Design patterns are vital for programmers. They improve the efficiency of your programming as you can solve complex problems with a few lines of code by using design patterns. If you’re interested in learning Python, learning Python design patterns is a must. Learning them will make it easier for you to tackle various problems and make your code more functional.
You shouldn’t consider design patterns as completed designs that you can convert into code directly. They are templates that explain how you can solve a specific problem efficiently. If you are a beginner in python and data science, upGrad’s data science programs can definitely help you dive deeper into the world of data and analytics.
There are many Python design patterns you should know about. The following points will explain them better:
Types of Design Patterns
There are primarily three categories of design patterns:
- Creational design patterns
- Structural design patterns
- Behavioural design patterns
They all have sub-categories that help you solve particular kinds of problems. It’s vital to be familiar with the different types of Python design patterns as each one works for a specific issue. Design patterns make it easier for you to communicate with your team, complete your projects earlier, and find any errors quickly.
Here are the primary categories and subcategories of Python design patterns:
1. Creational Design Patterns
Creational patterns give you the necessary information about the object or class instantiation. The most popular implementations of creational design patterns are class creational patterns and object creational patterns. Object creation patterns can utilize delegation, while class creation patterns can employ inheritance similarly.
- Singleton Method
The singleton method ensures that a class has only a single instance and gives a global access point for the same. This way, you can be sure that a class has only one instance.
- Prototype Method
The prototype method allows you to replicate objects without requiring your code to depend on their classes. It enhances your efficiency greatly and gives you an alternative to inheritance.
- Builder Method
The builder method allows you to construct advanced objects in steps. This way, you can make various kinds of a single object while using the same code.
- Abstract Factory Method
The abstract factory method allows you to create families of objects related to each other without giving particular concrete classes.
- Factory Method
The factory method gives you an interface to create objects in a superclass. However, it enables subclasses to modify the object type you can create.
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2. Structural Design Patterns
A structural design pattern organizes various objects and classes to build bigger structures and offer new functionalities. It focuses on improving the efficiency and flexibility of your classes and objects.
Structural design patterns use inheritance to create the necessary interfaces. They also identify the relationships that simplify the structure.
- FlyWeight Method
The flyweight method allows you to fit more objects into the available RAM by letting them share common components of state instead of storing all of the data in one object.
- Proxy Method
With the proxy method, you can add a placeholder for a specific object. The proxy would handle access to the object so you can act before or after the request reaches the same.
- Facade Method
The facade method gives you a simple interface to a framework, library, or advanced class set. It lets you isolate the code from the subsystem.
- Decorator Method
The decorator method lets you add new behaviours to different objects dynamically without modifying their implementation. It does so by placing them inside wrapper objects that have the behaviours. Python is among the most suitable programming languages to implement this design pattern.
- Composite Method
The composite method specifies an object group that you can treat just like you would treat a single instance of those objects. In other words, this method lets you compose objects into tree-type structures.
- Bridge Method
The bridge method allows you to split large classes into two distinct hierarchies, implementation, and abstraction. Another highlight of this method is that you can develop them independently from each other.
- Adapter Method
The adapter method allows collaboration between objects with incompatible interfaces. It follows the single responsibility principle and the open/closed principle. You should use the adapter method through the client interface, as it will allow you to change the adapters without modifying the client code.
3. Behavioural Design Patterns
Behavioural design patterns allow you to find the patterns for communication among objects and implement them as required. These patterns are related to the algorithms and the responsibilities assigned between objects. Following are the various classifications of behavioural design patterns:
- Visitor Method
With this method, you can separate the algorithms from the objects they operate on. This method follows the single responsibility principle, which means you can move a behavior’s multiple versions into a class. However, it requires you to update every visitor when you add or remove a class from the hierarchy.
- Template Method
The template method specifies an algorithm’s skeleton in the superclass while letting the subclass override particular steps of the algorithm without requiring any changes in the structure. A great advantage of this method is it enables you to pull the duplicate code into the necessary superclass.
- Strategy Method
The strategy method lets you define the family of algorithms. You can put them in different classes and make the objects interchangeable by using this method. It enables you to isolate certain implementation information and makes it easy to introduce various strategies without requiring you to change the code.
- State Method
This method enables an object to modify its behaviour if its internal state changes. This allows you to employ the state in the form of a derived class of the state pattern. It operates changes in the state by using methods from the pattern’s superclass.
- Observer Method
The observer method allows you to specify a subscription system that notifies various objects about any events happening to the objects they observe. It defines one to multiple dependencies, so if an object’s state changes, every one of its dependents gets a notification.
- Memento Method
With the memento method, you can save and restore the last state of an object without exposing its implementation details. It focuses on capturing and externalizing an object’s internal state without disturbing the code’s encapsulation. The undo and redo options present in various software solutions such as text editors, IDEs, and MS Paint, are an excellent example of the memento method’s implementation.
- Mediator Method
The mediator method lets you reduce coupling between a program’s components. It does so by allowing them to communicate indirectly by using a particular mediator object. This method simplifies the modification and extension of components as they don’t remain dependent on other classes. The mediator method has four components, the mediator, the concrete mediator, the colleague, and the concrete colleague.
- Iterator Method
The iterative method lets you go through a collection’s elements without exposing the elements’ details. It enables you to access the components of advanced data structures sequentially, without repetition. You can go through various kinds of data structures while using the iterator method, such as stack, graphs, trees, and many others.
- Command Method
The command method enables you to parameterize clients with logging or queuing of requests. This means the button you used for one function can be used for another one. The command method encapsulates the necessary information to trigger an event or perform a particular action.
- Chain of Responsibility Method
The chain of responsibility method is the object-oriented form of if…elif…elif…else. It enables you to pass requests through the handlers’ chain. You can rearrange the condition-action blocks during run-time by using the chain of responsibility method. It focuses on decoupling the senders from the receivers of a request form.
Become a Python Professional
The various Python design patterns we discussed in the previous section were just the tip of the iceberg. Python is a broad programming language with multiple functionalities and applications.
While studying Python, you must learn it in the context of its application. That way, you will learn the subject efficiently and will be able to test your skills quickly. Currently, one of the most in-demand and widespread applications of Python is in data science.
If you’re interested in learning Python and utilizing it as a professional, it would be best to join a data science course.
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Python design patterns offer you a ton of advantages. They let you make the coding process more efficient by solving problems quickly. Design patterns also simplify your code and make it easier to share it with other professionals, which is particularly useful during collaborations.
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