A collection of design patterns and idioms in Python.
Creational Patterns:
| Pattern | Description | Viewed |
|---|---|---|
| abstract_factory | use a generic function with specific factories | next |
| borg | a singleton with shared-state among instances | next |
| builder | instead of using multiple constructors, builder object receives parameters and returns constructed objects | |
| factory | delegate a specialized function/method to create instances | next |
| lazy_evaluation | lazily-evaluated property pattern in Python | |
| pool | preinstantiate and maintain a group of instances of the same type | |
| prototype | use a factory and clones of a prototype for new instances (if instantiation is expensive) | next |
Structural Patterns:
| Pattern | Description | Viewed |
|---|---|---|
| 3-tier | data<->business logic<->presentation separation (strict relationships) | |
| adapter | adapt one interface to another using a white-list | next |
| bridge | a client-provider middleman to soften interface changes | next |
| composite | lets clients treat individual objects and compositions uniformly | next |
| decorator | wrap functionality with other functionality in order to affect outputs | next |
| facade | use one class as an API to a number of others | |
| flyweight | transparently reuse existing instances of objects with similar/identical state | next |
| front_controller | single handler requests coming to the application | |
| mvc | model<->view<->controller (non-strict relationships) | |
| proxy | an object funnels operations to something else | next |
Behavioral Patterns:
| Pattern | Description | Viewed |
|---|---|---|
| chain_of_responsibility | apply a chain of successive handlers to try and process the data | next |
| catalog | general methods will call different specialized methods based on construction parameter | |
| chaining_method | continue callback next object method | |
| command | bundle a command and arguments to call later | next |
| iterator | traverse a container and access the container's elements | next |
| iterator (alt. impl.) | traverse a container and access the container's elements | next |
| mediator | an object that knows how to connect other objects and act as a proxy | next |
| memento | generate an opaque token that can be used to go back to a previous state | next |
| observer | provide a callback for notification of events/changes to data | next |
| publish_subscribe | a source syndicates events/data to 0+ registered listeners | |
| registry | keep track of all subclasses of a given class | |
| specification | business rules can be recombined by chaining the business rules together using boolean logic | |
| state | logic is organized into a discrete number of potential states and the next state that can be transitioned to | next |
| strategy | selectable operations over the same data | Yes |
| template | an object imposes a structure but takes pluggable components | next |
| visitor | invoke a callback for all items of a collection | next |
Design for Testability Patterns:
| Pattern | Description | Viewed |
|---|---|---|
| dependency_injection | 3 variants of dependency injection | Yes |
Fundamental Patterns:
| Pattern | Description | Viewed |
|---|---|---|
| delegation_pattern | an object handles a request by delegating to a second object (the delegate) |
Others:
| Pattern | Description | Viewed |
|---|---|---|
| blackboard | architectural model, assemble different sub-system knowledge to build a solution, AI approach - non gang of four pattern | |
| graph_search | graphing algorithms - non gang of four pattern | |
| hsm | hierarchical 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?
Pluggable Libs Through Design Patterns
When an implementation is added or modified, please review the following guidelines:
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.
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.
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.
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