125 lines
3.7 KiB
Python
125 lines
3.7 KiB
Python
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"""
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Functions to generate methods and pin them to the appropriate classes.
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"""
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from __future__ import annotations
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import operator
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from pandas.core.dtypes.generic import (
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ABCDataFrame,
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ABCSeries,
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)
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from pandas.core.ops import roperator
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def _get_method_wrappers(cls):
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"""
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Find the appropriate operation-wrappers to use when defining flex/special
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arithmetic, boolean, and comparison operations with the given class.
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Parameters
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----------
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cls : class
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Returns
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-------
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arith_flex : function or None
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comp_flex : function or None
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"""
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# TODO: make these non-runtime imports once the relevant functions
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# are no longer in __init__
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from pandas.core.ops import (
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flex_arith_method_FRAME,
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flex_comp_method_FRAME,
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flex_method_SERIES,
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)
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if issubclass(cls, ABCSeries):
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# Just Series
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arith_flex = flex_method_SERIES
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comp_flex = flex_method_SERIES
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elif issubclass(cls, ABCDataFrame):
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arith_flex = flex_arith_method_FRAME
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comp_flex = flex_comp_method_FRAME
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return arith_flex, comp_flex
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def add_flex_arithmetic_methods(cls) -> None:
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"""
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Adds the full suite of flex arithmetic methods (``pow``, ``mul``, ``add``)
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to the class.
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Parameters
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----------
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cls : class
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flex methods will be defined and pinned to this class
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"""
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flex_arith_method, flex_comp_method = _get_method_wrappers(cls)
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new_methods = _create_methods(cls, flex_arith_method, flex_comp_method)
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new_methods.update(
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{
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"multiply": new_methods["mul"],
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"subtract": new_methods["sub"],
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"divide": new_methods["div"],
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}
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)
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# opt out of bool flex methods for now
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assert not any(kname in new_methods for kname in ("ror_", "rxor", "rand_"))
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_add_methods(cls, new_methods=new_methods)
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def _create_methods(cls, arith_method, comp_method):
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# creates actual flex methods based upon arithmetic, and comp method
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# constructors.
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have_divmod = issubclass(cls, ABCSeries)
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# divmod is available for Series
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new_methods = {}
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new_methods.update(
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{
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"add": arith_method(operator.add),
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"radd": arith_method(roperator.radd),
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"sub": arith_method(operator.sub),
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"mul": arith_method(operator.mul),
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"truediv": arith_method(operator.truediv),
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"floordiv": arith_method(operator.floordiv),
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"mod": arith_method(operator.mod),
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"pow": arith_method(operator.pow),
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"rmul": arith_method(roperator.rmul),
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"rsub": arith_method(roperator.rsub),
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"rtruediv": arith_method(roperator.rtruediv),
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"rfloordiv": arith_method(roperator.rfloordiv),
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"rpow": arith_method(roperator.rpow),
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"rmod": arith_method(roperator.rmod),
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}
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)
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new_methods["div"] = new_methods["truediv"]
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new_methods["rdiv"] = new_methods["rtruediv"]
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if have_divmod:
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# divmod doesn't have an op that is supported by numexpr
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new_methods["divmod"] = arith_method(divmod)
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new_methods["rdivmod"] = arith_method(roperator.rdivmod)
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new_methods.update(
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{
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"eq": comp_method(operator.eq),
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"ne": comp_method(operator.ne),
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"lt": comp_method(operator.lt),
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"gt": comp_method(operator.gt),
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"le": comp_method(operator.le),
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"ge": comp_method(operator.ge),
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}
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)
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new_methods = {k.strip("_"): v for k, v in new_methods.items()}
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return new_methods
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def _add_methods(cls, new_methods) -> None:
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for name, method in new_methods.items():
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setattr(cls, name, method)
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