Coverage for /pythoncovmergedfiles/medio/medio/usr/local/lib/python3.11/site-packages/nbclient/jsonutil.py: 40%

1"""Utilities to manipulate JSON objects.""" 

2 

3# NOTE: this is a copy of ipykernel/jsonutils.py (+blackified) 

4 

5# Copyright (c) IPython Development Team. 

6# Distributed under the terms of the Modified BSD License. 

7from __future__ import annotations 

8 

9import math 

10import numbers 

11import re 

12import types 

13from binascii import b2a_base64 

14from datetime import datetime 

15from typing import Any 

16 

17# ----------------------------------------------------------------------------- 

18# Globals and constants 

19# ----------------------------------------------------------------------------- 

20 

21# timestamp formats 

22ISO8601 = "%Y-%m-%dT%H:%M:%S.%f" 

23ISO8601_PAT = re.compile( 

24 r"^(\d{4}-\d{2}-\d{2}T\d{2}:\d{2}:\d{2})(\.\d{1,6})?Z?([\+\-]\d{2}:?\d{2})?$" 

25) 

26 

27# holy crap, strptime is not threadsafe. 

28# Calling it once at import seems to help. 

29datetime.strptime("2000-01-01", "%Y-%m-%d") 

30 

31# ----------------------------------------------------------------------------- 

32# Classes and functions 

33# ----------------------------------------------------------------------------- 

34 

35 

36# constants for identifying png/jpeg data 

37PNG = b"\x89PNG\r\n\x1a\n" 

38# front of PNG base64-encoded 

39PNG64 = b"iVBORw0KG" 

40JPEG = b"\xff\xd8" 

41# front of JPEG base64-encoded 

42JPEG64 = b"/9" 

43# constants for identifying gif data 

44GIF_64 = b"R0lGODdh" 

45GIF89_64 = b"R0lGODlh" 

46# front of PDF base64-encoded 

47PDF64 = b"JVBER" 

48 

49 

50def encode_images(format_dict: dict[str, str]) -> dict[str, str]: 

51 """b64-encodes images in a displaypub format dict 

52 

53 Perhaps this should be handled in json_clean itself? 

54 

55 Parameters 

56 ---------- 

57 

58 format_dict : dict 

59 A dictionary of display data keyed by mime-type 

60 

61 Returns 

62 ------- 

63 

64 format_dict : dict 

65 A copy of the same dictionary, 

66 but binary image data ('image/png', 'image/jpeg' or 'application/pdf') 

67 is base64-encoded. 

68 

69 """ 

70 return format_dict 

71 

72 

73def json_clean(obj: Any) -> Any: 

74 """Clean an object to ensure it's safe to encode in JSON. 

75 

76 Atomic, immutable objects are returned unmodified. Sets and tuples are 

77 converted to lists, lists are copied and dicts are also copied. 

78 

79 Note: dicts whose keys could cause collisions upon encoding (such as a dict 

80 with both the number 1 and the string '1' as keys) will cause a ValueError 

81 to be raised. 

82 

83 Parameters 

84 ---------- 

85 obj : any python object 

86 

87 Returns 

88 ------- 

89 out : object 

90 

91 A version of the input which will not cause an encoding error when 

92 encoded as JSON. Note that this function does not *encode* its inputs, 

93 it simply sanitizes it so that there will be no encoding errors later. 

94 

95 """ 

96 # types that are 'atomic' and ok in json as-is. 

97 atomic_ok = (str, type(None)) 

98 

99 # containers that we need to convert into lists 

100 container_to_list = (tuple, set, types.GeneratorType) 

101 

102 # Since bools are a subtype of Integrals, which are a subtype of Reals, 

103 # we have to check them in that order. 

104 

105 if isinstance(obj, bool): 

106 return obj 

107 

108 if isinstance(obj, numbers.Integral): 

109 # cast int to int, in case subclasses override __str__ (e.g. boost enum, #4598) 

110 return int(obj) 

111 

112 if isinstance(obj, numbers.Real): 

113 # cast out-of-range floats to their reprs 

114 if math.isnan(obj) or math.isinf(obj): 

115 return repr(obj) 

116 return float(obj) 

117 

118 if isinstance(obj, atomic_ok): 

119 return obj 

120 

121 if isinstance(obj, bytes): 

122 return b2a_base64(obj).decode("ascii") 

123 

124 if isinstance(obj, container_to_list) or ( 

125 hasattr(obj, "__iter__") and hasattr(obj, "__next__") 

126 ): 

127 obj = list(obj) 

128 

129 if isinstance(obj, list): 

130 return [json_clean(x) for x in obj] 

131 

132 if isinstance(obj, dict): 

133 # First, validate that the dict won't lose data in conversion due to 

134 # key collisions after stringification. This can happen with keys like 

135 # True and 'true' or 1 and '1', which collide in JSON. 

136 nkeys = len(obj) 

137 nkeys_collapsed = len(set(map(str, obj))) 

138 if nkeys != nkeys_collapsed: 

139 raise ValueError( 

140 "dict cannot be safely converted to JSON: " 

141 "key collision would lead to dropped values" 

142 ) 

143 # If all OK, proceed by making the new dict that will be json-safe 

144 out = {} 

145 for k, v in iter(obj.items()): 

146 out[str(k)] = json_clean(v) 

147 return out 

148 if isinstance(obj, datetime): 

149 return obj.strftime(ISO8601) 

150 

151 # we don't understand it, it's probably an unserializable object 

152 raise ValueError("Can't clean for JSON: %r" % obj)