Python 3 Design Patterns Playbook

Patterns are tools, not mandates, and their usage should be pragmatic and attuned to the project’s unique goals. Misconceptions often cloud the understanding of design patterns, hindering their optimal utilization. One fallacy is the belief that design patterns can magically fix poor code. Design patterns enhance well-structured code, but they can’t rescue fundamentally flawed designs.
Other developers might believe that a new instance is created every time and decide that they should keep around the service instance to avoid the slow initialization process. The config dictionary contains all the values required to initialize each of the services. The next step is to define an interface that

will use those values to create a concrete implementation of a music service. To understand the complexities of a general purpose solution, let’s take a look at a different problem.

Not All Objects Can Be Created Equal

The Singleton pattern is used when we want to guarantee that only one instance of a given class exists during runtime. Based on my experience, it’s easier to simply create one instance intentionally and then use it instead of implementing the Singleton pattern. However, because Python is so powerful and flexible, we need some rules (or patterns) when programming in it. So, let see what patterns are, and how they relate to Python. We will also proceed to implement a few essential Python design patterns.

  • It shows how patterns could be applied to real-world problems.
  • Another misconception views design patterns as rigid templates to be followed blindly.
  • The basic requirements for the example above are that you want to serialize Song objects into their string representation.
  • Factory Method is a widely used, creational design pattern that can be used in many situations where multiple concrete implementations of an interface exist.
  • Based on my experience, it’s easier to simply create one instance intentionally and then use it instead of implementing the Singleton pattern.
  • This tutorial will discuss what Design Pattern is and how we can implement using the Python programming language.

The application defines a config dictionary representing the application configuration. The configuration is used as the keyword arguments to the factory regardless of the service you want to access. The factory creates the concrete implementation of the music service based on the specified key parameter. The best approach is to define a new type of object that provides a general interface and is responsible for the creation of a concrete service. The Builder object has all the logic to create and initialize a service instance. You will implement a Builder object for each of the supported services.

Creational Design Pattern

Someone wiser than I once said that Factory is built into Python. For example, today it’s a relational database, but tomorrow it could be whatever, with the interface we need (again those pesky ducks). At the same time Python is a 100 percent object-oriented language. Functions are objects, first class objects (whatever that means). This fact about functions being objects is important, so please remember it. Andrei is an IT professional with experience ranging from low-level programming to complex systems design and implementation.
python design patterns
Because you started with some existing code, all the components of Factory Method are members of the same class SongSerializer. Once you make this change, you can verify that the behavior has not changed. Then, you do the same for the XML option by introducing a new method ._serialize_to_xml(), moving the implementation to it, and modifying the elif path to call it. In the following sections, you will learn how to make changes to existing code without changing the behavior. In the below diagram, we describe the basic structure of the design pattern documentation.
Let’s start by pointing out that creational patterns are not commonly used in Python. I build, lead, and mentor software development teams, and for the past few years I’ve been focusing on cloud services and back-end applications using Python among other languages. You can see that the correct instance is created depending on the specified service type.

What is not so good here is that the execute function does much more than executing something. We are not following the single responsibility principle to the letter. Let’s say you have a working method for logging information to a given destination. Your method expects the destination to have a write() method (as every file object has, for example).
Lets you fit more objects into the available amount of RAM by sharing common parts of state between multiple objects instead of keeping all of the data in each object. Provides a simplified interface to a library, a framework, or any other complex set of classes. Lets you split a large class or a set of closely related classes into two separate hierarchies—abstraction and implementation—which can be developed independently of each other. The implementation structure of ObjectFactory is the same you saw in SerializerFactory. Still, the current implementation is specifically targeted to the serialization problem above, and it is not reusable in other contexts.
python design patterns
Design Patterns is the most essential part of Software Engineering, as they provide the general repeatable solution to a commonly occurring problem in software design. They usually represent some of the best practices adopted by experienced object-oriented software developers. We can not consider the Design Patterns as the finished design that can be directly converted into code. They are only templates that describe how to solve a particular problem with great efficiency.
The Song class implements the Serializable interface by providing a .serialize(serializer) method. In the method, the Song class uses the serializer object to write its own information without any knowledge of the format. The application can allow the user to select an option that identifies the concrete algorithm. Factory Method can provide the concrete implementation of the algorithm based on this option. Nevertheless, the code above is hard to maintain because it is doing too much.

python design patterns

For example, you can see that create_local_music_service() specifies a local_music_location parameter and ignores the rest. Factory Method can be used to solve a wide range of problems. An Object Factory gives additional flexibility to the design when requirements change.
Other patterns are not needed due of the nature of the language. This is important because if it doesn’t, then the client will have to complete the initialization and use complex conditional code to fully initialize the provided objects. This defeats the purpose of the Factory Method design pattern. The basic requirements for the example above are that you want to serialize Song objects into their string representation. It seems the application provides features related to music, so it is plausible that the application will need to serialize other type of objects like Playlist or Album.
python design patterns
The first step when you see complex conditional code in an application is to identify the common goal of each of the execution paths (or logical paths). The ideal situation would be if any of those changes in requirements could be implemented without changing the .serialize() method. This example is short and simplified, but it still has a lot of complexity. There are three logical or execution paths depending on the value of the format parameter.

In Python, nothing obliges you to write classes and instantiate objects from them. If you don’t need complex structures in your project, you can just write functions. Even better, you can write a flat script for executing some simple and quick task without structuring the code at all. As a result, Python program design can be unconstrained and straightforward. The difference is in the interface that exposes to support creating any type of object.

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