|
|
"""Utilities to manipulate JSON objects.
|
|
|
"""
|
|
|
#-----------------------------------------------------------------------------
|
|
|
# Copyright (C) 2010-2011 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 math
|
|
|
import re
|
|
|
import sys
|
|
|
import types
|
|
|
from datetime import datetime
|
|
|
|
|
|
try:
|
|
|
# base64.encodestring is deprecated in Python 3.x
|
|
|
from base64 import encodebytes
|
|
|
except ImportError:
|
|
|
# Python 2.x
|
|
|
from base64 import encodestring as encodebytes
|
|
|
|
|
|
from IPython.utils import py3compat
|
|
|
from IPython.utils.encoding import DEFAULT_ENCODING
|
|
|
from IPython.utils import text
|
|
|
next_attr_name = '__next__' if py3compat.PY3 else 'next'
|
|
|
|
|
|
#-----------------------------------------------------------------------------
|
|
|
# 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+$")
|
|
|
|
|
|
#-----------------------------------------------------------------------------
|
|
|
# Classes and functions
|
|
|
#-----------------------------------------------------------------------------
|
|
|
|
|
|
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
|
|
|
|
|
|
|
|
|
def extract_dates(obj):
|
|
|
"""extract ISO8601 dates from unpacked JSON"""
|
|
|
if isinstance(obj, dict):
|
|
|
obj = dict(obj) # don't clobber
|
|
|
for k,v in obj.iteritems():
|
|
|
obj[k] = extract_dates(v)
|
|
|
elif isinstance(obj, (list, tuple)):
|
|
|
obj = [ extract_dates(o) for o in obj ]
|
|
|
elif isinstance(obj, basestring):
|
|
|
if ISO8601_PAT.match(obj):
|
|
|
obj = datetime.strptime(obj, ISO8601)
|
|
|
return obj
|
|
|
|
|
|
def squash_dates(obj):
|
|
|
"""squash datetime objects into ISO8601 strings"""
|
|
|
if isinstance(obj, dict):
|
|
|
obj = dict(obj) # don't clobber
|
|
|
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
|
|
|
|
|
|
def date_default(obj):
|
|
|
"""default function for packing datetime objects in JSON."""
|
|
|
if isinstance(obj, datetime):
|
|
|
return obj.strftime(ISO8601)
|
|
|
else:
|
|
|
raise TypeError("%r is not JSON serializable"%obj)
|
|
|
|
|
|
|
|
|
# constants for identifying png/jpeg data
|
|
|
PNG = b'\x89PNG\r\n\x1a\n'
|
|
|
JPEG = b'\xff\xd8'
|
|
|
|
|
|
def encode_images(format_dict):
|
|
|
"""b64-encodes images in a displaypub format dict
|
|
|
|
|
|
Perhaps this should be handled in json_clean itself?
|
|
|
|
|
|
Parameters
|
|
|
----------
|
|
|
|
|
|
format_dict : dict
|
|
|
A dictionary of display data keyed by mime-type
|
|
|
|
|
|
Returns
|
|
|
-------
|
|
|
|
|
|
format_dict : dict
|
|
|
A copy of the same dictionary,
|
|
|
but binary image data ('image/png' or 'image/jpeg')
|
|
|
is base64-encoded.
|
|
|
|
|
|
"""
|
|
|
encoded = format_dict.copy()
|
|
|
pngdata = format_dict.get('image/png')
|
|
|
if isinstance(pngdata, bytes) and pngdata[:8] == PNG:
|
|
|
encoded['image/png'] = encodebytes(pngdata).decode('ascii')
|
|
|
jpegdata = format_dict.get('image/jpeg')
|
|
|
if isinstance(jpegdata, bytes) and jpegdata[:2] == JPEG:
|
|
|
encoded['image/jpeg'] = encodebytes(jpegdata).decode('ascii')
|
|
|
return encoded
|
|
|
|
|
|
|
|
|
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]
|
|
|
>>> sorted(json_clean(dict(x=1, y=2)).items())
|
|
|
[('x', 1), ('y', 2)]
|
|
|
>>> sorted(json_clean(dict(x=1, y=2, z=[1,2,3])).items())
|
|
|
[('x', 1), ('y', 2), ('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 = (unicode, int, types.NoneType)
|
|
|
|
|
|
# containers that we need to convert into lists
|
|
|
container_to_list = (tuple, set, types.GeneratorType)
|
|
|
|
|
|
if isinstance(obj, float):
|
|
|
# cast out-of-range floats to their reprs
|
|
|
if math.isnan(obj) or math.isinf(obj):
|
|
|
return repr(obj)
|
|
|
return obj
|
|
|
|
|
|
if isinstance(obj, atomic_ok):
|
|
|
return obj
|
|
|
|
|
|
if isinstance(obj, bytes):
|
|
|
return obj.decode(DEFAULT_ENCODING, 'replace')
|
|
|
|
|
|
if isinstance(obj, container_to_list) or (
|
|
|
hasattr(obj, '__iter__') and hasattr(obj, next_attr_name)):
|
|
|
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)
|
|
|
|
