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Python is a high-level, interpreted, and general-purpose programming language that emphasizes readable codes. The Python syntax is designed to help programmers to complete coding projects in as few steps as possible, especially when compared to other languages like C++ and Java.
It was founded in 1991 by Guido Van Rossum. The language has undergone a lot of changes since it was first released with many add-ons already developed.
Python is a programming language that has steadily grown in popularity over the last few years. According to this survey, it is the second-most preferred language for developers.
Some of the main reasons for its dominance include the multipurpose nature and ease of use. It is no surprise that it is the language of choice in data science and machine learning.
Established developers around the world are deploying Python across various projects, while new developers are increasingly learning the language to get through the front door in the job market.
However, the language isn’t without its downsides. This piece takes a look at some of the advantages and disadvantages of Python.
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Table of Contents
Let us look into the advantages of Python first. Below listed are the top pros on why to choose Python as your preferred programming language.
Python comes with an extensive library. There is code for a wide range of purposes including unit-testing, web browsers, threading, databases, CGI, documentation generation, and more.
This ensures that programmers won’t have to write complete codes from scratch for everything.
Python can be extended to other popular programming languages easily.
This advantage is felt more when working on projects that will require extension with languages such as C or C++.
It is easy to add Python code into the source code of a different language (for example, C++).
With this feature, developers can include scripting capabilities in the codes of other languages.
In addition to being extensible, the embeddable feature of Python makes it a really flexible language.
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Python’s simplicity and its extensive libraries mean that programmers are more productive when using it, compared to other languages such as Java and C++.
The libraries mean programmers can focus more on writing codes that are relevant to the project only.
As the world moves deeper into the Internet of Things, the Python language will become more relevant.
It is already the language on the Raspberry Pi, and its peculiarities will help it become a powerful driver of the interconnected world where we are headed.
Python is easy to learn and code. This is why experts will advise against starting with it before moving to other languages like Java—the transition will be harder.
In Python, printing a “Hello World” only requires a print statement.
In Java, on the other hand, you have to create a class first. If you already know Java and other similar languages, Python will be super easy.
The simplicity of the language is why it is a popular option for prototyping.
Since Python is not verbose, reading it is as simple as reading a normal language. It is why it is easy to understand.
Indentation is mandatory, and blocks are not defined by curly braces—making the code easy to read.
Due to the explicit syntax that allows code to be more readable, Python’s codebase is more maintainable than those completed in other languages.
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Python is free to download, and the source code is available to everyone.
You can make changes to the source code and distribute it as you wish. The extensive collection of libraries is included in the download to simplify your tasks.
The open-source nature of the language means it is constantly getting better with each passing year as many people contribute towards fixing obvious flaws and launching new functions.
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As long as you don’t include any system-dependent features, you can easily port your Python code to another platform.
With other programming languages like C++, for example, you have to make some changes before it can run elsewhere.
Python is an interpreted language because statements are executed one by one. This makes debugging easier, in comparison to compiled languages.
The Python language is in use across a wide spectrum.
You’ll find it in use for web, mobile app, frontend, and back end development. It can be used in both object-oriented and functional programming.
Its versatility doesn’t end in software development either. It is also a great scripting language for people who only need to use scripts to solve specific challenges instead of fully developing software.
Python is also a popular language in data science and machine learning. This is because of its robust and mature libraries which allow engineers that deal with data to produce results faster. Some of Python’s popular libraries include Pandas, Keras, Scikit-learn, and more.
Across universities, Python is gradually becoming the preferred language for teaching programming basics to students, thanks to its ease of learning and use.
New programmers find it easier to get started on Python.
The simplicity of the language has also helped many people to find their way into development, completely self-taught.
The community of programmers using Python is one of the most inclusive in the industry.
This means that newcomers are never alone. Answers to most questions can be found in developer forums, and there are tons of expert blogs online that are solely dedicated to helping people to widen their knowledge of the language and become super-proficient in it.
Over the last few years, Python has grown into the language of choice for large projects and python apps by brands like Dropbox, YouTube, Yahoo, and Google
Companies in other sectors, such as healthcare, education, and finance, are not left behind.
There is no denying the fact that the language is now very mature.
Although Python has a lot of advantages, it is not without its downsides. Some of the disadvantages of Python programming are covered below:
Python code is executed line by line.
As an interpreted language, this leads to slower execution. This limitation can be ignored except when the speed of execution is a top priority in a project.
If the project has a friendly timeline, the limited speed won’t be a major concern.
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Since Python is dynamically-typed, programmers don’t need to declare the type of variable while writing the code.
It helps simplify the coding process for programmers, but it can lead to run-time errors.
In machine learning and data science, this is a big problem because type error can make working with data a lot more difficult than it should be.
This is why some programmers prefer to use statically typed language.
Python consumes a lot of memory.
During projects, memory consumption has to be tracked very carefully.
Following the best coding practices will make it easier to avoid potential memory-related problems.
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Python’s multithreading model doesn’t really have multiple threads running at the same time as a result of the global interpreter lock (GIL). One thread can only hold the GIL at one time.
This makes it impossible to truly achieve multithreading with the standard Python.
Programmers that want multithreading while working with Python use different implementations such as a C extension, PyPy, IronPython, and Jython.
Python’s functional programming can be difficult to read.
This is because the compiler doesn’t support functional optimizations.
It also lacks some basic features of functional programming that has to be implemented manually.
This defeats the entire purpose of using the language for its ease of use and simplicity.
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Deciding on the first programming language to get started on is an interesting process.
However, it is not a decision you should take lightly.
It will generally take hundreds of hours to practice and become competent in any language you choose. So you need to ensure you are making the best possible decision.
The top factors you should keep in mind include:
Python and Java are popular options for a first language, but there for many people, there is an even better third option to consider—JavaScript.
It ticks the four boxes we have mentioned above, and it is the perfect middle ground that bridges the learning differences between Java and Python.
This is not to say that it is better than other languages, but it is the number one skill hiring managers want to see today.
When you have mastered JavaScript, you can move to Java and then Python.
Python is last in this recommendation because of its simplicity.
As we stated above, learning Java after you have learned JavaScript and Python is a lot more difficult. So this is the right progression for most people. However, your situation might be slightly different.
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