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Overview

This article discusses the use of apiplate as a testbed for learning Python development and asking questions to the community with solid examples. The author explains that this project began as an attempt to complete the Challenge #333, which involved building a Web API-driven data site. The article also mentions the use of various technologies such as Python, OpenAPI/Swagger, Flask/Connexion, Celery, Google Closure Compiler, Swagger UI v2, Reclinejs, Slickgrid, and Backbone.

Features

• Python: The project is developed using the Python programming language.
• OpenAPI/Swagger: The OpenAPI/Swagger specification is used to define the API endpoints.
• Flask/Connexion: Flask is used as the web framework, and Connexion is used to connect the API specification with the Flask app.
• Celery: Celery is used as the distributed task queue for executing asynchronous tasks.
• Google Closure Compiler: The Google Closure Compiler is used to minify the JavaScript code.
• Swagger UI v2: Swagger UI v2 is used to visualize and interact with the API documentation.
• Reclinejs: Reclinejs is used for building data applications using Backbone.js.
• Slickgrid: Slickgrid is used as a dependency for using slickgrid in the project.
• Backbone: Backbone is used as the JavaScript library for structuring the application.

Summary

This article discusses the use of apiplate as a testbed for learning Python development and asking questions to the community. The author explains the various features of the project, including the use of technologies such as Python, OpenAPI/Swagger, Flask/Connexion, Celery, Google Closure Compiler, Swagger UI v2, Reclinejs, Slickgrid, and Backbone. The installation process is also described, providing step-by-step instructions for setting up and running the project.