[Python-Dev] Investigating Python memory footprint of one real Web application

[INADA Naoki]

Hi, all.

After reading Instagram's blog article [1], I’m thinking about how
Python can reduce memory usage of Web applications.
My company creating API server with Flask, SQLAlchemy and typing.
(sorry, it's closed source).
So I can get some data from it's codebase.

[1]: https://engineering.instagram.com/dismissing-python-garbage-collection-at-instagram-4dca40b29172#.lenebvdgn

Report is here
https://gist.github.com/methane/ce723adb9a4d32d32dc7525b738d3c31


My thoughts are:

* Interning (None,) seems worth enough.

* There are many empty dicts.  Allocating ma_keys lazily may reduce
memory usage.

* Most large strings are docstring.  Is it worth enough that option
for trim docstrings, without disabling asserts?

* typing may increase memory footprint, through functions
__attributes__ and abc.
   * Can we add option to remove or lazy evaluate __attributes__ ?
   * Using string literal for annotating generic type may reduce WeakRef usage.
   * Since typing will be used very widely in this year.  Need more
investigating.