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Use DottedObjectName traits in zmq and parallel modules.
Use DottedObjectName traits in zmq and parallel modules.

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jsonutil.py
157 lines | 5.3 KiB | text/x-python | PythonLexer
Fernando Perez
Created JSON-safety utilities....
r2947 """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
MinRK
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r4006 import re
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r2947 import types
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r4006 from datetime import datetime
#-----------------------------------------------------------------------------
# Globals and constants
#-----------------------------------------------------------------------------
# timestamp formats
ISO8601="%Y-%m-%dT%H:%M:%S.%f"
ISO8601_PAT=re.compile(r"^\d{4}-\d{2}-\d{2}T\d{2}:\d{2}:\d{2}\.\d+$")
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r2947
#-----------------------------------------------------------------------------
# Classes and functions
#-----------------------------------------------------------------------------
MinRK
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r4036 def rekey(dikt):
"""Rekey a dict that has been forced to use str keys where there should be
ints by json."""
for k in dikt.iterkeys():
if isinstance(k, basestring):
ik=fk=None
try:
ik = int(k)
except ValueError:
try:
fk = float(k)
except ValueError:
continue
if ik is not None:
nk = ik
else:
nk = fk
if nk in dikt:
raise KeyError("already have key %r"%nk)
dikt[nk] = dikt.pop(k)
return dikt
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r4006 def extract_dates(obj):
"""extract ISO8601 dates from unpacked JSON"""
if isinstance(obj, dict):
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r4010 obj = dict(obj) # don't clobber
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r4006 for k,v in obj.iteritems():
obj[k] = extract_dates(v)
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r4008 elif isinstance(obj, (list, tuple)):
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r4006 obj = [ extract_dates(o) for o in obj ]
elif isinstance(obj, basestring):
if ISO8601_PAT.match(obj):
obj = datetime.strptime(obj, ISO8601)
return obj
MinRK
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r4008 def squash_dates(obj):
"""squash datetime objects into ISO8601 strings"""
if isinstance(obj, dict):
MinRK
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r4010 obj = dict(obj) # don't clobber
MinRK
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r4008 for k,v in obj.iteritems():
obj[k] = squash_dates(v)
elif isinstance(obj, (list, tuple)):
obj = [ squash_dates(o) for o in obj ]
elif isinstance(obj, datetime):
obj = obj.strftime(ISO8601)
return obj
MinRK
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r4006 def date_default(obj):
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r4008 """default function for packing datetime objects in JSON."""
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r4006 if isinstance(obj, datetime):
return obj.strftime(ISO8601)
else:
raise TypeError("%r is not JSON serializable"%obj)
Fernando Perez
Created JSON-safety utilities....
r2947 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)