11/1/2020 Python Visual Studio For Mac
Trying to figure out Python with Visual Studio on Mac. Dependencies and Libraries don't seem to install/launch correctly.
Active1 year, 7 months ago
According to the description for Python Tools for Visual Studio, it only statement that it could install for Visual Studio 2015, VS2013, VS2012 and VS2010. It doesn't mentioned that it is support Visual Studio for Mac. Python Tools for Visual Studio is a completely free extension, developed and supported by Microsoft with contributions from the community. Visit our Github page to see or participate in PTVS development. In this short article I'm going to give you an overview of Visual Studio Code, a free and open source IDE for Windows, Mac OS X and Linux, from Microsoft.This IDE is highly configurable and extensible with plugins, including a very good one for Python. Visual Studio Team reported Oct 08 at 07:37 PM Migrated from Visual Studio for Mac UserVoice forum Python support like PTVS would be an absolute game changer. Trying to figure out Python with Visual Studio on Mac. Dependencies and Libraries don't seem to install/launch correctly. For example, I have pandas on my system, installed via pip, and if I do.
For example, I have pandas on my system, installed via pip, and if I do
from a Python prompt, it works fine.
With Visual Studio Code, if I create a file with the above code, autocomplete recognizes that pandas is installed
When I try to run, I get an ImportError: No module named pandas
Any ideas?
Update: It works in VSCode's terminal, just not when I run the code in the debugger.
Laurence Moroney
Laurence MoroneyLaurence Moroney
1 Answer
Laurence Moroney is right -- this issue occurs when VS Code is using a Python interpreter different from the one that has your libraries installed.
See Configuring Python Environments for instructions on changing the interpreter globally in VS Code. Don't forget to restart VS Code afterwards.
Bernd VerstBernd Verst
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In this tutorial, you use Python 3 to create the simplest Python 'Hello World' application in Visual Studio Code. By using the Python extension, you make VS Code into a great lightweight Python IDE (which you may find a productive alternative to PyCharm).
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This tutorial introduces you to VS Code as a Python environment, primarily how to edit, run, and debug code through the following tasks:
This tutorial is not intended to teach you Python itself. Once you are familiar with the basics of VS Code, you can then follow any of the programming tutorials on python.org within the context of VS Code for an introduction to the language.
If you have any problems, feel free to file an issue for this tutorial in the VS Code documentation repository.
Note: You can use VS Code with Python 2 with this tutorial, but you need to make appropriate changes to the code, which are not covered here.
Prerequisites
To successfully complete this tutorial, complete the following requirements:
Windows Subsystem for Linux
If you are working on Windows and want an isolated environment for working with Python, the Windows Subsystem for Linux (WSL) is a great option. You can enable WSL and install a Linux distribution on your Windows machine, completely isolated from your normal development environment. This Python tutorial can be done inside WSL, using the VS Code Remote - WSL extension.
For more information, 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.
Once you have WSL running, you can return to this tutorial and verify the prerequisites with a WSL terminal or VS Code integrated terminal.
Verify the Python installation
To verify that you've installed Python successfully on your machine, run one of the following commands (depending on your operating system):
If the installation was successful, the output window should show the version of Python that you installed.
Start VS Code in a project (workspace) folder
At 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:
When using an Anaconda distribution, be sure to use an Anaconda command prompt.
By starting VS Code in a folder, that folder becomes your 'workspace'. VS Code stores settings that are specific to that workspace in
.vscode/settings.json , which are separate from user settings that are stored globally.
Alternately, you can run VS Code through the operating system UI, then use File > Open Folder to open the project folder.
Select a Python interpreter
Python is an interpreted language, and in order to run Python code and get Python IntelliSense, you must tell VS Code which interpreter to use.
From within VS Code, select a Python 3 interpreter by opening the Command Palette (⇧⌘P (Windows, Linux Ctrl+Shift+P)), start typing the Python: Select Interpreter command to search, then select the command. You can also use the Select Python Environment option on the Status Bar if available (it may already show a selected interpreter, too):
The command presents a list of available interpreters that VS Code can find automatically, including virtual environments. If you don't see the desired interpreter, see Configuring Python environments.
Note: When using an Anaconda distribution, the correct interpreter should have the suffix
('base':conda) , for example Python 3.7.3 64-bit ('base':conda) .
Selecting an interpreter sets the
python.pythonPath value in your workspace settings to the path of the interpreter. To see the setting, select File > Preferences > Settings (Code > Preferences > Settings on macOS), then select the Workspace Settings tab.
Note: If you select an interpreter without a workspace folder open, VS Code sets
python.pythonPath in your user settings instead, which sets the default interpreter for VS Code in general. The user setting makes sure you always have a default interpreter for Python projects. The workspace settings lets you override the user setting.
Create a Python Hello World source code file
From the File Explorer toolbar, select the New File button on the
hello folder:
Name the file
hello.py , and it automatically opens 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.
Next, start entering the following source code if using Python 3:
When you start typing
print , notice how IntelliSense presents auto-completion options.
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. :
Feel free to experiment with IntelliSense some more, but then revert your changes so you have only the
msg variable and the print call, and save the file (⌘S (Windows, Linux Ctrl+S)).
For full details on editing, formatting, and refactoring, see Editing code. The Python extension also has full support for Linting.
Run Hello World
It's simple to run
hello.py with Python. Right-click anywhere in the editor window and select Run Python File in Terminal (which saves the file automatically):
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The command 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 two other ways you can run Python within VS Code:
Configure and run the debugger
Let's now try debugging our simple Hello World program.
First, set a breakpoint on line 2 of
hello.py by placing the cursor on the print call and pressing F9. Alternately, just click in the editor's left gutter, next to the line numbers. When you set a breakpoint, a red circle appears in the gutter.
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.
Python Tools For Visual Studio For Mac
Note: VS Code uses JSON files for all of its various configurations;
launch.json is the standard name for a file containing debugging configurations.
These different configurations are fully explained in Debugging configurations; for now, just select Python File, which is the configuration that runs the current file shown in the editor using the currently selected Python interpreter. Once selected the Python extension creates a
launch.json file within a .vscode folder (located in the folder's root directory) that contains a pre-defined configuration based on your selection (you can also learn more about this file in Debugging configurations).
The debugger will 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 will see now defined
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 Hello world 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:
Select the blue Continue button on the toolbar again (or press F5) to run the program to completion. 'Hello World' 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 (or the first line if
stopOnEntry is set to true, in which case the debugger stops before any code is run.)
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 Debug > 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
print statements to quickly inspect variables without necessarily stepping through each line of code in a debugger. In VS Code, you can instead use Logpoints. A Logpoint is like a breakpoint except that it logs a message to the console and doesn't stop the program. For more information, see Logpoints in the main VS Code debugging article.
Troubleshooting
If for some reason VS Code doesn't generate
launch.json for you, create the .vscode/launch.json file within the project folder (creating the .vscode folder if you need to), then paste the following contents into launch.json :
If you see 'SyntaxError: invalid syntax' as shown below, you may have attempted to start debugging when
launch.json was showing in the editor. The error occurs because launch.json is not Python code like hello.py :
Select
hello.py and try again. Alternately, create a debug configuration specifically for the hello.py file by adding the following lines in launch.json within the configuration array. Then select this configuration in the debugger drop-down and start the debugger again.
Visual Studio
If you see the message, 'Python interpreter is not found because python.exe is not in the workspace directory,' or 'You need to install a Python interpreter before you start debugging,' then you may have
pythonPath: ${workspaceFolder} in your launch.json file, but your Python interpreter actually exists in a different path. Check the value, or remove the pythonPath property altogether.
Install and use packages
Let's now run an example that's a little more interesting. In Python, packages are how you obtain any number of useful code libraries, typically from PyPI. For this example, you use the
matplotlib and numpy packages to create a graphical plot as is commonly done with data science. (Note that matplotlib cannot show graphs when running in the Windows Subsystem for Linux as it lacks the necessary UI support.)
Return to the Explorer view (the top-most icon on the left side, which shows files), create a new file called
standardplot.py , and paste in the following source code:
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, try running the file in the debugger using the 'Python: Current file' configuration as described in the last section. (If you still have
'stopOnEntry': true in that configuration, you need to select the run command again to continue.)
Unless you're using an Anaconda distribution or have previously installed the
matplotlib package, you should see the message, 'ModuleNotFoundError: No module named 'matplotlib'. Such a message indicates that the required package isn't available in your system.
To install the
matplotlib package (which also installs numpy as a dependency), stop the debugger and use the Command Palette to run Terminal: Create New Integrated Terminal (⌃⇧` (Windows, Linux Ctrl+Shift+`))). This command opens a command prompt for your selected interpreter.
A best practice among Python developers is to avoid installing packages into a global interpreter environment. You instead use a project-specific
virtual environment that contains a copy of a global interpreter. Once you activate that environment, any packages you then install are isolated from other environments. Such isolation reduces many complications that can arise from conflicting package versions. To create a virtual environment and install the required packages, enter the following commands as appropriate for your operating system:
Visual Studio For Mac Python
Note: For additional information about virtual environments, see Environments.
For additional examples of creating and activating a virtual environment and installing packages, see the Django tutorial and the Flask tutorial.
Next steps
You can configure VS Code to use any Python environment you have installed, including virtual and conda environments. You can also use a separate environment for debugging. For full details, see Environments.
To learn more about the Python language, follow any of the programming tutorials listed on python.org within the context of VS Code.
Python Visual Studio 2017 Mac
To learn to build web apps with the Django and Flask frameworks, see the following tutorials:
There is then much more to explore with Python in Visual Studio Code:
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