[Numpy-discussion] Proposal of timeline for dropping Python 2.7 support

Charles R Harris charlesr.harris at gmail.com
Fri Nov 17 10:35:18 EST 2017

On Fri, Nov 17, 2017 at 5:35 AM, Peter Cock <p.j.a.cock at googlemail.com>

> Since Konrad Hinsen no longer follows the NumPy discussion list
> for lack of time, he has not posted here - but he has commented
> about this on Twitter and written up a good blog post:
> http://blog.khinsen.net/posts/2017/11/16/a-plea-for-
> stability-in-the-scipy-ecosystem/
> In a field where scientific code is expected to last and be developed
> on a timescale of decades, the change of pace with Python 2 and 3
> is harder to handle.
> Regards,
> Peter
Konrad has been making that argument for a long time, and I don't know what
the long term solution is. However, the use of Fortran as a benchmark of
stability is a bit misleading. Fortran was undergoing rapid development in
the years before Fortran 77, with Fortran II, DEC Fortran, and Rational
Fortran being somewhat incompatible variations on the theme, and it was
only with the standardization of the language that stability could be
assumed. And if you wrote in a language that didn't survive the winnowing,
Algol-68 for instance, you were in trouble. But even apart from from the
languages, the hardware was changing, with different floating point formats
on different hardware, so that prior to IEEE-754 the results of
computations carried out on one machine were not always the same as results
on another. Such differences still persist, with dependencies on math
library and compiler versions, choice of rounding, and hardware, although
with much reduced in effect. The C language is another example, the lack of
a C99 standard, maintained compiler on Windows for Python 2.7 being one of
the considerations in dropping support for Python 2. And let us not
overlook C++, which, IMHO, has only reached its Fortran 77 equivalent with

I think the take away here is that we are still in the very early days of
scientific computing with Python, it has really only been coming on strong
for maybe five years. Those of us, including Konrad, who were early
adopters scouting the terrain, were bound to end up with a few arrows in
our back. Early adoption is always a gamble, with a tradeoff between the
risk of choosing a language that mutates or dies, versus the payoff of
using a language that blossoms and makes life easier. In my mind, Python
3.5 is the rough equivalent of Fortran 77, or maybe Fortran 95, and I don't
know when the Python scientific stack will truly settle, but I expect it
will be sometime in the next 5-10 years. At that point, we may want to look
at having a "reference" version of NumPy, but I think it is still too early
to make such a guarantee, although we do try to avoid being too disruptive
while still making progress.

These considerations are probably cold comfort to folks like Konrad who
have extensive code bases, some probably dating back to Numeric, that they
need to maintain, but I do think things will get better.


-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mail.python.org/pipermail/numpy-discussion/attachments/20171117/79816acf/attachment.html>

More information about the NumPy-Discussion mailing list