Skip to main content

util for profiling python code mainly in django projects, but can be used also on ordinary python code

Project description

django-profiler is util for profiling python code mainly in django projects but can be used also on ordinary python code. It counts sql queries a measures time of code execution. It logs its output via standard python logging library and uses logger profiling. If your profiler name doesn’t contain any empty spaces e.g. Profiler(‘Profiler1’) django-profiler will log all the output to the profiling.Profiler logger.

Requirements

  • python 2.7+

Installation

Install via pip or copy this module into your project or into your PYTHON_PATH.

Configuration

django settings.py constants

PROFILING_LOGGER_NAME
PROFILING_SQL_QUERIES

It is possible to change default django-profiler logger name by defining PROFILING_LOGGER_NAME = ‘logger_name’ in your django settings.py.

To log also sql queries into profiler logger set PROFILING_SQL_QUERIES to True in your django settings.py module.

Examples

Example 1

Using context manager approach. Output will be logged to profiling logger.

from profiling import Profiler
with Profiler('Complex Computation'):
    # code with some complex computations

Example 2

Using context manager approach. Output will be logged to profiling.Computation logger.

from profiling import Profiler
with Profiler('Computation'):
    # code with some complex computations

Example 3

Using standard approach. Output will be logged to profiling logger.

from profiling import Profiler
profiler =  Profiler('Complex Computation')
profiler.start()
# code with some complex computations
profiler.stop()

Example 4

Using standard approach and starting directly in constructor. Output will be logged to profiling logger.

from profiling import Profiler
profiler =  Profiler('Complex Computation', start=True)
# code with some complex computations
profiler.stop()

Example 5

Using decorator approach. Output will be logged to profiling.complex_computations logger.

from profiling import profile

@profile
def complex_computations():
    #some complex computations

Example 6

Using decorator approach. Output will be logged to profiling.ComplexClass.complex_computations logger.

from profiling import profile

class ComplexClass(object):
    @profile
    def complex_computations():
        #some complex computations

Example 7

Using decorator approach. Output will be logged to profiling.complex_computations logger. profile execution stats are logged to profiling.complex_computations logger.

from profiling import profile

@profile(stats=True)
def complex_computations():
    #some complex computations

Example 8

Using decorator approach. Output will be logged to profiling.complex_computations logger. profile execution stats are printed to sys.stdout.

import sys

from profiling import profile

@profile(stats=True, stats_buffer=sys.stdout)
def complex_computations():
    #some complex computations

Example 9

Using decorator approach. Output will be logged to profiling.ComplexClass.complex_computations logger. profile stats will be logged to profiling.ComplexClass.complex_computations.

from profiling import profile

class ComplexClass(object)
   @profile(stats=True)
   def complex_computations():
       #some complex computations

Tests

Tested on evnironment

  • Xubuntu Linux 11.10 oneiric 64-bit

  • python 2.7.2+

  • python unittest

Running tests

To run the test run command:

$ python test.py
$ python setup.py test

Author

char0n (Vladimír Gorej, CodeScale s.r.o.)

References

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

django-profiler-2.0.0.tar.gz (6.1 kB view hashes)

Uploaded Source

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page