A Collection of Design Patterns/Idioms in Python

Python Patterns

A collection of design patterns and idioms in Python.

Current Patterns

Creational Patterns:

abstract_factoryuse a generic function with specific factories
borga singleton with shared-state among instances
builderinstead of using multiple constructors, builder object receives parameters and returns constructed objects
factorydelegate a specialized function/method to create instances
lazy_evaluationlazily-evaluated property pattern in Python
poolpreinstantiate and maintain a group of instances of the same type
prototypeuse a factory and clones of a prototype for new instances (if instantiation is expensive)

Structural Patterns:

3-tierdata<->business logic<->presentation separation (strict relationships)
adapteradapt one interface to another using a white-list
bridgea client-provider middleman to soften interface changes
compositelets clients treat individual objects and compositions uniformly
decoratorwrap functionality with other functionality in order to affect outputs
facadeuse one class as an API to a number of others
flyweighttransparently reuse existing instances of objects with similar/identical state
front_controllersingle handler requests coming to the application
mvcmodel<->view<->controller (non-strict relationships)
proxyan object funnels operations to something else

Behavioral Patterns:

chain_of_responsibilityapply a chain of successive handlers to try and process the data
cataloggeneral methods will call different specialized methods based on construction parameter
chaining_methodcontinue callback next object method
commandbundle a command and arguments to call later
iteratortraverse a container and access the container's elements
iterator (alt. impl.)traverse a container and access the container's elements
mediatoran object that knows how to connect other objects and act as a proxy
mementogenerate an opaque token that can be used to go back to a previous state
observerprovide a callback for notification of events/changes to data
publish_subscribea source syndicates events/data to 0+ registered listeners
registrykeep track of all subclasses of a given class
specificationbusiness rules can be recombined by chaining the business rules together using boolean logic
statelogic is organized into a discrete number of potential states and the next state that can be transitioned to
strategyselectable operations over the same data
templatean object imposes a structure but takes pluggable components
visitorinvoke a callback for all items of a collection

Design for Testability Patterns:

dependency_injection3 variants of dependency injection

Fundamental Patterns:

delegation_patternan object handles a request by delegating to a second object (the delegate)


blackboardarchitectural model, assemble different sub-system knowledge to build a solution, AI approach - non gang of four pattern
graph_searchgraphing algorithms - non gang of four pattern
hsmhierarchical state machine - non gang of four pattern


Design Patterns in Python by Peter Ullrich

Sebastian Buczyński - Why you don't need design patterns in Python?

You Don't Need That!

Pluggable Libs Through Design Patterns


When an implementation is added or modified, please review the following guidelines:


All files with example patterns have ### OUTPUT ### section at the bottom (migration to OUTPUT = """...""" is in progress).

Run append_output.sh (e.g. ./append_output.sh borg.py) to generate/update it.


Add module level description in form of a docstring with links to corresponding references or other useful information.

Add "Examples in Python ecosystem" section if you know some. It shows how patterns could be applied to real-world problems.

facade.py has a good example of detailed description, but sometimes the shorter one as in template.py would suffice.

In some cases class-level docstring with doctest would also help (see adapter.py) but readable OUTPUT section is much better.

Python 2 compatibility

To see Python 2 compatible versions of some patterns please check-out the legacy tag.


When everything else is done - update corresponding part of README.

Travis CI

Please run tox or tox -e ci37 before submitting a patch to be sure your changes will pass CI.

You can also run flake8 or pytest commands manually. Examples can be found in tox.ini.

Contributing via issue triage 

You can triage issues and pull requests which may include reproducing bug reports or asking for vital information, such as version numbers or reproduction instructions. If you would like to start triaging issues, one easy way to get started is to subscribe to python-patterns on CodeTriage.

Download Details: 
Author: faif
Source Code: https://github.com/faif/python-patterns 

#python #designpatterns

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A Collection of Design Patterns/Idioms in Python
Ray  Patel

Ray Patel


top 30 Python Tips and Tricks for Beginners

Welcome to my Blog , In this article, you are going to learn the top 10 python tips and tricks.

1) swap two numbers.

2) Reversing a string in Python.

3) Create a single string from all the elements in list.

4) Chaining Of Comparison Operators.

5) Print The File Path Of Imported Modules.

6) Return Multiple Values From Functions.

7) Find The Most Frequent Value In A List.

8) Check The Memory Usage Of An Object.

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Ray  Patel

Ray Patel


Lambda, Map, Filter functions in python

Welcome to my Blog, In this article, we will learn python lambda function, Map function, and filter function.

Lambda function in python: Lambda is a one line anonymous function and lambda takes any number of arguments but can only have one expression and python lambda syntax is

Syntax: x = lambda arguments : expression

Now i will show you some python lambda function examples:

#python #anonymous function python #filter function in python #lambda #lambda python 3 #map python #python filter #python filter lambda #python lambda #python lambda examples #python map

Shardul Bhatt

Shardul Bhatt


Why use Python for Software Development

No programming language is pretty much as diverse as Python. It enables building cutting edge applications effortlessly. Developers are as yet investigating the full capability of end-to-end Python development services in various areas. 

By areas, we mean FinTech, HealthTech, InsureTech, Cybersecurity, and that's just the beginning. These are New Economy areas, and Python has the ability to serve every one of them. The vast majority of them require massive computational abilities. Python's code is dynamic and powerful - equipped for taking care of the heavy traffic and substantial algorithmic capacities. 

Programming advancement is multidimensional today. Endeavor programming requires an intelligent application with AI and ML capacities. Shopper based applications require information examination to convey a superior client experience. Netflix, Trello, and Amazon are genuine instances of such applications. Python assists with building them effortlessly. 

5 Reasons to Utilize Python for Programming Web Apps 

Python can do such numerous things that developers can't discover enough reasons to admire it. Python application development isn't restricted to web and enterprise applications. It is exceptionally adaptable and superb for a wide range of uses.

Robust frameworks 

Python is known for its tools and frameworks. There's a structure for everything. Django is helpful for building web applications, venture applications, logical applications, and mathematical processing. Flask is another web improvement framework with no conditions. 

Web2Py, CherryPy, and Falcon offer incredible capabilities to customize Python development services. A large portion of them are open-source frameworks that allow quick turn of events. 

Simple to read and compose 

Python has an improved sentence structure - one that is like the English language. New engineers for Python can undoubtedly understand where they stand in the development process. The simplicity of composing allows quick application building. 

The motivation behind building Python, as said by its maker Guido Van Rossum, was to empower even beginner engineers to comprehend the programming language. The simple coding likewise permits developers to roll out speedy improvements without getting confused by pointless subtleties. 

Utilized by the best 

Alright - Python isn't simply one more programming language. It should have something, which is the reason the business giants use it. Furthermore, that too for different purposes. Developers at Google use Python to assemble framework organization systems, parallel information pusher, code audit, testing and QA, and substantially more. Netflix utilizes Python web development services for its recommendation algorithm and media player. 

Massive community support 

Python has a steadily developing community that offers enormous help. From amateurs to specialists, there's everybody. There are a lot of instructional exercises, documentation, and guides accessible for Python web development solutions. 

Today, numerous universities start with Python, adding to the quantity of individuals in the community. Frequently, Python designers team up on various tasks and help each other with algorithmic, utilitarian, and application critical thinking. 

Progressive applications 

Python is the greatest supporter of data science, Machine Learning, and Artificial Intelligence at any enterprise software development company. Its utilization cases in cutting edge applications are the most compelling motivation for its prosperity. Python is the second most well known tool after R for data analytics.

The simplicity of getting sorted out, overseeing, and visualizing information through unique libraries makes it ideal for data based applications. TensorFlow for neural networks and OpenCV for computer vision are two of Python's most well known use cases for Machine learning applications.


Thinking about the advances in programming and innovation, Python is a YES for an assorted scope of utilizations. Game development, web application development services, GUI advancement, ML and AI improvement, Enterprise and customer applications - every one of them uses Python to its full potential. 

The disadvantages of Python web improvement arrangements are regularly disregarded by developers and organizations because of the advantages it gives. They focus on quality over speed and performance over blunders. That is the reason it's a good idea to utilize Python for building the applications of the future.

#python development services #python development company #python app development #python development #python in web development #python software development

Samanta  Moore

Samanta Moore


Builder Design Pattern

What is Builder Design Pattern ? Why we should care about it ?

Starting from **Creational Design Pattern, **so wikipedia says “creational design pattern are design pattern that deals with object creation mechanism, trying to create objects in manner that is suitable to the situation”.

The basic form of object creations could result in design problems and result in complex design problems, so to overcome this problem Creational Design Pattern somehow allows you to create the object.

Builder is one of the** Creational Design Pattern**.

When to consider the Builder Design Pattern ?

Builder is useful when you need to do lot of things to build an Object. Let’s imagine DOM (Document Object Model), so if we need to create the DOM, We could have to do lot of things, appending plenty of nodes and attaching attributes to them. We could also imagine about the huge XML Object creation where we will have to do lot of work to create the Object. A Factory is used basically when we could create the entire object in one shot.

As **Joshua Bloch (**He led the Design of the many library Java Collections Framework and many more) – “Builder Pattern is good choice when designing the class whose constructor or static factories would have more than handful of parameters

#java #builder #builder pattern #creational design pattern #design pattern #factory pattern #java design pattern

Art  Lind

Art Lind


Python Tricks Every Developer Should Know

Python is awesome, it’s one of the easiest languages with simple and intuitive syntax but wait, have you ever thought that there might ways to write your python code simpler?

In this tutorial, you’re going to learn a variety of Python tricks that you can use to write your Python code in a more readable and efficient way like a pro.

Let’s get started

Swapping value in Python

Instead of creating a temporary variable to hold the value of the one while swapping, you can do this instead

>>> FirstName = "kalebu"
>>> LastName = "Jordan"
>>> FirstName, LastName = LastName, FirstName 
>>> print(FirstName, LastName)
('Jordan', 'kalebu')

#python #python-programming #python3 #python-tutorials #learn-python #python-tips #python-skills #python-development