E
Eric Snow
Does anyone have (or know of) accurate totals and percentages on how
Python is used? I'm particularly interested in the following
groupings:
- new development vs. stable code-bases
- categories (web, scripts, "big data", computation, etc.)
- "bare metal" vs. on top of some framework
- regional usage
I'm thinking about this partly because of the discussion on
python-ideas about the perceived challenges of Unicode in Python 3.
All the rhetoric, anecdotal evidence, and use-cases there have little
meaning to me, in regards to Python as a whole, without an
understanding of who is actually affected.
For instance, if frameworks (like django and numpy) could completely
hide the arguable challenges of Unicode in Python 3--and most projects
were built on top of frameworks--then general efforts for making
Unicode easier in Python 3 should go toward helping framework writers.
Not only are such usage numbers useful for the Unicode discussion
(which I wish would get resolved and die so we could move on to more
interesting stuff
). They help us know where efforts could be
focused in general to make Python more powerful and easier to use
where it's already used extensively. They can show us the areas that
Python isn't used much, thus exposing a targeted opportunity to change
that.
Realistically, it's not entirely feasible to compile such information
at a comprehensive level, but even generally accurate numbers would be
a valuable resource. If the numbers aren't out there, what would some
good approaches to discovering them? Thanks!
-eric
Python is used? I'm particularly interested in the following
groupings:
- new development vs. stable code-bases
- categories (web, scripts, "big data", computation, etc.)
- "bare metal" vs. on top of some framework
- regional usage
I'm thinking about this partly because of the discussion on
python-ideas about the perceived challenges of Unicode in Python 3.
All the rhetoric, anecdotal evidence, and use-cases there have little
meaning to me, in regards to Python as a whole, without an
understanding of who is actually affected.
For instance, if frameworks (like django and numpy) could completely
hide the arguable challenges of Unicode in Python 3--and most projects
were built on top of frameworks--then general efforts for making
Unicode easier in Python 3 should go toward helping framework writers.
Not only are such usage numbers useful for the Unicode discussion
(which I wish would get resolved and die so we could move on to more
interesting stuff
). They help us know where efforts could befocused in general to make Python more powerful and easier to use
where it's already used extensively. They can show us the areas that
Python isn't used much, thus exposing a targeted opportunity to change
that.
Realistically, it's not entirely feasible to compile such information
at a comprehensive level, but even generally accurate numbers would be
a valuable resource. If the numbers aren't out there, what would some
good approaches to discovering them? Thanks!
-eric