When optimizing code, I often need to timeit a part of code or a function.
I am using then the following class
```
import logging
import time
from functools import wraps
from typing import Optional
_logger = logging.getLogger("Timer")
class Timer:
def __init__(self, description: Optional[str] = None, logger:
Optional[logging.Logger] = None):
self.description = "<anonymous code block>" if description is None else
description
self.logger = _logger if logger is None else logger
self.msg = "'%(description)s' ran in %(time).3f seconds"
def __enter__(self):
self.start = time.perf_counter()
return self
def __exit__(self, *args):
self.end = time.perf_counter()
self.interval = self.end - self.start
self.logger.debug(
self.msg, {"description": self.description, "time": self.interval}
# f"Thread: '{get_ident()}' '{self.description}' ran in
{round(self.interval, 3)} seconds"
)
def __call__(self, f):
# decorator call
@wraps(f)
def wrapper(*args, **kw):
with Timer(description=f.__qualname__):
return f(*args, **kw)
return wrapper
```
that I can use either as a context manager in
```
with Timer("how long does this take?") as t:
time.sleep(1)
# output: DEBUG:Timer:'how long does this take?' ran in 1.000 seconds
```
or as a decorator
```
@Timer()
def my_function():
"""this is my function"""
time.sleep(2)
my_function()
# output: DEBUG:Timer:'my_function' ran in 2.000 seconds
```
This class could be added to the timeit module as it fits well its functional
scope.
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