What Is The Future of Python?

 

Future of Python

Python is undoubtedly a programming language that is loved by beginners and experienced developers alike. From web development to scripting, data analysis to automation, it is ubiquitous.

It has been a relevant language and maintained a dominant position amongst the popular programming languages used worldwide. According to the TIOBE index 2021, Python is the third most popular programming language in the world.

 

What Is The Future Scope Of Python?

Python is also the fastest-growing language, with a fourfold increase ever since its beginning in 1991. Since 2012, it has risen above popular programming languages such as JavaScript and C#, C++, Java, and PHP.

Many future technologies are counting on Python due to its helpful features. Python training can open many career opportunities for you in these growing technologies.

Big Data

Handling big data is a challenging task, and Python offers a number of libraries to handle big data.  Python provides several libraries to manage big data. You can do it faster than any other programming language.

If you do a task with 200 lines of code in Java, you can do the same task in just 20 codes in Python. This is an exceptional feature, useful when working with huge datasets. Also, as there is no limitation to data in Python, you can easily process data with your laptop or desktop.

You can use Python to write Hadoop MapReduce programs and interact with HDFS using the PyDoop package. The HDFS API facilitates connection to an HDFS installation, read and write files and get seamless information on files, directories, and other file systems.

The MapReduce API helps you solve complex problems with minimal programming efforts. Additionally, Advance MapReduce concepts like ‘Record Readers’ and ‘Counters’ can be implemented in Python using the PyDoop.

Artificial Intelligence (AI)

Python surely dominates over other object-oriented programming languages in artificial intelligence. Python has plenty of libraries, frameworks, and tools that reduce human efforts and increase efficiency and accuracy.

It offers the least code, which accelerates development processes.  Some of the libraries used in machine learning are PyML, scikit-learn, PyBrain, GraphLab Create, MDP Toolkit MIPy, etc., while libraries like NumPy and SciPy are used for computing purposes. For general artificial intelligence, libraries like AIMA, pyDatalog, SimpleAI, and EasyAI are useful.

Internet Of Things (IoT)

IoT has been used across industries to streamline the process and make it efficient. Python is a scripting language preferred for IoT applications. It is ideal for the back-end and software development of devices.

You can develop codes faster in Python, as it comes integrated with numerous libraries and frameworks that support different platforms.

Python is ideal for developing device prototypes. This means even if you rewrite some of your code during production to Java. C, or C+, the system will still function in Python.

Data Science

Data science is analyzing data to find hidden meanings in it. Several programming languages are used in data science, and Python holds a special place. That’s why many data scientists prefer going for Python certification.

It is more readable and requires fewer codes. This is the reason it wins over other programming languages. The Pandas library simplifies the data analysis process.  SciPy, closely related to NumPy, offers tools and techniques for scientific data analysis. Additionally, scikit-learn and PyBrain are ML libraries that offer modules for building neural networks and data preprocessing.

Libraries like Pandas, NumPy, and Matplotlib, Seaborn, Statsmodels, SciPY, and Requests in Python make data science processes such as data cleaning, data visualization, and data visualization analysis, and machine learning easier.

Networking

Python plays a vital role in networking. It allows creating scripts for automating complex network configurations. It is used to write, read and configure switches and routers and perform networking and automation tasks securely and cost-effectively.

Some of the libraries and tools used by network engineers for automation are Ansible, Netmiko, NAPALM (Network Automation and Programmability Abstraction Layer with Multivendor Support), Junos PyEZ, Pyeapi, PySNMP, and Paramiko SSH.

Conclusion

The career opportunities related to Python have grown significantly in the past few years. Several prominent organizations such as Walt Disney Feature Animation, Google, NASA, IBM, and more are already using Python.

There are ample job options you can choose from after graduating from Python bootcamp. Formal training will give you hands-on experience and also boost your portfolio.