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- """Utilities to manipulate JSON objects."""
- # NOTE: this is a copy of ipykernel/jsonutils.py (+blackified)
- # Copyright (c) IPython Development Team.
- # Distributed under the terms of the Modified BSD License.
- from __future__ import annotations
- import math
- import numbers
- import re
- import types
- from binascii import b2a_base64
- from datetime import datetime
- from typing import Any
- # -----------------------------------------------------------------------------
- # 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("2000-01-01", "%Y-%m-%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: dict[str, str]) -> dict[str, str]:
- """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.
- """
- return format_dict
- def json_clean(obj: Any) -> Any:
- """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 = (str, 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):
- return b2a_base64(obj).decode("ascii")
- 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 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 iter(obj.items()):
- out[str(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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