Why I Python a great language for Software Robots

There is no question that Python as a programming language is very impressive in 2021 and beyond.  The use of Python as a language has grown incredibly fast, despite it’s low runtime latencies compared to compiled languages like C++ .  The technical innovation and human like syntax behind the language that allows developer to write logical and maintainable code in significantly less lines makes it to be considered one of the top programming languages.  But what exactly makes Python a popular programming language, especially for mission critical software robots.

Python has impressive corporate sponsors

So, while C# has Microsoft, and PHP has Facebook, Python has Google in its corner which adopted the language in 2006 and commonly use Python for much of their internal tooling, software automation, and even entire back end servers using it. In addition to Google’s heavy use of Python there are other huge website using the Python Django framework such as Spotify, Pinterest, Instagram, DropBox, and Google’s own YouTube.

Ease of Use

Python continues to impress its new users and entry-level programmers with ease of functions.  The language is rated as one of the most accessible programming languages because it has a simplified syntax, which is rarely complicated, and emphasizes natural language.  Following the ease of learning and usage, python codes are simply written and have quick execution time when compared to other interpreted languages. It also gives an edge of experimentation via the simplicity of refactoring a Python code base.   This may be due to its developer’s general-purpose language design where code leads to self documenting itself through intuitive and elegant logic elements.

Many people can even learn the core Python principles within a week or two of studying the language through free YouTube tutorial playlists. Then after learning Python well enough many people can even start making money from home with their new skills quicker than learning programming concepts in more challenging languages.


Multi-purpose programming languages are quite more popular than limited-applicable ones.  Python is bound to be popular with multiple applications across different fields. Some of the fields include Data science, web development, systems automation and administration, mapping and geography, mathematical computing, finance and trading, game development, and application scripting.

Impressive Python Libraries

With its excellent libraries that are able to boost development, Python follows core programming principles of “don’t repeat yourself” by exposing many rich features that developers can reuse in their own programs.  It has a host of programs and platforms that users can browse through using the “PIP” dependency management tool. While many people are grateful that Python is a very simple language to understand what they should actually be grateful for is the extensive libraries that are being created as a result of Python being simple to learn and work with.

Some of my favourite industry standard libraries are listed below:

  • SciPy – engineering applications
  • Scikit – Machine Learning applications
  • Numpy – Powerful matrix library
  • Matlab – can create such quality figures that are really good for publication
  • Pandas – Data frame library
  • Beautiful Soup – HTML parsing and web scraping
  • Django – Web development framework
  • Flask – Web application micro framework.
  • SQL Alchemy – Library for creating Domain Object Models that can interact with relational databases such as MySQL and Postgres
  • Tensor Flow – Used for making production quality machine learning applications


Flexibility is a core principle that developers opt for in a programming language.  With zero restrictions and dynamic variable typing, there is plenty of room for users to manoeuvrer the language in a way that works best for them while developing any application.  This freedom is not guaranteed with other languages. So, if for nothing else, Python is known for this feature. This can also lead to bad coding practices if used too carelessly by newer developers that don’t take care to structure their code well as an application’s code base grows larger.

Big Data, Machine Learning, and Cloud Computing

These three aspects of computer programming are the hottest trends at the moment.  That is because they would be getting to use more trusting, reliable, and efficient computing methodologies to improve their operations.  Python is the second-most-popular tool, following R language when it comes to data science and analytics.

However, most of the workloads in different organizations are powered only by Python.  The research and development processes in some organizations are also powered by python language due to the ease of analysis and usable data organization. Libraries that support such operations include Boto3 for interacting with AWS cloud infrastructure, OpenCV for computer vision, and TensorFlow for neural network training in machine learning applications.

Software Automation

There is no denying that automation is a big deal and to some an ice breaker into coding. Programming languages make software running more effective and efficient to run. It runs automation by using simple software frameworks and tasks, all of which can be done without being overly-dependent on humans.  Python’s simplicity allows developers improved ability to create automation code, thus, making it popular for that purpose and is a part of most developers toolkits.


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