Python is one of the most popular programming languages compared to others. It is used in virtually in every industry and scientific field that you can imagine, like Data Science, Web Development, Game Development, etc.
Python’s functions can be carried out with simple commands and less text. In fact, it plays an essential role in our lives too; it is those invisible forces present in our mobile phones, web searches, gaming, and beyond!
Let’s have a look at What Python is and why use Python?
What is Python?
Python is a high-level, object-oriented programming language, often used to build websites and software and conduct data analysis. According to TIOBE, Python is the third most popular programming language globally.
It is an interpreted language, which means it has an interpreter to execute the program directly without depending on complicated machine languages. In fact, Van Rossum wanted Python to be as understandable and transparent as English. He also built the language as open-source; anyone can contribute to it.
Especially “Readability” is a key factor in Python’s ideology. It focuses on the words we choose and how we put them into sentences and paragraphs.
But…Why is it Called Python?
Python is named after Monty Python. Guido van Rossum read the published scripts from “Monty Python’s Flying Circus.”, so he decided to call the language Python.”
Why Use Python?
We have found reasons why Python is so popular; it is time to discuss why you should use Python. Apart from the versatility and simplicity mentioned above, there are several other good reasons to use Python
1.) Python developers are in demand:
Python developers are in demand these days because it is compatible with major platforms and systems. So if you want to start or switch careers, Python developer would be a great option.
2.) Well-paid career:
The average annual salary of a Python developer is $119,861 or $61.47 per hour.
3.) Many job opportunities:
Python can be used in many growing technologies in particular AI, machine learning, etc., which is a future-proof skill.
4.) Python gives you tested scalability:
You cannot predict when your number of users increases, and scalability will become a priority. That’s why it is good to use a language that scales great and is easy to maintain.
Why Python, then? There are a few reasons:
- With its robust standard library it will help you write your code faster;
- You can gain access to the Python libraries and frameworks, so you won’t have to build everything from scratch;
- Readable and Maintainable Code. You can review your code more efficiently with a simple and straightforward language.
Advantages of Python
Now we are going to discuss some of the advantages of the Python language:
Easy to Learn
Python is a very simple programming language whose syntax is English-like which makes it easier to read and learn the code.
Due to the simplicity of this language, developers can focus on solving the problem. They don’t need to spend their time understanding the syntax.
Python directly executes the code line by line. So if an error occurs, it stops and reports back the error.
Without running the code, Python doesn’t know the variable. It automatically assigns the data type during execution.
Python Applications & Real World Uses
Of course, Python is a most liked and in-demand skill to learn. But what is Python used for?
Python can be used in many fields, for instance:
- AI and machine learning
- Data analytics
- Web Development
- Data Science
- Data Engineering
Let’s take a look at some of the real ways you can use Python.
#1. Python for Web Development
Python is used to develop the back-end of a website or application, the parts that a user doesn’t see. Furthermore, its role in web development can include sending data to and from servers, processing data and communicating with databases, URL routing, and ensuring cyber security.
Python offers various frameworks for web development including Flask and Django.
Some web development jobs are back-end engineers, full-stack engineers, Python developers, software engineers, and DevOps engineers.
#2. Python for IoT
These days many developers prefer the Python language over other languages. In the Internet of Things (IoT), Python is an excellent choice for both the back end and development side. Moreover, Python helps you reduce the volume of data accessible in the cloud, and it is a great ally to develop device prototypes.
Python for IoT is accessible to code, syntax similar to the English language; prototyping is rapid, easy integration with other languages.
#3. Python for Machine Learning
Now machine learning improves business growth by performing many commonplace tasks. And all thanks to programming languages like Python. The benefits of Python for machine learning are its simplicity and consistency. Thus implementing Machine learning algorithms can be tricky and requires a lot of time.
It requires well-structured coding solutions. In fact, programmers turned to Python frameworks and libraries to reduce development time. Python has a substantial set of libraries for Machine learning like Keras, TensorFlow, and SciKit-learn.
#4. Python for data analysis
One of the most extensive uses of Python is to analyze data. A data analyst uses programming tools to mine large amounts of complex data and find relevant information from this data.
Data Analysis libraries are Pandas DataFrames, Numpy multidimensional arrays, and SciPy to work with various datasets. Moreover, Python helps prepare data for analysis, perform simple statistical analysis, create meaningful data visualizations, predict future trends from data, import data sets, clean Manipulate pandas DataFrame and Summarize data.
#5. Python for Fintech
Python is a great choice for startups and offers several benefits for entrepreneurs irrespective of the industry they are involved in. As a matter of fact, the Python talent pool available to Fintech ventures is growing day by day. Approximately 73% of the Stack Overflow Survey respondents claimed to love Python.
By using the Python/Django combination, you get to implement the specific ready-made components quickly and adjust your FinTech MVP to its users’ needs.
Creating a financial service is quite complicated, so the more transparent the programming language, the better it is for both the startup owner and the development team.
#6. Python for Data Science
As we know that many programming languages provide the much-needed options to execute Data Science jobs, it has become challenging to handpick a particular language. As we can see that Python’s rise in the share over 2015 rose by 51%, showing its impact as a popular Data Science tool.
Python’s readability, scalability, and flexibility to data science operations have made it one of the most suitable languages among developers.
Python’s data science tasks are conducting data mining, carrying out machine learning algorithms, and possessing designated libraries for data preservation and preprocessing.
With a Python data visualization library, you can create a wide range of plots and visual representations, such as:
- Lines, Bars, and Markers.
- Subplots, axes, and figures.
- Statistics (Box Plots, Bar Charts, and Histograms).
- Pie and polar charts
- Images, contours, and fields.
- 3D Plots.
#7. Python for Finance
Python is increasingly being utilized in finance, often in quantitative and qualitative analysis areas. Though it can be a precious tool in determining asset price trends and predictions and automating workflows across various data sources.
As we know already, Python is a perfect tool for working with extensive data collection, and there are various libraries available to assist with compiling and processing information. Because of these reasons, it’s one of the preferred languages in the finance industry.
#8. Python for Data Engineering
Python is an interpreted object-oriented, high-level programming language that is becoming more popular for Data Engineering. The use of this language in Data Engineering is required to create Data pipelines, perform an in-depth analysis and set up Statistical Models.
Python for Data Engineering mainly comprises Data wrangling like reshaping, joining discrete sources, aggregating, and API interaction.
Many teams use Python in Data Engineering instead of ETL tools, so the knowledge of core programming languages like Python is a must.
#9. Python for AI
This is the most dynamic language in contrast to all other programming languages, and it has so many libraries, making it one of the best languages for AI. Python, together with NumPy, sci-kit-learn, and iPython, forms the basis for starting your AI project.
In fact, Python is the most favorite language among data scientists. Between C++ and Python, Python has more edge and is more suitable for AI due to its simple syntax and readability promoting the rapid testing of complex machine learning algorithms.
In Python, almost every idea can be fastly validated through 20-30 lines of code. Therefore it is a pretty helpful language for AI.
#10. Python for Data Analytics
Data Analytics is a rapidly developing field that utilizes Python programming. One of the main reasons for using Python for data analytics is that it provides a wide range of libraries including NumPy, Pandas, SciPy, and Scikit-Learn. The language is easy to learn, scalable and flexible; it has broad community support to solve problems.
Python for Data Analytics helps to create and manage data structures quickly. For example, Panda offers many tools to manipulate, analyze and even represent data structures and complex datasets.
Python projects for beginners
We have mentioned some Python project ideas for beginners. These can help you develop your knowledge and challenge your abilities with Python:
- Create an image slider
- create a loan calculator
- Build a Digital clock
- Music player
- Converting text to speech program
Once you become an expert in the basics of Python, each of these can challenge you and help you sharpen the skills you’ve already learned.
Also Read:- Best IDE for Python Development
Frequently asked questions (FAQ) Related to Python
Should I learn Python 3 or Python 2?
Python 3 is preferable over Python 2. According to the survey conducted by JetBrains, 93% of the Python users worked with Python 3.
How much time is required to learn Python?
Due to its simplicity, it is possible to learn the basics of Python in a few weeks. Many courses are available online, which takes 7-8 weeks to complete the whole course with a few hours of learning each week.
Why is Python the best choice for Startup?
There are various reasons why Python is a preferred language for startups. To name a few, it’s because the language is:
- cutting edge,
In conclusion, Python has become a popular choice among numerous organizations with a vast support network and a diverse range of libraries.
It lets you optimize your development resources by writing code faster, has a clear and simple syntax, and offers extensive support from various tutorials and guides used by tech giants like Google, YouTube, or Reddit; there’s no reason why you shouldn’t do the same.
If you want to hire a Python programmer, contact us at Invedus, one of the leading python companies in India.