You can download the latest version of Python from https://www.python.org/downloads/ for this chapter.

Alternative Python interpreter implementations can be found at the following sites:

• Stackless Python: https://github.com/stackless-dev/stackless
• PyPy: https://pypy.org
• Jython: https://www.jython.org
• IronPython: https://ironpython.net
• MicroPython: https://micropython.org

The code files for this chapter can be found at https://github.com/PacktPublishing/Expert-Python-Programming-Third-Edition/tree/master/chapter1.

Python history starts somewhere in the late 1980s, but its 1.0 release date was in the year 1994. So, it isn't a young language. There could be a whole timeline of major Python releases mentioned here, but what really matters is a single date: Python 3.0—December 3, 2008.

At the time of writing, almost ten years have passed since the first Python 3 release. It is also seven years since the creation of PEP 404—the official document that un-released Python 2.8 and officially closed the 2.x branch. Although a lot of time has passed, there is a specific dichotomy in the Python community—while the language is developing very fast, there is a large group of its users that do not want to move forward with it.

The answer is simple—Python changes because there is such a need. The competition does not sleep. Every few months, a new language pops out, out of nowhere, claiming to solve every problem of all its predecessors. Most projects like these lose the developers' attention very shortly, and their popularity is often driven by sudden hype.

This is a sign of some bigger problem. People design new languages because they find that existing ones do not solve their problems in the best way possible. It would be silly to not recognize such a need. Also, more and more widespread usage of Python shows that it could, and should, be improved on in many places.

Many improvements in Python are driven by the needs of particular fields where it is being used. The most significant one is web development. Thanks to the ever-increasing demand for speed and performance...

The Python community has a well-established way of dealing with changes. While speculative Python language ideas are mostly discussed on specific mailing lists (python-ideas@python.org), nothing major ever gets changed without the existence of a new document, called a Python Enhancement Proposal (PEP).

It is a formalized document that describes, in detail, the proposal of change to be made in Python. It is also the starting point for the community discussion. The whole purpose, format, and workflow around these documents is also standardized in the form of a PEP—precisely the PEP 1 document (http://www.python.org/dev/peps/pep-0001).

PEP documentation is very important for Python, and, depending on the topic, they serve different purposes:

• Informing: They summarize the information needed by core Python developers...

So, thanks to new, exciting features, is Python 3 well adopted among its community? It's hard to say. The once-popular page, Python 3 Wall of Superpowers (https://python3wos.appspot.com), that tracked the compatibility of the most popular packages with the Python 3 branch was, at the beginning, named Python 3 Wall of Shame.

The site is no longer maintained, but in the list from the last time it was updated, on April 22, 2018, it shows that exactly 191 from 200 of the most popular Python packages at that time were compatible within Python 3. So, we can see that Python 3 seems to be finally well-adopted in the community of open source Python programmers. Still, this does not mean that all teams building their applications are finally using Python 3. At least, since most of the popular Python packages are available in Python...

It has already been stated that Python 3 breaks backward compatibility with Python 2 on a syntax level. Still, it is not a complete redesign. Also, it does not cause every Python module written for some 2.x release to stop working under Python 3. It is possible to write completely cross-compatible code that will run on both major releases without additional tools or techniques, but usually it is possible only for simple applications.

Despite my personal opinion on Python 2 compatibility that I exposed earlier in this chapter, it is impossible to simply forget about it at this time. There are still some useful packages that are really worth using, but are...

The reference Python interpreter implementation is called CPython and, as its name suggests, it is written entirely in the C language. It was always C and probably will be still for a very long time. That's the implementation that most Python programmers choose because it is always up to date with the language specification and is the interpreter that most libraries are tested on. But, besides C, Python interpreter was written in a few other languages. Also, there are some modified versions of CPython interpreter available under different names and tailored exactly for some niche applications. Most of them are a few milestones behind CPython, but provide a great opportunity to use and promote the language in a specific environment.

In this section, we will discuss some of the most prominent and interesting alternative Python implementations.

The best way to know the status of Python is to stay informed about what's new and to constantly read Python-related resources. The web is full of such resources. The most important and obvious ones were already mentioned earlier, but here they are repeated to keep this list consistent:

• Python documentation
• Python Package Index (PyPI)
• PEP 0 – Index of Python Enhancement Proposals (PEPs)

The other resources, such as books and tutorials, are useful, but often get outdated very fast. What does not get outdated are the resources that are actively curated by the community or released periodically. The few that are worth recommending are as follows:

• Awesome Python (https://github.com/vinta/awesome-python) includes a curated list of popular packages and frameworks.
• r/Python (https://www.reddit.com/r/Python/) is a Python subreddit where you can find news...

This chapter concentrated on the current status of Python and the process of change that was visible throughout the history of that language. We started with a discussion of how and why Python changes and described what the main results of that process are, including the differences between Python 2 and 3. We've learned how to reliably deal with those changes and learned some useful techniques that allow us to provide code that is compatible with various versions of Python and different versions of its libraries.

Then, we took a different look at the idea of changes in programming language. We've reviewed some of the popular alternative Python interpreters and discussed their main differences compared to default CPython implementation.

In the next chapter, we will describe modern ways of setting up repeatable and consistent development environments for Python...