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      WSL

      How To Develop a Docker Application on Windows using WSL, Visual Studio Code, and Docker Desktop


      Introduction

      The advent of the Windows Subsystem for Linux 2 (WSL 2 or WSL for short) has simplified Linux-based development on Windows. The WSL 2 allows for direct integration with Docker Desktop and has plugins for direct development using Visual Studio Code.

      In this tutorial you’ll set up a development environment on Windows using Visual Studio Code, the WSL, and Docker Desktop. You’ll build a Python Flask web service in Docker to demonstrate the development functionality of these tools.

      Prerequisites

      In order to follow along with this guide, you’ll need:

      • Personal Computer with Windows 10 and the WSL 2 installed: You’ll want to ensure that the WSL is installed correctly and that you have Ubuntu 20.04 installed into the WSL. You can follow the tutorial How To Install the Windows Subsystem for Linux 2 on Microsoft Windows 10 to set this up.

      • VSCode Installed: You can download and install VSCode from its official website. You do not need to worry about installing plugins. The required plugins will be discussed in this tutorial.

      Step 1 — Installing Docker Desktop and Connecting to the WSL

      Docker is a common development tool used by developers to deploy applications. Docker Desktop has the advantage of also being able to run and integrate with your WSL Linux environments.

      Set up Docker by downloading Docker Desktop from Docker’s website and clicking the Get Docker button to start the download.

      Go to Docker's website and download Docker Desktop

      Run the executable once you get it downloaded and allow it to make changes.

      Run the executable and let Docker make changes

      During the installation make sure that Install required Windows components for WSL 2 is checked. Whether or not you want a Desktop icon is up to you.

      Make sure that

      After the installation process is done you’ll be prompted to log out and back in for your changes to take effect. Click on the Close button and then make sure to log out and back in so that the changes take effect.

      Once Docker is done installing you'll need to logout and log back in for changes to take effect

      Log back in and launch Docker Desktop from the Start menu.

      Launch Docker Desktop from the start menu

      Warning: When you first launch Docker it will prompt you with a Docker tutorial.

      Docker Tutorial Launched

      If you are unfamiliar with Docker it may be worth your time to do the Docker tutorial, but it is not required for this current tutorial. Once you have either done the tutorial or skipped it, continue on.

      The Docker dashboard will show up. This is where any running containers will appear as well as settings and status of Docker. If you see the logo is green in the bottom left corner that means that Docker is running. If it is yellow then Docker Desktop is still starting; give it a minute or so to finish. If the indicator is red, then Docker is unable to start.

      The Docker dashboard will open. If the logo in the bottom left is green it means Docker is running

      Next you’ll need to expose Docker to the WSL so you can run Docker on your Ubuntu environment. Click on the Gear icon in the top right corner to open Settings. From there you’ll click the Resource tab and then click WSL Integration. You’ll see your Ubuntu environment there, but toggled off, along with any other WSL environments you may have installed.

      Go to Settings, select Resources, and select WSL Integration. You'll see your WSL Ubuntu there, not selected

      Enable Docker in your Ubuntu environment by clicking on the slider to turn it on, and then click Apply & Restart. Once the restart is done your Ubuntu environment will have access to Docker.

      Select your WSL Ubuntu and click Apply & Restart

      Now you can test your Docker connectivity with the WSL. Open a terminal to the operating system you enabled Docker in, Ubuntu in this case, and run the Docker hello world command:

      Your Ubuntu environment should download and run the hello world container and display its output.

      Test Docker by running Docker run hello-world in your WSL Ubuntu

      Now that you have Docker connected to the WSL you’ll learn how to develop within the WSL directly using Visual Studio Code and the Remote Development Extension.

      Step 2 — Using Visual Studio Code’s Remote Extension to Develop within the WSL

      You can integrate your WSL Ubuntu environment with your Visual Studio Code, henceforth known as VSCode, to be able to develop directly in a Linux environment.

      First, open VSCode. Go to the Extensions tab on the left hand side of the window. Search for Remote - WSL and the Remote - WSL extension will appear. Click on it and click Install to install it.

      Open VSCode, go to Extensions and search for Remote. Install the Remote - WSL Extension

      Once the installation is completed, press CTRL + Shift + P to open the VSCode command dialog. Type Remote-WSL and you’ll see a few options appear. You can open a new WSL environment, open an existing folder, etc. Select Remote-WSL: New WSL Window. This will open a new VSCode window connected to the Ubuntu WSL environment.

      Press CTRL + Shift + P to open the VSCode command dialog and type Remote. You'll see WSL there. Select Remote-WSL: New WSL Window

      Now that you’re in this new window you can press CTRL + Shift + ` or by clicking on Terminal -> New Terminal in the navigation bar to open up a new terminal and you’ll be dropped into the WSL terminal. Any file you create will be stored in the WSL filesystem as well.

      If you open a new terminal you'll open your Ubuntu terminal and be able to develop using VSCode directly in the WSL

      Now that you have your development environment set up, you’ll build a Python microservice using the Flask framework that creates a 301 redirect to a site that you specify as an environment variable and package it within a Docker container.

      Step 3 — Setting Up Your Developer Environment

      First you’ll want to set up a development environment so you can develop your code using Visual Studio Code. Navigate to the sidebar on the left hand side and click on the topmost icon that looks like a sheet of paper. You will be prompted to either Open a Folder or Clone a Repository.

      File explorer dialog box open

      From here select Open a Folder. The default location will be your home directory. Select this option and click OK.

      Open home directory

      You may be prompted by Visual Studio Code asking if you trust the authors of this folder. This is a security measure to ensure that no automatically executed code can harm your PC. In this case, everything is good so select Yes, I trust the authors.

      Author Trust Dialog box

      Now you should see your home directory in the file explorer panel to the left. Next, create a directory to store your project. Navigate to the folder icon with a plus symbol. When you hover over the icon a popup should appear saying New Folder. Click on this icon to create a new folder and name it my-app. A new empty directory should appear in the explorer to the right.

      New Folder Icon
      You now have your developer environment set up and ready to build your Python microservice in the next step.

      Step 4 — Creating a Python Virtual Environment for Your Project

      Before you get started coding, you need to set up your Python developer environment. In this step, you will install and activate your Python requirements within a virtual environment for easier management.

      You can do all of this from within the terminal in Visual Studio Code. Press the CTRL + Shift + ` key combo to open a new terminal or click on New Terminal under the Terminal section in the top navigation bar. Once you’ve done this you should see a new terminal appear at the bottom of the Visual Studio Code window.

      New terminal in Visual Studio Code

      From this terminal navigate into the directory you created for you code, my-app.

      Next, install the python3-venv Ubuntu package so you can create Python virtual environments.

      • sudo apt update && sudo apt install python3-venv

      Now create your virtual environment using Python:

      This will create a directory called myapp in your current directory. Inside, it will install a local version of Python and a local version of pip, the package manager for Python. You can use this to install and configure an isolated Python environment for your project.

      Before you install your project’s Python requirements, activate the virtual environment:

      • source myapp/bin/activate

      Your prompt should change to indicate that you are now operating within a Python virtual environment. It will look something like this: (myapp)user@host:~/my-app$.

      With your virtual environment active, install flask and gunicorn with the local instance of pip:

      • pip install flask gunicorn

      Note: Once you have activate your virtual environment (when your prompt has (myapp) preceding it), use pip instead of pip3, even if you are using Python 3. The virtual environment’s copy of the tool is always named pip, regardless of the Python version.

      Now that you have the packages installed, you will need to save this requirement and its dependencies. This is good practice so you can recreate your developer environment as needed and will aid in installing the correct packages into your Dockerfile in a later step.

      Use pip to save your environment’s information to a requirements.txt file:

      • pip freeze > requirements.txt

      Now that you have a working virtual environment for development, let’s build the microservice.

      Step 5 — Building a Python Microservice to Redirect Traffic

      The first thing you’ll need to do is create a Python file named app.py and a Dockerfile to specify your Docker requirements. You can create files via the terminal with the touch command and then refreshing the explorer:

      You can also use the file explorer to create a new file by clicking on your my-app folder, then clicking on the New File icon that looks like a piece of paper with a plus sign, then typing out the full name and extension of the file.

      Create your app.py

      Use either method to create app.py and Dockerfile.

      Once you’ve done this, open app.py. The microservice you are going to write today will have only one endpoint, as defined by the @app.route("/") decorator. This endpoint will use the redirect method within the Flask library to perform a 301 redirect to a site that is specified in an environment variable. If no environment variable is set, the app will redirect to DigitalOcean’s website by default.

      Open app.py by clicking on it and add the following lines of code.

      Add an import statement to import the os package, which will enable the microservice to read the environment variable you’ll define later:

      import os
      

      Next, import the Flask class and redirect function from the flask library. You’ll use these to set up your web framework and to redirect traffic to another site.

      from flask import Flask,redirect
      

      Next, create a Flask object that can be acted upon within the code. This is the instance of your web app that you will register routes to.

      app = Flask(__name__)
      

      Create a single method at the / route. You’ll use your Flask instance to decorate the function to specify the route. Within the function, you will use the Flask redirect function to perform a 301 redirect to another site that will be read from an environment variable. If the environment variable is not found, your app will default redirect to DigitalOcean’s home page. This is to ensure your app doesn’t crash if you forget to set an environment variable.

      @app.route('/')
      def hello():
          # Attempt to read REDIRECT_TO from the environment. If nothing is set
          # perform a 301 redirect to DigitalOcean's website
          return redirect(os.environ.get("REDIRECT_TO", "https://www.digitalocean.com"), code=301)
      

      Finally, create a main function that runs your Flask app externally on port 8080. The address 0.0.0.0 is used to designate that you want your app to run on the externally facing network interface of your device, not the local loopback device, also known as localhost.

      if __name__ == '__main__':
          app.run(host="0.0.0.0", port=8080)
      

      The finished app.py can be found below:

      # Import the os package to read the environment variable
      import os
      
      # Import the Flask class and redirect function from the flask library
      from flask import Flask,redirect
      
      
      # Create a Flask object to be acted upon
      app = Flask(__name__)
      
      # Python decorator that specifies the web route that will execute the code below
      @app.route('/')
      def hello():
          # Attempt to read REDIRECT_TO from the environment. If nothing is set
          # perform a 301 redirect to DigitalOcean's website
          return redirect(os.environ.get("REDIRECT_TO", "https://www.digitalocean.com"), code=301)
      
      # Main function that executes the Flask app
      if __name__ == '__main__':
          app.run(host="0.0.0.0", port=8080)
      

      Once you are done, save the file as app.py.

      Now that your app is written, let’s test it.

      Step 6 — Testing Your Microservice

      Now that your app is written, it is time to test it. In the terminal you opened in Visual Studio Code with the activated virtual environment, run the command:

      You should see Flask output that looks similar to this:

      Output

      * Serving Flask app 'app' (lazy loading) * Environment: production WARNING: This is a development server. Do not use it in a production deployment. Use a production WSGI server instead * Debug mode: off * Running on all addresses. * WARNING: This is a development server. Do not use it in a production deployment. * Running on https://256.333.112.1:8080/ (Press CTRL+C to quit)

      This means that your Flask app is running. Open a browser and navigate to localhost:8080. When you do you should see output happen in your terminal and be redirected to DigitalOcean’s website. This is because you have not specified anywhere for your Flask app to redirect to, so it is using the default.

      To stop your Flask app, click in the Visual Studio Code window to ensure it is active and then press CTRL+C. You’ll see the prompt stop and you’ll be presented with your terminal again.

      Next, run the following command to set your redirect to something else.

      • REDIRECT_TO="https://digitalocean.com/community/tutorials"

      Run your Flask app again using the command

      Go to your browser again and navigate to localhost:8080. You should then be directed to the DigitalOcean tutorials page.

      Note: If you plan on testing multiples redirects with the same container, you may want to use a form of incognito mode. Most modern browsers will cache a 301 redirect, so if you change the environment variable, you may end up at the same site and not see your changes reflected. Using an incognito window or clearing your cache will help with this.

      With this, your app is done and is ready to be built into a Docker image.

      Step 7 — Building and Running Your Microservice in Docker

      In this final step you’re going to package your Python app as a microservice using Docker and a Dockerfile. A Dockerfile is a list of build commands that Docker uses to create your image. These can be commands to install packages, copy files, and more.

      Open the Dockerfile you created in a previous step so you can edit it. In this file you’re going to specify the base image, tell Docker where you want the code to run, create an environment variable that holds the redirect target, copy over all the necessary files to the Docker image, install the necessary Python packages, and finally add the command that will be executed when the container is run.

      Add the following code to Dockerfile to do this.

      First, you need to specify the base image you want to use. The python base image will contain the latest version of Python.

      FROM python 
      

      Next, set your working directory. This is the default directory that Docker will run commands in and drop you into if you connect with ssh.

      WORKDIR /var/www/
      

      Set the REDIRECT_TO environment variable to the default location you want to redirect to. Here I’m setting it to DigitalOcean’s Community Tutorial site. This can be changed when you run the image via the command line.

      ENV REDIRECT_TO=https://digitalocean.com/community/tutorials
      

      Copy your app.py and requirements.txt into your Docker container, using fully qualified paths for the destination.

      COPY ./app.py /var/www/app.py
      COPY ./requirements.txt /var/www/requirements.txt
      

      Run the necessary command to install the Python library requirements within your Docker image.

      RUN pip install -r /var/www/requirements.txt
      

      Finally, set the image run command to run your app. This is the command that is run whenever anyone tries to run your Docker container.

      CMD python3 app.py
      

      The complete Dockerfile is listed below.

      # Choose your base image
      FROM python 
      
      # Set your working directory
      WORKDIR /var/www/
      
      # Set environment variable for redirect. Can be overwritten by Docker run command
      ENV REDIRECT_TO=https://digitalocean.com/community/tutorials
      
      # Copy the necessary files
      COPY ./app.py /var/www/app.py
      COPY ./requirements.txt /var/www/requirements.txt
      
      # Install the necessary packages
      RUN pip install -r /var/www/requirements.txt
      
      # Run the app
      CMD python3 app.py
      

      When you are done, save the file.

      Now you can build the Docker image locally for testing. Run the following command to build your image and tag it with the name myapp. The -t option applies the tag to the Docker image:

      Finally, it’s time to test your Docker image. In your Dockerfile above you set an environment variable REDIRECT_TO to point at a website. This will overwrite the default value in your code so when you run this container, whatever site you specified in the Dockerfile will be your new location.

      Note: If you are prompted by windows to grant permission to Docker to access the network, click Allow.

      To test your image, run the following command:

      • docker run -p 8080:8080 myapp

      While your image is running, navigate to a browser and type localhost:8080 in the navigation bar and you should be redirected to the site listed in the Dockerfile.

      Warning: Sometimes the WSL terminal doesn’t recognize CTRL + C as a way to stop your Docker image. In this instance you’ll need to open another terminal and search for your running Docker image using the command:

      This will show an output similar to this:

      Output

      CONTAINER ID IMAGE COMMAND CREATED STATUS PORTS NAMES 3f081712283e myapp "/bin/sh -c 'python3…" About a minute ago Up About a minute 0.0.0.0:8080->8080/tcp, :::8080->8080/tcp reverent_saha

      Take the container id, which in this example is 3f081712283e and use the docker kill command to stop it.

      Finally, let’s test changing the environment variable of the redirect in the docker run command.

      Type the following command to change the environment variable to the DigitalOcean cloud console page, https://cloud.digitalocean.com.

      • docker run -p 8080:8080 -e REDIRECT_TO=https://cloud.digitalocean.com myapp

      Now if you go to a browser and browse to localhost:8080 you will be redirected to the site specified on the command line.

      Conclusion

      You have successfully set up a developer environment on Windows using the WSL, Visual Studio Code, and Docker Desktop. You’ve demonstrated how to build, test, and package code on Windows, allowing you to have more options when it comes to developer environments.



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      Developing on Windows With the WSL


      How to Join

      This Tech Talk is free and open to everyone. Register below to get a link to join the live stream or receive the video recording after it airs.

      Date Time RSVP
      June 9, 2021 11:00 a.m.–12:00 p.m. ET / 3:00–4:00 p.m. GMT

      About the Talk

      Wish you had a Linux command line experience on Windows? The Windows Subsystem for Linux can give you this! In this talk, we’ll install the WSL, go over how it works and how to use it, install the new Windows Command Line, and configure our IDEs and Docker to integrate with the WSL. Come learn about the WSL, how to install it and how to use it to develop your next idea.

      What You’ll Learn

      • How to install the Windows Subsystem for Linux and new Windows Command Line
      • How to integrate Docker with WSL
      • How to integrate WSL with your IDEs

      This Talk Is Designed For

      Software engineers who want to program on Windows.

      To join the live Tech Talk, register here.



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      Trying the New WSL 2. It’s Fast! (Windows Subsystem for Linux)


      In this post, I cover some first impressions from my experience installing and running WSL2 (Windows Subsystem for Linux) in my dev workflow.

      I haven’t done any exhaustive, scientific, or precise tests by any means. What I have found though is that WSL is about 5 times faster for everyday web development tasks like npm or yarn.

      Also, hot reloading and working with create-react-app or the vue-cli is faster!

      Read on for installation, getting started, gotchas, and specific timing on npx create-react-app

      What does WSL 2 bring?

      This is the process I went through and the surprises I encountered while installing.

      Installing WSL2 on Windows 10

      Microsoft now has stable documentation on how to install WSL and update to WSL2.

      To get up and running, follow the guide above through to the point where you set up a new linux distribution.

      Checking if the Install Worked

      The following command will show us what distros we have installed and what version they are on:

      • wsl --list --verbose
      • # or shorthand
      • wsl -l -v

      Installation Failure

      If you already had Ubuntu installed on WSL 1, you may have to completely uninstall and reinstall it.

      If your computer is having trouble running the update command (like my computer), then you may want to completely uninstall and reinstall your distro.

      I went into the Windows settings under Apps > Apps and Features and uninstalled Ubuntu:

      Then I made sure that the default version I wanted for all new installs was version 2:

      • wsl --set-default-version 2

      Now we can go into the Windows Store to install it:

      Once we’re installed, then we can check to be sure that version 2 was installed. Open up Powershell and run:

      Running WSL

      You can open up Windows Terminal and use the Ubuntu dropdown:

      Alternatively you can open up either cmd or Powershell and run:

      • # open up windows subsystem for linux
      • wsl

      Gotchas with WSL 2

      Speed when transferring between file systems is a little slow right now. That’s not a worry for me since I never transferred. I worked solely inside of my Windows files which were mounted into the Linux system.

      Here’s a guide on User Experience changes from WSL 1 to WSL 2. The two big gotchas are:

      1. Move your files into the Linux file system instead of your Windows system
      2. You will need to access localhost apps like [localhost:3000](http://localhost:3000) via an IP address like 192.168.28.2:3000

      Move all files into Linux

      To take advantage of all the new speed improvements in WSL 2, our files will need to be moved into the Linux filesystem.

      The best way to figure out where to move your files is to find the home directory in Linux, then open it in Windows explorer. Run the following:

      • # find the home folder
      • cd ~
      • # open up windows explorer for this folder
      • explorer.exe .

      Notice the path as a Network path:

      We can now move our files from our Windows folders into this new networked folder. We’ll be able to access it from our WSL and interact with it as if it were still in the same Windows files.

      For instance, we can install Node using a tool like n and then run npm start to run a local server for let’s say a React app.

      Network Isn’t localhost Yet

      When we create an app using create-react-app or the vue-cli, we will usually run a command like yarn start or yarn serve to run a local server.

      Normally we would be able to check on our application right in our browser using [localhost:3000](http://localhost:3000) for React or [localhost:8080](http://localhost:8080) for Vue.

      In the early stages of WSL 2, we can’t use localhost. We need to use an IP since Linux is inside a VM.

      To access your application currently, we will use an IP.

      Notice the 192.168.28.2:3000. We’ll use that to access our application:

      A Quick Comparison and Speed Test

      This entire exercise was to get a setup that was faster than the previous one. Let’s see if this setup is any faster!

      I don’t have anything too scientific. I’ll go back and run more tests, but I was frustrated how long a new React app took WSL 1 to make.

      For now, our test will be to run npx create-react-app my-new-app.

      We’ll be comparing the following machines. I know this isn’t scientific at all. I wish I had more computers with similar setups. I wish I had done these speed tests before I upgraded to WSL 2. Oh well. We have what we have!

      • My desktop machine (super powerful, more than the laptops for sure)
      • Surface Book 2 15" i7
      • MacBook Pro 15" 2015
      • npx create-react-app my-new-app

      Here are the numbers I got from running the test a few times on each platform.

      • Surface Book 2 WSL 1: 257 seconds
      • Surface Book 2 WSL 2: 52 seconds
      • 2015 MacBook Pro: 45 seconds
      • 2018 MacBook Pro: 38 seconds

      While still not as fast as the latest MacBook Pro, WSL 2 has made significant improvements over WSL 1.

      What’s Next?

      We’ll keep getting updates and I’ll keep testing to see if performance is improving. I would love to get to a point where WSL 2 on Windows could be as fast as a 2018 MacBook Pro.

      I love both Windows and Mac platforms and with WSL 2, my tools on both platforms has gotten even closer:

      Happy coding!



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