The bigger challenges happen after an application has hit production and is ready to go into maintenance mode. If said bad practices are created as anti-patterns, they allow developers a means to recognize these in advance so that they can avoid common mistakes that can occur - this is parallel to the way in which design patterns provide us with a way to recognize common techniques that are useful.
It describes when it applies, whether or not it can be applied in view of other design constraints, and the consequences and trade-offs of its use. Since we must eventually implement our designs, a design pattern also provides sample Although design patterns describe object-oriented designs, they are based on practical solutions that have been implemented in mainstream object-oriented programming languages Design patterns can be broken down into a number of different categories. Creational design patterns focus on handling object creation mechanisms where objects are created in a manner suitable for the situation we're working in.
The basic approach to object creation might otherwise lead to added complexity in a project whilst these patterns aim to solve this problem by controlling the creation process.
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Some of the patterns that fall under this category are: Constructor, Factory, Abstract, Prototype, Singleton and Builder. Structural patterns are concerned with object composition and typically identify simple ways to realize relationships between different objects. They help ensure that when one part of a system changes, the entire structure of the system doesn't need to do the same. They also assist in recasting parts of the system which don't fit a particular purpose into those that do. Behavioral patterns focus on improving or streamlining the communication between disparate objects in a system.
In my early experiences of learning about design patterns, I personally found the following table a very useful reminder of what a number of patterns has to offer - it covers the 23 Design Patterns mentioned by the GoF. The original table was summarized by Elyse Nielsen back in and I've modified it where necessary to suit our discussion in this section of the book.
Prototype A fully initialized instance used for copying or cloning. Singleton A class with only a single instance with global access points. Bridge Separates an object's interface from its implementation so the two can vary independently. Composite A structure of simple and composite objects which makes the total object more than just the sum of its parts. Decorator Dynamically add alternate processing to objects.
Facade A single class that hides the complexity of an entire subsystem. Flyweight A fine-grained instance used for efficient sharing of information that is contained elsewhere. Proxy A place holder object representing the true object. Iterator Sequentially access the elements of a collection without knowing the inner workings of the collection. Mediator Defines simplified communication between classes to prevent a group of classes from referring explicitly to each other.
Memento Capture an object's internal state to be able to restore it later. Observer A way of notifying change to a number of classes to ensure consistency between the classes.
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There isn't a true single answer to this question; each script and web application we work on is likely to have its own individual needs and we need to think about where we feel a pattern can offer real value to an implementation. For example, some projects may benefit from the decoupling benefits offered by the Observer pattern which reduces how dependent parts of an application are on one another whilst others may simply be too small for decoupling to be a concern at all. That said, once we have a firm grasp of design patterns and the specific problems they are best suited to, it becomes much easier to integrate them into our application architectures.
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Object constructors are used to create specific types of objects - both preparing the object for use and accepting arguments which a constructor can use to set the values of member properties and methods when the object is first created. Where the "Object" constructor in the final example creates an object wrapper for a specific value, or where no value is passed, it will create an empty object and return it.
Inside a constructor, the keyword this references the new object that's being created. Revisiting object creation, a basic constructor may look as follows:. The above is a simple version of the constructor pattern but it does suffer from some problems. One is that it makes inheritance difficult and the other is that functions such as toString are redefined for each of the new objects created using the Car constructor. This isn't very optimal as the function should ideally be shared between all of the instances of the Car type. Thankfully as there are a number of both ES3 and ES5-compatible alternatives to constructing objects, it's trivial to work around this limitation.
Using object literals can assist in encapsulating and organizing your code and Rebecca Murphey has previously written about this topic in depth should you wish to read into object literals further. That said, if we're opting for this technique, we may be equally as interested in the Module pattern. It still uses object literals but only as the return value from a scoping function. The Module pattern was originally defined as a way to provide both private and public encapsulation for classes in conventional software engineering.
What this results in is a reduction in the likelihood of our function names conflicting with other functions defined in additional scripts on the page. The Module pattern encapsulates "privacy", state and organization using closures. It provides a way of wrapping a mix of public and private methods and variables, protecting pieces from leaking into the global scope and accidentally colliding with another developer's interface. With this pattern, only a public API is returned, keeping everything else within the closure private.
Variables can't technically be declared as being public nor private and so we use function scope to simulate this concept. Within the Module pattern, variables or methods declared are only available inside the module itself thanks to closure. Variables or methods defined within the returning object however are available to everyone.
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From a historical perspective, the Module pattern was originally developed by a number of people including Richard Cornford in It was later popularized by Douglas Crockford in his lectures. Another piece of trivia is that if you've ever played with Yahoo's YUI library, some of its features may appear quite familiar and the reason for this is that the Module pattern was a strong influence for YUI when creating their components.
Let's begin looking at an implementation of the Module pattern by creating a module which is self-contained. Here, other parts of the code are unable to directly read the value of our incrementCounter or resetCounter. The counter variable is actually fully shielded from our global scope so it acts just like a private variable would - its existence is limited to within the module's closure so that the only code able to access its scope are our two functions.
Our methods are effectively namespaced so in the test section of our code, we need to prefix any calls with the name of the module e. When working with the Module pattern, we may find it useful to define a simple template that we use for getting started with it. Here's one that covers namespacing, public and private variables:. Looking at another example, below we can see a shopping basket implemented using this pattern.
The module itself is completely self-contained in a global variable called basketModule. The basket array in the module is kept private and so other parts of our application are unable to directly read it. It only exists with the module's closure and so the only methods able to access it are those with access to its scope i.
Inside the module, you may have noticed that we return an object. This gets automatically assigned to basketModule so that we can interact with it as follows:. Notice how the scoping function in the above basket module is wrapped around all of our functions, which we then call and immediately store the return value of. This has a number of advantages including:. This variation of the pattern demonstrates how globals e. This effectively allows us to import them and locally alias them as we wish.
This next variation allows us to declare globals without consuming them and could similarly support the concept of global imports seen in the last example. Dojo Dojo provides a convenience method for working with objects called dojo. This takes as its first argument a dot-separated string such as myObj. Using setObject allows us to set the value of children, creating any of the intermediate objects in the rest of the path passed if they don't already exist. For example, if we wanted to declare basket. For more information on dojo.
There are a number of ways in which jQuery code unspecific to plugins can be wrapped inside the Module pattern. Ben Cherry previously suggested an implementation where a function wrapper is used around module definitions in the event of there being a number of commonalities between modules. In the following example, a library function is defined which declares a new library and automatically binds up the init function to document.
We also can't access private members in methods that are added to the object at a later point. That said, in many cases the Module pattern is still quite useful and when used correctly, certainly has the potential to improve the structure of our application. Other disadvantages include the inability to create automated unit tests for private members and additional complexity when bugs require hot fixes.
It's simply not possible to patch privates. Instead, one must override all public methods which interact with the buggy privates. Developers can't easily extend privates either, so it's worth remembering privates are not as flexible as they may initially appear. For further reading on the Module pattern, see Ben Cherry's excellent in-depth article on it. The Revealing Module pattern came about as Heilmann was frustrated with the fact that he had to repeat the name of the main object when we wanted to call one public method from another or access public variables.
The result of his efforts was an updated pattern where we would simply define all of our functions and variables in the private scope and return an anonymous object with pointers to the private functionality we wished to reveal as public. The pattern can also be used to reveal private functions and properties with a more specific naming scheme if we would prefer:. This pattern allows the syntax of our scripts to be more consistent. It also makes it more clear at the end of the module which of our functions and variables may be accessed publicly which eases readability.
A disadvantage of this pattern is that if a private function refers to a public function, that public function can't be overridden if a patch is necessary. This is because the private function will continue to refer to the private implementation and the pattern doesn't apply to public members, only to functions. Public object members which refer to private variables are also subject to the no-patch rule notes above. As a result of this, modules created with the Revealing Module pattern may be more fragile than those created with the original Module pattern, so care should be taken during usage.
The Singleton pattern is thus known because it restricts instantiation of a class to a single object. Classically, the Singleton pattern can be implemented by creating a class with a method that creates a new instance of the class if one doesn't exist. In the event of an instance already existing, it simply returns a reference to that object. Singletons differ from static classes or objects as we can delay their initialization, generally because they require some information that may not be available during initialization time.
Here, getInstance becomes a little like a Factory method and we don't need to update each point in our code accessing it. FooSingleton above would be a subclass of BasicSingleton and implement the same interface. It is important to note the difference between a static instance of a class object and a Singleton: whilst a Singleton can be implemented as a static instance, it can also be constructed lazily, without the need for resources nor memory until this is actually needed.
They're often an indication that modules in a system are either tightly coupled or that logic is overly spread across multiple parts of a codebase. Singletons can be more difficult to test due to issues ranging from hidden dependencies, the difficulty in creating multiple instances, difficulty in stubbing dependencies and so on. Miller Medeiros has previously recommended this excellent article on the Singleton and its various issues for further reading as well as the comments to this article, discussing how Singletons can increase tight coupling.
I'm happy to second these recommendations as both pieces raise many important points about this pattern that are also worth noting. The Observer is a design pattern where an object known as a subject maintains a list of objects depending on it observers , automatically notifying them of any changes to state. When a subject needs to notify observers about something interesting happening, it broadcasts a notification to the observers which can include specific data related to the topic of the notification. When we no longer wish for a particular observer to be notified of changes by the subject they are registered with, the subject can remove them from the list of observers.
It's often useful to refer back to published definitions of design patterns that are language agnostic to get a broader sense of their usage and advantages over time. When something changes in our subject that the observer may be interested in, a notify message is sent which calls the update method in each observer. When the observer is no longer interested in the subject's state, they can simply detach themselves.
We can now expand on what we've learned to implement the Observer pattern with the following components:. Next, let's model the Subject and the ability to add, remove or notify observers on the observer list. We then define a skeleton for creating new Observers. The update functionality here will be overwritten later with custom behaviour.
We then define ConcreteSubject and ConcreteObserver handlers for both adding new observers to the page and implementing the updating interface. See below for inline comments on what these components do in the context of our example. In this example, we looked at how to implement and utilize the Observer pattern, covering the concepts of a Subject, Observer, ConcreteSubject and ConcreteObserver.
Whilst very similar, there are differences between these patterns worth noting. The Observer pattern requires that the observer or object wishing to receive topic notifications must subscribe this interest to the object firing the event the subject. This event system allows code to define application specific events which can pass custom arguments containing values needed by the subscriber.
The idea here is to avoid dependencies between the subscriber and publisher. This differs from the Observer pattern as it allows any subscriber implementing an appropriate event handler to register for and receive topic notifications broadcast by the publisher. The general idea here is the promotion of loose coupling.
Rather than single objects calling on the methods of other objects directly, they instead subscribe to a specific task or activity of another object and are notified when it occurs. They also help us identify what layers containing direct relationships which could instead be replaced with sets of subjects and observers. This effectively could be used to break down an application into smaller, more loosely coupled blocks to improve code management and potentials for re-use. Further motivation behind using the Observer pattern is where we need to maintain consistency between related objects without making classes tightly coupled.
Consequently, some of the issues with these patterns actually stem from their main benefits. For example, publishers may make an assumption that one or more subscribers are listening to them. Say that we're using such an assumption to log or output errors regarding some application process. If the subscriber performing the logging crashes or for some reason fails to function , the publisher won't have a way of seeing this due to the decoupled nature of the system.
Another draw-back of the pattern is that subscribers are quite ignorant to the existence of each other and are blind to the cost of switching publishers. Due to the dynamic relationship between subscribers and publishers, the update dependency can be difficult to track. Below we can see some examples of this:.
Next, let's imagine we have a web application responsible for displaying real-time stock information. The application might have a grid for displaying the stock stats and a counter for displaying the last point of update. When the data model changes, the application will need to update the grid and counter. When our subscribers receive notification that the model itself has changed, they can update themselves accordingly. In our implementation, our subscriber will listen to the topic "newDataAvailable" to find out if new stock information is available.
If a new notification is published to this topic, it will trigger gridUpdate to add a new row to our grid containing this information. It will also update a last updated counter to log the last time data was added. Notice how submitting a rating only has the effect of publishing the fact that new user and rating data is available. It's left up to the subscribers to those topics to then delegate what happens with that data. In our case we're pushing that new data into existing arrays and then rendering them using the Underscore library's.
Quite often in Ajax-heavy applications, once we've received a response to a request we want to achieve more than just one unique action. One could simply add all of their post-request logic into a success callback, but there are drawbacks to this approach. What this means is that although keeping our post-request logic hardcoded in a callback might be fine if we're just trying to grab a result set once, it's not as appropriate when we want to make further Ajax-calls to the same data source and different end-behavior without rewriting parts of the code multiple times.
Using Observers, we can also easily separate application-wide notifications regarding different events down to whatever level of granularity we're comfortable with - something which can be less elegantly done using other patterns. Notice how in our sample below, one topic notification is made when a user indicates they want to make a search query and another is made when the request returns and actual data is available for consumption. It's left up to the subscribers to then decide how to use knowledge of these events or the data returned.
The benefits of this are that, if we wanted, we could have 10 different subscribers utilizing the data returned in different ways but as far as the Ajax-layer is concerned, it doesn't care. Its sole duty is to request and return data then pass it on to whoever wants to use it. This separation of concerns can make the overall design of our code a little cleaner.
The Observer pattern is useful for decoupling a number of different scenarios in application design and if you haven't been using it, I recommend picking up one of the pre-written implementations mentioned today and just giving it a try out. It's one of the easier design patterns to get started with but also one of the most powerful. In the section on the Observer pattern, we were introduced to a way of channeling multiple event sources through a single object.
It's common for developers to think of Mediators when faced with this problem, so let's explore how they differ. The dictionary refers to a mediator as a neutral party that assists in negotiations and conflict resolution. In our world, a mediator is a behavioral design pattern that allows us to expose a unified interface through which the different parts of a system may communicate.
If it appears a system has too many direct relationships between components, it may be time to have a central point of control that components communicate through instead. The Mediator promotes loose coupling by ensuring that instead of components referring to each other explicitly, their interaction is handled through this central point.
This can help us decouple systems and improve the potential for component reusability. A real-world analogy could be a typical airport traffic control system. A tower Mediator handles what planes can take off and land because all communications notifications being listened out for or broadcast are done from the planes to the control tower, rather than from plane-to-plane. A centralized controller is key to the success of this system and that's really the role a Mediator plays in software design.
Another analogy would be DOM event bubbling and event delegation. If all subscriptions in a system are made against the document rather than individual nodes, the document effectively serves as a Mediator. Instead of binding to the events of the individual nodes, a higher level object is given the responsibility of notifying subscribers about interaction events. When it comes to the Mediator and Event Aggregator patterns, there are some times where it may look like the patterns are interchangeable due to implementation similarities.
However, the semantics and intent of these patterns are very different. And even if the implementations both use some of the same core constructs, I believe there is a distinct difference between them. I also believe they should not be interchanged or confused in communication because of the differences. A Mediator is an object that coordinates interactions logic and behavior between multiple objects.
The result is workflow that is easier to understand and maintain. The similarities boil down to two primary items: events and third-party objects. These differences are superficial at best, though. When we dig into the intent of the pattern and see that the implementations can be dramatically different, the nature of the patterns become more apparent. Both the event aggregator and mediator use events, in the above examples.
Both the event aggregator and mediator, by design, use a third-party object to facilitate things. The event aggregator itself is a third-party to the event publisher and the event subscriber. It acts as a central hub for events to pass through. The mediator is also a third party to other objects, though. So where is the difference?
The answer largely comes down to where the application logic and workflow is coded.
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In the case of an event aggregator, the third party object is there only to facilitate the pass-through of events from an unknown number of sources to an unknown number of handlers. All workflow and business logic that needs to be kicked off is put directly into the object that triggers the events and the objects that handle the events. In the case of the mediator, though, the business logic and workflow is aggregated into the mediator itself.
The mediator decides when an object should have its methods called and attributes updated based on factors that the mediator knows about. It encapsulates the workflow and process, coordinating multiple objects to produce the desired system behaviour. The individual objects involved in this workflow each know how to perform their own task. It just fires the event and moves on.
A mediator pays attention to a known set of input or activities so that it can facilitate and coordinate additional behavior with a known set of actors objects. Through the process, the author walks you through program refinements that help expand your knowledge. This book covers the field of natural language processing, which has to do with the understanding and manipulation of data about spoken languages such as English, Spanish, Hindi, and others.
This is a field with growing applications. Computers and natural language assistants such as Siri and Google Now understand how to interpret natural language commands.
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This text book will come in handy if you are a student and need help for a course, or just want an academic introduction to Python. The book is aimed at entry-level computer science college students. As such, you will find an academic treatment of program design, computer science theory and the fundamentals of computing. The book will also teach you how computers work, hardware basics, data structures, and object oriented programming. Advanced developers need to take care to internalize best practices. In addition, advanced topics such as neural networks and computer vision offer challenges that can expand your skillset.
Here are the top books you will want to check out. Rather than give a merely theoretical approach to computing algorithms, Grokking Algorithms makes the topic highly practical. It will show you how to write your own spell checker programs using graph algorithms, as well as apply algorithms to data compression problems. The techniques you learn cover major algorithm classes such as sorting and searching. The highly engaging writing style makes the topics easier to grasp and apply in your everyday coding.
This book will give you an applied introduction to the vastly growing field of machine learning. You will learn to use the scikit-learn library to solve machine learning problems. You will learn to apply supervised learning algorithms as well as unsupervised learning algorithms. Python favors a simple, "Pythonic" way of accomplishing things. This dot is the one you use to call methods in Java, or C for instance.
Basically, the rule says that you should not chain method calls. For other classes, you should respect this rule. It is ok-ish to have public attributes in Piece and Location. However, the boardRepresentation method is awful, take a look at this line:. This is far from One Dot Per Line. However, as you need to perform an action on this attribute, you need a new method addTo. Then again, you should change the visibility of your attribute. Also, extracting the code to get the first character of the representation in a new method looks like a good idea as it may be reused at some point.
Finally, here is the updated Board class:. You may answer that it is because you write the same name over and over again? And I would answer that this method is reused multiple times, and that it looks like code duplication. So you will say that the method name is too long anyway. And I would tell you that maybe your class has multiple responsibilities, which is bad as it violates the Single Responsibility Principle.
It is a rule I use to follow while designing a software by naming things. No class over 50 lines and no package over 10 files. Well, it depends on you, but I think you could change the number of lines from 50 to The idea behind this rule is that long files are harder to read , harder to understand, and harder to maintain.
This rule is probably the hardest one, but it promotes high cohesion , and better encapsulation. A picture is worth a thousand words, so here is the explanation of this rule in picture. The main question was Why two attributes? My answer was Why not?