Merge pull request #14 from jetbrains-academy/konstantin/deploy_on_do…

…cker_fixes

Fixes of Deploy API on Docker lesson

.github/workflows/links_checker.yml

@@ -0,0 +1,23 @@
+name: LinksChecker
+
+on:
+  # Triggers the workflow on push or pull request events for specific branches
+  push:
+    branches: [ "master" ]
+  pull_request:
+    branches: [ "master" ]
+
+  # Allows you to run this workflow manually from the Actions tab
+  workflow_dispatch:
+
+jobs:
+  links-checker-job:
+    runs-on: ubuntu-latest
+    steps:
+      - name: Check out repository code
+        uses: actions/checkout@v4
+
+      - name: Call the action jetbrains-academy/links-checker-action
+        uses: jetbrains-academy/links-checker-action@main
+        with:
+          dir: ./

Deploy API on Docker/Postman/task-info.yaml → Deploy API on Docker/API Testing/task-info.yaml

@@ -10,7 +10,7 @@ files:
     visible: true
   - name: requirements.txt
     visible: true
-  - name: Postman1.png
+  - name: images/httpie_post.png
     visible: false
-  - name: Postman2.png
+  - name: images/httpie_get.png
     visible: false

Deploy API on Docker/API Testing/task.md

@@ -0,0 +1,24 @@
+Developers need to test their APIs. There are plenty of tools for these tasks, allowing you to send a wide variety of HTTP, REST, and other requests. For example, [Postman](https://www.postman.com/) or the integrated [HTTP Client](https://www.jetbrains.com/help/pycharm/http-client-in-product-code-editor.html) in PyCharm Professional. 
+
+In this task, we will use the open-source tool [HTTPie](https://httpie.io). All such applications are similar in some way, so you can use HTTPie or any other tool by analogy.
+
+You can download and install a desktop version of HTTPie [here](https://httpie.io/desktop).
+
+### GET request
+As with all such programs, the interface allows you to specify the query type, parameters, headers, authorization type, and more. For the very first request, we only need to specify the URL `http://0.0.0.0:5000/items` and press the **Send** button.
+
+Remember to launch our Flask application beforehand!
+
+![](images/httpie_get.png)
+
+HTTPie automatically detects the language of the response, links, and formats text inside the body to make inspection easy.
+
+### POST request
+Next, create a POST request. To do this, specify the `POST` request type, the URL `http://0.0.0.0:5000/items`, and the Body of the request. Select `Text` as the Body type.
+
+After executing the request, you should get a response containing the request body.
+
+![](images/httpie_post.png)
+
+### Explore your app
+Check that all the other methods defined in your API work as expected (getting a specific device, deleting a device, updating a device).

Deploy API on Docker/Docker Intro/main.py

@@ -1,3 +1,2 @@
 if __name__ == "__main__":
-    # Write your solution here
     pass

Deploy API on Docker/Docker Intro/task-info.yaml

@@ -1,16 +1,28 @@
 type: theory
 files:
-- name: main.py
-  visible: true
-- name: __init__.py
-  visible: false
-- name: images/img.png
-  visible: false
-- name: images/img_1.png
-  visible: false
-- name: images/img_2.png
-  visible: false
-- name: images/img_3.png
-  visible: false
-- name: images/img_4.png
-  visible: false
+  - name: main.py
+    visible: true
+  - name: __init__.py
+    visible: false
+  - name: images/docker.png
+    visible: false
+  - name: images/edit_dark.svg
+    visible: false
+  - name: images/edit.svg
+    visible: false
+  - name: images/run.svg
+    visible: false
+  - name: images/run_dark.svg
+    visible: false
+  - name: images/add_dark.svg
+    visible: false
+  - name: images/add.svg
+    visible: false
+  - name: images/settings_docker_dark.png
+    visible: false
+  - name: images/settings_docker.png
+    visible: false
+  - name: images/services.png
+    visible: false
+  - name: images/services_dark.png
+    visible: false

Deploy API on Docker/Docker Intro/task.md

@@ -1,7 +1,6 @@
 Running the app as described before works just fine, but it assumes you have the Python environment set up correctly. We can avoid this issue by running the application in a **Docker container**.
 
 ### Docker Containers
-
 Docker containers provide code isolation, independence, and portability. Docker is essentially needed 
 if one intends to deploy their application into production. Docker containers have fully prescribed 
 dependencies with which they can be created. These dependencies, as well as the instructions on how 
@@ -11,30 +10,26 @@ A **Dockerfile** is basically a set of instructions for building a container ima
 
 Read more about Docker in [Docker docs](https://docs.docker.com/).
 
-### Enable Docker support in IntelliJ IDEA
-
-1. Install and run Docker. For more information, see the Docker documentation.
-
-2. Configure the Docker daemon connection settings:
-
-
-a) Press ⌘, to open the IDE settings and select **Build, Execution, Deployment | Docker**.
-
-
-b) Click **+** to add a Docker configuration and specify how to connect to the Docker daemon.
-
-The connection settings depend on your Docker version and operating system. For more information, see [Docker configuration](https://www.jetbrains.com/help/idea/docker-connection-settings.html).
+### Docker support in JetBrains IDEs
+JetBrains IDEs allow you to manage Docker containers using a graphical interface. Only a few simple steps are required to set this up.
 
-The **Connection successful** message should appear at the bottom of the dialog.
+### 1. Install and run Docker
+For more information, see the [Docker documentation](https://docs.docker.com/engine/install/) specific to your operating system.
 
-![](images/img.png)
+### 2. Configure the Docker daemon connection settings
 
-3. Connect to the Docker daemon.
-   The configured Docker connection should appear in the Services tool window (**View | Tool Windows | Services** or ⌘8). Select the Docker node ![](images/img_2.png) and click ![](images/img_3.png), or select **Connect** from the context menu.
+1. Open the IDE settings (you can use the shortcut &shortcut:ShowSettings;) and select **Build, Execution, Deployment | Docker**.
+2. Click ![](images/add.svg) to add a Docker configuration and specify how to connect to the Docker daemon.  
+    The connection settings depend on your Docker version and operating system. For more information, see [Docker configuration](https://www.jetbrains.com/help/pycharm/settings-docker.html).  
+    The **Connection successful** message should appear at the bottom of the dialog.  
+
+![](images/settings_docker.png)
 
-![](images/img_1.png)
+### 3. Connect to the Docker daemon
+The configured Docker connection should appear in the Services tool window (**View | Tool Windows | Services** or &shortcut:ActivateServicesToolWindow;). Select the Docker node ![](images/docker.png) and click ![](images/run.svg), or select **Connect** from the context menu. Once connected, it will look like this:
+<div style="text-align:center;"><img src="images/services.png" style="width:70%;" alt="Run MyRunConfig"></div>
 
-To edit the Docker connection settings, select the Docker node and click ![](images/img_4.png) on the toolbar, or select **Edit Configuration** from the context menu.
+To edit the Docker connection settings, select the Docker node and click ![](images/edit.svg) on the toolbar, or select **Edit Configuration** from the context menu.
 
 <style>
 img {

Deploy API on Docker/Docker run configuration setup/task-info.yaml

@@ -10,7 +10,35 @@ files:
     visible: true
   - name: requirements.txt
     visible: true
-  - name: config2.png
+  - name: images/add.svg
     visible: false
-  - name: config1.png
+  - name: images/add_dark.svg
+    visible: false
+  - name: images/browse_dark.svg
+    visible: false
+  - name: images/browse.svg
+    visible: false
+  - name: images/port_bindings_dark.png
+    visible: false
+  - name: images/port_bindings.png
+    visible: false
+  - name: images/add_configuration.png
+    visible: false
+  - name: images/add_configuration_dark.png
+    visible: false
+  - name: images/run.svg
+    visible: false
+  - name: images/run_dark.svg
+    visible: false
+  - name: images/run_myrunconfig_dark.png
+    visible: false
+  - name: images/run_myrunconfig.png
+    visible: false
+  - name: images/stop_container_dark.png
+    visible: false
+  - name: images/stop_container.png
+    visible: false
+  - name: images/delete_image.png
+    visible: false
+  - name: images/delete_image_dark.png
     visible: false

Deploy API on Docker/Docker run configuration setup/task.md

@@ -1,19 +1,52 @@
-## Docker run configuration setup
-
-Another caveat: to connect to the application running in a container, you need to 	
-map specific container ports to specific ports on the host. In the previous task, this setup was already done for you. 
-To do it yourself, you need to:
-
-- From the main menu, select **Run | Edit Configurations**.
-- In the **Run/Debug Configurations dialog**, click **+**, select **Docker**, and then select the **Dockerfile** configuration.
-- In **Build**, select the correct Dockerfile path.
-![](config1.png)
-- Then click **Modify** and select **Bind ports**.
-- In **Bind ports**, click the folder symbol, and in the window that opens (Port Bindings), click **+** and add 
-the ports to be bound. In our case, add `5000` to both Host post and Container port. Leave everything else as is.
-![](config2.png)
-- Add the name of the container and image tag. Please use "flask-app-invsys" and "flask-app-invsys-img" respectively.
-- Click **Ok** two times.
-
-Now, if you run the Dockerfile, you should be able to access your app via `http://0.0.0.0:5000/items`. 
+So, by now, we know that to run our solution in a container, we need to:
+- Build an image according to the Dockerfile.
+- Start the container from this image.
+- Bind the container's port to our host machine's port so that we can access our application in the container.
+
+The course checking system handles all of this for you, but let's also learn how to do it ourselves.
+This is not difficult at all, as all these actions can be delegated to the IDE.
+
+[Run configurations](https://www.jetbrains.com/help/pycharm/run-debug-configuration.html) are specially designed for these tasks. They allow describing exactly how to run an application and specifying various launch parameters. In this lesson, we will focus only on [Docker run configurations](https://www.jetbrains.com/help/pycharm/docker-run-configurations.html).
+
+**Note: In this course, do not remove or modify run configurations that you didn't create on your own!**
+
+### Create Docker run configuration
+- From the main menu, select **Run | Edit Configurations…**
+- In the opened **Run/Debug Configurations** window, click ![](images/add.svg), select **Docker**, and then select the **Dockerfile** configuration.
+- Specify the name of your configuration. It can be anything you like; we chose `MyRunConfig`.
+- Specify the path to the required `Dockerfile`. This will be the path to the `Dockerfile` for this lesson.
+- Add the **Image tag** and the **Container name**. Please use `flask-app-invsys-img` and `flask-app-invsys`, respectively.
+
+![](images/add_configuration.png)
+
+- Next, click **Modify** and select **Bind ports**.
+- In the **Bind ports:** field that appears, click on ![](images/browse.svg) to open the **Port Bindings** window.
+- Click ![](images/add.svg) and add the ports to be bound. 
+- In our case, add `5000` to both **Host port** and **Container port**. Leave everything else as is.
+![](images/port_bindings.png)
+- Click **OK** two times to save your port binding and run configuration!
+
+### Launch your configuration
+In the upper right corner of the IDE, select your run configuration from the list if it is not already selected. Afterward, click on ![](images/run.svg) or use the shortcut &shortcut:Run; to run your configuration.
+<div style="text-align:center;"><img src="images/run_myrunconfig.png" style="width:40%;" alt="Run MyRunConfig"></div>
+
+Now, after you run the Dockerfile, you should be able to access your app via http://0.0.0.0:5000/items. 
 Otherwise, you will get a "Connection refused" error.
+
+### Shut down your configuration
+To stop your Docker container, just open the panel [Services](tool_window://Services) (or use the shortcut &shortcut:ActivateServicesToolWindow;), right-click the container, and select **Stop Container**. From this context menu, you can also delete the container using the **Delete...** option. This will delete only the container — no local files will be deleted.
+<div style="text-align:center;"><img src="images/stop_container.png" style="width:50%;" alt="Run MyRunConfig"></div>
+
+### Don't forget
+A Docker image contains application code, libraries, tools, dependencies, and other files needed to run your application.
+When your application does not work as expected and you find an error, correcting it in your project will not save this change to the image you previously created and ran. You should delete an old
+Docker image and rebuild it after fixing the problem.
+
+You can also delete your image from the [Services](tool_window://Services) panel:
+<div style="text-align:center;"><img src="images/delete_image.png" style="width:60%;" alt="Run MyRunConfig"></div>
+
+<style>
+img {
+  display: inline !important;
+}
+</style>

Deploy API on Docker/Dockerfile/docker-compose.yml

@@ -5,4 +5,4 @@ services:
         container_name: flask-app-invsys
         image: flask-app-invsys-img
         ports:
-            - "5000:5000"
+            - "5000:5000"

Deploy API on Docker/Dockerfile/requirements.txt

@@ -1,3 +1,3 @@
 Flask
 flask-restful
-marshmallow
+marshmallow

Deploy API on Docker/Dockerfile/task-info.yaml

@@ -5,7 +5,9 @@ files:
     placeholders:
       - offset: 0
         length: 141
-        placeholder_text: '# TODO'
+        placeholder_text: '# Add the contents of the Dockerfile from the task description'
+  - name: requirements.txt
+    visible: true
   - name: tests/test_task.py
     visible: false
   - name: __init__.py
@@ -16,10 +18,6 @@ files:
     visible: true
   - name: dal.py
     visible: true
-  - name: requirements.txt
-    visible: true
-  - name: delete_image.png
-    visible: false
   - name: runConfigurations/Deploy_on_Docker_Dockerfile_Test.run.xml
     visible: false
   - name: docker-compose.yml