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https://github.com/devopsinsiders/addtasktodomicroservice
📝 AddTaskTodoMicroservice 📥 repository encompasses the microservice tailored for adding tasks within the Todo application. Focused on task creation, it provides an endpoint dedicated to seamless addition operations, streamlining the process of task integration and enhancing productivity within the application. 🚀
https://github.com/devopsinsiders/addtasktodomicroservice
microservice python
Last synced: 1 day ago
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📝 AddTaskTodoMicroservice 📥 repository encompasses the microservice tailored for adding tasks within the Todo application. Focused on task creation, it provides an endpoint dedicated to seamless addition operations, streamlining the process of task integration and enhancing productivity within the application. 🚀
- Host: GitHub
- URL: https://github.com/devopsinsiders/addtasktodomicroservice
- Owner: devopsinsiders
- Created: 2023-11-10T20:23:30.000Z (12 months ago)
- Default Branch: main
- Last Pushed: 2023-12-16T06:52:04.000Z (11 months ago)
- Last Synced: 2024-11-06T12:15:37.255Z (1 day ago)
- Topics: microservice, python
- Language: Python
- Homepage: https://devopsinsiders.com
- Size: 15.6 KB
- Stars: 7
- Watchers: 2
- Forks: 13
- Open Issues: 0
-
Metadata Files:
- Readme: Readme.md
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README
# 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.