dfply.base

Module Contents

dfply.base._recursive_apply(f, l)

dfply.base.contextualize(arg, context)

dfply.base.flatten(l)

dfply.base._check_delayed_eval(args, kwargs)

dfply.base._context_args(args)

dfply.base._context_kwargs(kwargs)

dfply.base._delayed_function(function, args, kwargs)

dfply.base.make_symbolic(f)

class dfply.base.Intention(function=lambda x: x, invert=False)

Bases:object

evaluate(self, context)

__getattr__(self, attribute)

__invert__(self)

__call__(self, *args, **kwargs)

dfply.base._magic_method_names = ['__abs__', '__add__', '__and__', '__cmp__', '__complex__', '__contains__', '__delattr__', '__delete__', '__delitem__', '__delslice__', '__div__', '__divmod__', '__enter__', '__eq__', '__exit__', '__float__', '__floordiv__', '__ge__', '__get__', '__getitem__', '__getslice__', '__gt__', '__hash__', '__hex__', '__iadd__', '__iand__', '__idiv__', '__ifloordiv__', '__ilshift__', '__imod__', '__imul__', '__index__', '__int__', '__ior__', '__ipow__', '__irshift__', '__isub__', '__iter__', '__itruediv__', '__ixor__', '__le__', '__len__', '__long__', '__lshift__', '__lt__', '__mod__', '__mul__', '__ne__', '__neg__', '__nonzero__', '__oct__', '__or__', '__pos__', '__pow__', '__radd__', '__rand__', '__rcmp__', '__rdiv__', '__rdivmod__', '__reversed__', '__rfloordiv__', '__rlshift__', '__rmod__', '__rmul__', '__ror__', '__rpow__', '__rrshift__', '__rshift__', '__rsub__', '__rtruediv__', '__rxor__', '__set__', '__setitem__', '__setslice__', '__sub__', '__truediv__', '__unicode__', '__xor__', '__str__']

dfply.base._set_magic_method(name)

dfply.base.X

class dfply.base.pipe(function)

Bases:object

__name__ = pipe

__rshift__(self, other)

__rrshift__(self, other)

__call__(self, *args, **kwargs)

class dfply.base.IntentionEvaluator(function, eval_symbols=True, eval_as_label=[], eval_as_selector=[])

Bases:object

Parent class for symbolic argument decorators. Default behavior is to recursively turn the arguments and keyword arguments of a decorated function into symbolic.Call objects that can be evaluated against a pandas DataFrame as it comes down a pipe.

__name__ = IntentionEvaluator

_evaluate(self, df, arg)

_evaluate_label(self, df, arg)

_evaluate_selector(self, df, arg)

_evaluator_loop(self, df, arg, eval_func)

_symbolic_eval(self, df, arg)

_symbolic_to_label(self, df, arg)

_symbolic_to_selector(self, df, arg)

_recursive_arg_eval(self, df, args)

_recursive_kwarg_eval(self, df, kwargs)

_find_eval_args(self, request, args)

_find_eval_kwargs(self, request, kwargs)

__call__(self, *args, **kwargs)

dfply.base.symbolic_evaluation(function=None, eval_symbols=True, eval_as_label=[], eval_as_selector=[])

class dfply.base.group_delegation(function)

Bases:object

__name__ = group_delegation

_apply(self, df, *args, **kwargs)

__call__(self, *args, **kwargs)

dfply.base.dfpipe(f)