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specify windows working directory The create_shortcut built-in function used in the windows post-installation script allows the working directory to be specified. If it is not specified, the working directory will default to something like "C:\Windows". Specifying the working directory as "%HOMEDRIVE%%HOMEPATH%" seems a better default, it sets the working directory the the current user's home directory.

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jsonutil.py
90 lines | 3.3 KiB | text/x-python | PythonLexer
"""Utilities to manipulate JSON objects.
"""
#-----------------------------------------------------------------------------
# Copyright (C) 2010 The IPython Development Team
#
# Distributed under the terms of the BSD License. The full license is in
# the file COPYING.txt, distributed as part of this software.
#-----------------------------------------------------------------------------
#-----------------------------------------------------------------------------
# Imports
#-----------------------------------------------------------------------------
# stdlib
import types
#-----------------------------------------------------------------------------
# Classes and functions
#-----------------------------------------------------------------------------
def json_clean(obj):
"""Clean an object to ensure it's safe to encode in JSON.
Atomic, immutable objects are returned unmodified. Sets and tuples are
converted to lists, lists are copied and dicts are also copied.
Note: dicts whose keys could cause collisions upon encoding (such as a dict
with both the number 1 and the string '1' as keys) will cause a ValueError
to be raised.
Parameters
----------
obj : any python object
Returns
-------
out : object
A version of the input which will not cause an encoding error when
encoded as JSON. Note that this function does not *encode* its inputs,
it simply sanitizes it so that there will be no encoding errors later.
Examples
--------
>>> json_clean(4)
4
>>> json_clean(range(10))
[0, 1, 2, 3, 4, 5, 6, 7, 8, 9]
>>> json_clean(dict(x=1, y=2))
{'y': 2, 'x': 1}
>>> json_clean(dict(x=1, y=2, z=[1,2,3]))
{'y': 2, 'x': 1, 'z': [1, 2, 3]}
>>> json_clean(True)
True
"""
# types that are 'atomic' and ok in json as-is. bool doesn't need to be
# listed explicitly because bools pass as int instances
atomic_ok = (basestring, int, float, types.NoneType)
# containers that we need to convert into lists
container_to_list = (tuple, set, types.GeneratorType)
if isinstance(obj, atomic_ok):
return obj
if isinstance(obj, container_to_list) or (
hasattr(obj, '__iter__') and hasattr(obj, 'next')):
obj = list(obj)
if isinstance(obj, list):
return [json_clean(x) for x in obj]
if isinstance(obj, dict):
# First, validate that the dict won't lose data in conversion due to
# key collisions after stringification. This can happen with keys like
# True and 'true' or 1 and '1', which collide in JSON.
nkeys = len(obj)
nkeys_collapsed = len(set(map(str, obj)))
if nkeys != nkeys_collapsed:
raise ValueError('dict can not be safely converted to JSON: '
'key collision would lead to dropped values')
# If all OK, proceed by making the new dict that will be json-safe
out = {}
for k,v in obj.iteritems():
out[str(k)] = json_clean(v)
return out
# If we get here, we don't know how to handle the object, so we just get
# its repr and return that. This will catch lambdas, open sockets, class
# objects, and any other complicated contraption that json can't encode
return repr(obj)