标签：#designpatterns

I keep coming back to java.util.ServiceLoader . I have used it to put a JSON layer behind a contract, so the core code carries no direct dependency on any particular JSON library and I can swap the implementation without touching callers. The same shape works for JWT handling, where the concrete library might be jose4j or another JOSE implementation, and you can easily find other decoupling use-cases. The motivation is always the same: the application should depend on a capability, not on a vendor. A while back I wrote about exactly that idea in Rediscovering Java ServiceLoader: Beyond Plugins and Into Capabilities , where the argument was to treat ServiceLoader as capability discovery rather than a plugin system. That piece hit the limitation everyone hits — the no-argument constructor — and worked around it with a default constructor plus a dynamic proxy that built the real object through a factory on each call. It works, but it is indirection bolted on after the fact, not a design. This post is the part I never pinned down back then: turning that workaround into a small, explicit pattern. The running example below is a mock payments system, with Stripe and PayPal specializations, because it is compact enough to show end to end. The JSON and JWT cases cited can be built with the same structure. The two limits ServiceLoader leaves you The first is the no-argument constructor. Whatever ServiceLoader instantiates must have a public, parameterless constructor. My StripePaymentService takes an API key, so it cannot be the class ServiceLoader loads — not unless I bolt on some init-after-construction step, which I would rather avoid. The second is selection, or rather the lack of it. ServiceLoader gives you every implementation it finds, in roughly classpath order. There is no id, nothing to prioritise on, and no way to ask whether a given one even applies in the current environment. With two backends on the classpath and only one configured, working out which to use is

Enterprise Design Patterns in Python: Repository & Unit of Work 🐍🏗️ Series: Enterprise Application Architecture | Source: Fowler's EAA Catalog | Code: GitHub Repository 🧠 What Are Enterprise Design Patterns? Martin Fowler's Patterns of Enterprise Application Architecture (2002) is one of the most influential books in software engineering. It documents recurring architectural solutions — patterns — that solve common problems in enterprise systems: how to organize domain logic, how to talk to databases, how to handle transactions, and more. In this article, we'll explore two of the most powerful and widely-used patterns from that catalog: Pattern Category Core Purpose Repository Data Source Abstracts data access behind a collection-like interface Unit of Work Data Source Tracks object changes and commits them as a single transaction These two patterns work beautifully together — and you'll see exactly why with a real-world example. 🛒 The Problem: An E-Commerce Order System Imagine you're building a backend for an online store. When a customer places an order: A new Order is created Each Product 's stock is decremented A Payment record is registered If any of these steps fail midway, the entire operation should roll back — no partial state. This is exactly the problem the Unit of Work pattern solves, and the Repository pattern makes it all cleanly testable. 📁 Repository Pattern Definition "A Repository mediates between the domain and data mapping layers using a collection-like interface for accessing domain objects." — Martin Fowler, PoEAA The Repository acts as an in-memory collection of domain objects. Your business logic never knows if it's talking to PostgreSQL, SQLite, or even a mock list — it just calls .add() , .get() , .list() . Domain Model # models.py from dataclasses import dataclass , field from typing import List from uuid import uuid4 @dataclass class Product : id : str name : str price : float stock : int @dataclass class OrderItem : product_id : str qua