:py:mod:`medcat.utils.saving.coding` ==================================== .. py:module:: medcat.utils.saving.coding Module Contents --------------- Classes ~~~~~~~ .. autoapisummary:: medcat.utils.saving.coding.EncodeableObject medcat.utils.saving.coding.PartEncoder medcat.utils.saving.coding.SetEncoder medcat.utils.saving.coding.PartDecoder medcat.utils.saving.coding.SetDecoder medcat.utils.saving.coding.PatternEncoder medcat.utils.saving.coding.PatternDecoder medcat.utils.saving.coding.CustomDelegatingEncoder medcat.utils.saving.coding.CustomDelegatingDecoder Functions ~~~~~~~~~ .. autoapisummary:: medcat.utils.saving.coding.register_encoder_decoder medcat.utils.saving.coding.default_hook medcat.utils.saving.coding.default_postprocessing Attributes ~~~~~~~~~~ .. autoapisummary:: medcat.utils.saving.coding.SET_IDENTIFIER medcat.utils.saving.coding.PATTERN_IDENTIFIER medcat.utils.saving.coding.PostProcessor medcat.utils.saving.coding.DEFAULT_ENCODERS medcat.utils.saving.coding.DEFAULT_DECODERS medcat.utils.saving.coding.LOADING_POSTPROCESSORS .. py:class:: EncodeableObject Bases: :py:obj:`Protocol` Base class for protocol classes. Protocol classes are defined as:: class Proto(Protocol): def meth(self) -> int: ... Such classes are primarily used with static type checkers that recognize structural subtyping (static duck-typing), for example:: class C: def meth(self) -> int: return 0 def func(x: Proto) -> int: return x.meth() func(C()) # Passes static type check See PEP 544 for details. Protocol classes decorated with @typing.runtime_checkable act as simple-minded runtime protocols that check only the presence of given attributes, ignoring their type signatures. Protocol classes can be generic, they are defined as:: class GenProto(Protocol[T]): def meth(self) -> T: ... .. py:method:: to_dict() Converts the object to a dict. :Returns: **dict** -- The dict to be serialised. .. py:exception:: UnsuitableObject Bases: :py:obj:`ValueError` Inappropriate argument value (of correct type). .. py:class:: PartEncoder Bases: :py:obj:`Protocol` Base class for protocol classes. Protocol classes are defined as:: class Proto(Protocol): def meth(self) -> int: ... Such classes are primarily used with static type checkers that recognize structural subtyping (static duck-typing), for example:: class C: def meth(self) -> int: return 0 def func(x: Proto) -> int: return x.meth() func(C()) # Passes static type check See PEP 544 for details. Protocol classes decorated with @typing.runtime_checkable act as simple-minded runtime protocols that check only the presence of given attributes, ignoring their type signatures. Protocol classes can be generic, they are defined as:: class GenProto(Protocol[T]): def meth(self) -> T: ... .. py:method:: try_encode(obj) Try to encode an object :param obj: The object to encode :type obj: object :raises UnsuitableObject: If the object is unsuitable for encoding. :Returns: **Any** -- The encoded object .. py:data:: SET_IDENTIFIER :value: '==SET==' .. py:data:: PATTERN_IDENTIFIER :value: '==PATTERN==' .. py:class:: SetEncoder Bases: :py:obj:`PartEncoder` JSONEncoder (and decoder) for sets. Generally, JSON doesn't support serializing of sets natively. This encoder adds a set identifier to the data when being serialized and provides a method to read said identifier upon decoding. .. py:method:: try_encode(obj) Try to encode an object :param obj: The object to encode :type obj: object :raises UnsuitableObject: If the object is unsuitable for encoding. :Returns: **Any** -- The encoded object .. py:class:: PartDecoder Bases: :py:obj:`Protocol` Base class for protocol classes. Protocol classes are defined as:: class Proto(Protocol): def meth(self) -> int: ... Such classes are primarily used with static type checkers that recognize structural subtyping (static duck-typing), for example:: class C: def meth(self) -> int: return 0 def func(x: Proto) -> int: return x.meth() func(C()) # Passes static type check See PEP 544 for details. Protocol classes decorated with @typing.runtime_checkable act as simple-minded runtime protocols that check only the presence of given attributes, ignoring their type signatures. Protocol classes can be generic, they are defined as:: class GenProto(Protocol[T]): def meth(self) -> T: ... .. py:method:: try_decode(dct) Try to decode the dictionary. :param dct: The dict to decode. :type dct: dict :Returns: **Union[dict, Any]** -- The dict if unable to decode, the decoded object otherwise .. py:class:: SetDecoder Bases: :py:obj:`PartDecoder` Base class for protocol classes. Protocol classes are defined as:: class Proto(Protocol): def meth(self) -> int: ... Such classes are primarily used with static type checkers that recognize structural subtyping (static duck-typing), for example:: class C: def meth(self) -> int: return 0 def func(x: Proto) -> int: return x.meth() func(C()) # Passes static type check See PEP 544 for details. Protocol classes decorated with @typing.runtime_checkable act as simple-minded runtime protocols that check only the presence of given attributes, ignoring their type signatures. Protocol classes can be generic, they are defined as:: class GenProto(Protocol[T]): def meth(self) -> T: ... .. py:method:: try_decode(dct) Decode sets from input dicts. :param dct: The input dict :type dct: dict :Returns: **Union[dict, set]** -- The original dict if this was not a serialized set, the set otherwise .. py:class:: PatternEncoder Bases: :py:obj:`PartEncoder` Base class for protocol classes. Protocol classes are defined as:: class Proto(Protocol): def meth(self) -> int: ... Such classes are primarily used with static type checkers that recognize structural subtyping (static duck-typing), for example:: class C: def meth(self) -> int: return 0 def func(x: Proto) -> int: return x.meth() func(C()) # Passes static type check See PEP 544 for details. Protocol classes decorated with @typing.runtime_checkable act as simple-minded runtime protocols that check only the presence of given attributes, ignoring their type signatures. Protocol classes can be generic, they are defined as:: class GenProto(Protocol[T]): def meth(self) -> T: ... .. py:method:: try_encode(obj) Try to encode an object :param obj: The object to encode :type obj: object :raises UnsuitableObject: If the object is unsuitable for encoding. :Returns: **Any** -- The encoded object .. py:class:: PatternDecoder Bases: :py:obj:`PartDecoder` Base class for protocol classes. Protocol classes are defined as:: class Proto(Protocol): def meth(self) -> int: ... Such classes are primarily used with static type checkers that recognize structural subtyping (static duck-typing), for example:: class C: def meth(self) -> int: return 0 def func(x: Proto) -> int: return x.meth() func(C()) # Passes static type check See PEP 544 for details. Protocol classes decorated with @typing.runtime_checkable act as simple-minded runtime protocols that check only the presence of given attributes, ignoring their type signatures. Protocol classes can be generic, they are defined as:: class GenProto(Protocol[T]): def meth(self) -> T: ... .. py:method:: try_decode(dct) Decode re.Patttern from input dicts. :param dct: The input dict :type dct: dict :Returns: **Union[dict, set]** -- The original dict if this was not a serialized pattern, the pattern otherwise .. py:data:: PostProcessor .. py:data:: DEFAULT_ENCODERS :type: List[Type[PartEncoder]] .. py:data:: DEFAULT_DECODERS :type: List[Type[PartDecoder]] .. py:data:: LOADING_POSTPROCESSORS :type: List[PostProcessor] :value: [] .. py:function:: register_encoder_decoder(encoder, decoder, loading_postprocessor) .. py:class:: CustomDelegatingEncoder(delegates, *args, **kwargs) Bases: :py:obj:`json.JSONEncoder` Extensible JSON encoder for Python data structures. Supports the following objects and types by default: +-------------------+---------------+ | Python | JSON | +===================+===============+ | dict | object | +-------------------+---------------+ | list, tuple | array | +-------------------+---------------+ | str | string | +-------------------+---------------+ | int, 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``). .. py:method:: __init__(delegates, *args, **kwargs) 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, 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 non-ASCII characters escaped. If ensure_ascii is false, the output can contain non-ASCII characters. 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 RecursionError). 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 an (item_separator, key_separator) tuple. The default is (', ', ': ') if *indent* is ``None`` and (',', ': ') otherwise. 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``. .. py:method:: default(obj) 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) # Let the base class default method raise the TypeError return JSONEncoder.default(self, o) .. py:method:: def_inst(*args, **kwargs) :classmethod: .. py:class:: CustomDelegatingDecoder(delegates) Bases: :py:obj:`json.JSONDecoder` Simple JSON decoder Performs the following translations in decoding by default: +---------------+-------------------+ | JSON | Python | +===============+===================+ | object | dict | +---------------+-------------------+ | array | list | +---------------+-------------------+ | string | str | +---------------+-------------------+ | number (int) | int | +---------------+-------------------+ | number (real) | float | +---------------+-------------------+ | true | True | +---------------+-------------------+ | false | False | +---------------+-------------------+ | null | None | +---------------+-------------------+ It also understands ``NaN``, ``Infinity``, and ``-Infinity`` as their corresponding ``float`` values, which is outside the JSON spec. .. py:attribute:: _def_inst :type: Optional[CustomDelegatingDecoder] .. py:method:: __init__(delegates) ``object_hook``, if specified, will be called with the result of every JSON object decoded and its return value will be used in place of the given ``dict``. This can be used to provide custom deserializations (e.g. to support JSON-RPC class hinting). ``object_pairs_hook``, if specified will be called with the result of every JSON object decoded with an ordered list of pairs. The return value of ``object_pairs_hook`` will be used instead of the ``dict``. This feature can be used to implement custom decoders. If ``object_hook`` is also defined, the ``object_pairs_hook`` takes priority. ``parse_float``, if specified, will be called with the string of every JSON float to be decoded. By default this is equivalent to float(num_str). This can be used to use another datatype or parser for JSON floats (e.g. decimal.Decimal). ``parse_int``, if specified, will be called with the string of every JSON int to be decoded. By default this is equivalent to int(num_str). This can be used to use another datatype or parser for JSON integers (e.g. float). ``parse_constant``, if specified, will be called with one of the following strings: -Infinity, Infinity, NaN. This can be used to raise an exception if invalid JSON numbers are encountered. If ``strict`` is false (true is the default), then control characters will be allowed inside strings. Control characters in this context are those with character codes in the 0-31 range, including ``'\t'`` (tab), ``'\n'``, ``'\r'`` and ``'\0'``. .. py:method:: object_hook(dct) .. py:method:: def_inst() :classmethod: .. py:function:: default_hook(dct) .. py:function:: default_postprocessing(cdb)