Step-by-Step Process To Deploy Python Application In Docker Compose

Step 1: Launch an Instance

• Go to the AWS console and log in with credentials or create an account
• Now launch an EC2 instance

Now connect with terminal

Step 2: Install Docker

• Install docker by using following commands

sudo yum -y install docker

• Now start and enable docker by using following commands

sudo systemctl start docker
sudo systemctl enable docker
sudo systemctl status docker

Step 3: Install docker-compose

Now install docker compose by using following commands

sudo curl -L https://github.com/docker/compose/releases/download/1.22.0/docker-compose-$(uname -s)-$(uname -m) -o /usr/local/bin/docker-compose

Now change permissions to docker-compose by using following commands

sudo chmod +x /usr/local/bin/docker-compose

+x means we are giving execution permissions only to docker-compose.

Step 4: Create Dockerfile

Now we are creating dockerfile inside this dockerfile we are defining our python application

FROM amazonlinux:latest

# Update packages and install necessary dependencies
RUN yum update -y && \
    yum install -y git python3-pip

# Clone the repository
RUN git clone https://github.com/Sada-Siva-Reddy07/fish.git /fish

# Set the working directory
WORKDIR /fish

# Install Python dependencies
RUN pip3 install -r requirements.txt

# Expose port 2000 (if required)
EXPOSE 2000

# Specify the command to run the Python application
CMD ["python3", "./app.py"]

Here is the git repository link you can clone from my git repository if you want

“https://github.com/Sada-Siva-Reddy07/fish.git”.

Step 5: Create Docker-compose file

version: '3.3'

services:
  python_app:
    build:
      context: .
      dockerfile: Dockerfile
    ports:
      - "2000:2000"

Step 6: Build docker Image

• Now build docker image by using following command

docker-compose build 

• We can check docker images by using following command

docker-compose images

Step-7: Run the Docker-compose up

Now run the docker-compose up command to run the containers

docker-compose up

Step 7: Verify

Now copy and browse public ip along with port number

In the domain of present day software development, Python has arisen as a powerhouse language, leaned toward for its simplicity, readability, and flexibility. With Python, developers can make a wide cluster of uses, from web services and APIs to data handling pipelines and AI models. Notwithstanding, conveying and overseeing Python applications across different conditions can introduce difficulties, especially with regards to ensuring consistency and reproducibility.

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