A runtime step profiler - for Python.
Aggregating runtime statistics and/or finding bottlenecks in code is one of the most common challenges as a software engineer. This is a library to aid that. In comparison to most existing libraries this one is focused on step profiling; aggregation of runtime information in steps marked by keys/tags/labels and optional meta data, which is used to create a summary of all steps in form of a transaction. As a bonus it also supports decorating code contexts and functions.
This is an MVP that most likely will be extended with more profiling features.
Install using pip:
$ pip install totalrecall
Very basic example:
import totalrecall
from time import sleep
# ---------------------------------------------------
# EXAMPLE: runtime step profiler
# ------------------------------------------------
profiler = totalrecall.timer('profile something - using timer', begin = False)
profiler.begin('task 1')
sleep(0.1)
profiler.begin('task 2')
sleep(0.2)
profiler.begin('task 3')
sleep(0.3)
profiler.end()
print('[profiler.time / basic]: TIME: {0}'.format(profiler.time))
print('[profiler.time / basic]: STEPS: {0}'.format(profiler.steps))
# ---------------------------------------------------
# EXAMPLE: runtime step profiler (detailed)
# ------------------------------------------------
profiler = totalrecall.timer('profile something - using timer',
begin = False,
enabled = True,
verbose = True,
colors = True,
)
profiler.begin('task 1')
sleep(0.1)
profiler.begin('task 2')
sleep(0.2)
profiler.begin('task 3')
sleep(0.3)
profiler.end()
print('[profiler.time / detailed]: TIME: {0}'.format(profiler.time))
print('[profiler.time / detailed]: STEPS: {0}'.format(profiler.steps))
# ---------------------------------------------------
# EXAMPLE: runtime context profiler
# ------------------------------------------------
profiler = totalrecall.context('profile something 2 - using context')
with profiler:
sleep(1)
print('[profiler.context / basic]: TIME: {0}'.format(profiler.time))
print('[profiler.context / basic]: STEPS: {0}'.format(profiler.steps))
# ---------------------------------------------------
# EXAMPLE: runtime function profiler
# ------------------------------------------------
profiler = totalrecall.function('profile something 2 - using context')
@profiler
def foo():
sleep(1)
print('[profiler.function / basic]: TIME: {0}'.format(profiler.time))
print('[profiler.function / basic]: STEPS: {0}'.format(profiler.steps))
Clone down source code:
$ make install
Run colorful tests, with only native environment (dependency sandboxing up to you):
$ make test
Run less colorful tests, with multi-environment (using tox):
$ make test-tox
This project was mainly initiated - in lack of solid existing alternatives - to be used at our work at Markable.ai to have common code conventions between various programming environments where Python (research, CV, AI) is heavily used.
Thanks to op-bk for creative help with naming this library.
Released under the MIT license.