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Mastering Flask Web and API Development

Mastering Flask Web and API Development

By : Sherwin John C. Tragura
5 (2)
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Mastering Flask Web and API Development

Mastering Flask Web and API Development

5 (2)
By: Sherwin John C. Tragura

Overview of this book

Flask is a popular Python framework known for its lightweight and modular design. Mastering Flask Web and API Development will take you on an exhaustive tour of the Flask environment and teach you how to build a production-ready application. You’ll start by installing Flask and grasping fundamental concepts, such as MVC and ORM database access. Next, you’ll master structuring applications for scalability through Flask blueprints. As you progress, you’ll explore both SQL and NoSQL databases while creating REST APIs and implementing JWT authentication, and improve your skills in role-based access security, utilizing LDAP, OAuth, OpenID, and databases. The new project structure, managed by context managers, as well as ASGI support, has revolutionized Flask, and you’ll get to grips with these crucial upgrades. You'll also explore out-of-the-box integrations with technologies, such as RabbitMQ, Celery, NoSQL databases, PostgreSQL, and various external modules. The concluding chapters discuss enterprise-related challenges where Flask proves its mettle as a core solution. By the end of this book, you’ll be well-versed with Flask, seeing it not only as a lightweight web and API framework, but also as a potent problem-solving tool in your daily work, addressing integration and enterprise issues alongside Django and FastAPI.
Table of Contents (18 chapters)
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1
Part 1:Learning the Flask 3.x Framework
6
Part 2:Building Advanced Flask 3.x Applications
12
Part 3:Testing, Deploying, and Building Enterprise-Grade Applications

Configuring the logging mechanism

Flask utilizes the standard logging modules of Python. The app instance has a built-in logger() method, which is pre-configured and can log views, repositories, services, and events. The only problem is that this default logger cannot perform info logging because the default severity level of the configuration is WARNING. By the way, turn off debug mode when running applications with a logger to avoid logging errors.

The Python logging mechanism has the following severity levels:

  • Debug: This level has a severity value of 10 and can provide traces of results during the debugging process.
  • Info: This level has a severity value of 20 and can provide general details about execution flows.
  • Warning: This level has a severity value of 30 and can inform about areas of the application that may cause problems in the future due to some changes in the platform or API classes.
  • Error: This level has a severity value of 40 and can track down...

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