hub/venv/lib/python3.7/site-packages/ipykernel/jsonutil.py

198 lines
6.4 KiB
Python

"""Utilities to manipulate JSON objects."""
# Copyright (c) IPython Development Team.
# Distributed under the terms of the Modified BSD License.
from binascii import b2a_base64
import math
import re
import types
from datetime import datetime
import numbers
from ipython_genutils import py3compat
from ipython_genutils.py3compat import unicode_type, iteritems
from ipython_genutils.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{1,6})?Z?([\+\-]\d{2}:?\d{2})?$")
# holy crap, strptime is not threadsafe.
# Calling it once at import seems to help.
datetime.strptime("1", "%d")
#-----------------------------------------------------------------------------
# Classes and functions
#-----------------------------------------------------------------------------
# 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'
# constants for identifying gif data
GIF_64 = b'R0lGODdh'
GIF89_64 = b'R0lGODlh'
# front of PDF base64-encoded
PDF64 = b'JVBER'
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', 'image/jpeg' or 'application/pdf')
is base64-encoded.
"""
# no need for handling of ambiguous bytestrings on Python 3,
# where bytes objects always represent binary data and thus
# base64-encoded.
if py3compat.PY3:
return format_dict
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 = b2a_base64(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 = b2a_base64(jpegdata)
encoded['image/jpeg'] = jpegdata.decode('ascii')
gifdata = format_dict.get('image/gif')
if isinstance(gifdata, bytes):
# make sure we don't double-encode
if not gifdata.startswith((GIF_64, GIF89_64)):
gifdata = b2a_base64(gifdata)
encoded['image/gif'] = gifdata.decode('ascii')
pdfdata = format_dict.get('application/pdf')
if isinstance(pdfdata, bytes):
# make sure we don't double-encode
if not pdfdata.startswith(PDF64):
pdfdata = b2a_base64(pdfdata)
encoded['application/pdf'] = pdfdata.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.
"""
# types that are 'atomic' and ok in json as-is.
atomic_ok = (unicode_type, type(None))
# containers that we need to convert into lists
container_to_list = (tuple, set, types.GeneratorType)
# Since bools are a subtype of Integrals, which are a subtype of Reals,
# we have to check them in that order.
if isinstance(obj, bool):
return obj
if isinstance(obj, numbers.Integral):
# cast int to int, in case subclasses override __str__ (e.g. boost enum, #4598)
return int(obj)
if isinstance(obj, numbers.Real):
# cast out-of-range floats to their reprs
if math.isnan(obj) or math.isinf(obj):
return repr(obj)
return float(obj)
if isinstance(obj, atomic_ok):
return obj
if isinstance(obj, bytes):
if py3compat.PY3:
# unanmbiguous binary data is base64-encoded
# (this probably should have happened upstream)
return b2a_base64(obj).decode('ascii')
else:
# Python 2 bytestr is ambiguous,
# needs special handling for possible binary bytestrings.
# imperfect workaround: if ascii, assume text.
# otherwise assume binary, base64-encode (py3 behavior).
try:
return obj.decode('ascii')
except UnicodeDecodeError:
return b2a_base64(obj).decode('ascii')
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(unicode_type, obj)))
if nkeys != nkeys_collapsed:
raise ValueError('dict cannot 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 iteritems(obj):
out[unicode_type(k)] = json_clean(v)
return out
if isinstance(obj, datetime):
return obj.strftime(ISO8601)
# we don't understand it, it's probably an unserializable object
raise ValueError("Can't clean for JSON: %r" % obj)