apache_beam.dataframe.frame_base module¶
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class apache_beam.dataframe.frame_base.UnusableUnpickledDeferredBase(name)[source]¶
- Bases: - object- Placeholder object used to break the transitive pickling chain in case a DeferredBase accidentially gets pickled (e.g. as part of globals). - Trying to use this object after unpickling is a bug and will result in an error. 
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apache_beam.dataframe.frame_base.name_and_func(method: Union[str, Callable]) → Tuple[str, Callable][source]¶
- For the given method name or method, return the method name and the method itself. - For internal use only. No backwards compatibility guarantees. 
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apache_beam.dataframe.frame_base.wont_implement_method(base_type, name, reason=None, explanation=None)[source]¶
- Generate a stub method that raises WontImplementError. - Note either reason or explanation must be specified. If both are specified, explanation is ignored. - Parameters: - base_type – The pandas type of the method that this is trying to replicate.
- name – The name of the method that this is aiming to replicate.
- reason – If specified, use data from the corresponding entry in
_WONT_IMPLEMENT_REASONSto generate a helpful exception message and docstring for the method.
- explanation – If specified, use this string as an explanation for why this operation is not supported when generating an exception message and docstring.
 
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apache_beam.dataframe.frame_base.not_implemented_method(op, issue='20318', base_type=None)[source]¶
- Generate a stub method for - opthat simply raises a NotImplementedError.- For internal use only. No backwards compatibility guarantees. 
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apache_beam.dataframe.frame_base.maybe_inplace(func)[source]¶
- Handles the inplace= kwarg available in many pandas operations. - This decorator produces a new function handles the inplace kwarg. When inplace=False, the new function simply yields the result of func directly. - When inplace=True, the output of func is used to replace this instances expression. The result is that any operations applied to this instance after the inplace operation will refernce the updated expression. - For internal use only. No backwards compatibility guarantees. 
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apache_beam.dataframe.frame_base.args_to_kwargs(base_type, removed_method=False, removed_args=None)[source]¶
- Convert all args to kwargs before calling the decorated function. - When applied to a function, this decorator creates a new function that always calls the wrapped function with only keyword arguments. It inspects the argspec for the identically-named method on base_type to determine the name to use for arguments that are converted to keyword arguments. - For internal use only. No backwards compatibility guarantees. - Parameters: - base_type – The pandas type of the method that this is trying to replicate.
- removed_method – Whether this method has been removed in the running Pandas version.
- removed_args – If not empty, which arguments have been dropped in the running Pandas version.
 
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apache_beam.dataframe.frame_base.with_docs_from(base_type, name=None, removed_method=False)[source]¶
- Decorator that updates the documentation from the wrapped function to duplicate the documentation from the identically-named method in base_type. - Any docstring on the original function will be included in the new function under a “Differences from pandas” heading. - removed_method used in cases where a method has been removed in a later version of Pandas. 
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apache_beam.dataframe.frame_base.populate_defaults(base_type, removed_method=False, removed_args=None)[source]¶
- Populate default values for keyword arguments in decorated function. - When applied to a function, this decorator creates a new function with default values for all keyword arguments, based on the default values for the identically-named method on base_type. - For internal use only. No backwards compatibility guarantees. - Parameters: - base_type – The pandas type of the method that this is trying to replicate.
- removed_method – Whether this method has been removed in the running Pandas version.
- removed_args – If not empty, which arguments have been dropped in the running Pandas version.
 
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exception apache_beam.dataframe.frame_base.WontImplementError(msg, reason=None)[source]¶
- Bases: - NotImplementedError- An subclass of NotImplementedError to raise indicating that implementing the given method is not planned. - Raising this error will also prevent this doctests from being validated when run with the beam dataframe validation doctest runner.