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Pros and Cons of Python Programming Language
| Pros | Cons |
| Beginner-friendly | Issues with design |
| Large Community | Slower than compiled languages |
| Flexible and Extensible | Security |
| Extensive Libraries | Work Environment |
| Embeddable | High memory consumption |
| Highly Scalable | Dynamically-typed language |
| IoT Opportunities | Complex multithreading |
| Portable | Garbage collection leads to potential memory losses |
Pros of Python
1. Beginner-Friendly
Python is an excellent platform for beginners who want to step into coding. This programming language is easy to learn, understand and code as it does not include too many technicalities.
Even the developers who are new to coding and do not have experience in it find it beginner-friendly. It is a verbose language because reading python is very similar to reading English.
The language does not need curly braces to define the blocks deep into the technicalities. However, indentation is mandatory, which further aids in the readability of code.
2. Large Community
The Python community boasts many coders, developers, professionals, and students on the same platform, helping one another and bringing the best out of it.
This feature makes Python one of the best platforms for developers as they can seek help from experienced and knowledgeable developers.
3. Flexible and Extensible
Python is extremely flexible and can be extended to other languages. Developers can write code in C and C++ and build new features in the dynamically-typed language.
4. Extensive Libraries
Python features an extensive set of libraries and contains code for various purposes like documentation-generation, regular expressions, web-browsers, unit-testing, CGI, databases, image manipulation, etc. Hence, it eliminates the need to write the complete code manually.
5. Embeddable
Python is extensible, and most of its codes can even be written in other languages such as C++. This lets us add scripting capabilities to our code in the other language.
6. Highly Scalable
Python is scalable, and many apps are in the market to prove it. Instagram and Pinterest are two of the most popular apps, receiving millions of user requests successfully.
Instagram, Pinterest, and Facebook are some of the most popular applications in everyday use that outshine the power of Python.
7. IOT Opportunities
Since Python forms the basis of new platforms like Raspberry Pi, it finds the future bright for the Internet Of Things.
Python is a way to connect the language with the real world. With Python and Raspberry Pi, the future for IoT is bright. Raspberry is a popular device used to integrate IoT technologies into real-world applications.
8. Machine Learning
Python is an excellent choice when your business needs web projects to be integrated with Machine Learning algorithms. Web Projects that require Python use it because it provides rich libraries, making it easier for the developers to work with data.
9. Portable
Python is portable, which means it can be run on any other platform. Here, you need to code only once, and you can run it anywhere. This is called WORA (Write Once Run Anywhere). This makes it easier for the developers to work with Python as they do not need to make changes to it in case they want to run it on another platform.
Cons of Python
While Python is a versatile language and offers many benefits, it also comes with a set of advantages. Have a look at some of the drawbacks of Python.
1. Issues with Design
Python developers sometimes have to deal with complicated designs. Therefore, highly efficient and experienced developers are preferred over beginners.
2. Slower than Compiled Languages
Python is slow compared to other non-compiled languages as it requires a lot of computational power. So, this is the thing that you need to look at before choosing Python.
3. Security
Python is not 100% secure. You need to take the necessary steps to ensure the code’s security. However, performing the right QA testing can fix this concern.
4. Work Environment
Before working with Python, you must set up a work environment. Many trouble can arise while setting up the environment, affecting beginners’ programming experience.
So, it would be better to go for Python IDEs and set up the environment with the help of official guides.
5. Python’s Memory Consumption and Garbage Collection
Python language comes with high memory usage, and the high memory consumption should be tackled carefully during the project. It uses reference counting in its garbage collection, which often leads to potential memory losses.
6. Python is Dynamically Typed
Developers working in Data Science and Machine Learning projects prefer statically-typed language over dynamically typed language. The reason is that the statically typed language potentially minimizes a lot of errors and bugs in the system.
7. Multithreading in Python
Multithreading in Python is not exactly true multithreading due to its global interpreter lock (GIL). The multithreading model in Python does not have threads that run at the same time. Here, one thread can hold the GIL at one time, which clearly implies that this is not the exact multithreading.
Python developers need to use a different implementation of Python such as Jython, IronPython, PyPy, or C extension to achieve true multithreading.
The Cons of Using Python for Web Applications
Despite Python’s advantages, it also has downsides you should keep in mind if you’re considering using this language for your project.
Fewer Seasoned Developers
When you need to have an app created for you, you certainly want the most experienced developers to do the job. However, it’s not so simple with Python, since not many expert programmers are working with this language, especially when you compare it to Java.
Lack of True Multiprocessor Support
Multiprocessing is an important part of writing an application. Python does support multiprocessing, although it might not be as flexible or convenient as other languages. This can create certain limitations when you’re writing the code.
Speed Limitations
Python is often criticized for its speed. It is an interpreted script language, which makes it relatively slower than a lot of its compiled counterparts, such as C/C++ or Java, due to the different methods it uses to translate code. Yet, some Python benchmarks work faster than those of C and C++.
That being said, Python is not the only one with potential speed problems. Ruby, Perl, and even JavaScript are on the slower end of the scale as well.
Some issues connected to speed have been addressed and optimized, so Python remains one of the top choices of software development teams.
Not the Go-To Language for Mobile App Development
It’s not a bad language for mobile development. It’s just that few companies use it for that purpose, preferring native development for iOS and Android or React Native development. You’ll probably have a hard time recruiting developers with experience in Python mobile development, too, for the same reason. It’s just not as popular as other technologies in this sphere.
Need native or cross-platform mobile apps?Hire a reliable technical partner.
Not Ideal for Memory-Intensive Tasks
Python is a language known for the flexibility of its data types. This results in fairly high memory consumption and makes it inconvenient to use for memory-intensive tasks.
Design Restrictions
Python is dynamically typed, meaning that it executes certain tasks during app runtime that would otherwise be completed in a statically typed language. This puts some restrictions on the design. If your design is loaded with elements, it might stall the program and prevent smooth operation.
Another thing you should be aware of when considering Python for your project is that concurrency and parallelism aren’t intended for elegant use in Python. Because of that, the design might not look as sophisticated as you’d like
Applications of Python
Python is a general-purpose programming language that can be used for many different types of applications-including web development, Data Analysis, Machine Learning, Artificial Intelligence, Natural Language Processing, Computer Vision & Robotics, Game Programming, Scientific Research, and more!
1. Web Development
Python can be utilized to make web applications at a fast rate. Why would that be? It is a direct result of the structures Python uses to make these applications. There is the common-backend rationale that goes into making these structures and various libraries that can assist with incorporating conventions like HTTPS, FTP, SSL, and so on, and even help in the processing of JSON, XML, E-Mail, and more!
Probably the most notable web development frameworks are Django, Flask, Pyramid. The security, versatility, accommodation that frameworks provide is commendable if we compare it to beginning the development of a website from level zero.
2. Game Development
The development of interactive games is done using Python. There are libraries such as PySoy, which is a 3D game engine that supports Python 3, and PyGame, which provides a library for game development. Games, for example, Civilization-IV, Disney’s Toontown Online, Vega Strike, and so on have been fabricated utilizing Python.
3. Machine Learning and Artificial Intelligence
Machine Learning Artificial Intelligence is currently the raging technological phenomenon as they yield the most encouraging professions for what’s to come. We use the data stored or better to make the computer learn from its past experiences, and then we use certain algorithms to create new software that makes it learn by itself. The programming language that for the most part, everybody picks? It’s Python. Why? Backing for these areas with the libraries that exist currently like Pandas, Scikit-Learn, NumPy thus some more.
Learn the algorithm, employ the Python library, and voila! you have your solution to the problem at hand. However, assuming you need to go the bad-to-the-bone way, you can formulate your own code which yields a superior arrangement, which actually is a lot simpler when we contrast it with other languages.
4. Data Sciences
Data is money if you know how to use it to increase profits and take calculated risks, and one thing that sets apart Python from other languages is the fact that it offers a lot of built-in functions and tools that make life easier for developers. These include NumPy, Pandas, Matplotlib, SciPy, etc.
All these packages help programmers perform various tasks faster than they would otherwise do so. Various libraries frequently used for data analysis are- Pandas, NumPy, Matplotlib, and Seaborn. Common data science tasks such as data cleaning, exploratory data analysis, and feature engineering can be solved with those libraries.
Matplotlib, Seaborn, and many other data libraries are helpful in plotting graphs, and if you want to become a Data Scientist, this is the amazing array of benefits that Python has to offer.
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