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As Python web development is used in more and more projects, automated deployment has become an essential part. In the first part, we explained the basic deployment methods of Python web applications and the use of related tools. In this article, we will continue to introduce some more advanced automated deployment techniques to help you complete your deployment tasks more efficiently.
1. Use Fabric to automate deployment
Fabric is a Python library for automating command execution and running Shell scripts on local or remote machines. It can make the deployment process more automated and simplify complex deployment operations. The following is a sample code:
from fabric import Connection from invoke import Responder def deploy(): c = Connection(host='server_name', user='username', connect_kwargs={"password": "password"}) sudo_pass = Responder(pattern=r'[sudo] password:', response='password ') c.run('sudo apt-get update', pty=True, watchers=[sudo_pass]) c.run('sudo apt-get install -y nginx', pty=True, watchers=[sudo_pass]) c.put('path/to/local/folder', '/path/to/remote/folder') c.run('sudo service nginx restart', pty=True, watchers=[sudo_pass])
The above example is a sample code that uses Fabric to automatically deploy a Python web application. It first sends some commands from the local to the remote server, then performs some installation and configuration operations, and uploads local files to the remote server.
It should be noted that when executing the sudo command, you need to use the Responder sublibrary to process the input of the sudo password.
2. Use Docker container deployment
Docker is an open source application container engine that can help you deploy and manage applications more easily. With Docker, an entire application and all its dependencies can be packaged into a container and run on any platform that supports the Docker engine. The following is an example of using Docker to deploy a Python web application:
FROM python:3.6.4-alpine3.7 RUN mkdir /app WORKDIR /app COPY requirements.txt . RUN pip install -r requirements.txt COPY . . EXPOSE 8000 CMD ["python", "manage.py", "runserver", "0.0.0.0:8000"]
The above example Dockerfile is a file built based on the python:3.6.4-alpine3.7 image. It first copies the requirements.txt file into the container and executes pip install in the container to install all the application's dependencies. Then copy the entire application into the container and expose port 8000 in the container. Finally, run the Django application on port 8000.
In this way, we can use Docker to deploy Python web applications. Not only is it easy to manage, but it also makes it easy to deploy applications in different environments.
3. Use Jenkins for automated CI/CD
Jenkins is a popular open source CI/CD automation tool that can help developers quickly build, test, deliver and deploy applications. It can be integrated into Git, Docker and other development tools to automatically build and test code, and automatically deploy the code after passing the test. The following is an example of using Jenkins for CI/CD:
We can create a Jenkins Job named "Python Web App" and run Select the "Poll SCM" option in the build trigger to automatically build and deploy the application when there are new commits in the Git repository.
Create a file named "Jenkinsfile" in the root directory of the project and specify the following command:
pipeline { agent any stages { stage('Build') { steps { sh 'docker build -t python:latest .' } } stage('Test') { steps { sh 'docker run --rm python:latest python manage.py test' } } stage('Deploy') { steps { sshagent(['my-ssh-key']) { sh 'ssh user@server "docker-compose down && docker-compose up -d"' } } } } }
This Jenkinsfile You can tell Jenkins how to build the application, run tests and deploy the code. In the "Deploy" phase, it uses SSH to connect to the remote server and uses Docker Compose to deploy the application.
Once we have configured the Jenkinsfile and Jenkins Job, we can start using Jenkins for automated CI/CD. Just submit new code in the Git repository, and Jenkins will automatically detect the new submission and automatically build, test, and deploy the application.
Summary:
In Python web development, automated deployment is a very important task. In this article we introduce some techniques for automating the deployment of Python web applications using tools such as Fabric, Docker, and Jenkins. Through these techniques, we can deploy applications more efficiently and improve development efficiency and code quality. Hope these tips are helpful to you.
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