3 items tagged "python"

  • Finding your way in programming: top 10 languages summarized

    Finding your way in programming: top 10 languages summarize

    The landscape of programming languages is rich and expanding, which can make it tricky to focus on just one or another for your career. We highlight some of the most popular languages that are modern, widely used, and come with loads of packages or libraries that will help you be more productive and efficient in your work.

    1. Python — Artificial Intelligence & Machine Learning

    • Level: Beginner
    • Popular Frameworks: Django, Flask
    • Platform: Web, Desktop
    • Popularity: #1 on PYPL Popularity Index of March 2021, #3 on Tiobe Index for March 2021, Loved by 66.7% of StackExchange developers in 2020, and wanted by 30%, the most of any language.

    Developed by Guido van Rossum in the 1990s, the multi-purpose high-level Python has grown extremely fast over the years to become one of the most popular programming languages today.

    And the number one reason for Python’s popularity is its beginner-friendliness, which allows anyone, even individuals with no programming background, to pick up Python and start creating simple programs.

    But that’s not all. It also offers an exceptionally vast collection of packages and libraries that can play a key role in reducing the ETA for your projects, along with a strong community of like-minded developers that is eager to help.

    What this language is used for — 

    Although Python can be used to build pretty much anything, it really shines when it comes to working on technologies like Artificial Intelligence, Machine Learning, Data Analytics. Python also proves to be useful for web development, creating enterprise applications, and GUIs for applications.

    Python is used in many application domains. Here’s a sampling — 


     Additional Resources:

    2. JavaScript — Rich Interactive Web Development

    • Level: Beginner
    • Popular Frameworks:React.js, Vue, Meteor
    • Platform: Web, Desktop, Frontend scripting
    • Popularity: #3 on PYPL Popularity Index of March 2021, #7 on Tiobe Index for March 2021, Loved by 58.3% of StackExchange developers in 2020, and wanted by 18.5%, the most of any language.

    JavaScript was one of the key programming languages alongside HTML and CSS that helped build the internet. JavaScript was created in 1995 by Netscape, the company that released the famous Netscape Navigator browser, to eliminate the crudeness of static web pages and add a pinch of dynamic behavior to them.

    Today, JavaScript has become a high-level multi-paradigm programming language that serves as the world’s top frontend programming language for the web, handling all the interactions offered by the webpages, such as pop-ups, alerts, events, and many more like them.

    What this language is used for — 

    JavaScript is the perfect option if you want your app to run across a range of devices, such as smartphones, cloud, containers, micro-controllers, and on hundreds of browsers. For the server-side workloads, there’s Node.js, a proven JavaScript runtime that is being used by thousands of companies today.

    Additional Resources:

    3. Java — Enterprise Application Development

    • Level: Intermediate
    • Popular Frameworks: Spring, Hibernate, Strut
    • Platform: Web, Mobile, Desktop
    • Popularity: #2 on PYPL Popularity Index of March 2021, #2 on Tiobe Index for March 2021, Loved by 44.1% of StackExchange developers in 2020.

    Java has remained the de-facto programming language for building enterprise-grade applications for more than 20 years now.

    Created by Sun Microsystems’ James Gosling in 1995, the object-oriented programming language Java has been serving as a secure, reliable, and scalable tool for developers ever since.

    Some of the features offered by Java that make it more preferable than several other programming languages are its garbage collection capabilities, backward compatibility, platform independence via JVM, portability, and high performance.

    Java’s popularity can be seen clearly among the Fortune 500 members as 90% of them use Java to manage their business efficiently.

    What this language is used for — 

    Apart from being used to develop robust business applications, Java has also been used extensively in Android, making it a prerequisite for Android developers. Java also allows developers to create apps for a range of industries, such as banking, electronic trading, e-commerce, as well as apps for distributed computing.

    Additional Resources:

    4. R — Data Analysis

    • Level: Intermediate
    • Popular Studio: R Studio
    • Platform: Mainly desktop
    • Popularity: #7 on PYPL Popularity Index of March 2021.

    If you do any sort of data analysis or work on Machine Learning projects, the chances are that you may have heard about R. The R programming language was first released to the public in 1993 by its creators Ross Ihaka and Robert Gentleman as an implementation of the S programming language with a special focus on statistical computing and graphical modeling.

    Over the years, R became one of the best programming languages for projects requiring extensive data analysis, graphical data modeling, spatial and time-series analysis.

    R also provides great extensibility via its functions and extensions that offer a ton of specialized techniques and capabilities to developers. The language also works remarkably well with code from other programming languages, such as C, C++, Python, Java, and .NET.

    What this language is used for — 

    Apart from some of the uses mentioned above, R can be used for behavior analysis, data science, and machine learning projects that involve classification, clustering, and more.

    Additional Resources:

    5. C/C++ — Operating Systems and System Tools

    • Level: C — Intermediate to Advanced, C++ — Beginner to Intermediate
    • Popular Frameworks: MFC, .Net, Qt, KDE, GNOME
    • Platform: Mobile, Desktop, Embedded

    Believe it or not, the programming languages C/C++ were all the rage in the very late 20th century. Why?

    It’s because C and C++ are both very low-level programming languages, offering blazing fast performance, which is why they were and are still being used to develop operating systems, file systems, and other system-level applications.

    While C was released in the 70s by Dennis Ritchie, C++, an extension to C with classes and many other additions, such as object-oriented features, was released later by Bjarne Stroustrup in the mid-80s. 

    Even after close to 50 years, both the programming languages are still being used to create rock-steady and some of the fastest applications of all times.

    What this language is used for — 

    As C & C++ both offer full access to the underlying hardware, they have been used to create a wide variety of applications and platforms, such as system applications, real-time systems, IoT, embedded systems, games, cloud, containers, and more.

    Additional Resources: 

    6. Golang — Server-Side Programming

    • Level: Beginner to intermediate
    • Popular Framework: Revel, Beego
    • Platform: Cross-platform, mainly desktop
    • Popularity: Loved by 62.3% of StackExchange developers in 2020, and wanted by 17.9%, the most of any language.

    Go, or Golang, is a compiled programming language developed by the search giant Google. Created in 2009, Golang is an effort by the designers at Google to eliminate all the faults in the languages used throughout the organization and by keeping all the best features intact.

    Golang is fast and has a simple syntax, allowing anyone to pick up the programming language. It also comes with cross-platform support, making it easy and efficient to use.

    Go claims to offer a mix of high-performance like C/C++, simplicity, and usability like Python, along with efficient concurrency handling like Java.

    What this language is used for — 

    Go is primarily used in back-end technologies, cloud services, distributed networks, IoT, but it has also been used to create console utilities, GUI applications, and web applications.

    Additional Resources :

    7. C# — Application & Web Development Using .NET

    • Level: Intermediate
    • Popular Frameworks: .NET, Xamarin
    • Platform: Cross-platform, including mobile and enterprise software applications
    • Popularity: #4 on PYPL Popularity Index of March 2021, #5 on Tiobe Index for March 2021, Loved by 59.7% of StackExchange developers in 2020.

    C# was Microsoft’s approach to developing a programming language similar to the object-oriented C as part of its .NET initiative. The general-purpose multi-paradigm programming language was unveiled in 2000 by Anders Hejlsberg and has a syntax similar to C, C++, and Java. 

    This was a huge plus point for developers who were familiar with either of these languages. It also offered relatively faster compilation and execution along with seamless scalability.

    C# was designed keeping in mind the .NET ecosystem, which allows developers to access a range of libraries and frameworks offered by Microsoft. And with the integration with Windows, C# becomes extremely easy to use, even perfect for developing Windows-based apps.

    What this language is used for — 

    Developers can use C# for a range of projects, including game development, server-side programming, web development, creating web forms, mobile applications, and more. C# has also been used to develop apps for the Windows platform, specifically Windows 8 and 10.

    Additional Resources: 

    8. PHP — Web Development

    • Level: Beginner
    • Popular Frameworks: CakePHP, Larawell, Symfony, Phalcon
    • Platform: Cross-platform (desktop, mobile, web) Back-end web scripting.
    • Popularity: #6 on PYPL Popularity Index of March 2021, #8 on Tiobe Index for March 2021.

    Just like Guido van Rossum’s Python, PHP also came to fruition as a side project by Rasmus Lerdorf, with the initial development dating back to the year 1994.

    Rasmus’s version of PHP was originally intended to help him maintain his personal homepage, but over the years, the project evolved to support web forms and databases.

    Today, PHP has become a general-purpose scripting language that’s being used around the globe, primarily for server-side web development. It is fast, simple, and is platform-independent, along with a large open-source software community.

    What this language is used for — 

    A large number of companies are using PHP today to create tools like CMS (Content Management Systems), eCommerce platforms, and web applications. PHP also makes it extremely easy to create web pages in an instant.

    9. SQL — Data Management

    • Level: Beginner
    • Platform: Back-end database management
    • Popularity: #10 on Tiobe Index for March 2021, Loved by 56.6% of StackExchange developers in 2020.

    SQL, short for Structured Query Language, is probably one of the most crucial programming languages on this list.

    Designed by Donald D. Chamberlin and Raymond F. Boyce in 1974, the special-purpose programming language has played a key role in enabling developers to create and manage tables and databases for storing relational data over hundreds of thousands of data fields.

    Without SQL, organizations would have to rely on older and possibly slower methods of storing and accessing vast amounts of data. With SQL, much of these tasks can be done within seconds.

    Over the years, SQL has helped spawn a large number of RDBMS (Relational Database Management Systems) that offer much more than just the creation of tables and databases.

    What this language is used for — 

    Pretty much every other project or industry that needs to deal with large amounts of data stored in tables or databases uses SQL through an RDBMS.

    Additional Resources:

    10. Swift — For Mobile App Development on iOS

    • Level: Beginner
    • Popular Frameworks: Alamofire, RxSwift, Snapkit
    • Platform: Mobile (Apple iOS apps, specifically)
    • Popularity: #9 on PYPL Popularity Index of March 2021, Loved by 59.5% of StackExchange developers in 2020.

    Apple’s full control over its hardware and software has allowed it to deliver smooth and consistent experiences across its range of devices. And that’s where Swift comes in.

    Swift is Apple’s own programming language that was released in 2014 as a replacement for its Objective-C programming language. It is a multi-paradigm general-purpose programming language that’s extremely efficient and designed to improve developer productivity.

    Swift is a modern programming language (newest on this list), fast, powerful, and offers full interoperability with Objective-C. Over the years, Swift received numerous updates that helped it gain significant popularity among Apple’s iOS, macOS, watchOS, and tvOS platforms.

    What this language is used for — 

    Paired with Apple’s Cocoa and Cocoa Touch framework, Swift can be used to create apps for virtually every Apple device, such as iPhones, iPads, Mac, Watch, and other devices.

    Additional Resources — 


    Now let’s quickly conclude this article by giving you an insight into the importance and career growth opportunities associated with these programming languages. Every programming language has its own set of benefits, and out of all the entries, you can enter the field of your choice.

    Mastering Python can help you land one of the top 3 highest paying job roles in the industry. With Python, you can apply for Software Engineer, DevOps Engineer, Data Scientist, and can even secure job positions in the most reputed companies with a handsome package.

    You can simply opt for Quantitative Analyst, Data Visualization, Expert, Business Intelligence Expert, and Data Analyst with R.

    Regarding JavaScript, there is a high demand for Javascript developers offering a modest salary.

    But there’s no beating the efficiency of C/C++ when it comes to building system tools and operating systems as it continues to enjoy the number one spot on TIOBE’s software quality index. SQL remains one of the best programming languages to tinker around vast databases, while C# proves perfect for Windows. Swift has also been seeing a rise in popularity among developers looking to build for Apple’s hardware. As for PHP and Go, they continue to maintain a respectable position in the industry.

    So, out of the 10 programming languages, it’s totally up to you which one is your go-to choice and makes your career in. So choose wisely!

    Author: Claire D. Costa

    Source: KDnuggets

  • The Advantages of Python for Businesses  

    The Advantages of Python for Businesses

    Enterprises are making a foray into the digital realm to be a part of digitization. To set up their foot in the digital industry, they need to choose a portable, scalable, flexible, and high-level programming language for product development. One programming language that meets all their demands is Python. This general-purpose programming language has been around for decades and is still gaining strong momentum for its simplicity, platform independency, user-friendliness, GUI support, and quick development time. It comes with a slew of libraries and frameworks that offer the most practical features to enterprises to digitize their operations and supercharge business growth.

    Python has been on the list of top programming languages since its release. It grabbed the third position in the list of commonly used programming languages in a 2021 developer survey conducted by Stack Overflow. Furthermore, Python ranked first in the TIOBE Index for September 2022. This index is updated once a month and is used to check the popularity of programming languages based on the number of developers available across the globe, courses, and third-party vendors. This indicates that Python is a strong contender in developing enterprise-grade solutions. From Startups and SMBs to large enterprises including Instagram, Google, Uber, Netflix, Shopify, and more are leveraging the potential of Python to stay competitive. If you also planning to outwit your competitors in 2023, you should consider Python for AI and ML product development.

    5 Reasons Why Businesses Should Invest in Python

    1) Supports Big Data

    Data plays a significant role in the success of a business. In today’s time, enterprises are churning out large volumes of data. According to a report by IDC, the worldwide data is expected to grow by 61% and will reach 175 zettabytes by 2025. The rise in data presents an opportunity for businesses to unlock new revenue streams, drive workforce productivity, optimize operations efficiency, and do much more. Since Python supports Big Data, enterprises can use this programming language to develop BI and Analytics tools and discover patterns and insights hidden in Big Data. By extracting insights hidden in Big Data, enterprises can make actionable decisions to supercharge their business growth.

    2) Integration With IoT

    IoT is one of the emerging technologies embraced by enterprises across verticals. Last year, the number of connected IoT devices was more than 10 million and it is expected that this number will surpass 25 billion by 2025 and 41 billion by 2027. Furthermore, it is estimated that global IoT spending will grow to around 1.6 trillion by 2025. Businesses can boost their IoT capabilities since Python offers platforms like Raspberry Pi that facilitate programmers to develop enterprise-grade solutions using the concepts of IoT. In other words, integration with IoT makes Python the most preferred programming language for developing future-proof solutions that drive business growth.

    3) Promotes Test-Driven Development

    Another strong reason to consider Python for development is that it promotes test-driven development. Many Python frameworks leverage a test-driven development approach that allows developers to write the test case before they start writing codes. The reported test cases come in handy since they allow developers to test the code simultaneously resulting in quick prototype and MVP development. When starting new projects, businesses should invest in Python since creating prototypes and MVP of big projects is a complete breeze with this programming language.

    4) Data Security

    Did you know? More than 40 billion records were exposed globally last year. On average, an enterprise per year encounters 130 security breaches. What’s more alarming is that cybercrime comprising everything from data hacking to embezzlement or theft, and destruction has increased by 600%. This may be the reason why data and its security have become a key concern for enterprises both large and small alike. Fortunately, enterprises can steer clear of cyber attacks using

    5) Compatibility With Major Platforms

    Compatibility plays a crucial role when it comes to product development since it determines the user-friendliness and usability of the product. For instance, you have a business application that runs on a single platform, and when you plan to tap into other platforms, you may have to invest in building applications for other platforms from scratch. On the other hand, the code developed in Python runs across all the major platforms or Operating Systems (OS) without recompilation.

    Summing Up

    Businesses looking for a robust, secure, and functional application should consider Python since it meets all the requirements of developing a modern solution tailored to unique requirements. Furthermore, it supports a host of emerging technologies such as the Internet of Things (IoT), Big Data, Artificial Intelligence, and ML, making it a coveted choice for developing future-proof solutions to drive business growth and profitability.

    Author: Alice Gray

    Source: Datafloq

  • The Language of Data Science: Python vs R

    The Language of Data Science: Python vs R

    Python may be the second choice to R, but its popularity and ease of use positions it to dominate data science.

    “When [Netflix’s data science team] started, there was one single kind of data scientist,” says Christine Doig, director of innovation for personalized experiences at Netflix. “Now the role has been integrated into the organization.” This isn’t just a Netflix thing. Across all industries, enterprises are embracing data science to craft personalized, engaging experiences, optimize pricing, and more. As they do so, they’re expanding the use of data science into product management, marketing, and other areas.

    This is why the language that organizations use to decipher their data will increasingly be Python, not R. As organizations look to a more diverse group to help with data science, Python’s mass appeal makes for an easy on-ramp.

    R or Python?

    Historically, if you wanted to do data science, you needed to know R. As detailed on the R project’s site, “R is an integrated suite of software facilities for data manipulation, calculation, and graphical display.” It’s not really a programming language, per se, but includes one. Originally built for statistical and numerical analysis, R has remained true to those roots and remains an excellent tool, particularly for statisticians in their role as data scientists. This strength can also be a weakness, given the spread of data science well beyond the area of statistical analysis.

    It’s true, as Sheetal Kalburgi, associate product manager at Anaconda, points out, that “data scientists are more technical and statistical” and often are “responsible for tasks like developing complex statistical algorithms that communicate product performance, predict outcomes, design experiments such as A/B testing, and optimize computational operations, to name a few.” But they also tend to be well versed in programming, which is where your average data scientist is much more likely to have a programming background than a hard-core statistics background.

    Even if a company’s business problem centers on statistics, it’s still often going to be the case that Python will prove superior, if only because of familiarity. As Van Lindberg, general counsel for the Python Software Foundation told me, “Python is the second-best language for everything. R may be the best for stats, but Python is the second … and the second-best for [machine learning], web services, shell tools, and (insert use case here). If you want to do more than just stats, then Python’s breadth is an overwhelming win.”

    No one really wants the silver medal instead of gold, but in this case, second place means Python will make itself useful for a much broader array of use cases. As Peter Wang, CEO of Anaconda, said in an interview, “Python had a broader scope from the beginning.” Engineering and science DNA is “baked into the Python core.” It’s therefore going to be the right answer much more often than R.

    Python swallows data science

    That’s not a criticism of R so much as a recognition of the momentum and mass Python has going for it. According to a recent SlashData survey of more than 20,000 developers, Python is a developer darling, coming in second only to JavaScript in terms of popularity. Part of this stems from the huge community around Python that extends Python’s utility into all sorts of domains (deep learning, artificial intelligence, and more) while fine-tuning it in key areas to improve performance. It’s increasingly difficult to find any areas where Python isn’t pushing to be the first-choice option, not merely “second best,” to use Lindberg’s phrasing.

    Part of Python’s popularity stems simply from how easy it is to use. Given that enterprises are desperately trying to find data science talent, the easiest path is to mint existing employees. Even those without an engineering background find it easy to embrace Python’s simple syntax and readability and appreciate how useful it is for quick prototyping.

    Lately, Python's ease of use has gotten even easier as Anaconda released PyScript, which makes Python more accessible to front-end developers by making it possible to write Python in HTML to build web applications. This is just one more innovation in a long string of innovations in the Python community to expand the breadth and depth of what developers and data scientists can do with Python.

    Those innovations, and the Python community that benefits from them, increasingly make the decision to use Python that much easier. For areas where R or another alternative might be first choice, Wang suggests Python’s history as a great glue language means that “maybe someone will build a nice Python wrapper to expose a thin shim to expose some R capabilities” or otherwise make it easy for a data scientist to build with Python while adding complements from other communities, like R.

    All this helps explain why Python looks set to help drive the next decade of data science, given how robust it is for experienced data scientists and less-experienced aspirants.

    Author: Matt Asay

    Source: Infoworld

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