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https://github.com/devopsinsiders/gettaskstodomicroservice

๐Ÿ” GetTasksTodoMicroservice ๐Ÿ“Šrepository houses the microservice designed for retrieving tasks within the Todo application. Specializing in task retrieval, it offers endpoints for fetching tasks based on various criteria, such as user ID and task status, facilitating efficient task management and organization. ๐Ÿš€
https://github.com/devopsinsiders/gettaskstodomicroservice

microservice python

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๐Ÿ” GetTasksTodoMicroservice ๐Ÿ“Šrepository houses the microservice designed for retrieving tasks within the Todo application. Specializing in task retrieval, it offers endpoints for fetching tasks based on various criteria, such as user ID and task status, facilitating efficient task management and organization. ๐Ÿš€

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README

        

Certainly! Here's a README file to help you run the Python application using Docker:

# Running the Python Application with Docker

This 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.

## Prerequisites

Before getting started, make sure you have the following prerequisites installed on your system:

- [Docker](https://docs.docker.com/get-docker/)
- Docker Compose (usually included with Docker Desktop on Windows and Docker for Mac)

## Step 1: Clone the Repository

Clone the application's source code from your version control system or download it as a zip archive and extract it to your local machine.

```bash
git clone
cd
```

## Step 2: Update Connection String

Edit the `app.py` file to update the `connection_string` variable with the appropriate connection details for your SQL Server database.

## Step 3: Build the Docker Image

To build the Docker image, open a terminal, navigate to the project directory, and run the following command:

```bash
docker build -t my-python-app .
```

Replace `my-python-app` with a suitable name for your Docker image.

## Step 4: Run the Docker Container

After successfully building the Docker image, you can run the application in a Docker container with the following command:

```bash
docker run -p 8000:8000 my-python-app
```

Replace `my-python-app` with the name you provided in step 3.

The `-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.

## Step 5: Access the Application

Your 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`.

## API Endpoints

- `/tasks`: List all tasks (GET)
- `/tasks/{task_id}`: Retrieve a single task by ID (GET)
- `/tasks`: Create a new task (POST)
- `/tasks/{task_id}`: Update an existing task by ID (PUT)
- `/tasks/{task_id}`: Delete a task by ID (DELETE)

## Cleaning Up

To stop and remove the Docker container, press `Ctrl + C` in the terminal where the container is running. Then, remove the container with:

```bash
docker rm -f
```

Replace `` with the actual container ID, which you can obtain from `docker ps`.

## Conclusion

You'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.