Optimize the bytecode for float(0) ?

[matrixise]

BPO	33682
Nosy	@vstinner, @stevendaprano, @matrixise

^{Note: these values reflect the state of the issue at the time it was migrated and might not reflect the current state.}

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GitHub fields:

assignee = None
closed_at = <Date 2018-05-29.13:01:34.963>
created_at = <Date 2018-05-29.12:47:12.095>
labels = ['invalid', '3.8']
title = 'Optimize the bytecode for float(0) ?'
updated_at = <Date 2018-05-29.13:01:34.961>
user = 'https://github.com/matrixise'

bugs.python.org fields:

activity = <Date 2018-05-29.13:01:34.961>
actor = 'matrixise'
assignee = 'none'
closed = True
closed_date = <Date 2018-05-29.13:01:34.963>
closer = 'matrixise'
components = []
creation = <Date 2018-05-29.12:47:12.095>
creator = 'matrixise'
dependencies = []
files = []
hgrepos = []
issue_num = 33682
keywords = []
message_count = 5.0
messages = ['318016', '318017', '318019', '318020', '318021']
nosy_count = 3.0
nosy_names = ['vstinner', 'steven.daprano', 'matrixise']
pr_nums = []
priority = 'normal'
resolution = 'not a bug'
stage = 'resolved'
status = 'closed'
superseder = None
type = None
url = 'https://bugs.python.org/issue33682'
versions = ['Python 3.8']

[matrixise]

Hi,

Maybe already discussed with Victor but I think there is no optimization when we have this simple case for float(X) and int(X)

Example:

>>> import dis
>>> dis.dis("x = float(0)")
  1           0 LOAD_NAME                0 (float)
              2 LOAD_CONST               0 (0)
              4 CALL_FUNCTION            1
              6 STORE_NAME               1 (x)
              8 LOAD_CONST               1 (None)
             10 RETURN_VALUE
>>> dis.dis("x = 1 + 1")
  1           0 LOAD_CONST               0 (2)
              2 STORE_NAME               0 (x)
              4 LOAD_CONST               1 (None)
              6 RETURN_VALUE
>>> dis.dis("x = int(0)")
  1           0 LOAD_NAME                0 (int)
              2 LOAD_CONST               0 (0)
              4 CALL_FUNCTION            1
              6 STORE_NAME               1 (x)
              8 LOAD_CONST               1 (None)
             10 RETURN_VALUE
>>> 

There is an optim for x = 1 + 1

[matrixise]

Victor, if you confirm, maybe you could help me for a mentoring for this issue?

[vstinner]

float and int names can be replaced in the current namespace, so you cannot implement such optimization :-(

http://fatoptimizer.readthedocs.io/en/latest/optimizations.html#call-pure
http://fatoptimizer.readthedocs.io/en/latest/semantics.html#builtin-functions-replaced-in-the-middle-of-a-function

Example in the REPL:

>>> float=bool
>>> float(0)
False

>>> int=len
>>> int("hello world!")
12

I suggest to close this issue as NOTABUG. You need to implement guards at runtime to implement such optimizations without breaking the Python semantics. It is exactly what I implemented in my FAT Python project:
https://faster-cpython.readthedocs.io/fat_python.html

[stevendaprano]

I'm sorry, it isn't clear what optimizations for float(X) and int(X) you are referring to.

I can only guess that you want to optimize:

    float(0)

to use LOAD_CONST 0.0 instead of calling the float() function. If that is what you want, we can't do that because float() may have been shadowed or replaced. Optimizing 1+1 is safe because it involves only literals and operators, no name look-ups.

If that is not what you want, please explain what optimization you are referring to.

[matrixise]

@victor, Thanks and you are right, int and float are not keywords of Python, in this case, we can override them.

@steven, in fact, the optimization was, when you see float/int (if they are keywords), don't call the function via the bytecode.

Thanks and I close this issue.