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Jython is an implementation of the high-level, dynamic, object-oriented
language Python written in 100% Pure Java, and seamlessly integrated with
the Java platform. It thus allows you to run Python on any Java platform.
"""Implementation of JSONEncoder
"""
import re
try:
from _json import encode_basestring_ascii as c_encode_basestring_ascii
except ImportError:
c_encode_basestring_ascii = None
try:
from _json import make_encoder as c_make_encoder
except ImportError:
c_make_encoder = None
ESCAPE = re.compile(r'[\x00-\x1f\\"\b\f\n\r\t]')
ESCAPE_ASCII = re.compile(r'([\\"]|[^\ -~])')
HAS_UTF8 = re.compile(r'[\x80-\xff]')
ESCAPE_DCT = {
'\\': '\\\\',
'"': '\\"',
'\b': '\\b',
'\f': '\\f',
'\n': '\\n',
'\r': '\\r',
'\t': '\\t',
}
for i in range(0x20):
ESCAPE_DCT.setdefault(chr(i), '\\u{0:04x}'.format(i))
#ESCAPE_DCT.setdefault(chr(i), '\\u%04x' % (i,))
# Assume this produces an infinity on all machines (probably not guaranteed)
INFINITY = float('1e66666')
FLOAT_REPR = repr
def encode_basestring(s):
"""Return a JSON representation of a Python string
"""
def replace(match):
return ESCAPE_DCT[match.group(0)]
return '"' + ESCAPE.sub(replace, s) + '"'
def py_encode_basestring_ascii(s):
"""Return an ASCII-only JSON representation of a Python string
"""
if isinstance(s, str) and HAS_UTF8.search(s) is not None:
s = s.decode('utf-8')
def replace(match):
s = match.group(0)
try:
return ESCAPE_DCT[s]
except KeyError:
n = ord(s)
if n < 0x10000:
return '\\u{0:04x}'.format(n)
#return '\\u%04x' % (n,)
else:
# surrogate pair
n -= 0x10000
s1 = 0xd800 | ((n >> 10) & 0x3ff)
s2 = 0xdc00 | (n & 0x3ff)
return '\\u{0:04x}\\u{1:04x}'.format(s1, s2)
#return '\\u%04x\\u%04x' % (s1, s2)
return '"' + str(ESCAPE_ASCII.sub(replace, s)) + '"'
encode_basestring_ascii = (
c_encode_basestring_ascii or py_encode_basestring_ascii)
class JSONEncoder(object):
"""Extensible JSON encoder for Python data structures.
Supports the following objects and types by default:
+-------------------+---------------+
| Python | JSON |
+===================+===============+
| dict | object |
+-------------------+---------------+
| list, tuple | array |
+-------------------+---------------+
| str, unicode | string |
+-------------------+---------------+
| int, long, float | number |
+-------------------+---------------+
| True | true |
+-------------------+---------------+
| False | false |
+-------------------+---------------+
| None | null |
+-------------------+---------------+
To extend this to recognize other objects, subclass and implement a
``.default()`` method with another method that returns a serializable
object for ``o`` if possible, otherwise it should call the superclass
implementation (to raise ``TypeError``).
"""
item_separator = ', '
key_separator = ': '
def __init__(self, skipkeys=False, ensure_ascii=True,
check_circular=True, allow_nan=True, sort_keys=False,
indent=None, separators=None, encoding='utf-8', default=None):
"""Constructor for JSONEncoder, with sensible defaults.
If skipkeys is false, then it is a TypeError to attempt
encoding of keys that are not str, int, long, float or None. If
skipkeys is True, such items are simply skipped.
If ensure_ascii is true, the output is guaranteed to be str
objects with all incoming unicode characters escaped. If
ensure_ascii is false, the output will be unicode object.
If check_circular is true, then lists, dicts, and custom encoded
objects will be checked for circular references during encoding to
prevent an infinite recursion (which would cause an OverflowError).
Otherwise, no such check takes place.
If allow_nan is true, then NaN, Infinity, and -Infinity will be
encoded as such. This behavior is not JSON specification compliant,
but is consistent with most JavaScript based encoders and decoders.
Otherwise, it will be a ValueError to encode such floats.
If sort_keys is true, then the output of dictionaries will be
sorted by key; this is useful for regression tests to ensure
that JSON serializations can be compared on a day-to-day basis.
If indent is a non-negative integer, then JSON array
elements and object members will be pretty-printed with that
indent level. An indent level of 0 will only insert newlines.
None is the most compact representation.
If specified, separators should be a (item_separator, key_separator)
tuple. The default is (', ', ': '). To get the most compact JSON
representation you should specify (',', ':') to eliminate whitespace.
If specified, default is a function that gets called for objects
that can't otherwise be serialized. It should return a JSON encodable
version of the object or raise a ``TypeError``.
If encoding is not None, then all input strings will be
transformed into unicode using that encoding prior to JSON-encoding.
The default is UTF-8.
"""
self.skipkeys = skipkeys
self.ensure_ascii = ensure_ascii
self.check_circular = check_circular
self.allow_nan = allow_nan
self.sort_keys = sort_keys
self.indent = indent
if separators is not None:
self.item_separator, self.key_separator = separators
if default is not None:
self.default = default
self.encoding = encoding
def default(self, o):
"""Implement this method in a subclass such that it returns
a serializable object for ``o``, or calls the base implementation
(to raise a ``TypeError``).
For example, to support arbitrary iterators, you could
implement default like this::
def default(self, o):
try:
iterable = iter(o)
except TypeError:
pass
else:
return list(iterable)
return JSONEncoder.default(self, o)
"""
raise TypeError(repr(o) + " is not JSON serializable")
def encode(self, o):
"""Return a JSON string representation of a Python data structure.
>>> JSONEncoder().encode({"foo": ["bar", "baz"]})
'{"foo": ["bar", "baz"]}'
"""
# This is for extremely simple cases and benchmarks.
if isinstance(o, basestring):
if isinstance(o, str):
_encoding = self.encoding
if (_encoding is not None
and not (_encoding == 'utf-8')):
o = o.decode(_encoding)
if self.ensure_ascii:
return encode_basestring_ascii(o)
else:
return encode_basestring(o)
# This doesn't pass the iterator directly to ''.join() because the
# exceptions aren't as detailed. The list call should be roughly
# equivalent to the PySequence_Fast that ''.join() would do.
chunks = self.iterencode(o, _one_shot=True)
if not isinstance(chunks, (list, tuple)):
chunks = list(chunks)
return ''.join(chunks)
def iterencode(self, o, _one_shot=False):
"""Encode the given object and yield each string
representation as available.
For example::
for chunk in JSONEncoder().iterencode(bigobject):
mysocket.write(chunk)
"""
if self.check_circular:
markers = {}
else:
markers = None
if self.ensure_ascii:
_encoder = encode_basestring_ascii
else:
_encoder = encode_basestring
if self.encoding != 'utf-8':
def _encoder(o, _orig_encoder=_encoder, _encoding=self.encoding):
if isinstance(o, str):
o = o.decode(_encoding)
return _orig_encoder(o)
def floatstr(o, allow_nan=self.allow_nan,
_repr=FLOAT_REPR, _inf=INFINITY, _neginf=-INFINITY):
# Check for specials. Note that this type of test is processor
# and/or platform-specific, so do tests which don't depend on the
# internals.
if o != o:
text = 'NaN'
elif o == _inf:
text = 'Infinity'
elif o == _neginf:
text = '-Infinity'
else:
return _repr(o)
if not allow_nan:
raise ValueError(
"Out of range float values are not JSON compliant: " +
repr(o))
return text
if (_one_shot and c_make_encoder is not None
and self.indent is None and not self.sort_keys):
_iterencode = c_make_encoder(
markers, self.default, _encoder, self.indent,
self.key_separator, self.item_separator, self.sort_keys,
self.skipkeys, self.allow_nan)
else:
_iterencode = _make_iterencode(
markers, self.default, _encoder, self.indent, floatstr,
self.key_separator, self.item_separator, self.sort_keys,
self.skipkeys, _one_shot)
return _iterencode(o, 0)
def _make_iterencode(markers, _default, _encoder, _indent, _floatstr,
_key_separator, _item_separator, _sort_keys, _skipkeys, _one_shot,
## HACK: hand-optimized bytecode; turn globals into locals
ValueError=ValueError,
basestring=basestring,
dict=dict,
float=float,
id=id,
int=int,
isinstance=isinstance,
list=list,
long=long,
str=str,
tuple=tuple,
):
def _iterencode_list(lst, _current_indent_level):
if not lst:
yield '[]'
return
if markers is not None:
markerid = id(lst)
if markerid in markers:
raise ValueError("Circular reference detected")
markers[markerid] = lst
buf = '['
if _indent is not None:
_current_indent_level += 1
newline_indent = '\n' + (' ' * (_indent * _current_indent_level))
separator = _item_separator + newline_indent
buf += newline_indent
else:
newline_indent = None
separator = _item_separator
first = True
for value in lst:
if first:
first = False
else:
buf = separator
if isinstance(value, basestring):
yield buf + _encoder(value)
elif value is None:
yield buf + 'null'
elif value is True:
yield buf + 'true'
elif value is False:
yield buf + 'false'
elif isinstance(value, (int, long)):
yield buf + str(value)
elif isinstance(value, float):
yield buf + _floatstr(value)
else:
yield buf
if isinstance(value, (list, tuple)):
chunks = _iterencode_list(value, _current_indent_level)
elif isinstance(value, dict):
chunks = _iterencode_dict(value, _current_indent_level)
else:
chunks = _iterencode(value, _current_indent_level)
for chunk in chunks:
yield chunk
if newline_indent is not None:
_current_indent_level -= 1
yield '\n' + (' ' * (_indent * _current_indent_level))
yield ']'
if markers is not None:
del markers[markerid]
def _iterencode_dict(dct, _current_indent_level):
if not dct:
yield '{}'
return
if markers is not None:
markerid = id(dct)
if markerid in markers:
raise ValueError("Circular reference detected")
markers[markerid] = dct
yield '{'
if _indent is not None:
_current_indent_level += 1
newline_indent = '\n' + (' ' * (_indent * _current_indent_level))
item_separator = _item_separator + newline_indent
yield newline_indent
else:
newline_indent = None
item_separator = _item_separator
first = True
if _sort_keys:
items = sorted(dct.items(), key=lambda kv: kv[0])
else:
items = dct.iteritems()
for key, value in items:
if isinstance(key, basestring):
pass
# JavaScript is weakly typed for these, so it makes sense to
# also allow them. Many encoders seem to do something like this.
elif isinstance(key, float):
key = _floatstr(key)
elif key is True:
key = 'true'
elif key is False:
key = 'false'
elif key is None:
key = 'null'
elif isinstance(key, (int, long)):
key = str(key)
elif _skipkeys:
continue
else:
raise TypeError("key " + repr(key) + " is not a string")
if first:
first = False
else:
yield item_separator
yield _encoder(key)
yield _key_separator
if isinstance(value, basestring):
yield _encoder(value)
elif value is None:
yield 'null'
elif value is True:
yield 'true'
elif value is False:
yield 'false'
elif isinstance(value, (int, long)):
yield str(value)
elif isinstance(value, float):
yield _floatstr(value)
else:
if isinstance(value, (list, tuple)):
chunks = _iterencode_list(value, _current_indent_level)
elif isinstance(value, dict):
chunks = _iterencode_dict(value, _current_indent_level)
else:
chunks = _iterencode(value, _current_indent_level)
for chunk in chunks:
yield chunk
if newline_indent is not None:
_current_indent_level -= 1
yield '\n' + (' ' * (_indent * _current_indent_level))
yield '}'
if markers is not None:
del markers[markerid]
def _iterencode(o, _current_indent_level):
if isinstance(o, basestring):
yield _encoder(o)
elif o is None:
yield 'null'
elif o is True:
yield 'true'
elif o is False:
yield 'false'
elif isinstance(o, (int, long)):
yield str(o)
elif isinstance(o, float):
yield _floatstr(o)
elif isinstance(o, (list, tuple)):
for chunk in _iterencode_list(o, _current_indent_level):
yield chunk
elif isinstance(o, dict):
for chunk in _iterencode_dict(o, _current_indent_level):
yield chunk
else:
if markers is not None:
markerid = id(o)
if markerid in markers:
raise ValueError("Circular reference detected")
markers[markerid] = o
o = _default(o)
for chunk in _iterencode(o, _current_indent_level):
yield chunk
if markers is not None:
del markers[markerid]
return _iterencode