The comparison and selection guide of the WERCKER class library and other Python class libraries

Wercker is a popular continuous integration and deployment tool that is suitable for automated construction, testing and deployment applications.Compared with other Python class libraries, Wercker provides some unique functions and advantages.This article will compare Wercker with other Python class libraries and provide a guide to select Wercker. 1. The advantage of Wercker 1. Construction of container: Wercker uses a docker container for construction and testing.This makes the construction process more reliable and repeated, avoiding problems caused by environmental differences. 2. Multi -environment support: Wercker supports the construction and deployment of multiple environments, including cloud platforms (such as AWS and Azure) and local environments.This allows developers to easily build and deploy applications in different environments. 3. Integration: Wercker provides integration with many popular development tools and services, such as Github, Slack and Hipchat.This makes teamwork and notifications simpler and convenient. 4. Flexible configuration: Wercker uses the configuration file of YAML format to allow developers to customize the construction process and deployment strategy.This makes the configuration more flexible and scalable. 5. Real -time log: Wercker provides real -time construction logs to facilitate developers to track the construction process and find problems in time. 2. Comparison with other Python class libraries Compared with other Python class libraries, Wercker has the following advantages: 1. Jenkins: Compared with Jenkins, Wercker's configuration is simpler and intuitive.Wercker uses yaml files for configuration, without having to write complex scripts.In addition, Wercker's Docker support makes the construction process more reliable and repeated. 2. Circleci: Compared with CircleCi, Wercker provides richer integration and more flexible configuration options.Wercker supports integration with many popular development tools and services, and can easily integrate with other tools used in the team. 3. Travis CI: Compared with Travis CI, Wercker provides more construction options and deployment goals.Wercker supports multiple construction steps and different construction strategies, which can easily configure the construction and deployment of different environments. 4. Gitlab CI: Compared with Gitlab CI, Wercker's integration and configuration are simpler and easy to use.Wercker can be seamlessly integrated with gitlab to provide real -time logs and results reports. 3. Select Guide The following factors should be considered when choosing to use Wercker: 1. Construction requirements: Understand the construction and deployment requirements of your own project.If the project needs to be constructed and deployed in multiple environments, Wercker may be a good choice. 2. Integrated demand: Consider other development tools and services used in the team.If you need to integrate with other tools, Wercker provides seamless integration with many popular tools. 3. Configuration complexity: Consider the complexity of configuration according to the team's skills level and project requirements.Wercker provides simple and intuitive configuration options for developers with different skills. The following is the code of the Wercker configuration file (Wercker.yml) of an example:: yaml box: python:3.8 build: steps: - script: name: Install dependencies code: pip install -r requirements.txt - script: name: Run tests code: python tests.py deploy: steps: - script: name: Deploy to production code: python deploy.py The above configuration file specifies the steps of construction and deployment.First, it uses the Docker container of Python 3.8 version.It then installs the project's dependence and run the test.Finally, it deploys the application into the production environment. It should be noted that the `Requirements.txt`, Tests.py` and` deploy.py` are the file names configured according to the actual situation of the project. Through the above comparison and selection guide, I hope to help readers understand the differences between Wercker and other Python class libraries, and provide some suggestions for choosing appropriate continuous integration and deployment tools.