essay on programming language in english

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What is Python? Executive Summary

Topics for Essays on Programming Languages: Top 7 Options

Java Platform Editions and Their Peculiarities

Python: a favorite of developers, javascript: the backbone of the web, typescript: narrowing down your topic, the present and future of php, how to use c++ for game development, how to have fun when learning swift.

‍ Delving into the realm of programming languages offers a unique lens through which we can explore the evolution of technology and its impact on our world. From the foundational assembly languages to today's sophisticated, high-level languages, each one has shaped the digital landscape.

Whether you're a student seeking a deep dive into this subject or a tech enthusiast eager to articulate your insights, finding the right topic can set the stage for a compelling exploration.

This article aims to guide you through selecting an engaging topic, offering seven top options for essays on programming languages that promise to spark curiosity and provoke thoughtful analysis.

"If you’re a newbie when it comes to exploring Java programming language, it’s best to start with the basics not to overcomplicate your assignment. Of course, the most obvious option is to write a descriptive essay highlighting the features of Java platform editions:

- Java Standard Edition (Java SE). It allows one to develop Java applications and ensures the essential functionality of the programming language;

- Java Enterprise Edition (Java EE). It's an extension of the previous edition for developing and running enterprise applications;

- Java Micro Edition serves for running applications on small and mobile devices.

You can explain the purpose of each edition and the key components to inform and give value to the readers. Or you can go in-depth and opt for a compare and contrast essay to show your understanding of the subject and apply critical thinking skills."

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You probably already know that this programming language is widely used globally.

Python is perfect for beginners who want to master programming because of the simple syntax that resembles English. Besides, look at the opportunities it opens:

- developing web applications, of course;

- building command-line interface (CLI) for routine tasks automation;

- creating graphical user interfaces (GUIs);

- using helpful tools and frameworks to streamline game development;

- facilitating data science and machine learning;

- analyzing and visualizing big data.

All these points can become solid ideas for your essay. For instance, you can use the list above as the basis for argumentation why one should learn Python. After doing your research, you’ll find plenty of evidence to convince your audience.

And if you’d like to spice things up, another option is to add your own perspective to the debate on which language is better: Python or JavaScript.

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"This programming language is no less popular than the previous one. It’s even considered easier to learn for a newbie. If you master it, you’ll gain a valuable skill that can help you start a lucrative career. Just think about it:

- JavaScript is used by almost all websites;

with it, you can develop native apps for iOS and Android;

- it allows you to grasp functional, object-oriented, and imperative programming;

you can create jaw-dropping visual effects for web pages and games;

- it’s also possible to work with AI, analyze data, and find bugs.

So, drawing on the universality of JavaScript and the career opportunities it brings can become a non-trivial topic for your essay.

Hint: look up job descriptions demanding the knowledge of JavaScript. Then, compare salaries to provide helpful up-to-date information. Your professor should be impressed with your approach to writing."

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"Yes, you guessed right - this programming language kind of strengthens the power of JavaScript. It allows developers to handle large-scale projects. TypeScript enables object-oriented programming and static typing; it has a single open-source compiler.

If you want your essay to stand out and show a deeper understanding of the programming basics, the best way is to go for a narrow topic. In other words, niche your writing by focusing on the features of TypeScript.

For example, begin with the types:

- Tuple, etc.

Having elaborated on how they work, proceed to explore the peculiarities, pros, and cons of TypeScript. Explaining when and why one should opt for it as opposed to JavaScript also won't hurt.

Here, you can dive into details as much as you want, but remember to give examples and use logical reasoning to prove your claims."

"This language intended for server-side web development has been around for a really long time: almost 80% of websites still use it.

But there’s a stereotype that PHP can’t compete with other modern programming languages. Thus, the debates on whether PHP is still relevant do not stop. Why not use this fact to compose a top-notch analytical essay?

Here’s how you can do it:

1. research and gather information, especially statistics from credible sources;

2. analyze how popular the programming language is and note the demand for PHP developers;

3. provide an unbiased overview of its perks and drawbacks and support it with examples;

4. identify the trends of using PHP in web development;

5. make predictions about the popularity of PHP over the next few years.

If you put enough effort into crafting your essay, it’ll not only deserve an “A” but will also become a guide for your peers interested in programming.

Did you like our article?

For more help, tap into our pool of professional writers and get expert essay editing services!

C++ is a universal programming language considered most suitable for developing various large-scale applications. Yet, it has gained the most popularity among video game developers as C++ is easier to apply to hardware programming than other languages.

Given that the industry of video games is fast-growing, you can write a paper on C++ programming in this sphere. And the simplest approach to take is offering advice to beginners.

For example, review the tools for C++ game development:

- GameSalad;

- Lumberyard;

- Unreal Engine;

- GDevelop;

- GameMaker Studio;

- Unity, among others.

There are plenty of resources to use while working on your essay, and you can create your top list for new game developers. Be sure to examine the tools’ features and customer feedback to provide truthful information for your readers.

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"Swift was created for iOS applications development, and people argue that this programming language is the easiest to learn. So, how about checking whether this statement is true or false?

The creators of Swift aimed to make it as convenient and efficient as possible. Let’s see why programmers love it:

- first of all, because it’s compatible with Apple devices;

- the memory management feature helps set priorities for introducing new functionality;

- if an error occurs, recovering is no problem;

- the language boasts a concise code and is pretty fast to learn;

- you can get advice from the dedicated Swift community if necessary.

Thus, knowing all these benefits, you can build your arguments in favor of learning Swift. But we also recommend reflecting on the opposite point of view to present the whole picture in your essay. And if you want to dig deeper, opt for a comparison with other programming languages."

Essays on programming I think about a lot

Every so often I read an essay that I end up thinking about, and citing in conversation, over and over again.

Here’s my index of all the ones of those I can remember! I’ll try to keep it up to date as I think of more.

There's a lot in here! If you'd like, I can email you one essay per week, so you have more time to digest each one:

Nelson Elhage, Computers can be understood . The attitude embodied in this essay is one of the things that has made the biggest difference to my effectiveness as an engineer:

I approach software with a deep-seated belief that computers and software systems can be understood. … In some ways, this belief feels radical today. Modern software and hardware systems contain almost unimaginable complexity amongst many distinct layers, each building atop each other. … In the face of this complexity, it’s easy to assume that there’s just too much to learn, and to adopt the mental shorthand that the systems we work with are best treated as black boxes, not to be understood in any detail. I argue against that approach. You will never understand every detail of the implementation of every level on that stack; but you can understand all of them to some level of abstraction, and any specific layer to essentially any depth necessary for any purpose.

Dan McKinley, Choose Boring Technology . When people ask me how we make technical decisions at Wave, I send them this essay. It’s probably saved me more heartbreak and regret than any other:

Let’s say every company gets about three innovation tokens. You can spend these however you want, but the supply is fixed for a long while. You might get a few more after you achieve a certain level of stability and maturity, but the general tendency is to overestimate the contents of your wallet. Clearly this model is approximate, but I think it helps. If you choose to write your website in NodeJS, you just spent one of your innovation tokens. If you choose to use MongoDB, you just spent one of your innovation tokens. If you choose to use service discovery tech that’s existed for a year or less, you just spent one of your innovation tokens. If you choose to write your own database, oh god, you’re in trouble.

Sandy Metz, The Wrong Abstraction . This essay convinced me that “don’t repeat yourself” (DRY) isn’t a good motto. It’s okay advice, but as Metz points out, if you don’t choose the right interface boundaries when DRYing up, the resulting abstraction can quickly become unmaintainable:

Time passes. A new requirement appears for which the current abstraction is almost perfect. Programmer B gets tasked to implement this requirement. Programmer B feels honor-bound to retain the existing abstraction, but since isn’t exactly the same for every case, they alter the code to take a parameter…. … Loop until code becomes incomprehensible. You appear in the story about here, and your life takes a dramatic turn for the worse.

Patrick McKenzie, Falsehoods Programmers Believe About Names . When programming, it’s helpful to think in terms of “invariants,” i.e., properties that we assume will always be true. I think of this essay as the ultimate reminder that reality has no invariants :

People’s names are assigned at birth. OK, maybe not at birth, but at least pretty close to birth. Alright, alright, within a year or so of birth. Five years? You’re kidding me, right?

Thomas Ptacek, The Hiring Post . This essay inspired me to put a lot of effort into Wave’s work-sample interview, and the payoff was huge—we hired a much stronger team, much more quickly, than I expected to be able to. It’s also a good reminder that most things that most people do make no sense:

Nothing in Alex’s background offered a hint that this would happen. He had Walter White’s resume, but Heisenberg’s aptitude. None of us saw it coming. My name is Thomas Ptacek and I endorse this terrible pun. Alex was the one who nonced. A few years ago, Matasano couldn’t have hired Alex, because we relied on interviews and resumes to hire. Then we made some changes, and became a machine that spotted and recruited people like Alex: line of business .NET developers at insurance companies who pulled Rails core CVEs out of their first hour looking at the code. Sysadmins who hardware-reversed assembly firmware for phone chipsets. Epiphany: the talent is out there, but you can’t find it on a resume. Our field selects engineers using a process that is worse than reading chicken entrails. Like interviews, poultry intestine has little to tell you about whether to hire someone. But they’re a more pleasant eating experience than a lunch interview.

Gergely Orosz, The Product-Minded Engineer . I send this essay to coworkers all the time—it describes extremely well what traits will help you succeed as an engineer at a startup:

Proactive with product ideas/opinions • Interest in the business, user behavior and data on this • Curiosity and a keen interest in “why?” • Strong communicators and great relationships with non-engineers • Offering product/engineering tradeoffs upfront • Pragmatic handling of edge cases • Quick product validation cycles • End-to-end product feature ownership • Strong product instincts through repeated cycles of learning

tef, Write code that is easy to delete, not easy to extend . The Wrong Abstraction argues that reusable code, unless carefully designed, becomes unmaintainable. tef takes the logical next step: design for disposability, not maintainability. This essay gave me lots of useful mental models for evaluating software designs.

If we see ‘lines of code’ as ‘lines spent’, then when we delete lines of code, we are lowering the cost of maintenance. Instead of building re-usable software, we should try to build disposable software.

Business logic is code characterised by a never ending series of edge cases and quick and dirty hacks. This is fine. I am ok with this. Other styles like ‘game code’, or ‘founder code’ are the same thing: cutting corners to save a considerable amount of time. The reason? Sometimes it’s easier to delete one big mistake than try to delete 18 smaller interleaved mistakes. A lot of programming is exploratory, and it’s quicker to get it wrong a few times and iterate than think to get it right first time.

tef also wrote a follow-up, Repeat yourself, do more than one thing, and rewrite everything , that he thinks makes the same points more clearly—though I prefer the original because “easy to delete” is a unifying principle that made the essay hang together really well.

Joel Spolsky, The Law of Leaky Abstractions . Old, but still extremely influential—“where and how does this abstraction leak” is one of the main lenses I use to evaluate designs:

Back to TCP. Earlier for the sake of simplicity I told a little fib, and some of you have steam coming out of your ears by now because this fib is driving you crazy. I said that TCP guarantees that your message will arrive. It doesn’t, actually. If your pet snake has chewed through the network cable leading to your computer, and no IP packets can get through, then TCP can’t do anything about it and your message doesn’t arrive. If you were curt with the system administrators in your company and they punished you by plugging you into an overloaded hub, only some of your IP packets will get through, and TCP will work, but everything will be really slow. This is what I call a leaky abstraction. TCP attempts to provide a complete abstraction of an underlying unreliable network, but sometimes, the network leaks through the abstraction and you feel the things that the abstraction can’t quite protect you from. This is but one example of what I’ve dubbed the Law of Leaky Abstractions: All non-trivial abstractions, to some degree, are leaky. Abstractions fail. Sometimes a little, sometimes a lot. There’s leakage. Things go wrong. It happens all over the place when you have abstractions. Here are some examples.

Reflections on software performance by Nelson Elhage, the only author of two different essays in this list! Nelson’s ideas helped crystallize my philosophy of tool design, and contributed to my views on impatience .

It’s probably fairly intuitive that users prefer faster software, and will have a better experience performing a given task if the tools are faster rather than slower. What is perhaps less apparent is that having faster tools changes how users use a tool or perform a task. Users almost always have multiple strategies available to pursue a goal — including deciding to work on something else entirely — and they will choose to use faster tools more and more frequently. Fast tools don’t just allow users to accomplish tasks faster; they allow users to accomplish entirely new types of tasks, in entirely new ways. I’ve seen this phenomenon clearly while working on both Sorbet and Livegrep…

Brandur Leach’s series on using databases to ensure correct edge-case behavior: Building Robust Systems with ACID and Constraints , Using Atomic Transactions to Power an Idempotent API , Transactionally Staged Job Drains in Postgres , Implementing Stripe-like Idempotency Keys in Postgres .

Normally, article titles ending with “in [technology]” are a bad sign, but not so for Brandur’s. Even if you’ve never used Postgres, the examples showing how to lean on relational databases to enforce correctness will be revelatory.

I want to convince you that ACID databases are one of the most important tools in existence for ensuring maintainability and data correctness in big production systems. Lets start by digging into each of their namesake guarantees.

There’s a surprising symmetry between an HTTP request and a database’s transaction. Just like the transaction, an HTTP request is a transactional unit of work – it’s got a clear beginning, end, and result. The client generally expects a request to execute atomically and will behave as if it will (although that of course varies based on implementation). Here we’ll look at an example service to see how HTTP requests and transactions apply nicely to one another.

In APIs idempotency is a powerful concept. An idempotent endpoint is one that can be called any number of times while guaranteeing that the side effects will occur only once. In a messy world where clients and servers that may occasionally crash or have their connections drop partway through a request, it’s a huge help in making systems more robust to failure. Clients that are uncertain whether a request succeeded or failed can simply keep retrying it until they get a definitive response.

Jeff Hodges, Notes on Distributed Systems for Young Bloods . An amazing set of guardrails for doing reasonable things with distributed systems (and note that, though you might be able to get away with ignoring it for a while, any app that uses the network is a distributed system). Many points would individually qualify for this list if they were their own article—I reread it periodically and always notice new advice that I should have paid more attention to.

Distributed systems are different because they fail often • Implement backpressure throughout your system • Find ways to be partially available • Use percentiles, not averages • Learn to estimate your capacity • Feature flags are how infrastructure is rolled out • Choose id spaces wisely • Writing cached data back to persistent storage is bad • Extract services.

J.H. Saltzer, D.P. Reed and D.D. Clark, End-to-End Arguments in System Design . Another classic. The end-to-end principle has helped me make a lot of designs much simpler.

This paper presents a design principle that helps guide placement of functions among the modules of a distributed computer system. The principle, called the end-to-end argument, suggests that functions placed at low levels of a system may be redundant or of little value when compared with the cost of providing them at that low level. Examples discussed in the paper include bit error recovery, security using encryption, duplicate message suppression, recovery from system crashes, and delivery acknowledgement. Low level mechanisms to support these functions are justified only as performance enhancements.

Bret Victor, Inventing on Principle :

I’ve spent a lot of time over the years making creative tools, using creative tools, thinking about them a lot, and here’s something I’ve come to believe: Creators need an immediate connection to what they’re creating.

I can’t really excerpt any of the actual demos, which are the good part. Instead I’ll just endorse it: this talk dramatically, and productively, raised my bar for what I think programming tools (and tools in general) can be. Watch it and be amazed.

Post the essays you keep returning to in the comments!

Liked this post? Get email for new ones: Also send the best posts from the archives

10x (engineer, context) pairs

What i’ve been doing instead of writing, my favorite essays of life advice.

format comments in markdown .

Quite a few of these are on my list, here’s some others that I keep returning to every so often:

• https://www.stilldrinking.org/programming-sucks
• https://medium.com/@nicolopigna/this-is-not-the-dry-you-are-looking-for-a316ed3f445f
• https://sysadvent.blogspot.com/2019/12/day-21-being-kind-to-3am-you.html
• https://jeffknupp.com/blog/2014/05/30/you-need-to-start-a-whizbang-project-immediately/

Great list! Some essays I end up returning to are:

• https://www.destroyallsoftware.com/compendium/software-structure?share_key=6fb5f711cae5a4e6
• https://caseymuratori.com/blog_0015

These are conference talks on youtube, not blog posts, but here’s a few of the ones I often end up sending to collaborators as addenda to discussions:

Don Reinertsen - Second Generation Lean Product Development Flow

Joshua Bloch

The Language of the System - Rich Hickey

Some posts:

https://speakerdeck.com/vjeux/react-css-in-js - diagnosis of problems with CSS (not because of React)

https://zachholman.com/talk/firing-people

Especially for fault-tolerant systems, “why restart helps” really opened my eyes:

• https://ferd.ca/the-zen-of-erlang.html

Oh, I forgot: http://web.mit.edu/2.75/resources/random/How%20Complex%20Systems%20Fail.pdf

Oldie but a goodie:

https://www.developerdotstar.com/mag/articles/reeves_design_main.html

+1 for that one

This is a great list. If i could make one addition it would have to be Rich Hickey’s “simple made easy”: https://www.youtube.com/watch?v=oytL881p-nQ

I was once working with a newly formed (4 person) team on a large and complex project under a tight deadline. For a while we weren’t seeing eye to eye on many of the key decisions we made. Watching and reflecting on this talk gave us a shared aim and, perhaps even more importantly, a shared language for making choices that would reduce the complexity of our system. It is a gift that keeps on giving.

Another one that belongs on this list: https://www.kitchensoap.com/2012/10/25/on-being-a-senior-engineer/

A couple of my favorites:

• https://nedbatchelder.com/text/deleting-code.html
• https://www.joelonsoftware.com/2002/01/23/rub-a-dub-dub/

Out of the Tar Pit. https://github.com/papers-we-love/papers-we-love/blob/master/design/out-of-the-tar-pit.pdf

I’d like to nominate another of Nelson Elhage’s posts:

• https://blog.nelhage.com/2016/03/design-for-testability

This has had more direct influence on my day-to-day code writing than anything else. (Also, his other writing on testing is great.)

As another commenter mentioned conference talks, Bryan Cantrill on debugging is important—it meshes well with Nelson’s Computer can be understood . ( https://www.slideshare.net/bcantrill/debugging-microservices-in-production )

A fave of mine: Clojure: Programming with Hand Tools https://www.youtube.com/watch?v=ShEez0JkOFw

Some essays I like:

Science and the compulsive programmer by Joseph Weizenbaum - written in 1976, but the described phenomena of a compulsive programmer still exists and may be relevant to many: https://www.sac.edu/academicprogs/business/computerscience/pages/hester_james/hacker.htm

https://www.mit.edu/~xela/tao.html - Tao of Programming - not sure if you can classify as an essay, but it is classic!

https://norvig.com/21-days.html - Teach Yourself Programming in Ten Years by Peter Novig - a great essay on how to master programming and why reading books like “Learn X in Y days” won’t be of much help. I recommend it to all beginners

Reginald Braithwaite, Golf is a good program spoiled - http://weblog.raganwald.com/2007/12/golf-is-good-program-spoiled.html . Raganwald has more great essays on his weblog, I just like this one the most.

The link of the last one ( https://vimeo.com/36579366 ) is broken. You may want to update it.

Paul Graham, “Maker’s Schedule, Manager’s Schedule " https://paulgraham.com/makersschedule.html

I keep thinking about those too:

https://www.teamten.com/lawrence/programming/write-code-top-down.html

https://rubyonrails.org/doctrine#provide-sharp-knives

Python Programming Language Essay

Introduction.

Web services are one of the developments that accompanied the increased use of internet. This implies that web developers had to constantly review the approaches used to access web content, and so was the development of the web services technology. This essay provides an overview of Python language and how it is related to the development of web services.

This essay provides an insight into Python programming language by highlighting the key concepts associated with the language and on overview of the development of web services using Python. In addition, the essay highlights the survey tools that can facilitate the development of web services in Python programing language.

Python programming language is one of dynamic and object-oriented programming languages used for the development of diverse kinds of software developed by the Python Software foundation. Its significant advantage is that facilitates integration with other programing languages and software development tools. In addition, it has in-built standard libraries that are extensive. This means that it facilitates the development of a better source code.

The programming paradigm of Python language embarks on the readability of the source code enhanced through clear syntax. Apart from object-oriented programming paradigm, Python can implement other programming methodologies such as functional programing and imperative programming (Beazley 67).

Another important feature of Python language that makes it suitable as a software development tool is that it has a dynamic type system and its memory management strategy is automatic. In addition, it can support the implementation of scripting applications. It is important to note that the development model of Python language is community based, implying that its reference implementation is free and bases on the open source platform. There are various interpreters for the language for various systems software, although programs developed by Python are executable in any environment irrespective of operating system environment (Hetland 78).

Brief history of Python programming language

The development of Python language began during the late 80s, with its implementation done on the December of 1989. Python was a successor of the ABC programming language, which had the capabilities of exception handling and implementing an interface with the Amoeba System Software. The release of Python 2.0 during 2000 saw the inclusion of newer features such as offering support for Unicode and garbage collection (Beazley 89).

The significant change was its transformation making its development process community based. The release of Python 3.0 took place during 2008. Python language boasts of winning two awards by the TIOBE as the programming of language of the year during 2007 and 2010, resulting to an increase in the popularity of the language (Hetland 56).

Implementation of web services in Python

A web service is defines as a program that can transform any client application to a web-based application. The development of web services significantly depends on the scripting abilities of a programming language. An important aspect of Python language is that it can be used in scripting, implying that it is an effective development tool for web services. Web services developed by Python function using the standard messaging formats and they can be interfaced with other software development tools using the conventional Application Programming Interface (API).

Web programming using Python entails two major paradigms: server programming and client programming (Beazley 90). Server programming entails the development of web services that run on the web server, while client programming entails the development of web services that that run on the client side (Hetland 90). There are diverse approaches to server programming, examples include the WebFrameworks used for development of server side services using Python; CgiScripts used to write scripting applications in Python; Webservers, which are server solutions developed using Python.

Web services developed in Python are primarily used to offer access and functionality of the APIs via the web. On the client side, Python language can be used in a number of ways including Web Browser Programming, Web Client Programming and Web services. There are various libraries in Python for the development of web services; examples include the Simple Object Access Protocol (SOAP) and the Web Services Description Language (WSDL).

Python language has extensive in-built tools that can provide support to Internet protocols, coupled with its code readability characteristic, Python is therefore one of the most appropriate programming languages that can be used in the development of dynamic web content using the concept of dynamic programming. Some of the in-built facilities included in Python that can facilitate dynamic programming and development of web services include (Beazley 123):

• Python comes with HTTP 1.1 server implementations, which has both file servers and CGI servers. An important feature of this characteristic is that their customization is easy and they incorporate the concept of automation of web tasks. HTTP 1.1 has tools for the implementation of HTTP requests. In addition, HTTP 1.1 implements secure web services.
• Another important feature of Python is that is has features used for parsing and constructing of Uniform Resource Locators (URLs). This is used to facilitate the handling of URLs by the web service in a more efficient manner.
• Python also has an included HTML and SGML modules used for parsing HTML tags during the development of web services. SGNL is a part of the parent language of Python language.
• Python can also support XML since it has in-built XML parsing features and SAX libraries embedded in the standard library.
• Python can also handle CGI requests, facilitating the process of developing codes for handling CGI.
• Low-level sockets serve to enhance network programming, which is an important strategy in the development web based applications.

Web Frameworks used in the development of web services in Python language

A web framework is an important aspect in the development of web services and web-based applications. They allow the web developer to design web services without the need deploy low-level protocols and sockets. Most of the available web frameworks technology based on server side scripting, with a few frameworks supporting client side scripting (Hetland 122).

Python language uses web frameworks for the development of web services through providing an avenue through which web developers can simply write codes basing on some standards of conformity to that particular framework. This concept of web service development in Python is known as plugging. Python language web frameworks provide diverse activities such as the interpretation of requests, production of responses and persistent data storage.

These processes are an integral part of the web services development (Beazley 67). An example of Python web frameworks is the Full stack frameworks, which consists of high-level components such as Django, Grok, Pylons and TurboGears. Python language can support other full stack web frameworks. The ability of Python language to support diverse web frameworks makes it one of the best programming languages that can be used for web service development.

In addition, they provide an avenue through which web developers can develop codes for web services (Drake 127). Python language frameworks also have the feature of customization, meaning that Python can be used to create abstractions, which can be used to implement specific tasks during the development of web service and their respective clients (Beazley 67).

Python language tool kits used in the development of web services

The two basic Python tool kits used in web service development are the gSOAP and the ZSI. The ZSI package found in Python has in-built capabilities that can support SOAP 1.1 messaging formats and WSDL frameworks. Web service development is easy to implement using ZSI package. The gSOAP toolkit also provides an effective platform for code development aimed implementing web services in Python language. Technologies such as JSON-RPC and SOAP also favor the development of codes for web services.

Under the JSON-RPC, Python-json-rpc is used in the development of web services. Environments such as the WSDL and Windows Common Foundation (WCF) on the other hand favor SOAP, which technologies such as Suds, Soaplib, psimblesoap and ZSI. It is also important to note that Python can be embedded in XML to develop web services under the XML-RPC platform. This comes as a provision in the inbuilt library of Python programming language (Drake 100).

The implementation of HTTP web services in python

HTTP web services are primarily used for exchanging data between various remote servers and clients. For instance, the HTTP GET is used to search for data in the server, while the HTTP POST is used for sending data to the remote server. There are other diving in operations implemented in HTTP web services using Python language.

They are used for data modification, creation and deletion operations. The significant advantage of the diving in strategy during code development for web services is due to the underlying simplicity compared to other web services development strategies using python language (Drake 102). Python has a number of libraries used for the implementation of web services basing on http platform. They are the http.client and the urllib.request.

The http.client is used to implement RFC 2616, while the url.lib provides a framework for development of standardized Application Program Interface. Another third-party library is httplib2, is an open source library used in the implementation of http in a more advanced manner compared to above libraries. The following section outlines the implementation of SOAP requests using Python programming language (Hetland 134).

SOAP (Simple Object Access Protocol)

SOAP is a protocol that is used for exchange of structured messaging formats during the development and implementation of web services. SOAP significantly relies on XML for the design of its message format. On addition, it also depends on protocols that are found in the application layer such as Remote Procedure Calls and HTTP in order to facilitate the transmission of the message.

An important characteristic of SOAP is that it can be used to form an integral part of the web services protocol stack, which are used for offering the framework for messaging. Messaging frameworks play an important role in the development of code for web services. This implies that programming languages, such as Python, that have messaging frameworks are effective in web services development. The three basic elements of the SOAP protocol based on the XML framework are the envelope, data types and conventions.

The envelope defines the elements contained in the message and the various approaches used in message processing (Drake 145). The convention is a set of procedures used to represent the SOAP requests and responses. As an instance of how SOAP requests and responses can be implemented, messages that are in the SOAP framework are sent to a web page that has the capability to handle web services.

An example of such a website can be a library database that has some specified search parameters to distinguish the various database elements such as year of publication, author name and so on. If the search data that is supposed to be returned is changed into a format that is standardized and based on the machine-parseable functionality, then a SOAP request can be implemented effectively during the development of web services (Hetland 67).

The SOAP request and response platform has several layers that are used for specifying the message formats, the transport protocols and the various strategies for message processing. It can be argued that SOAP is a more advanced XML-RPC, although it has features borrowed from WDDX. The SOAP specification framework comprises of the processing model, extensibility model, underlying protocol binding and the message construct.

The processing model of SOAP consists of the SOAP sender, which is primarily responsible for transmitting SOAP messages. The SOAP receiver serves as the destination for the SOAP messages while the passage path refers to a set of nodes that the message follows during transmission (Beazley 90).

The ultimate soap receiver denotes the final receiver of the SOAP messages. They are primarily used for processing the SOAP messages through analysis of the contents and the header information of the messages. In some cases, a SOAP intermediary is needed and serves to be the link between the SOAP sender and receiver (Drake 67).

The basic transport formats used in SOAP are the application layer protocols used in the present day internet infrastructure. SOAP uses the XML as the standard format for its messages because of its increased use in various internet applications. A drawback of the XML in the implementation of SOAP requests and responses is that if Python is implemented in it, it results into long lengths of code; therefore making code development for SOAP web services a cumbersome process (Hetland 90).

There have been criticisms concerning the effectiveness of the SOAP messages in the implementation of web services. Among its advantages is that SOAP is more extensible and flexible to be used in diverse transport protocols. Apart from usage in the standard transport protocol, the HTTP, SOAP can also be used in other transport protocols such as SMTP and JMS. Due to the fact that the SOAP model functions effectively on the HTTP transport platform, its implementation can be integrated into existing firewalls and proxies in order to enhance security of the web services during their implementation.

There are significant advantages concerning the development of web services basing on the SOAP model (Drake 170). One major disadvantage is that SOAP is significantly slower in comparison with other middle ware platforms such as COBRA. This slowness is a major issue during the sending of big SOAP messages over the web service (Beazley 78).

The slowness is due to issues associated with the XML format. The second disadvantage of the SOAP model in web service development is that roles of the various interacting users are not dynamic rather they are fixed. This implies that only a single user can have access to the services of the other party at a given time. In order to eliminate biasness during service usage, developers using the SOAP model incorporate some concept of polling in the development of web services (Drake 150).

Python language comes with SOAP libraries, making it effective in the implementation of SOAP requests and responses during the development of web services. There are diverse implementations of the SOAP model in Python programming language. The SOAP modules incorporated in Python are an integral part of the programming language during the development of web services using the SOAP model.

With the SOAP modules in its standard libraries, the development of SOAP model in Python eliminated the need to have Web Services Description Language (WSDL). The SOAP.py feature found in Python serves to support the development of Secure Sockets Layer (SSL). There are three basic approaches to development of web services in python programming language (Beazley 167). They are the Zolera Soap Infrastructure (ZSI), Soaplib and TGWebServices (TGWS). The following section provides an outline of the web services development strategies in python.

The ZSI offers the client and server libraries that are required for effective implementation of SOAP. In order to use ZSI, a web developer drafts a WDSL file, after which one codes the source code using python and then fed to the server. The WDSL files and its data structures are transformed into classes of python language, which can be fed to the client and server during the usage of web services (Beazley 125).

Soaplib is used in the generation of web services basing on the WDSL files and the source code written in python language. Its drawback is that it does not use the principles of full stack solutions (Beazley 145). This implies that has to be integrated with other web frameworks in order to be used effectively in the development of web services (Hetland 124).

TGWebServices

This is a component in the Turbo-Gears library of the python language. Its significant advantage during the implementation of web services using python is that it offers controller service to the base class, making it function as a root of the web service (Beazley 189). Its functionality is similar to Soaplib in the sense that during runtime, it produces a WDSL file from the source code. In addition, the library supports JSON and XML messages on the same code. A significant concern during the use of these libraries is interoperability. TGWS is reported to have SOAP faults. Another concern is feature completeness (Hetland 134).

It is evident that Python language is one of the most effective programming languages used in the development of web services. The ability to implement SOAP requests and response using python is an added advantage that favors the development of web services using Python (Drake 139).

Works cited

Beazley, David. Python Essential Reference . New Jersey: Addison-Wesley, 2009.

Drake, Fred . The Python Language Reference Manual . New York: Network Theory Limited, 2003.

Hetland, Magnus Lie. Python Algorithms: Mastering Basic Algorithms in the Python Language. New York: Apress, 2010.

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Introduction to Programming Languages

Introduction:.

A programming language is a set of instructions and syntax used to create software programs. Some of the key features of programming languages include:

• Syntax : The specific rules and structure used to write code in a programming language.
• Data Types : The type of values that can be stored in a program, such as numbers, strings, and booleans.
• Variables : Named memory locations that can store values.
• Operators : Symbols used to perform operations on values, such as addition, subtraction, and comparison.
• Control Structures : Statements used to control the flow of a program, such as if-else statements, loops, and function calls.
• Libraries and Frameworks: Collections of pre-written code that can be used to perform common tasks and speed up development.
• Paradigms : The programming style or philosophy used in the language, such as procedural, object-oriented, or functional.

Examples of popular programming languages include Python, Java, C++, JavaScript, and Ruby. Each language has its own strengths and weaknesses and is suited for different types of projects.

A programming language is a formal language that specifies a set of instructions for a computer to perform specific tasks. It’s used to write software programs and applications, and to control and manipulate computer systems. There are many different programming languages, each with its own syntax, structure, and set of commands. Some of the most commonly used programming languages include Java, Python, C++, JavaScript, and C#. The choice of programming language depends on the specific requirements of a project, including the platform being used, the intended audience, and the desired outcome. Programming languages continue to evolve and change over time, with new languages being developed and older ones being updated to meet changing needs.

Are you aiming to become a software engineer one day? Do you also want to develop a mobile application that people all over the world would love to use? Are you passionate enough to take the big step to enter the world of programming? Then you are in the right place because through this article you will get a brief introduction to programming. Now before we understand what programming is, you must know what is a computer. A computer is a device that can accept human instruction, processes it, and responds to it or a computer is a computational device that is used to process the data under the control of a computer program. Program is a sequence of instruction along with data. 

The basic components of a computer are: 

• Central Processing Unit(CPU)
• Output unit

The CPU is further divided into three parts-  

• Memory unit
• Control unit
• Arithmetic Logic unit

Most of us have heard that CPU is called the brain of our computer because it accepts data, provides temporary memory space to it until it is stored(saved) on the hard disk, performs logical operations on it and hence processes(here also means converts) data into information. We all know that a computer consists of hardware and software. Software is a set of programs that performs multiple tasks together. An operating system is also software (system software) that helps humans to interact with the computer system.  A program is a set of instructions given to a computer to perform a specific operation. or computer is a computational device that is used to process the data under the control of a computer program. While executing the program, raw data is processed into the desired output format. These computer programs are written in a programming language which are high-level languages. High level languages are nearly human languages that are more complex than the computer understandable language which are called machine language, or low level language. So after knowing the basics, we are ready to create a very simple and basic program. Like we have different languages to communicate with each other, likewise, we have different languages like C, C++, C#, Java, python, etc to communicate with the computers. The computer only understands binary language (the language of 0’s and 1’s) also called machine-understandable language or low-level language but the programs we are going to write are in a high-level language which is almost similar to human language.  The piece of code given below performs a basic task of printing “hello world! I am learning programming” on the console screen. We must know that keyboard, scanner, mouse, microphone, etc are various examples of input devices, and monitor(console screen), printer, speaker, etc are examples of output devices. 

At this stage, you might not be able to understand in-depth how this code prints something on the screen. The main() is a standard function that you will always include in any program that you are going to create from now onwards. Note that the execution of the program starts from the main() function. The clrscr() function is used to see only the current output on the screen while the printf() function helps us to print the desired output on the screen. Also, getch() is a function that accepts any character input from the keyboard. In simple words, we need to press any key to continue(some people may say that getch() helps in holding the screen to see the output).  Between high-level language and machine language, there are assembly languages also called symbolic machine code. Assembly languages are particularly computer architecture specific. Utility program ( Assembler ) is used to convert assembly code into executable machine code. High Level Programming Language is portable but requires Interpretation or compiling to convert it into a machine language that is computer understood.  Hierarchy of Computer language –  

There have been many programming languages some of them are listed below: 

Most Popular Programming Languages –   

Characteristics of a programming Language –  

• A programming language must be simple, easy to learn and use, have good readability, and be human recognizable.
• Abstraction is a must-have Characteristics for a programming language in which the ability to define the complex structure and then its degree of usability comes.
• A portable programming language is always preferred.
• Programming language’s efficiency must be high so that it can be easily converted into a machine code and its execution consumes little space in memory.
• A programming language should be well structured and documented so that it is suitable for application development.
• Necessary tools for the development, debugging, testing, maintenance of a program must be provided by a programming language.
• A programming language should provide a single environment known as Integrated Development Environment(IDE).
• A programming language must be consistent in terms of syntax and semantics.

Basic Terminologies  in Programming Languages:

• Algorithm : A step-by-step procedure for solving a problem or performing a task.
• Variable : A named storage location in memory that holds a value or data.
• Data Type : A classification that specifies what type of data a variable can hold, such as integer, string, or boolean.
• Function : A self-contained block of code that performs a specific task and can be called from other parts of the program.
• Control Flow : The order in which statements are executed in a program, including loops and conditional statements.
• Syntax : The set of rules that govern the structure and format of a programming language.
• Comment : A piece of text in a program that is ignored by the compiler or interpreter, used to add notes or explanations to the code.
• Debugging : The process of finding and fixing errors or bugs in a program.
• IDE : Integrated Development Environment, a software application that provides a comprehensive development environment for coding, debugging, and testing.
• Operator : A symbol or keyword that represents an action or operation to be performed on one or more values or variables, such as + (addition), – (subtraction), * (multiplication), and / (division).
• Statement : A single line or instruction in a program that performs a specific action or operation.

Basic Example Of Most Popular Programming Languages:

Here the basic code for addition of two numbers are given in some popular languages (like C, C++,Java, Python, C#, JavaScript etc.).

 Advantages of programming languages:

• Increased Productivity: Programming languages provide a set of abstractions that allow developers to write code more quickly and efficiently.
• Portability: Programs written in a high-level programming language can run on many different operating systems and platforms.
• Readability : Well-designed programming languages can make code more readable and easier to understand for both the original author and other developers.
• Large Community: Many programming languages have large communities of users and developers, which can provide support, libraries, and tools.

Disadvantages of programming languages:

• Complexity : Some programming languages can be complex and difficult to learn, especially for beginners.
• Performance : Programs written in high-level programming languages can run slower than programs written in lower-level languages.
• Limited Functionality : Some programming languages may not have built-in support for certain types of tasks or may require additional libraries to perform certain functions.
• Fragmentation: There are many different programming languages, which can lead to fragmentation and make it difficult to share code and collaborate with other developers.

Tips for learning new programming language:

• Start with the fundamentals : Begin by learning the basics of the language, such as syntax, data types, variables, and simple statements. This will give you a strong foundation to build upon.
• Code daily : Like any skill, the only way to get good at programming is by practicing regularly. Try to write code every day, even if it’s just a few lines.
• Work on projects : One of the best ways to learn a new language is to work on a project that interests you. It could be a simple game, a web application, or anything that allows you to apply what you’ve learned that is the most important part.
• Read the documentation : Every programming language has documentation that explains its features, syntax, and best practices. Make sure to read it thoroughly to get a better understanding of the language.
• Join online communities : There are many online communities dedicated to programming languages, where you can ask questions, share your code, and get feedback. Joining these communities can help you learn faster and make connections with other developers.
• Learn from others : Find a mentor or someone who is experienced in the language you’re trying to learn. Ask them questions, review their code, and try to understand how they solve problems.
• Practice debugging : Debugging is an essential skill for any programmer, and you’ll need to do a lot of it when learning a new language. Make sure to practice identifying and fixing errors in your code.

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