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Name: memprof
Version: 0.3.4
Summary: A memory profiler for Python. As easy as adding a decorator.
Home-page: http://jmdana.github.io/memprof/
Author: Jose M. Dana
Author-email: UNKNOWN
License: GNU General Public License v3 (GPLv3)
Description: # memprof
`memprof` is a memory profiler for Python.
It logs and plots the memory usage of all the variables during the execution of the decorated methods.
## Installation
### Stable
sudo pip install --upgrade memprof
or
sudo easy_install --upgrade memprof
or (Debian testing/unstable)
sudo apt-get install python-memprof
### Development
git clone git://github.com/jmdana/memprof.git
cd memprof
sudo python setup.py install
## Usage
Using `memprof` is as easy as adding a decorator to the methods that you want to profile:
@memprof
def foo():
And importing the module just by including the line below at the beginning of your Python file:
from memprof import *
Now you can run as usual and logfiles with the names of your methods will be created (e.g. `foo.log`).
### Generating plots
The logfiles are not very interesting so you might prefer to use the `-p`/`--plot` flag:
python -m memprof --plot <python_file>
python -m memprof -p <python_file>
Which, in addition to the logfile, will generate a plot (`foo.png`):
The grey bar indicates that the `foo` method wasn't running at that point.
The flag may also be passed as an argument to the decorator:
@memprof(plot = True)
Please keep in mind that the former takes precedence over the latter.
### Adjusting the threshold
You may also want to specify a `threshold`. The value will be the minimum size for a variable to appear in the plot (but it will always appear in the logfile!). The default value is 1048576 (1 MB) but you can specify a different `threshold` (in bytes) with the `-t`/`--threshold` flag:
python -m memprof --threshold 1024 <python_file>
python -m memprof -t 1024 <python_file>
The `threshold` may also be passed as an argument to the decorator:
@memprof(threshold = 1024)
Please keep in mind that the former takes precedence over the latter.
### mp_plot
If, after running `memprof`, you want to change the threshold and generate a new plot (or you forgot to use the `-p`/`--plot` flag with `memprof`), you don't have to re-run! Just call the command:
mp_plot [-h] [-t THRESHOLD] logfiles [logfiles ...]
and generate the plots again doing something like:
mp_plot -t 128 logfile1.log logfile2.log
or:
mp_plot -t 1024 *.log
etc.
## Contact
### Mailing list
* Subscribe by sending a message to <memprof+subscribe@googlegroups.com>
* Once subscribed, you can send emails to <memprof@googlegroups.com>
* List archives at http://groups.google.com/group/memprof
---
Copyright 2013-2015, Jose M. Dana
Keywords: memory usage profiler decorator variables charts plots graphical
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Topic :: Utilities
Classifier: Topic :: Software Development
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 2.6
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.1
Classifier: Programming Language :: Python :: 3.2
Classifier: Programming Language :: Python :: 3.3
Classifier: Operating System :: Unix
Classifier: Operating System :: MacOS
Classifier: Operating System :: POSIX
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Information Technology
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
Requires: matplotlib
Requires: cython
Provides: memprof
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