
Explore design patterns as proven, standard solutions that boost scalability, testability, and separation of concerns in your Python projects, guided by the Gang of Four's best practices.
Explore the three design pattern types: creational, structural, and behavioral, and how they affect object creation, project structure, and component interaction in the Python design patterns masterclass.
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Explore the singleton design pattern, its benefits and drawbacks, and implement a thread-safe Python singleton using locks to ensure a single instance across threads.
Separate creation from use with the factory method, enabling dynamic switching of currency implementations via a common interface. Build fiat and virtual currency factories for USA, Spain, and Japan.
Abstract factory creates factories for data sources, letting the client use the resource without caring about its implementation, as illustrated by the French and American restaurant example.
Explore the builder pattern in Python by constructing a network service with multiple parameters, including optional ones, using both classic and simplified named-parameter approaches.
In the Python design patterns masterclass, learn how the prototype pattern copies existing objects without tight coupling, using Python's copy and deep copy for testing and pre-production.
Apply the adapter pattern to convert one interface into another for a client. Use an adapter class to bridge to a third-party interface, ensuring data is adapted and stored.
Learn how the bridge pattern replaces inheritance with composition by separating shape and color into two components and linking them with a bridge, demonstrated with a Python device remote example.
Explore the composite design pattern by modeling a computer as a tree of components in Python and calculating the total price for the whole system or a subtree.
Learn how the decorator pattern, called the wrapper pattern, wraps a third-party class to add or override behavior without altering its code, illustrated with a coffee machine example in Python.
Discover how the facade pattern hides complex system details behind a simple interface, enabling easy client use, a repository facade, and caching in a Python example.
Explore how the flyweight design pattern in python reduces memory and processing footprint by sharing sprites through a factory. Distinct element state remains local while shared data is centralized.
Learn how the proxy design pattern fronts an object to manage lifecycle and access, using caching and sequencing to speed up and synchronize disk operations, while preserving the original interface.
Explore the chain of responsibility design pattern, where a chain of handlers processes or forwards requests, with examples of authentication, content type, and body headers.
Explore how the command design pattern decouples the user interface from business logic by encapsulating requests into command objects, processed by a command processor.
Explore the interpreter design pattern by building a binary expression tree from tokens to parse and recursively evaluate mathematical expressions using terminal and non-terminal expressions.
Explore the iterator pattern in Python by implementing an example that traverses a word collection in alphabetical and reverse alphabetical order using next and has next.
Explore the mediator pattern, a central hub that reduces dependencies by having components send messages to one mediator, which forwards to the correct recipients, demonstrated in a Python group chat.
Master memento design pattern to enable undo and redo by saving and restoring editor states. Build memento, originator, and caretaker to capture, store, and navigate state chain without exposing internals.
Explore the observer design pattern, where components subscribe to events and the manager notifies listeners when results are available, illustrated with open and save events and email/logger listeners.
Explore the state design pattern as a state machine with predefined, encapsulated states and transitions, demonstrated through a blog workflow (draft, moderation, published) and a four-state game.
Explore the strategy design pattern, enabling runtime selection of formatting or display strategies via an executor and context. See a Python example with lowercase and uppercase strategies.
Explore the template method design pattern that standardizes an algorithm via an abstract class, delegating concrete step implementations to subclasses such as database and file system storages.
Explore the visitor design pattern to add reporting to independent components without modification, using a report visitor to generate monthly and yearly costs from contracts.
Apply the design patterns from this Python design patterns masterclass to your code and applications, and carry practical insights into future projects.
Knowing how to build well structured programs and apps, that are scalable and robust is essential for every developer.
That's why I've created this course on Design Patterns for Python.
Here you will learn how to apply popular patterns to your code, such as Builder, Adapter, Abstract Factory, as well as lesser known but very useful patterns, such as Composite, Decorator, Strategy etc.
This course will teach you how to structure your code so that it is more maintainable as it grows, and that it's easier to debug and test. When building a new project, you are not trying to reinvent the wheel, but instead to implement the correct solutions to the problems that you encounter.
It will also teach you the terminology that you need when you communicate with top level developers. When they say they implemented a factory for a piece of code, or the added a builder pattern for the creation of a certain object, you will immediately know what they mean.
This course covers 3 types of design patterns
Creational
Structural
Behavioural
We will also include code samples at each step of the way, so that you already know how to implement these patterns in practice.
Sign up today, and let's learn how to use Design Patterns in Python.