Python With Visual Studio 2019 | Support For Multiple Interpreters

Step 1: Create a new Python project

A project is how Visual Studio manages all the files that come together to produce a single application. Application files include source code, resources, and configurations. A project formalizes and maintains the relationships among all the project’s files. The project also manages external resources that are shared between multiple projects. A project allows your application to effortlessly expand and grow. Using projects is easier than managing relationships by hand in unplanned folders, scripts, text files, and your memory.

This tutorial begins with a simple project containing a single, empty code file.

1. In Visual Studio, select File > New > Project to open the New Project dialog. You can also use the keyboard shortcut Ctrl+Shift+N. In the dialog, you can browse templates across different languages, select a template for your project, and specify where Visual Studio places files.

2. To view Python templates, select Installed > Python on the left menu, or search for “Python.” The search option is a great way to find a template when you can’t remember its location in the languages tree.

   Python support in Visual Studio includes several project templates, including web applications using the Bottle, Flask, and Django frameworks. For the purposes of this walkthrough, however, let’s start with an empty project.

3. Select the Python Application template, specify a name for the project, and select OK.

1. In Visual Studio, select File > New > Project or use the keyboard shortcut Ctrl+Shift+N. The Create a new project screen opens, where you can search and browse templates across different languages.

2. To view Python templates, search for python. Search is a great way to find a template when you can’t remember its location in the languages tree.

   Python web support in Visual Studio includes several project templates, such as web applications in the Bottle, Flask, and Django frameworks. When you install Python with the Visual Studio Installer, select Python Web Support under Optional to install these templates. For this tutorial, start with an empty project.

3. Select the Python Application template, and select Next.

4. On the Configure your new project screen, specify a name and file location for the project, and then select Create.

After a few moments, your new project opens in Visual Studio:

Here’s what you see:

• (1) The Visual Studio Solution Explorer window shows the project structure.
• (2) The default code file opens in the editor.
• (3) The Properties window shows more information for the item selected in Solution Explorer, including its exact location on disk.

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 Python in Visual Studio 2019

We need to enable the Python while installing the Visual Studio 2019. If you already installed Visual Studio, then we can enable it using the Visual Studio installer. Steps are the same to enable Python for those who are installing new or updating the Visual Studio which we have installed already. Open the installer and select the “Python development” as shown below.

Installation details of Python

We can see the installation details of the Python on the right-hand side in the installer after selecting the Python development. We can find how much MB of memory have been taken for installing Python.

Click the modify to enable Python in Visual Studio 2019. If you are installing new, we can find the installation button in the bottom instead of the Modify button. Once clicked, the Modify installation will be started.

Features in Visual Studio for Python

1. Editing is very easy and user-friendly. We can easily edit the Python code with the help of Tooltip, completion and code snippets.
2. We can install the libraries without trouble. Using search options, find the libraries and install whatever we need for our Python applications.
3. Debugging is very helpful to find the complex issues. Python in visual studio support debugging without project.
4. We can use effective source controller Git and TFS. We can use Git and TFS without a command line.
5. Unit testing is validating your changes in the editor. We can verify the code is working correctly without leaving the visual studio. We can view, edit, and debug the unit test from the test window.
6. Python tool for Visual Studio is a free extension, develop and support by Microsoft with contribution from the community.

Full-featured debugging

One of Visual Studio’s strengths is its powerful debugger. For Python in particular, Visual Studio includes Python/C++ mixed-mode debugging, remote debugging on Linux, debugging within the Interactive window, and debugging Python unit tests.

In Visual Studio 2019 and later, you can run and debug code without having a Visual Studio project file. See Quickstart: Open and run Python code in a folder for an example.

For more information:

• Debug Python
• Python/C++ mixed-mode debugging
• Remote debugging on Linux
• Feature tour of the Visual Studio Debugger

Switch the current project environment

In Visual Studio, you can change the active (current) environment for a Python project in Solution Explorer or from the toolbar by using the Add Environment feature.

1. Start the Add Environment process:

   • In Solution Explorer, right-click the Python Environments node for your project and select Add Environment.
   • Or, on the Python toolbar, select Add Environment from the Environment dropdown menu.

2. In the Add Environment dialog, select the Existing environment tab. Expand the Environment dropdown list and choose your desired environment, then select Add.

Note

If the environment you want to use isn’t listed, you might need to manually identify an existing environment.

Considerations about package installation

When you work with packages in Visual Studio, keep in mind the following considerations:

• Keep in mind that the displayed entries for packages might not be accurate in terms of the most current version or availability. The installation and uninstallation information shown for a package might not be reliable or available.

• Visual Studio uses the pip package manager if available, and downloads and installs it when required. Visual Studio can also use the easy_install package manager. Packages installed by using the

  
pip

  or
  
easy_install

  commands from the command line are also displayed.

• A common situation where pip fails to install a package is when the package includes source code for native components in *.pyd files. Without the required version of Visual Studio installed, pip can’t compile these components. The error message displayed in this situation is error: Unable to find vcvarsall.bat. The

  
easy_install

  command is often able to download precompiled binaries, and you can download a suitable compiler for older versions of Python from https://python.en.uptodown.com/windows/versions. For more information, see How to deal with the pain of “unable to find vcvarsallbat” on the Python tools team blog.

• The conda package manager generally uses

  
https://repo.continuum.io/pkgs/

  as the default channel, but other channels are available. For more information, see Manage Channels (docs.conda.io).

• Visual Studio doesn’t currently support using the

  
conda

  command to install packages into a conda environment. Use the
  
conda

  command from the command line instead.

Version Control integration

Collaborate on code with Git

Use Git as the default source control experience in Visual Studio right out of the box. From the new Git menu, you can create or clone repositories from GitHub or Azure DevOps. Use the integrated Git tool windows to commit and push changes to your code, manage branches, sync with your remote repositories, and resolve merge conflicts.

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.

Review Python interpreters

The following table lists Python interpreters that can be used with Visual Studio.

Interpreter	Description	Notes
CPython	The “native” and most commonly used interpreter, available in 32-bit and 64-bit versions (32-bit recommended). Includes the latest language features, maximum Python package compatibility, full debugging support, and interop with IPython. Review the considerations in Should I use Python 2 or Python 3? to help determine which version of Python to install.	Visual Studio 2015 and earlier don’t support Python 3.6 or later, and can return errors like Unsupported python version 3.6. For Visual Studio 2015 and earlier, use Python 3.5 or earlier.
IronPython	A .NET implementation of Python, available in 32-bit and 64-bit versions. Provides C#/F#/Visual Basic interop, access to .NET APIs, standard Python debugging (but not C++ mixed-mode debugging), and mixed IronPython/C# debugging.	IronPython doesn’t support virtual environments.
Anaconda	An open data science platform powered by Python. Includes the latest version of CPython and most of the difficult-to-install packages.	If you’re unable to decide on an interpreter, we recommend using Anaconda.
PyPy	A high-performance tracing JIT implementation of Python. Good for long-running programs and situations where you identify performance issues but can’t find other resolutions.	Works with Visual Studio but with limited support for advanced debugging features.
Jython	An implementation of Python on the Java Virtual Machine (JVM). Similar to IronPython, code running in Jython can interact with Java classes and libraries. However, many of the libraries intended for CPython might not be accessible.	Works with Visual Studio but with limited support for advanced debugging features.

Python support in Visual Studio on Windows

Python is a popular programming language that’s reliable, flexible, easy to learn, free to use on all operating systems, and supported by both a strong developer community and many free libraries. Python supports all manner of development, including web applications, web services, desktop apps, scripting, and scientific computing. Scientists, casual developers, professional developers, and many universities alike use Python for programming. You can learn more about the language on python.org and Python for Beginners.

Visual Studio is a powerful Python IDE on Windows. Visual Studio provides open-source support for the Python language through the Python Development and Data Science workloads (Visual Studio 2017 and later) and the free Python Tools for Visual Studio extension (Visual Studio 2015 and earlier). Tour the Visual Studio IDE to familiarize yourself with the IDE features for writing and editing Python code.

Visual Studio Code is available on Mac and Linux. For more information, see questions and answers.

To get started:

• Follow the installation instructions to set up the Python workload.

• Familiarize yourself with the Python capabilities of Visual Studio through the sections in this article.

• Go through one or more of the Quickstarts to create a project. If you’re unsure, start with Quickstart: Open and run Python code in a folder or Create a web app with Flask.

• Follow the Work with Python in Visual Studio tutorial for a full end-to-end experience.

Remove a virtual environment

Follow these steps to remove an existing environment for a project:

1. In Solution Explorer, right-click the virtual environment and select Remove.

2. Visual Studio asks whether you want to remove or delete the virtual environment.

   • Select Remove to make the environment unavailable to the project but leave it on the file system.
   • Select Delete to both remove the environment from the project and delete it from the file system. The base interpreter is unaffected.

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.

Creating a Python Project

We can develop web applications using Python with above one of the frameworks. Open Visual Studio 2019 and select “Create new project”.

Select the language dropdown as “Python”. We can see all the project templates of the project for Python.

We can see the template with a different framework. We can choose and develop any one of the templates a can develop the application based on our requirement.

Support for multiple interpreters

Visual Studio’s Python Environments window gives you a single place to manage all of your global Python environments, conda environments, and virtual environments. Visual Studio automatically detects installations of Python in standard locations, and allows you to configure custom installations. With each environment, you can easily manage packages, open an interactive window for that environment, and access environment folders.

Use the Open interactive window command to run Python interactively within the context of Visual Studio. Use the Open in PowerShell command to open a separate command window in the folder of the selected environment. In that command window, you can run any python script.

For more information:

Create a virtual environment

You can create a new virtual environment directly in Visual Studio as follows:

1. Start the Add Environment process:

   • In Solution Explorer, right-click the Python Environments node for your project and select Add Environment.
   • Or, on the Python toolbar, select Add Environment from the Environment dropdown menu.

2. In the Add Environment dialog, select the Virtual environment tab:

3. Configure the required fields:

   Required field Description Project Identify the project in which to create the environment. Name Provide the name for the new virtual environment. Base interpreter Specify the base language interpreter for the virtual environment. Location The system assigns the default location for the virtual environment. To change the location, select the Change virtual environment location link, browse to the location and choose Select folder.

4. Configure any desired optional fields:

   Optional field Description Install packages from file Specify the path to a requirements.txt file to add packages to the virtual environment. Enter the location and name of the file or browse (…) to the location and select the file. Set as current environment Activate the new environment in the selected project after the environment is created. Set as default environment for new projects Automatically set and activate the environment in any new projects created in Visual Studio. This setting is also available via the Make this the default environment for new projects option in the Python Environments window. When you use this option, place the virtual environment in a location outside of a specific project. View in Python Environments window Specify whether to show the Python Environments window after you create the new environment. Make this environment available globally Specify whether the virtual environment should also act as a global environment. When you use this option, place the virtual environment in a location outside of a specific project.

5. Select Create to finalize the virtual environment.

Visual Studio displays a progress bar while it configures the environment and downloads any necessary packages.

After the process completes, Visual Studio activates the new virtual environment and adds it to the Python Environments node in Solution Explorer. The environment is also available in the Python Environments window for the containing project.

Project system, and project and item templates

Visual Studio helps you manage the complexity of a project as it grows over time. A Visual Studio project is more than a folder structure. A project aids in the understanding of how different files are used and how they relate to each other. Visual Studio helps you distinguish app code, test code, web pages, JavaScript, build scripts, and so on, which then enable file-appropriate features. A Visual Studio solution helps you manage multiple related projects, such as a Python project and a C++ extension project.

Note

In Visual Studio 2019 and later, you can open a folder containing Python code and run that code without creating a Visual Studio project or solution file. For more information, see Quickstart: Open and run Python code in a folder. Keep in mind that there are benefits to using a project file, as explained in this section.

The following image shows an example of a Visual Studio solution containing both Python and Flask projects in Solution Explorer.

Project and item templates automate the process of setting up different types of projects and files. The templates save you valuable time and relieve you from managing intricate and error-prone details. Visual Studio provides templates for web, Azure, data science, console, and other types of projects. You can find templates for files like Python classes, unit tests, Azure web configuration, HTML, and even Django apps.

For more information:

• Manage Python projects
• Item templates reference
• Python project templates
• Work with C++ and Python
• Create project and item templates
• Solutions and projects in Visual Studio

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.

Use virtual environments

A virtual environment is a unique combination of a specific Python interpreter and a specific set of libraries that’s different from other global and conda environments. A virtual environment is specific to a project and is maintained in a project subfolder. The folder contains the environment’s installed libraries along with a pyvenv.cfg file that specifies the path to the environment’s base interpreter on the file system. (A virtual environment doesn’t contain a copy of the interpreter, only a link to it.)

One benefit to using a virtual environment is that as you develop your project over time, the virtual environment always reflects the exact dependencies of your project. This behavior is different from a shared global environment, which contains any number of libraries whether you use them in your project or not. From a virtual environment, you can easily create a requirements.txt file, which is used to reinstall package dependencies on other development or production computers. For more information, see Manage required packages with requirements.txt.

When you open a project in Visual Studio that contains a requirements.txt file, Visual Studio automatically gives you the option to recreate the virtual environment. On computers where Visual Studio isn’t installed, you can use the

pip install -r requirements.txt

command to restore the necessary packages.

Because a virtual environment contains a hard-coded path to the base Python interpreter, and you can recreate the environment by using the requirements.txt file, you typically omit the environment subfolder from source control. After you add a virtual environment to your project, it appears in the Python Environments window. You can then activate it like any other environment and manage its packages.

Python Frameworks

There are following famous frameworks are available. If we are learning following Python frameworks we have good opportunities.

Django

A Python-based free and open-source web framework. It is the model –template –view(MTV) architectural pattern. It is the main primary goal is to ease the creation of complex website.

Pyramid

Python web application framework. It is designed to make creating web applications easier. It is an open-source. It is designed to easy to use.

TurboGears

This is a Python web application framework. It is designed around the model, view and controller architecture. It is designed to make rapid web application development in Python easier and more maintainable.

Web2py

The open-source web application framework is written in the Python programming language. web2py focuses on rapid development, favors convention over configuration approach and follows a model–view–controller (MVC) architectural pattern.

Flask

Flask is a micro web framework written in Python. It is classified as a microframework because it does not require particular tools or libraries

CherryPy

CherryPy is an object-oriented web application framework using the Python programming language. It is designed for rapid development of web applications

Falcon

A light-weight micro-framework written in Python for building web APIs and app backbends. It is like Falcon. It has a clean design that embraces HTTP and the REST architectural style.

Rich editing, IntelliSense, and code comprehension

Visual Studio provides a first-class Python editor, including syntax coloring, autocomplete across all your code and libraries, code formatting, signature help, refactoring, linting, and type hints. Visual Studio also provides unique features like class view, Go to Definition, Find All References, and code snippets. Direct integration with the Interactive window helps you quickly develop existing Python code in a file.

For more information:

Questions and answers

Q. Is Python support available with Visual Studio for Mac?

A. Visual Studio for Mac isn’t currently supported. For more information, see What’s happening to Visual Studio for Mac? Visual Studio Code on Windows, Mac, and Linux works well with Python through available extensions.

Q. What can I use to build UI with Python?

A. The main offering in this area is the Qt Project with bindings for Python known as PySide (the official binding) (also see PySide downloads) and PyQt. Python support in Visual Studio doesn’t include any specific tools for UI development.

Q. Can a Python project produce a stand-alone executable?

A. Python is generally an interpreted language, where code is run on demand in a suitable Python-capable environment such as Visual Studio and web servers. Visual Studio doesn’t currently provide the means to create a stand-alone executable, which essentially means a program with an embedded Python interpreter. However, the Python community offers different means to create executables as described on StackOverflow. CPython also supports being embedded within a native application, as described on the blog post, Using CPython’s embeddable zip file.

Prerequisites

• Visual Studio. To install the product, follow the steps in Install Visual Studio.

• You can only switch between existing environments. If you don’t have an environment other than the default global environment, see the following sections about working with virtual environments. For more information, see Create and manage Python environments in Visual Studio.

Detect your environment

Visual Studio shows all known environments in the Python Environments window. It automatically detects updates to existing interpreters.

If Visual Studio doesn’t detect an installed environment, see Manually identify an existing environment.

If you want to provide new forms of detection for Python environments, see PTVS Environment Detection (github.com).

Registry entries

Visual Studio (all versions) automatically detects each installed Python interpreter and its environment by checking the registry according to PEP 514 – Python registration in the Windows registry. Python installations are typically found under the HKEY_LOCAL_MACHINE\SOFTWARE\Python (32-bit) and HKEY_LOCAL_MACHINE\SOFTWARE\WOW6432Node\Python (64-bit) key within nodes for the distribution, such as PythonCore (CPython) and ContinuumAnalytics (Anaconda).

Rich editing, IntelliSense, and code comprehension

Visual Studio provides a first-class Python editor, including syntax coloring, autocomplete across all your code and libraries, code formatting, signature help, refactoring, linting, and type hints. Visual Studio also provides unique features like class view, Go to Definition, Find All References, and code snippets. Direct integration with the Interactive window helps you quickly develop existing Python code in a file.

For more information:

Project system, and project and item templates

Visual Studio helps you manage the complexity of a project as it grows over time. A Visual Studio project is more than a folder structure. A project aids in the understanding of how different files are used and how they relate to each other. Visual Studio helps you distinguish app code, test code, web pages, JavaScript, build scripts, and so on, which then enable file-appropriate features. A Visual Studio solution helps you manage multiple related projects, such as a Python project and a C++ extension project.

Note

In Visual Studio 2019 and later, you can open a folder containing Python code and run that code without creating a Visual Studio project or solution file. For more information, see Quickstart: Open and run Python code in a folder. Keep in mind that there are benefits to using a project file, as explained in this section.

The following image shows an example of a Visual Studio solution containing both Python and Flask projects in Solution Explorer.

Project and item templates automate the process of setting up different types of projects and files. The templates save you valuable time and relieve you from managing intricate and error-prone details. Visual Studio provides templates for web, Azure, data science, console, and other types of projects. You can find templates for files like Python classes, unit tests, Azure web configuration, HTML, and even Django apps.

For more information:

• Manage Python projects
• Item templates reference
• Python project templates
• Work with C++ and Python
• Create project and item templates
• Solutions and projects in Visual Studio

Keywords searched by users: python with visual studio 2019

Categories: Có được 18 Python With Visual Studio 2019

See more here: kientrucannam.vn

See more: https://kientrucannam.vn/vn/