##// END OF EJS Templates
Multiple improvements to tab completion....
Multiple improvements to tab completion. I refactored the API quite a bit, to retain readline compatibility but make it more independent of readline. There's still more to do in cleaning up our init_readline() method, but now the completer objects have separate rlcomplete() and complete() methods. The former uses the quirky readline API with a state flag, while the latter is stateless, takes only text information, and is more suitable for GUIs and other frontends to call programatically. Made other minor fixes to ensure the test suite passes in full. While all this code is a bit messy, we're getting in the direction of the APIs we need in the long run.

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clearcmd.py
87 lines | 2.6 KiB | text/x-python | PythonLexer
# -*- coding: utf-8 -*-
""" IPython extension: add %clear magic """
from IPython.core import ipapi
import gc
ip = ipapi.get()
def clear_f(self,arg):
""" Clear various data (e.g. stored history data)
%clear in - clear input history
%clear out - clear output history
%clear shadow_compress - Compresses shadow history (to speed up ipython)
%clear shadow_nuke - permanently erase all entries in shadow history
%clear dhist - clear dir history
%clear array - clear only variables that are NumPy arrays
Examples:
In [1]: clear in
Flushing input history
In [2]: clear shadow_compress
Compressing shadow history
In [3]: clear shadow_nuke
Erased all keys from shadow history
In [4]: clear dhist
Clearing directory history
"""
api = self.getapi()
user_ns = self.user_ns # local lookup, heavily used
for target in arg.split():
if target == 'out':
print "Flushing output cache (%d entries)" % len(user_ns['_oh'])
self.outputcache.flush()
elif target == 'in':
print "Flushing input history"
pc = self.outputcache.prompt_count + 1
for n in range(1, pc):
key = '_i'+`n`
user_ns.pop(key,None)
try:
del user_ns[key]
except: pass
# must be done in-place
self.input_hist[:] = ['\n'] * pc
self.input_hist_raw[:] = ['\n'] * pc
elif target == 'array':
# Support cleaning up numpy arrays
try:
from numpy import ndarray
# This must be done with items and not iteritems because we're
# going to modify the dict in-place.
for x,val in user_ns.items():
if isinstance(val,ndarray):
del user_ns[x]
except AttributeError:
print "Clear array only works if Numpy is available."
elif target == 'shadow_compress':
print "Compressing shadow history"
api.db.hcompress('shadowhist')
elif target == 'shadow_nuke':
print "Erased all keys from shadow history "
for k in ip.db.keys('shadowhist/*'):
del ip.db[k]
elif target == 'dhist':
print "Clearing directory history"
del user_ns['_dh'][:]
gc.collect()
# Activate the extension
ip.define_magic("clear",clear_f)
import ipy_completers
ipy_completers.quick_completer(
'%clear','in out shadow_nuke shadow_compress dhist')