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- """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)
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