BUG: binary operations with custom classes raise errors

[mvashishtha]

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Reproducible Example

import modin.pandas as pd
import pandas

class CustomNumber():
  def __init__(self, value: int):
    self.value = value
  def __add__(self, other):
    return self.value + other
  def __radd__(self, other):
    return other + self.value

# pandas works without error and gives series of [5]
print(pandas.Series([1]) + CustomNumber(4))
# modin raises error
print(pd.Series([1]) + CustomNumber(4))

Issue Description

other is not a scalar in _validate_other here, so we check dtype here and raise TypeError.

Expected Behavior

Can add custom classes that overload addition operators to pandas objects.

Error Logs

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
Input In [1], in <cell line: 15>()
     13 print(pandas.Series([1]) + CustomNumber(4))
     14 # raises error
---> 15 print(pd.Series([1]) + CustomNumber(4))

File ~/software_sources/modin/modin/logging/logger_decorator.py:128, in enable_logging.<locals>.decorator.<locals>.run_and_log(*args, **kwargs)
    113 """
    114 Compute function with logging if Modin logging is enabled.
    115
   (...)
    125 Any
    126 """
    127 if LogMode.get() == "disable":
--> 128     return obj(*args, **kwargs)
    130 logger = get_logger()
    131 logger_level = getattr(logger, log_level)

File ~/software_sources/modin/modin/pandas/series.py:172, in Series.__add__(self, right)
    170 @_doc_binary_op(operation="addition", bin_op="add")
    171 def __add__(self, right):
--> 172     return self.add(right)

File ~/software_sources/modin/modin/logging/logger_decorator.py:128, in enable_logging.<locals>.decorator.<locals>.run_and_log(*args, **kwargs)
    113 """
    114 Compute function with logging if Modin logging is enabled.
    115
   (...)
    125 Any
    126 """
    127 if LogMode.get() == "disable":
--> 128     return obj(*args, **kwargs)
    130 logger = get_logger()
    131 logger_level = getattr(logger, log_level)

File ~/software_sources/modin/modin/pandas/series.py:495, in Series.add(self, other, level, fill_value, axis)
    491 """
    492 Return Addition of series and other, element-wise (binary operator add).
    493 """
    494 new_self, new_other = self._prepare_inter_op(other)
--> 495 return super(Series, new_self).add(
    496     new_other, level=level, fill_value=fill_value, axis=axis
    497 )

File ~/software_sources/modin/modin/logging/logger_decorator.py:128, in enable_logging.<locals>.decorator.<locals>.run_and_log(*args, **kwargs)
    113 """
    114 Compute function with logging if Modin logging is enabled.
    115
   (...)
    125 Any
    126 """
    127 if LogMode.get() == "disable":
--> 128     return obj(*args, **kwargs)
    130 logger = get_logger()
    131 logger_level = getattr(logger, log_level)

File ~/software_sources/modin/modin/pandas/base.py:571, in BasePandasDataset.add(self, other, axis, level, fill_value)
    565 def add(
    566     self, other, axis="columns", level=None, fill_value=None
    567 ):  # noqa: PR01, RT01, D200
    568     """
    569     Return addition of `BasePandasDataset` and `other`, element-wise (binary operator `add`).
    570     """
--> 571     return self._binary_op(
    572         "add", other, axis=axis, level=level, fill_value=fill_value
    573     )

File ~/software_sources/modin/modin/logging/logger_decorator.py:128, in enable_logging.<locals>.decorator.<locals>.run_and_log(*args, **kwargs)
    113 """
    114 Compute function with logging if Modin logging is enabled.
    115
   (...)
    125 Any
    126 """
    127 if LogMode.get() == "disable":
--> 128     return obj(*args, **kwargs)
    130 logger = get_logger()
    131 logger_level = getattr(logger, log_level)

File ~/software_sources/modin/modin/pandas/base.py:396, in BasePandasDataset._binary_op(self, op, other, **kwargs)
    392     kwargs.pop("broadcast", None)
    393     return self._default_to_pandas(
    394         getattr(self._pandas_class, op), other, **kwargs
    395     )
--> 396 other = self._validate_other(other, axis, dtype_check=True)
    397 exclude_list = [
    398     "__add__",
    399     "__radd__",
   (...)
    405     "__rxor__",
    406 ]
    407 if op in exclude_list:

File ~/software_sources/modin/modin/logging/logger_decorator.py:128, in enable_logging.<locals>.decorator.<locals>.run_and_log(*args, **kwargs)
    113 """
    114 Compute function with logging if Modin logging is enabled.
    115
   (...)
    125 Any
    126 """
    127 if LogMode.get() == "disable":
--> 128     return obj(*args, **kwargs)
    130 logger = get_logger()
    131 logger_level = getattr(logger, log_level)

File ~/software_sources/modin/modin/pandas/base.py:317, in BasePandasDataset._validate_other(self, other, axis, dtype_check, compare_index)
    299         self_dtypes = [
    300             dtype
    301             for label, dtype in zip(
   (...)
    304             if label in other
    305         ]
    307     if not all(
    308         (is_numeric_dtype(self_dtype) and is_numeric_dtype(other_dtype))
    309         or (is_object_dtype(self_dtype) and is_object_dtype(other_dtype))
   (...)
    315         for self_dtype, other_dtype in zip(self_dtypes, other_dtypes)
    316     ):
--> 317         raise TypeError("Cannot do operation with improper dtypes")
    318 return result

TypeError: Cannot do operation with improper dtypes

Installed Versions

INSTALLED VERSIONS

commit : fd776a5
python : 3.8.13.final.0
python-bits : 64
OS : Darwin
OS-release : 21.5.0
Version : Darwin Kernel Version 21.5.0: Tue Apr 26 21:08:22 PDT 2022; root:xnu-8020.121.3~4/RELEASE_X86_64
machine : x86_64
processor : i386
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8

Modin dependencies

modin : 0.17.0+9.gfd776a5a
ray : 2.0.1
dask : 2022.01.1
distributed : 2022.01.1
hdk : None

pandas dependencies

pandas : 1.5.1
numpy : 1.23.1
pytz : 2022.1
dateutil : 2.8.2
setuptools : 61.2.0
pip : 22.1.2
Cython : None
pytest : 7.1.2
hypothesis : None
sphinx : 5.1.1
blosc : None
feather : 0.4.1
xlsxwriter : None
lxml.etree : 4.9.1
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 3.1.2
IPython : 8.4.0
pandas_datareader: None
bs4 : 4.11.1
bottleneck : None
brotli : None
fastparquet : 2022.11.0
fsspec : 2022.7.1
gcsfs : None
matplotlib : 3.5.2
numba : None
numexpr : 2.8.3
odfpy : None
openpyxl : 3.0.10
pandas_gbq : 0.17.7
pyarrow : 8.0.0
pyreadstat : None
pyxlsb : None
s3fs : 2022.7.1
scipy : 1.9.0
snappy : None
sqlalchemy : 1.4.39
tables : 3.7.0
tabulate : None
xarray : 2022.6.0
xlrd : 2.0.1
xlwt : None
zstandard : None
tzdata : None