  1. Launch Visual Studio.

  2. Select Alt + I to open the Python Interactive window.

  3. In the window, enter the statement


    2+2

    .

    The statement output

    displays in the window. If you don’t see the correct output, recheck your steps.

Configure and run the debugger

Let’s now try debugging our Python program. Debugging support is provided by the Python Debugger extension, which is automatically installed with the Python extension. To ensure it has been installed correctly, open the Extensions view (⇧⌘X (Windows, Linux Ctrl+Shift+X)) and search for

@installed python debugger

. You should see the Python Debugger extension listed in the results.

Next, set a breakpoint on line 2 of

hello.py

by placing the cursor on the

Next, to initialize the debugger, press F5. Since this is your first time debugging this file, a configuration menu will open from the Command Palette allowing you to select the type of debug configuration you would like for the opened file.

Note: VS Code uses JSON files for all of its various configurations;


launch.json

is the standard name for a file containing debugging configurations.

Select Python File, which is the configuration that runs the current file shown in the editor using the currently selected Python interpreter.

The debugger will start, and then stop at the first line of the file breakpoint. The current line is indicated with a yellow arrow in the left margin. If you examine the Local variables window at this point, you can see that the

msg

variable appears in the Local pane.

A debug toolbar appears along the top with the following commands from left to right: continue (F5), step over (F10), step into (F11), step out (⇧F11 (Windows, Linux Shift+F11)), restart (⇧⌘F5 (Windows, Linux Ctrl+Shift+F5)), and stop (⇧F5 (Windows, Linux Shift+F5)).

The Status Bar also changes color (orange in many themes) to indicate that you’re in debug mode. The Python Debug Console also appears automatically in the lower right panel to show the commands being run, along with the program output.

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

Tip Debugging information can also be seen by hovering over code, such as variables. In the case of


msg

, hovering over the variable will display the string

Roll a dice!

in a box above the variable.

You can also work with variables in the Debug Console (If you don’t see it, select Debug Console in the lower right area of VS Code, or select it from the … menu.) Then try entering the following lines, one by one, at the > prompt at the bottom of the console:


msg msg.capitalize() msg.split()

Select the blue Continue button on the toolbar again (or press F5) to run the program to completion. “Roll a dice!” appears in the Python Debug Console if you switch back to it, and VS Code exits debugging mode once the program is complete.

If you restart the debugger, the debugger again stops on the first breakpoint.

To stop running a program before it’s complete, use the red square stop button on the debug toolbar (⇧F5 (Windows, Linux Shift+F5)), or use the Run > Stop debugging menu command.

For full details, see Debugging configurations, which includes notes on how to use a specific Python interpreter for debugging.

Tip: Use Logpoints instead of print statements: Developers often litter source code with

How to Run Python in Visual Studio Code on Windows 10 2022 Best IDE
How to Run Python in Visual Studio Code on Windows 10 2022 Best IDE

Feedback

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Step 5: Install packages in your Python environment

Previous step: Run code in the debugger

The Python developer community has produced thousands of useful packages that you can incorporate into your own projects. Visual Studio provides a UI to manage packages in your Python environments.

Install dependencies in a virtual environment

You can also install the Python package dependencies in an existing virtual environment.

  1. In Solution Explorer, expand your project, and then expand the Python Environments node.

  2. Locate the virtual environment node that you want to install the packages for. Right-click the node, and select Install from requirements.txt.

If you need to create a virtual environment, see Use virtual environments.

How to Select Python Interpreter in Visual Studio Code (vscode)
How to Select Python Interpreter in Visual Studio Code (vscode)

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