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Backport PR #2384: Adapt inline backend to changes in matplotlib...
Backport PR #2384: Adapt inline backend to changes in matplotlib Matplotlib recently merged https://github.com/matplotlib/matplotlib/pull/1125 that makes it simpler to use objective oriented figure creation by automatically creating the right canvas for the backend. To solve that all backends must provide a backend_xxx.FigureCanvas. This is obviosly missing from the inline backend. The change is needed to make the inline backend work with mpl's 1.2.x branch which is due to released soon. Simply setting the default canvas equal to a Agg canvas appears to work for both svg and png figures but I'm not sure weather that is the right approach. Should the canvas depend on the figure format and provide a svg canvas for a svg figure? (Note that before this change to matplotlib the canvas from a plt.figure call seams to be a agg type in all cases) Edit: I made the pull request against 0.13.1 since it would be good to have this in the stable branch for when mpl is released. Just let me know and I can rebase it against master

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iploggerapp.py
103 lines | 3.0 KiB | text/x-python | PythonLexer
#!/usr/bin/env python
# encoding: utf-8
"""
A simple IPython logger application
Authors:
* MinRK
"""
#-----------------------------------------------------------------------------
# Copyright (C) 2011 The IPython Development Team
#
# Distributed under the terms of the BSD License. The full license is in
# the file COPYING, distributed as part of this software.
#-----------------------------------------------------------------------------
#-----------------------------------------------------------------------------
# Imports
#-----------------------------------------------------------------------------
import os
import sys
import zmq
from IPython.core.profiledir import ProfileDir
from IPython.utils.traitlets import Bool, Dict, Unicode
from IPython.parallel.apps.baseapp import (
BaseParallelApplication,
base_aliases,
catch_config_error,
)
from IPython.parallel.apps.logwatcher import LogWatcher
#-----------------------------------------------------------------------------
# Module level variables
#-----------------------------------------------------------------------------
#: The default config file name for this application
default_config_file_name = u'iplogger_config.py'
_description = """Start an IPython logger for parallel computing.
IPython controllers and engines (and your own processes) can broadcast log messages
by registering a `zmq.log.handlers.PUBHandler` with the `logging` module. The
logger can be configured using command line options or using a cluster
directory. Cluster directories contain config, log and security files and are
usually located in your ipython directory and named as "profile_name".
See the `profile` and `profile-dir` options for details.
"""
#-----------------------------------------------------------------------------
# Main application
#-----------------------------------------------------------------------------
aliases = {}
aliases.update(base_aliases)
aliases.update(dict(url='LogWatcher.url', topics='LogWatcher.topics'))
class IPLoggerApp(BaseParallelApplication):
name = u'iplogger'
description = _description
config_file_name = Unicode(default_config_file_name)
classes = [LogWatcher, ProfileDir]
aliases = Dict(aliases)
@catch_config_error
def initialize(self, argv=None):
super(IPLoggerApp, self).initialize(argv)
self.init_watcher()
def init_watcher(self):
try:
self.watcher = LogWatcher(config=self.config, log=self.log)
except:
self.log.error("Couldn't start the LogWatcher", exc_info=True)
self.exit(1)
self.log.info("Listening for log messages on %r"%self.watcher.url)
def start(self):
self.watcher.start()
try:
self.watcher.loop.start()
except KeyboardInterrupt:
self.log.critical("Logging Interrupted, shutting down...\n")
def launch_new_instance():
"""Create and run the IPython LogWatcher"""
app = IPLoggerApp.instance()
app.initialize()
app.start()
if __name__ == '__main__':
launch_new_instance()