Book Image

Python Architecture Patterns

By : Jaime Buelta
Book Image

Python Architecture Patterns

By: Jaime Buelta

Overview of this book

Developing large-scale systems that continuously grow in scale and complexity requires a thorough understanding of how software projects should be implemented. Software developers, architects, and technical management teams rely on high-level software design patterns such as microservices architecture, event-driven architecture, and the strategic patterns prescribed by domain-driven design (DDD) to make their work easier. This book covers these proven architecture design patterns with a forward-looking approach to help Python developers manage application complexity—and get the most value out of their test suites. Starting with the initial stages of design, you will learn about the main blocks and mental flow to use at the start of a project. The book covers various architectural patterns like microservices, web services, and event-driven structures and how to choose the one best suited to your project. Establishing a foundation of required concepts, you will progress into development, debugging, and testing to produce high-quality code that is ready for deployment. You will learn about ongoing operations on how to continue the task after the system is deployed to end users, as the software development lifecycle is never finished. By the end of this Python book, you will have developed "architectural thinking": a different way of approaching software design, including making changes to ongoing systems.
Table of Contents (23 chapters)
2
Part I: Design
6
Part II: Architectural Patterns
12
Part III: Implementation
15
Part IV: Ongoing operations
21
Other Books You May Enjoy
22
Index

Partial profiling

In many scenarios, profilers will be useful in environments where the system is in operation and we cannot wait until the process finishes before obtaining profiling information. Typical scenarios are web requests.

If we want to analyze a particular web request, we may need to start a web server, produce a single request, and stop the process to obtain the result. This doesn't work as well as you may think due to some problems that we will see.

But first, let's create some code to explain this situation.

Example web server returning prime numbers

We will use the final version of the function check_if_prime and create a web service that returns all the primes up to the number specified in the path of the request. The code will be the following, and it's fully available in the server.py file on GitHub at https://github.com/PacktPublishing/Python-Architecture-Patterns/blob/main/chapter_14_profiling/server.py.

from http.server import...