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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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map.py
121 lines | 3.7 KiB | text/x-python | PythonLexer
# encoding: utf-8
"""Classes used in scattering and gathering sequences.
Scattering consists of partitioning a sequence and sending the various
pieces to individual nodes in a cluster.
"""
__docformat__ = "restructuredtext en"
#-------------------------------------------------------------------------------
# Copyright (C) 2008 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 types
from IPython.utils.data import flatten as utils_flatten
#-------------------------------------------------------------------------------
# Figure out which array packages are present and their array types
#-------------------------------------------------------------------------------
arrayModules = []
try:
import Numeric
except ImportError:
pass
else:
arrayModules.append({'module':Numeric, 'type':Numeric.arraytype})
try:
import numpy
except ImportError:
pass
else:
arrayModules.append({'module':numpy, 'type':numpy.ndarray})
try:
import numarray
except ImportError:
pass
else:
arrayModules.append({'module':numarray,
'type':numarray.numarraycore.NumArray})
class Map:
"""A class for partitioning a sequence using a map."""
def getPartition(self, seq, p, q):
"""Returns the pth partition of q partitions of seq."""
# Test for error conditions here
if p<0 or p>=q:
print "No partition exists."
return
remainder = len(seq)%q
basesize = len(seq)/q
hi = []
lo = []
for n in range(q):
if n < remainder:
lo.append(n * (basesize + 1))
hi.append(lo[-1] + basesize + 1)
else:
lo.append(n*basesize + remainder)
hi.append(lo[-1] + basesize)
result = seq[lo[p]:hi[p]]
return result
def joinPartitions(self, listOfPartitions):
return self.concatenate(listOfPartitions)
def concatenate(self, listOfPartitions):
testObject = listOfPartitions[0]
# First see if we have a known array type
for m in arrayModules:
#print m
if isinstance(testObject, m['type']):
return m['module'].concatenate(listOfPartitions)
# Next try for Python sequence types
if isinstance(testObject, (types.ListType, types.TupleType)):
return utils_flatten(listOfPartitions)
# If we have scalars, just return listOfPartitions
return listOfPartitions
class RoundRobinMap(Map):
"""Partitions a sequence in a roun robin fashion.
This currently does not work!
"""
def getPartition(self, seq, p, q):
return seq[p:len(seq):q]
#result = []
#for i in range(p,len(seq),q):
# result.append(seq[i])
#return result
def joinPartitions(self, listOfPartitions):
#lengths = [len(x) for x in listOfPartitions]
#maxPartitionLength = len(listOfPartitions[0])
#numberOfPartitions = len(listOfPartitions)
#concat = self.concatenate(listOfPartitions)
#totalLength = len(concat)
#result = []
#for i in range(maxPartitionLength):
# result.append(concat[i:totalLength:maxPartitionLength])
return self.concatenate(listOfPartitions)
dists = {'b':Map}