Yes , it is. With the exception of control flow, everything in Python is an object. A flexible programming language enables large-scale data processing systems. Simula is considered the first object-oriented programming language. All user defined types are objects. All operations performed on objects must be only through methods exposed at the objects. Abstraction is the concept of object-oriented programming that "shows" only essential attributes and "hides" unnecessary information.
The main purpose of abstraction is hiding the unnecessary details from the users. It is one of the most important concepts of OOPs. Encapsulation in OOP Meaning: In object-oriented computer programming languages, the notion of encapsulation or OOP Encapsulation refers to the bundling of data, along with the methods that operate on that data, into a single unit. Many programming languages use encapsulation frequently in the form of classes.
Encapsulation works on providing interactions through function calling only. Using keyword private or protected stops the use of data members outside class.
The data thus remains accessible to functions inside class. Encapsulation is also called information hiding as it restricts the use of data inside class. At this time, it is one of the best choices for fast software, with alternatives like Rust seriously lacking ecosystem support for a lot of use cases.
Photoshop is one of the most popular and advanced graphics editor. Windows OS. Microsoft Office. Mozilla Firefox. And the focus is horribly adverse towards what really matters in programming — the user. The user cares about objects, not templates of objects and the structure the engineers have designed.
Fortunately there is a way out of this endless struggle. If you truly want to move from classes to objects however, follow the website link, and the user will thank you! OOP is so succesfull for the simple reason that universe around us is full of cooperating objects. OOP is easy to comprehend and design, if someone does not over engineer it. But, in alternative universe, maybe there are function MyCarGo driver that internally destroys me and creates my new identical copy at the destination place….
But for me classes are more like useful brackets. If the long sequential task can be divided into separate subtasks I may employ the same strategy downstream. Then the main bracket class just sequentially intantiates a bunch a number of subclasses and calls their one public function.
Of course you have interconnected systems where one change fires an event and that event is caught and processed but even then this often just means that a further task is to be sequentially be worked on. Some coders do indeed hate OOP. Good OOP is what all code should strive to look as. Build simple modules that achieve a purpose and are trimmed clean of any unnecessary function.
If anything, it will enable the developer with flexibility, to build a system that can easily be fractured and provided in its necessary parts strictly. This makes maintaining and updating the system a beautiful process. Most developers love it. So FP advocates do what people who fail at fair competition always do: go into politics. They lie. You still need good design. Interesting article that omits at least one elephant in the room: SQL.
The SQL standard had virtually no provision or requirements for OOP concepts until structured types in SQL and still today not all major vendors support that and none supports it fully, I believe. Yet its easy to think of a table as an object and a function as a method, but the two are not usually bound together, with triggers and structured types being possible exceptions.
But then SQL offers a kind of declarative programming which is neither oop nor strictly imperative and not fully covered by those paradigms or the functional paradigm for that matter. I think the question is wrong.
Old procedural code did not scale and OOP promised something that did, but failed to deliver and was destroyed totally by Giuseppe Castagna decades ago as theoretically unsound and almost completely useless for any application the so-called covariance problem makes methods useless for handling any problem with two variant arguments, which is almost every interesting problem.
The question is why OOP is still taught by those that should know better and why researchers still waste time trying to invent a perpetual motion machine.
The answer is probably that the other alternative, functional programming, is even more useless. The algebraic framework which has the desirable properties is over three decades old but it is very hard for even professional mathematicians to understand, and has never been modelled successfully in a programming language.
Category theory is just plain hard, and humans always take the easy way out, the path of least resistance: make a huge mess but we do not care as long as everyone else is making a mess too. Can anybody elaborate, or redirect me to elaborations, on how concepts from OOP and FP facilitate on their ways tasks like creation, test, documentation, fix, improvement and reuse?
The title is absolutely exaggerated. Where is my proof? Where is your proof? OOP is still necessary for many reasons. In some fields you just want to use plain C for the sake of simplicity. But a OOP started with Simula a language for simulation. I think one aspect is often not mentioned: the packaging of functions with data definitions. It is this grouping into classes that allows OO languages to model the real world so easily. Keeping methods and the data they maintain as state within objects is how encapsulation encourages reusable code and prevents large classes of bugs.
Take a look at what the awesome Julia language offers: multiple dispatch. OOP is a tool just like any other programming construct. It has appropriate uses and inappropriate uses. The tool needs to be selected for the job.
OOP lends great advantage to large scale tasks. It adds unnecessary complexity to simple tasks. I think this is caused by the following: 1. All of the books that promote complex OOP architectures and concepts where they have absolutely no business. The overuse of inheritance. Developer narcissism — people who gravitate to the most complex solutions because they want to prove how smart or hip they are.
OOP is valuable to be sure, but has been used in many deleterious ways. The problem identified by Joel remains the single biggest issue in software development today. However, if you are working on a small project it might not be the best choice. There are many things to consider, but variable scope can be a nightmare without the protection that OOP provides. The textbook UML user guide from my college days summed it up best… if you want to build a dog house for your dog… just go to the hardware store, get some nails, lumber, and a few tools.
Thus, authors stressed using models to identify use cases and pattern reuse. Coding is a matter of abstraction. We abstract real life objects and situations into variables and functions. So what makes one generation of languages different from the other? Each one is a product of its time and the data abstraction needs posed by said time. The first generation, machine code and assembly, arrived when computers were still novel and applications were more simple.
The code focused on instructing the machine to automate a set of simple tasks. The second generation, C, arrived when data needs increased and applications became more complicated.
C took care of most of the machine-specific details and allowed coders to focus on abstraction problem solving. C simplified programming. The third generation, Java, arrived well in time with the computer revolution.
Computer systems could already be found everywhere, and the web was really starting to take off. OOP took a simple idea, that modularization is the easiest way to solve any given problem, and standardized that idea amongst coders. The problem was that procedural languages rendered modularization a hell of a hassle. But the world needed modularization and its simplicity because of the ever increasing integration and reliance on computer systems.
OOP then came to the rescue by spawning its own set of languages, 3rd gen languages, that easily facilitated modularization of code.
It essentially made computer programming more available to the public by making it easier. Both paradigms are equally capable. OOP being the next generation in line simply made coding easier and pushed programmers towards high level abstraction. The fourth generation, SQL, is on a whole different league of its own. The way it goes now is that we type up millions of 3rd gen lines, we add in a few thousand 4th gen lines, and if push comes to shove we throw in a few segments of 2nd gen code for optimization and compatibility with low level sysyems.
It all however must compile to 1st gen code in the end — ready to load up on RAM. I do agree with most of the comments that OOP is not hated in general. Maybe functional languages are a bit of a hype right now, and most of these do not have OOP features. Just because a lot of people leave stereotypical OOP languages does not mean they hate them. The opposite of OOP is procedural and the opposite of functional is imperative.
Scala shows that an OOP language can have functional programming for the implementation of their methods. Subtyping is a marker of OOP and inheritance is most often the implementation of this concept in a specific programming language. Prototypes or copying from an existing object are other ways to implement subtyping.
I think one of the major reasons at least in my line of work that OOP is so prevalent is that it is currently the best way to write GUIs. I love using Qt to write my GUI. I am not sure, though, if I would like to write a library like this. Strong adherence to every single OOP principle all the time is quite tedious. On the other hand I do hate sticking perfectly to encapsulation all the way through. And with this part of OO design principles I strongly disagree.
Some OOP languages even lets you have the compiler write the setter and getter automatically and use assignment syntax to call these.
So, why would you enforce them everywhere? I have seen academic examples where you could switch out the implementation of the class entirely. However, I think this is too much overhead for the small possibility that it might happen in the future. Interfaces are just like interfaces of electronics — we have a panel with some buttons but the details of what happens when their are pressed are hidden from the user — same happens with interfaces in oop though interfaces can have some additional meanings.
As you can see OOP allows us to express code in natural way which mirrors the real world with its objects and actions. OOP is an evolution of procedural programming — which in its turn was created to allow us express code in a more natural manner to us humans than assembly — which is designed around how the computer works, not around how we think, communicate, understand the world.
Some people seem to forget that if they ever were aware of it. Yes, it is sometimes the case that OOP programs are not easily maintainable. In my experience, that fault often stems from overuse of inheritance, as has been noted in this discussion, particularly the creation of long chains of itty-bitty classes that individually do not add much.
If a class is merely the parent of a subclass, if it is not going to be instantiated and used itself, then maybe it does not need to be in the hierarchy. OOP is a tool like any other, and can be used well or badly. Slavishly following the OOP lessons that one learned in school may not result in code that can be understood by a new generation of maintainers. Over the years, I have found that OOP helps me organize my intentions and the actions of my code, and to isolate data and functions, and all of those reduce complexity and make debugging dramatically easier.
For instance, I just finished a large, multi-year research project in which the directions of the research changed dramatically over the many months. Every time we found an answer to a question, another question arose that required some additional coding, some recoding. Few modules remained unaltered for more than a few months at a time, but some did. The few that did were ones that represented well-understood objects, and isolated them data and function from changes in the business logic due to new requirements.
If the edit history of a class module had a year of dust on it, I considered that a real success. Not a big deal, but took more than four years to evolve to answer all the questions. Some programmers I know would surely have used classes where 40 sufficed. Functional Programming makes a lot of assumptions about the environment it runs in; so in OOP terms, programs that are functional run inside components or encapsulated environments; on the other side, OOP can leverage a lot from FP so as to achieve functionalities that are not dependent of the state of anything.
Small linear systems allow heavy application of algorithm driven design that favors functional design, such systems however are not flexible, there is a certain tolerance in which you can stretch the input and expect a valid output.
Another problem with such systems is the way they mutate as they generate knowledge about the problem they are designed to solve- although as correctly pointed in the article linear execution is the way the processor runs the code, the learning curves and the changes that come with them are non linear and not continuous- this makes the scalability of such systems poor.
On the other end big non-linear systems that address a domain of problems favor object design. This adds additional complexity because the design itself requires the build-up of meta-knowledge of the problem domain at hand, and a planned approach that transforms that meta-knowledge to a continuous coherent structure.
Going back to my initial point, when software development started the problems it addressed where operational and not systemic. Running an executable with a certain parameters generated output and removed itself from the memory. As the industry progressed however the problems became more and more complicated, and the programs started expressing more features. This itself did not require a paradigm shift, but with those features came the constantly growing code bases and the mutation of the problem sets.
In a way you may say that software systems came to life- and life in its core is polymorphic. This rendered functional approaches progressively more difficult and expensive to maintain which naturally lead to the adoption of the object orientated design. As time continued to pass, we saw the downfall of mainframes that ran huge loads, and the rise of clusters- this pushed further the object orientated approach because even more internal states had to managed, and the synchronization between servers required better encapsulation.
Ten the web happened- it took some time but with the markup as a universal application structure, the functional approach began to regain momentum- from applets to advanced scripting the DOM and the robust data transfer layer made small linear programs relevant again.
This naturally lead to more and more features in the browsers which however enabled more and more complicated programs and so we arrived at the single page applications and the content management frameworks, and the cloud farms. With the emergence of the IOT ecosystems we will see the same cycle again, we will go back to functional and than scale it to object.
As a side note the conflict at hand here for me is similar to an argument which color is better the red one or the green one, without any context. If we add context we may have an argument that for example red pops up so it is better for errors than green, but then green is calm on the eyes so it is good for a background etc….
The change in paradigms follows the lessons that life teaches, and the same is true with political systems, philosophical ideas, cultural phenomenons, morals and so on.
FP is a tool. Not every problem is a nail. Different tools for different problems. The discussion pops up everywhere once in a while.
Arguments are exchanged why certain things are more easy to do with OOP or FP, inheritance is discussed but no conclusion found. Next to computer science I studied cognitive psychology on university.
What even most psychologists are not aware of is that the way of thinking in humans variies a lot. Most people have vivid visual memories of past events or locations they have visited. For other pepole it completely impossible to have a mental picture in their inner eye. Some people do think in words and sentences.
They live with a narrator who almost constantly talks to them. Others cannot even comprehend the idea how this would be to have a inner voice talking to them. Some people argue OOP is intuitive. For me to model any real world in stateful objects performing methods is as counterintuitive as it can be. It makes me almost physical pain to look at these ways of modelling.
I have studied computer science, but when OOP became omnipresent left development because I hated OOP programming and changed to a consulting career. And there is very little chance that one party can clarify to the other party why the see OOP as a good or bad thing to model the world.
OOP in itself is not the problem. Organized people will find ways to organize code no matter what programming style, language style, framework they use. They will be well organized, know where to find things and do things in fastest possible manner.
The stated components are the instances of classes. Newer versions of them are instances of Inheritances. First of all, it is absolutely clear to me that there is not a slightest understanding what is the core idea of OOP. You create objects, gift them behaviour via interfaces, hide their data via encapsulation and then your code becomes very fluent when done right:.
Next, when you need a new Engine, you simply replace it, as you do in a real life. Again, you tell computer what to do, how to do it well, not at a business layer, at least. The behaviour you do. OOP is simply a way to organize your code.
I started many years ago programming Ansi-C. Functional programming was great as long as the program was small, but as the sources grew, errors and side effects became hard to avoid and maintain. With more than 30 kB of source code most of my project development slowed down significantly. With OOP things are very different. I still use some codes that are really old now, but still do their work.
And over the time some classes have grown very big. Some of them compile more than For small projects, functional programming is quick and effortless. But if things grow, OOP is the most efficient tool to handle your codes.
For web programming things are not so easy, as HTML can only generate global references. And there are other approaches like web components, that have a similar target. OOP successful?
If you mean widespread, then it is successful. However, I would say that it is not a success because the software I use on a daily basis that has been developed with OOP is just shitty, at every level. I have a shitty bug tracking app, a shitty time tracking app, a shitty database and a shitty communication app, a shitty email app, shitty collaboration app….. The one thing they all have in common is their shittiness.
The Trillion Dollar Disaster essay is spot on. Well your title is certainly provocative, but inaccurate. Most technology seems to evolve in a Hegelian fashion because humans are driving it.
As one becomes older they have the opportunity to see this more and more. The younger generation tends to be more vocal and champions their particular beliefs which are by definition myopic. Functional programming has a light shining on it now as the antithesis of the object based paradigm. As things evolve we will find some synthesis that includes concepts from both. Object oriented software evolved as way to manage complexity in systems that were becoming increasingly complex. It does this exceedingly well.
If you have over worked on a very large complex system, being able to address it at different levels of complexity, hierarchically is a god send over the alternative. It is especially beneficial to other team members who may be new to a system and have to learn it. Having objects structured in the language of the domain being addressed makes this possible.
It is also interesting to see a sophisticated object system become slightly more than the some of its parts as the virtual models shape themselves to the natural objects and relationships they represent. Larger, complex systems are its sweet spot. It becomes less adept without some care when you need to distribute processing and do more complex algorithmic work over larger data sets and then bring that data together after processing.
The immutability favored by the functional paradigm is a good fit for things like this. But from what I have seen, functional reads and flows very poorly. So a lot really depends on the domain you are working in and the problem you are trying to solve as to which paradigm might be a better fit.
You also have to consider what hardware things are being run on, and whether you are working in a compiled or interpreted language. Software maintenance is another giant factor which is often overlooked. I think for proper treatment of the subject the entire SDL would need to be factored in.
In my opinion, looking at the pros and conns, functional programming has niche applications for which it is suited. I was currently brought on to a project using react-native with the functional paradigm. It is a square peg in a round hole that I am stuck working on. These programming approaches have been passing through revolutionary phases just like computer hardware.
Initially for designing small and simple programs, the machine language was used. Next came the Assembly Language which was used for designing larger programs. Both machine and Assembly languages are machine dependent. Next came Procedural Programming Approach which enabled us to write larger and hundred lines of code.
Then in , a new programming approach called Structured Programming Approach was developed for designing medium sized programs.
In 's the size of programs kept increasing so a new approach known as OOP was invented. Monolithic Programming Approach: In this approach, the program consists of sequence of statements that modify data. All the statements of the program are Global throughout the whole program. The program control is achieved through the use of jumps i. In this approach, code is duplicated each time because there is no support for the function. Data is not fully protected as it can be accessed from any portion of the program.
So this approach is useful for designing small and simple programs. Procedural Programming Approach: This approach is top down approach. In this approach, a program is divided into functions that perform a specific task. Data is global and all the functions can access the global data. Program flow control is achieved through function calls and goto statements. This approach avoids repetition of code which is the main drawback of Monolithic Approach.
The basic drawback of Procedural Programming Approach is that data is not secured because data is global and can be accessed by any function. This approach is mainly used for medium sized applications.
Structured Programming Approach: The basic principal of structured programming approach is to divide a program in functions and modules. The use of modules and functions makes the program more comprehensible understandable. It helps to write cleaner code and helps to maintain control over each function.
This approach gives importance to functions rather than data. It focuses on the development of large software applications. The basic principal of the OOP approach is to combine both data and functions so that both can operate into a single unit. Such a unit is called an Object. This approach secures data also.
Now a days this approach is used mostly in applications. Using this approach we can write any lengthy code.
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