Python is a high-level, interpreted, and versatile, dynamic programming language that focuses on code readability. Python syntax helps programmers write code in fewer steps than Java or C ++. The language, founded in 1991 by developer Guido Van Rossum has easy and fun programming to do. Python is widely used in large organizations due to its multiple programming paradigms. They generally involve imperative and object-oriented functional programming. It has an extensive and complete standard library that has automatic management of memory and dynamic resources.
There is a multitude of programming languages used for application development around the world. Each has its specific characteristics, as well as its advantages and disadvantages. One of the most popular programming languages today is Python. Do you know what Python is? Python has become one of the few languages relevant to the present and great potential for the future. Since its inception in 1991 by a developer named Guido Van Rossum, Python’s reach has grown day by day, with several multinationals using it in their application development businesses.
While this says a lot, Python has some drawbacks, often leading app developers to prefer other languages. Through this article, we intend to highlight the ups and downs of Python development so that you can evaluate whether or not you want to use it in your next project.
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As an advanced programming language, Python is used in the development of high-level applications such as:
- Web Server Programming: Developers can perform server-side programming via Python libraries, such as Django and Flask.
- Prototyping: Using Python, developers can create rapid prototypes to present to the customer.
- Game Development: It is widely used in game development, including the GUI, via libraries such as PyGame.
Why do companies prefer Python?
Python has been at the top of the charts in recent years compared to other programming languages such as C, C ++, and Java and is widely used by programmers. The language has undergone a radical change since its launch 25 years ago, introducing many additional features. Python 1.0 had the Modula-3 modular system and interacted with the Amoeba operating system with different working tools. Python 2.0, introduced in 2000, had garbage collection capabilities and Unicode support. Python 3.0, introduced in 2008, had a constructive design that avoids duplication of modules and constructs. With the added features, businesses are now using Python 3.5.
Software development companies prefer the Python language due to its versatile functionality and small programming code. Almost 14% of programmers use it on operating systems such as UNIX, Linux, Windows, and Mac OS.
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Benefits of using Python
There is a reason why developers choose to write code in Python. It has some unique features that make programming a lot easier. Let’s take a look at some features that allow you to work with the advantages of Python:
- Easy to read and learn
Python is easy to read and understand the language. It doesn’t have complex syntax like other high-level languages, like C or C ++. With less complexity, Python allows you to think more clearly and focus on building your logic.
- Reduces maintenance costs
Due to its simplicity, Python simplifies application maintenance and reduces the costs involved, which is a big plus.
- Avoid damage due to software bugs
Python does not allow a code bug to trigger a segmentation error in the application. Therefore, it is considered a preferred language.
- Memory management
Python has an extensive library with memory management capabilities, which sets it apart from other programming languages. It includes a private heap that contains all Python objects and data structures, and a built-in memory manager to keep this heap confidential.
- Quick and easy
The Python community provides quick and convenient user support as well as rapid code adaptation. Some experts like to give Python the nickname “outside the box language” because it only requires simple code to run. Improving and testing code is much more comfortable with Python.
- Asynchronous coding
Asynchronous coding uses a single cycle of events to complete a task at small intervals. It is also beneficial for writing asynchronous code because it is easy to write and maintain. It does not require any complex search constraints, dead ends, or any other complexity.
- Integration with other languages
Python has libraries such as Cython and Jython, which allow integration with other languages such as C, C ++, and Java to enable cross-platform development. This is one of Python’s main advantages because no language is perfect, and sometimes development requires more linguistic features that are not possible in a language.
- Integration of business applications
It facilitates web application development by calling CORBA or COM components and making direct calls to and from Java / C ++ / C. Also, it offers reliable process control features and Internet data formats and protocols. Additionally, Python helps users process markup languages such as XL, executes the same byte code on advanced operating systems, and can be used as a scripting language.
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Disadvantages of Python
Python has several advantageous features, and programmers prefer this language over other programming languages because it is easy to learn and even program. However, this language has yet to find its way into some IT arenas that include business development stores. Therefore, this language may not address some of the business solutions, and limitations include:
- Slow execution speed
Python is an interpreted language, which means it works with an interpreter, not a compiler. Its execution is relatively slower than C, C ++, Java, and many other languages.
- High memory consumption
Python frameworks require more memory space. This language is not suitable for development with limited memory constraints.
- Not suitable for game development and mobile devices
Python is mainly used in desktop and web server development. It is not considered ideal for developing mobile applications and games due to more memory consumption and its slow processing speed compared to other programming languages.
- Developer restrictions
Once the developer gets used to this language’s ease and simplicity, it becomes difficult for him to go back to other languages.
- Error detection in codes
Since Python works via an interpreter rather than a compiler, errors and bugs cannot be detected during compilation, which is not a good thing for developers.
- Access to the database
Python is considered highly insecure and poses a security risk. There are some limitations when using Python to access databases. Compared to other popular technologies, such as JDBC and ODBC, the Python database access layer is somewhat underdeveloped and primitive. Therefore, it is not considered appropriate if developers are looking for a smooth interaction between complex legacy data.
- Design restrictions
One of the big problems with Python is the design constraints. The reason behind this restriction is that Python is dynamically typed.
- Difficult to test
Since it is an interpreter-based language, it isn’t easy to test code written in Python. All errors and bugs only appear at runtime, making it very difficult to test snippets written in Python.
Reasons for the popularity of Python
The main reason python has managed to grab the attention of programmers is because it is packed with features that make it to a new level. It is effortless and easy to read and write. As a result, the programmer can easily program without worrying about any confusion. Google, one of the largest search engines, depends on Python to code and run. To be clear, below are some features of Python that make it unique.
Yes, the best part about Python is that it is an open-source language that makes it very popular and available, among other things. Furthermore, the open-source codes can be used by anyone publicly on the net. It is also easy to work on the code or even modify it as needed.
- Rich and caring community
If you are an encoder, you should know that not all languages support the system. This is the most significant code concern that makes Python reliable. There is a language that makes it difficult for programmers to document the entire project, which brings us back to one of the main problems. Building a project can be too overwhelming when it comes to another programming language.
However, when choosing Python, there are no problems that can interrupt the process. The best part is that Python has been governing for so many years that getting the tutorial easy. Also, several guides and documents are available online and offline, making it easier for new programmers to manage.
The best part is that it has a rich and active community of programmers working to provide developer support. Plus, there’s no limit to helping the city, which makes it even more popular. So you can do it easily if you are new to the community.
- Multi-platform language
Another of Python’s best features is that it is incredibly diverse when it comes to the operating system. Put merely, and Python can be used for operating systems, such as Linus, Windows, Ubuntu, etc. So, you can quickly run the software without worrying about system support. It can be interpreted in the language using a portable resource, which makes its use advantageous. In summary, write code on the Mac platform and run smoothly on Windows too. You don’t need to write a multilingual code with it.
Once the resources and reasons for using Python are exact, let’s move on to the future of Python. There is no doubt that Python has managed to surpass other languages that take it to the top. Therefore, it has a wide range of opportunities that can be solved in the future. It has increased over time and increased by 45% in a few years. Several companies rely on Python developers to improve the user experience.
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What is Python for?
- Web development
Big websites and platforms like YouTube and Google rely heavily on Python for their critical infrastructure. This has further enhanced its reputation as a solid component of the web developer’s toolkit.
Yes, you can learn how to build a quality Python graphical user interface (GUI) calculator with this tutorial. It’s a great introduction to GUI programming and a solid Python project for beginners. Keep in mind that it will be helpful to have some coding experience before trying.
3. Operating systems
You heard right: Python is so robust that it can be used to build entire operating systems. The object-oriented design of this programming language makes it easy to manage large projects. Therefore, it is entirely reasonable to try such a difficult task with Python. While building an operating system isn’t usually a popular activity for Python, we thought it was worth mentioning.
And speaking of operating systems, Python is compatible with pretty much all of them! This means you can build native apps for Windows and Mac computers with it.
4. Desktop applications
As mentioned above, Python is an excellent choice for desktop applications with a GUI. The standard Python library contains tools for quickly working on simple desktop GUI applications.
Popular apps like Dropbox and BitTorrent are written primarily in Python, so it’s a proven language for this category of software engineering. This is what has attracted so many talents for Python programming. You can create something big and complicated, like Dropbox, with just one language. This means that a lot of frustration is removed from the development process.
5. Artificial intelligence and Machine learning
Artificial intelligence and machine learning have become buzzwords today, but the truth is that it all comes down to algorithms, code, and logic. Considering Python’s scope and power, it’s no surprise that there are some genuinely world-class tools for generating intelligent behavior in Python.
Arguably the most popular is the ubiquitous machine learning library, Scikit-Learn. Speaking from experience, Sklearn makes the process of building everything from classifiers to size regression models easier than it would otherwise be.
If neural networks are busier, there’s always TensorFlow. By adding the new Keras API, building a next-generation neural network is easier than ever.
6. Data science
Whether you’re doing direct data analysis or full data science, it would be hard to find a better toolset than Python.
The Pandas library is a quantum leap over the dusty Excel spreadsheets where financial analysis has been running for so long. If Panda isn’t fast enough for you, most basic vector operations can be done with NumPy. Numpy also offers the ability to do linear algebra, scientific calculus, and a host of other highly technical things. It is, therefore, a great tool to learn how to use it well.
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