{"id":18479621,"url":"https://github.com/devopsinsiders/deletetasktodomicroservice","last_synced_at":"2025-10-27T19:41:44.816Z","repository":{"id":206614832,"uuid":"717215065","full_name":"devopsinsiders/DeleteTaskTodoMicroservice","owner":"devopsinsiders","description":"🗑️ DeleteTaskTodoMicroservice 📋 repository hosts the microservice engineered to manage task deletions within the Todo application. 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Here's a README file to help you run the Python application using Docker:\n\n# Running the Python Application with Docker\n\nThis guide will walk you through the process of building a Docker image and running a Python application using FastAPI, which interacts with a Microsoft SQL Server database using PyODBC. The application is containerized for easy deployment and scaling.\n\n## Prerequisites\n\nBefore getting started, make sure you have the following prerequisites installed on your system:\n\n- [Docker](https://docs.docker.com/get-docker/)\n- Docker Compose (usually included with Docker Desktop on Windows and Docker for Mac)\n\n## Step 1: Clone the Repository\n\nClone the application's source code from your version control system or download it as a zip archive and extract it to your local machine.\n\n```bash\ngit clone \u003crepository_url\u003e\ncd \u003crepository_directory\u003e\n```\n\n## Step 2: Update Connection String\n\nEdit the `app.py` file to update the `connection_string` variable with the appropriate connection details for your SQL Server database.\n\n## Step 3: Build the Docker Image\n\nTo build the Docker image, open a terminal, navigate to the project directory, and run the following command:\n\n```bash\ndocker build -t my-python-app .\n```\n\nReplace `my-python-app` with a suitable name for your Docker image.\n\n## Step 4: Run the Docker Container\n\nAfter successfully building the Docker image, you can run the application in a Docker container with the following command:\n\n```bash\ndocker run -p 8000:8000 my-python-app\n```\n\nReplace `my-python-app` with the name you provided in step 3.\n\nThe `-p 8000:8000` option maps port 8000 on your host machine to the container's port 8000. You can change the host port if needed.\n\n## Step 5: Access the Application\n\nYour Python application is now running in a Docker container. You can access it by opening a web browser or sending HTTP requests to `http://localhost:8000`.\n\n## API Endpoints\n\n- `/tasks`: List all tasks (GET)\n- `/tasks/{task_id}`: Retrieve a single task by ID (GET)\n- `/tasks`: Create a new task (POST)\n- `/tasks/{task_id}`: Update an existing task by ID (PUT)\n- `/tasks/{task_id}`: Delete a task by ID (DELETE)\n\n## Cleaning Up\n\nTo stop and remove the Docker container, press `Ctrl + C` in the terminal where the container is running. Then, remove the container with:\n\n```bash\ndocker rm -f \u003ccontainer_id\u003e\n```\n\nReplace `\u003ccontainer_id\u003e` with the actual container ID, which you can obtain from `docker ps`.\n\n## Conclusion\n\nYou've successfully built and run a Python application using Docker. Feel free to make changes to the application, rebuild the Docker image, and deploy it to your preferred environment.","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdevopsinsiders%2Fdeletetasktodomicroservice","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fdevopsinsiders%2Fdeletetasktodomicroservice","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdevopsinsiders%2Fdeletetasktodomicroservice/lists"}