Lean Code – Python 3

Performance Matters

Python is a very popular programming language that can be used to create a vast array of diverse applications.  As a scripting language, Python applications do not execute as quickly as those that are compiled from languages such as C or C++.

If C or C++ are so much faster then why focus on Python at all?  The ability to quickly code applications in a relatively short period of time is only part of the appeal of Python.  Community support and a rapidly growing number of modules or packages greatly eases the ability to incorporate features that would otherwise be difficult or extremely time consuming to code in other languages.

Developing a “proof of concept” in a short period of time using Python provides the opportunity to present and discuss application capabilities or other functionality and features with a customer before committing to hard code in another language.  This also provides an opportunity to demonstrate your understanding of the customer’s requirements.

There may even be times where a customer is quite content with a program written solely in Python and these occasions are increasingly common!  Certainly Python applications can be supplemented with packages specifically created to address performance critical tasks.

At present, Python is in a transient state between version 2.7.13 and 3.6.2.  If you’re new to Python, I recommend learning version 3.  The reason for this is simple:  Performance.  Steven Lott’s article titled “Python 3.5 and the Upgrade Strategy” provides a compelling list of reasons to consider upgrading to Python 3 for those who are still using the legacy version 2.

Python.org’s “The Python Tutorial” makes getting started in Python fast and easy.  Python is not a difficult language to learn, however, as mentioned many times before, the performance of your application is as dependent on the programmer’s skill and knowledge as it is on the language itself

Until Next Time

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