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

Creating your own private index

Sometimes, you'll need to have your own private index, so you can serve your own packages without opening them to the full internet, for internal packages that need to be used across the company, but where it doesn't make sense to upload them to the public PyPI.

You can create your own private index that can be used to share those packages and install them by calling to that index.

To serve the packages, we need to run a PyPI server locally. There are several options in terms of available servers that can be used, but an easy option is pypiserver (https://github.com/pypiserver/pypiserver).

pypiserver can be installed in several ways; we will see how to run it locally, but to serve it correctly, you'll need to install it in a way that's available in your network. Check the documentation to see several options, but a good option is to use the official Docker image available.

To run pypiserver, first, install...