This blog will explain the differences between Python 2.7, Python 3.x, and PyPy.
If you’re learning to program, you may have heard of Python, but what is it exactly?
Python is an open source programming language. It’s relatively easy to learn, because of its simple syntax and readability. It is a general purpose high-level programming language that can be applied to many different classes of problems. Programming languages allow humans to communicate with computers in a higher level of abstraction than machine level code (binary).
The Python interpreter does not know what a variable is or that the plus sign means addition until it reads the code line by line and interprets it. The interpreter converts each line of code into binary so the computer can understand it. This process is called compilation and execution. Since this process takes some time, programmers write scripts that are short snippets of code in order to test chunks at a time before writing full programs. Think of scripts as little pieces to larger puzzles.
A script is run from a command line interpreter and is written in text format which allows scripts to be portable across operating systems (OS). The command line provides prompts for users to input commands and parameters without using a graphical user interface (GUI).
Python is a high level programming language that allows the programmer to express concepts in fewer lines of code. It is a programming language used for scientific and mathematical computing, data analysis, web development, and education. There are currently two major versions of Python available: 2.7 and 3.x. PyPy is an alternative implementation of the Python language. It is also a replacement for CPython (the standard implementation).
It is important to note that Python 2.x and Python 3.x are not backwards compatible with each other. Code written in Python 2 cannot be executed in 3 without modifications (and vice versa). This means that when using libraries or modules written in either version, they must be compatible with the version of Python you’re using them in. It can also mean rewriting large amounts of code if switching between versions.
As of 2013-2014, most popular third party modules (such as Django) are compatible with both versions of Python. A notable exception to this is Google App Engine, which only works with version 2.7 at the time of writing this post (2013-2014).
The Python 3.x series has been out for about two years now, and most of the major features have been ported to 2.7 or are planned for the 2.7.x series of releases. Python 2.7 will remain as the stable version of Python until 2020, so there is still plenty of time to port your code over to 3.x if you haven’t already done so.
If that was not enough Python for you, there is also PyPy – a high performance implementation of Python written in RPython (Restricted Python) and JIT compiled to machine code using a tracing just-in-time compiler (a specialty VM). The project aims to fully support the Python language as well as popular libraries such as numpy and pandas. PyPy is a very interesting project that can offer some significant performance gains for certain workloads (see below for benchmarks), especially those that spend a lot of time in loops or are CPU bound (e.g., scientific computing, image processing, etc.).
In this article we will go over some basic concepts and differences between CPython, PyPy, and the different versions of Python (2 vs 3). We will also perform some simple benchmarks comparing CPython 2.7, CPython 3.2
Python 2.7 is the last of the 2.x releases and has been around since 2010. It will be supported until 2020. Python 3.x is the present and future of the language. The PyPy project is a fast implementation of Python written in a restricted statically-typed subset of the Python language called RPython (Restricted Python).
RPython is not directly usable as a programming language, but it can be automatically translated into C code or executed by an interpreter just like CPython (the standard implementation of Python).
Python 2.7 focuses on removing duplicated constructs and modules so that there’s one obvious way to do something, rather than having multiple options. For example, in 3.x, integer division returns floating-point results, so it’s no longer necessary to explicitly convert the operands to floating point. Also, xrange() was removed because range() now behaves like xrange(). However, some features from 3.x are not backward compatible with 2.7, so code written for 2.7 may not work under 3.x without modification.
One major difference between PyPy and CPython is that PyPy comes with a just in time compiler which makes it run faster than CPython in most cases
A list of Python resources for beginning and intermediate programmers.
Python is a general-purpose programming language created in the late 1980s, and named after Monty Python, that’s used by thousands of people to do things from testing microchips at Intel, to powering Instagram, to building video games with the PyGame library. It’s small, very closely resembles the English language, and has hundreds of existing third-party libraries.
It’s also one of the most popular languages among data scientists, statisticians, researchers, and analysts. According to Guido Van Rossum (the original creator of Python) himself:
Python is now my second favorite programming language. My favorite programming language is Python.
Python 2 vs 3
Python 2 and Python 3 are two different but very similar versions of the language. Like with many programming languages, Python’s developers release an updated version every few years (usually for free). Most users are able to upgrade their software to the latest version without issue.
However, when it comes to large-scale applications – like ones backed by a corporation or used by hundreds or thousands of users – switching from one version of Python to another can be difficult because there may be code written for the old version that doesn’t work on the new version. This
Python 3.x has added a way to specify the type of parameters and return types of functions: function annotations, which are specified by adding a colon after the parameter name and then specifying the type.
def greeting(name: str) -> str:
return ‘Hello ‘ + name
print(greeting(‘World’))