##// END OF EJS Templates
normalize unicode notebook filenames...
normalize unicode notebook filenames used in comparison check for notebook name change. Unless the filenames are normalized, unchanged names may result in false positives for a name change (e.g. OS X uses NFD on the filesystem, so u'\xfc' roundtripped to the filesystem will be u'u\u0308'), which can result in the first save of a notebook after open performing the following actions: 1. save the recently opened notebook 2. `old_name != new_name`, so name change detected 3. delete old_name (which is actually new_name), which ultimately deletes the just-saved notebook In master, this has a symptom of the first checkpoint failing because the first save actually deleted the file, and you can't checkpoint a notebook that doesn't exist. closes #3360

File last commit:

r10051:8b72bfe0
r10777:9585bda6
Show More
jsonutil.py
224 lines | 7.1 KiB | text/x-python | PythonLexer
"""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 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
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'
# front of PNG base64-encoded
PNG64 = b'iVBORw0KG'
JPEG = b'\xff\xd8'
# front of JPEG base64-encoded
JPEG64 = b'/9'
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):
# make sure we don't double-encode
if not pngdata.startswith(PNG64):
pngdata = encodebytes(pngdata)
encoded['image/png'] = pngdata.decode('ascii')
jpegdata = format_dict.get('image/jpeg')
if isinstance(jpegdata, bytes):
# make sure we don't double-encode
if not jpegdata.startswith(JPEG64):
jpegdata = encodebytes(jpegdata)
encoded['image/jpeg'] = 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)