my.core.serialize: orjson with additional default and _serialize hook (#140)
basic orjson serialize, json.dumps fallback
Lots of surrounding changes from this discussion:
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8 changed files with 224 additions and 24 deletions
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@ -531,7 +531,13 @@ def test_guess_datetime() -> None:
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# TODO test @property?
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def asdict(thing) -> Json:
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def is_namedtuple(thing: Any) -> bool:
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# basic check to see if this is namedtuple-like
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_asdict = getattr(thing, '_asdict', None)
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return _asdict and callable(_asdict)
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def asdict(thing: Any) -> Json:
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# todo primitive?
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# todo exception?
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if isinstance(thing, dict):
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@ -539,19 +545,11 @@ def asdict(thing) -> Json:
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import dataclasses as D
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if D.is_dataclass(thing):
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return D.asdict(thing)
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# must be a NT otherwise?
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# todo add a proper check.. ()
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if is_namedtuple(thing):
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return thing._asdict()
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raise TypeError(f'Could not convert object {thing} to dict')
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# todo not sure about naming
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def to_jsons(it) -> Iterable[Json]:
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from .error import error_to_json # prevent circular import
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for r in it:
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if isinstance(r, Exception):
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yield error_to_json(r)
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else:
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yield asdict(r)
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datetime_naive = datetime
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@ -145,15 +145,9 @@ def extract_error_datetime(e: Exception) -> Optional[datetime]:
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import traceback
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from .common import Json
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def error_to_json(e: Exception, *, dt_col: str='dt', tz=None) -> Json:
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edt = extract_error_datetime(e)
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if edt is not None and edt.tzinfo is None and tz is not None:
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edt = edt.replace(tzinfo=tz)
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def error_to_json(e: Exception) -> Json:
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estr = ''.join(traceback.format_exception(Exception, e, e.__traceback__))
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return {
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'error': estr,
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dt_col : edt,
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}
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return {'error': estr}
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def test_datetime_errors() -> None:
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@ -7,7 +7,7 @@ from datetime import datetime
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from pprint import pformat
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from typing import Optional, TYPE_CHECKING, Any, Iterable, Type, List, Dict
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from . import warnings, Res
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from .common import LazyLogger
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from .common import LazyLogger, Json, asdict
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logger = LazyLogger(__name__)
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@ -97,8 +97,23 @@ def check_dataframe(f: FuncT, error_col_policy: ErrorColPolicy='add_if_missing',
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# todo doctor: could have a suggesion to wrap dataframes with it?? discover by return type?
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from .error import error_to_json
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error_to_row = error_to_json # todo deprecate?
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def error_to_row(e: Exception, *, dt_col: str='dt', tz=None) -> Json:
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from .error import error_to_json, extract_error_datetime
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edt = extract_error_datetime(e)
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if edt is not None and edt.tzinfo is None and tz is not None:
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edt = edt.replace(tzinfo=tz)
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err_dict: Json = error_to_json(e)
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err_dict[dt_col] = edt
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return err_dict
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# todo not sure about naming
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def to_jsons(it: Iterable[Res[Any]]) -> Iterable[Json]:
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for r in it:
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if isinstance(r, Exception):
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yield error_to_row(r)
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else:
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yield asdict(r)
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# mm. https://github.com/python/mypy/issues/8564
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@ -111,6 +126,7 @@ def _as_columns(s: Schema) -> Dict[str, Type]:
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if D.is_dataclass(s):
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return {f.name: f.type for f in D.fields(s)}
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# else must be NamedTuple??
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# todo assert my.core.common.is_namedtuple?
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return getattr(s, '_field_types')
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@ -124,7 +140,6 @@ def as_dataframe(it: Iterable[Res[Any]], schema: Optional[Schema]=None) -> DataF
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# https://github.com/pandas-dev/pandas/blob/fc9fdba6592bdb5d0d1147ce4d65639acd897565/pandas/core/frame.py#L562
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# same for NamedTuple -- seems that it takes whatever schema the first NT has
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# so we need to convert each individually... sigh
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from .common import to_jsons
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import pandas as pd
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columns = None if schema is None else list(_as_columns(schema).keys())
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return pd.DataFrame(to_jsons(it), columns=columns)
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189
my/core/serialize.py
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189
my/core/serialize.py
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@ -0,0 +1,189 @@
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import datetime
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from typing import Any, Optional, Callable
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from functools import lru_cache
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from .common import is_namedtuple
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from .error import error_to_json
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# note: it would be nice to combine the 'asdict' and _default_encode to some function
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# that takes a complex python object and returns JSON-compatible fields, while still
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# being a dictionary.
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# a workaround is to encode with dumps below and then json.loads it immediately
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DefaultEncoder = Callable[[Any], Any]
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def _default_encode(obj: Any) -> Any:
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"""
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Encodes complex python datatypes to simpler representations,
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before they're serialized to JSON string
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"""
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# orjson doesn't serialize namedtuples to avoid serializing
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# them as tuples (arrays), since they're technically a subclass
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if is_namedtuple(obj):
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return obj._asdict()
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if isinstance(obj, datetime.timedelta):
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return obj.total_seconds()
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if isinstance(obj, Exception):
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return error_to_json(obj)
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# note: _serialize would only be called for items which aren't already
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# serialized as a dataclass or namedtuple
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# discussion: https://github.com/karlicoss/HPI/issues/138#issuecomment-801704929
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if hasattr(obj, '_serialize') and callable(obj._serialize):
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return obj._serialize()
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raise TypeError(f"Could not serialize object of type {type(obj).__name__}")
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# could possibly run multiple times/raise warning if you provide different 'default'
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# functions or change the kwargs? The alternative is to maintain all of this at the module
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# level, which is just as annoying
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@lru_cache(maxsize=None)
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def _dumps_factory(**kwargs) -> Callable[[Any], str]:
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use_default: DefaultEncoder = _default_encode
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# if the user passed an additional 'default' parameter,
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# try using that to serialize before before _default_encode
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_additional_default: Optional[DefaultEncoder] = kwargs.get("default")
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if _additional_default is not None and callable(_additional_default):
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def wrapped_default(obj: Any) -> Any:
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try:
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# hmm... shouldn't mypy know that _additional_default is not None here?
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# assert _additional_default is not None
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return _additional_default(obj) # type: ignore[misc]
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except TypeError:
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# expected TypeError, signifies couldn't be encoded by custom
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# serializer function. Try _default_encode from here
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return _default_encode(obj)
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use_default = wrapped_default
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kwargs["default"] = use_default
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try:
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import orjson
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# todo: add orjson.OPT_NON_STR_KEYS? would require some bitwise ops
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# most keys are typically attributes from a NT/Dataclass,
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# so most seem to work: https://github.com/ijl/orjson#opt_non_str_keys
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def _orjson_dumps(obj: Any) -> str:
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# orjson returns json as bytes, encode to string
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return orjson.dumps(obj, **kwargs).decode('utf-8')
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return _orjson_dumps
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except ModuleNotFoundError:
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import json
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import warnings
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warnings.warn("You might want to install 'orjson' to support serialization for lots more types!")
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def _stdlib_dumps(obj: Any) -> str:
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return json.dumps(obj, **kwargs)
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return _stdlib_dumps
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def dumps(
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obj: Any,
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default: Optional[DefaultEncoder] = None,
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**kwargs,
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) -> str:
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"""
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Any additional arguments are forwarded -- either to orjson.dumps
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or json.dumps if orjson is not installed
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You can pass the 'option' kwarg to orjson, see here for possible options:
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https://github.com/ijl/orjson#option
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Any class/instance can implement a `_serialize` function, which is used
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to convert it to a JSON-compatible representation.
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If present, it is called during _default_encode
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'default' is called before _default_encode, and should raise a TypeError if
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its not able to serialize the type. As an example:
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from my.core.serialize import dumps
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class MyClass:
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def __init__(self, x):
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self.x = x
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def serialize_default(o: Any) -> Any:
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if isinstance(o, MyClass):
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return {"x": o.x}
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raise TypeError("Could not serialize...")
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dumps({"info": MyClass(5)}, default=serialize_default)
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"""
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return _dumps_factory(default=default, **kwargs)(obj)
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def test_serialize_fallback() -> None:
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import json as jsn # dont cause possible conflicts with module code
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import pytest
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# cant use a namedtuple here, since the default json.dump serializer
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# serializes namedtuples as tuples, which become arrays
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# just test with an array of mixed objects
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X = [5, datetime.timedelta(seconds=5.0)]
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# ignore warnings. depending on test order,
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# the lru_cache'd warning may have already been sent,
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# so checking may be nondeterministic?
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with pytest.warns(None):
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res = jsn.loads(dumps(X))
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assert res == [5, 5.0]
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def test_nt_serialize() -> None:
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import json as jsn # dont cause possible conflicts with module code
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import orjson # import to make sure this is installed
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from typing import NamedTuple
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class A(NamedTuple):
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x: int
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y: float
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res: str = dumps(A(x=1, y=2.0))
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assert res == '{"x":1,"y":2.0}'
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# test orjson option kwarg
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data = {datetime.date(year=1970, month=1, day=1): 5}
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res = jsn.loads(dumps(data, option=orjson.OPT_NON_STR_KEYS))
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assert res == {'1970-01-01': 5}
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def test_default_serializer() -> None:
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import pytest
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import json as jsn # dont cause possible conflicts with module code
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class Unserializable:
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def __init__(self, x: int):
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self.x = x
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# add something handled by the _default_encode function
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self.y = datetime.timedelta(seconds=float(x))
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with pytest.raises(TypeError):
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dumps(Unserializable(5))
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class WithUnderscoreSerialize(Unserializable):
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def _serialize(self) -> Any:
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return {"x": self.x, "y": self.y}
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res = jsn.loads(dumps(WithUnderscoreSerialize(6)))
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assert res == {"x": 6, "y": 6.0}
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# test passing additional 'default' func
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def _serialize_with_default(o: Any) -> Any:
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if isinstance(o, Unserializable):
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return {"x": o.x, "y": o.y}
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raise TypeError("Couldnt serialize")
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# this serializes both Unserializable, which is a custom type otherwise
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# not handled, and timedelta, which is handled by the '_default_encode'
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# in the 'wrapped_default' function
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res2 = jsn.loads(dumps(Unserializable(10), default=_serialize_with_default))
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assert res2 == {"x": 10, "y": 10.0}
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1
setup.py
1
setup.py
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@ -55,6 +55,7 @@ def main():
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'optional': [
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# todo document these?
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'logzero',
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'orjson',
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'cachew>=0.8.0',
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'mypy', # used for config checks
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],
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@ -18,3 +18,4 @@ from my.core.util import *
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from my.core.discovery_pure import *
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from my.core.types import *
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from my.core.stats import *
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from my.core.serialize import test_serialize_fallback
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1
tests/serialize.py
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1
tests/serialize.py
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@ -0,0 +1 @@
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from my.core.serialize import *
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1
tox.ini
1
tox.ini
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@ -23,6 +23,7 @@ setenv = MY_CONFIG = nonexistent
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commands =
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pip install -e .[testing]
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pip install cachew
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pip install orjson
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hpi module install my.location.google
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pip install ijson # optional dependency
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