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# SPDX-FileCopyrightText: Copyright 2020-2023, Contributors to pocketutils |
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# SPDX-PackageHomePage: https://github.com/dmyersturnbull/pocketutils |
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# SPDX-License-Identifier: Apache-2.0 |
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""" |
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""" |
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import base64 |
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import enum |
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import inspect |
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import json |
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from collections.abc import ( |
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Callable, |
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ItemsView, |
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KeysView, |
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Mapping, |
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Sequence, |
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ValuesView, |
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) |
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from dataclasses import dataclass |
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from datetime import date, datetime, tzinfo |
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from datetime import time as _time |
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from decimal import Decimal |
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from typing import Any, Self |
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from uuid import UUID |
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try: |
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import orjson |
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except ImportError: |
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orjson = None |
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__all__ = ["JsonEncoder", "JsonDecoder", "JsonUtils", "JsonTools"] |
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INF = float("Inf") |
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NEG_INF = float("-Inf") |
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NAN = float("NaN") |
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class MiscTypesJsonDefault(Callable[[Any], Any]): |
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def __call__(self: Self, obj: Any) -> Any: |
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""" |
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Tries to return a serializable result for `obj`. |
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Meant to be passed as `default=` in `orjson.dumps`. |
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Only encodes types that can always be represented exactly, |
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without any loss of information. For that reason, it does not |
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fall back to calling `str` or `repr` for unknown types. |
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Handles, at least: |
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- `decimal.Decimal` → str (scientific notation) |
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- `complex` or `np.complexfloating` → str (e.g. "(3+1j)") |
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- `typing.Mapping` → dict |
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- `typing.ItemsView` → dict |
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- `collections.abc.{Set,Sequence,...}` → list |
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- `enum.Enum` → str (name) |
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- `bytes | bytearray | memoryview` → str (base-64) |
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- `datetime.tzinfo` → str (timezone name) |
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- `typing.NamedTuple` → dict |
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- type or module → str (name) |
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Raise: |
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TypeError: If none of those options worked |
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""" |
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if obj is None: |
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return obj # we should never get here, but this seems safer |
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elif isinstance(obj, str | int | float | datetime | date | _time | UUID): |
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return obj # we should never get here, but let's be safe |
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elif isinstance(obj, Decimal | complex): |
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return str(obj) |
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elif isinstance(obj, enum.Enum): |
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return obj.name |
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elif isinstance(obj, bytes): |
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return base64.b64decode(obj) |
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elif isinstance(obj, bytes | bytearray | memoryview): |
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return base64.b64decode(bytes(obj)) |
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elif isinstance(obj, tzinfo): |
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return obj.tzname(datetime.now(tz=obj)) |
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elif isinstance(obj, set | frozenset | Sequence | KeysView | ValuesView): |
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return list(obj) |
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elif isinstance(obj, Mapping | ItemsView): |
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return dict(obj) |
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elif isinstance(obj, tuple) and hasattr(obj, "_asdict"): |
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# namedtuple |
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return obj._asdict() |
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elif inspect.isclass(obj) or inspect.ismodule(obj): |
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return obj.Self |
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raise TypeError() |
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_misc_types_default = MiscTypesJsonDefault() |
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@dataclass(frozen=True, slots=True, kw_only=True) |
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class JsonEncoder: |
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bytes_options: int |
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str_options: int |
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default: Callable[[Any], Any] |
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prep: Callable[[Any], Any] | None |
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def as_bytes(self: Self, data: Any) -> bytes | bytearray | memoryview: |
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if self.prep is not None: |
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data = self.prep(data) |
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return orjson.dumps(data, default=self.default, option=self.bytes_options) |
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def as_str(self: Self, data: Any) -> str: |
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if self.prep is not None: |
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data = self.prep(data) |
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x = orjson.dumps(data, default=self.default, option=self.str_options) |
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return x.decode(encoding="utf-8") + "\n" |
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@dataclass(frozen=True, slots=True) |
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class JsonDecoder: |
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def from_bytes(self: Self, data: bytes | bytearray | memoryview) -> Any: |
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if not isinstance(data, bytes | bytearray | memoryview): |
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raise TypeError(str(type(data))) |
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if not isinstance(data, bytes): |
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data = bytes(data) |
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if orjson: |
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return orjson.loads(data) |
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return json.loads(data.decode(encoding="utf-8")) |
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def from_str(self: Self, data: str) -> Any: |
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if orjson: |
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return orjson.loads(data) |
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json.loads(data) |
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@dataclass(slots=True, frozen=True) |
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class JsonUtils: |
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def misc_types_default(self: Self) -> Callable[[Any], Any]: |
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return _misc_types_default |
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def new_default( |
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self: Self, |
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*fallbacks: Callable[[Any], Any] | None, |
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first: Callable[[Any], Any] | None = _misc_types_default, |
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last: Callable[[Any], Any] | None = str, |
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) -> Callable[[Any], Any]: |
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""" |
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Creates a new method to be passed as `default=` to `orjson.dumps`. |
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Tries, in order: :meth:`orjson_default`, `fallbacks`, then `str`. |
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Args: |
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first: Try this first |
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fallbacks: Tries these, in order, after `first`, skipping any None |
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last: Use this as the last resort; consider `str` or `repr` |
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""" |
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then = [f for f in [first, *fallbacks] if f is not None] |
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def _default(obj): |
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for t in then: |
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try: |
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return t(obj) |
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except TypeError: |
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pass |
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if last is None: |
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raise TypeError() |
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return last(obj) |
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_default.__name__ = f"default({', '.join([str(t) for t in then])})" |
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return _default |
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def decoder(self: Self) -> JsonDecoder: |
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return JsonDecoder() |
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def encoder( |
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self: Self, |
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*fallbacks: Callable[[Any], Any] | None, |
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indent: bool = True, |
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sort: bool = False, |
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preserve_inf: bool = True, |
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last: Callable[[Any], Any] | None = str, |
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) -> JsonEncoder: |
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""" |
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Serializes to string with orjson, indenting and adding a trailing newline. |
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Uses :meth:`orjson_default` to encode more types than orjson can. |
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Args: |
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indent: Indent by 2 spaces |
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preserve_inf: Preserve infinite values with :meth:`preserve_inf` |
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sort: Sort keys with `orjson.OPT_SORT_KEYS`; |
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only for :meth:`typeddfs.json_utils.JsonEncoder.as_str` |
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last: Last resort option to encode a value |
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""" |
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import orjson |
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bytes_option = orjson.OPT_UTC_Z | orjson.OPT_NON_STR_KEYS |
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str_option = orjson.OPT_UTC_Z |
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if sort: |
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bytes_option |= orjson.OPT_SORT_KEYS |
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str_option |= orjson.OPT_SORT_KEYS |
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if indent: |
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str_option |= orjson.OPT_INDENT_2 |
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default = self.new_default(*fallbacks, first=_misc_types_default, last=last) |
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prep = self.preserve_inf if preserve_inf else None |
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return JsonEncoder(default=default, bytes_options=bytes_option, str_options=str_option, prep=prep) |
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def preserve_inf(self: Self, data: Any) -> Any: |
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""" |
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Recursively replaces infinite float and numpy values with strings. |
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Orjson encodes NaN, inf, and +inf as JSON null. |
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This function converts to string as needed to preserve infinite values. |
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Any float scalar (`np.floating` and `float`) will be replaced with a string. |
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Any `np.ndarray`, whether it contains an infinite value or not, will be converted |
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to an ndarray of strings. |
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The returned result may still not be serializable with orjson or :meth:`orjson_bytes`. |
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Trying those methods is the best way to test for serializeablity. |
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""" |
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# we go to great lengths to avoid importing numpy |
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# no np.isinf, np.isneginf, or np.isnan allowed |
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# we can use the fact that Numpy float types compare to float, |
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# including to -inf and +inf, where all comparisons between Inf/-Inf and NaN are False |
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# So our logic is is_infinite := (data > NEG_INF) != (data < INF) |
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# Meanwhile, we only need to deal with floats: |
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# - int and bool stay as-is |
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# - str stays as-is |
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# - complex gets converted to |
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if isinstance(data, Mapping): |
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return {str(k): self.preserve_inf(v) for k, v in data.items()} |
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elif ( |
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(isinstance(data, Sequence) or type(data).__name__ == "ndarray") |
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and not isinstance(data, str) |
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and not isinstance(data, bytes | bytearray | memoryview) |
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): |
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is_np_float_array = hasattr(data, "dtype") and str(data.dtype).startswith("dtype(float") |
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if ( |
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is_np_float_array |
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or all(isinstance(v, float) for v in data) |
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and all((v > NEG_INF) != (v < INF) for v in data) |
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): |
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# it's a list or array of floats containing -Inf or +Inf |
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# ==> convert to str to preserve |
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return [str(v) for v in data] |
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elif is_np_float_array: |
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# it's an array of other types, or of floats containing neither -Inf nor +Inf |
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# ==> convert to list (faster than recursing) |
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# noinspection PyUnresolvedReferences |
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return data.tolist() |
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else: |
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# it's an array of other types, or of floats containing neither -Inf nor +Inf |
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# ==> return float list as-is |
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return data |
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elif (isinstance(data, float) or (hasattr(data, "dtype") and str(data.dtype).startswith("dtype(float"))) and ( |
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data > NEG_INF |
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) != (data < INF): |
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# single float value with -Inf or +Inf |
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# ==> preserve inf |
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return str(data) |
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elif type(data).__name__ == "ndarray" and hasattr(data, "dtype"): |
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# it's a non-float Numpy array |
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# ==> convert to list |
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return data.astype(str).tolist() |
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return data |
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JsonTools = JsonUtils() |
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