pipey is an open source framework that provides declarative syntactical sugar within python. For those familiar with the R tidyverse ecosystem, pipey facilitates magrittr-style piping using the right bitshift operator >>, while staying largely pythonic in implementation. Unlike other pandas-oriented systems (e.g. dfply or pandas-ply), pipey is meant to be flexible, and therefore does not enforce any particular object input types, while providing additional custom functionality.

Installation

pip install pipey

Usage

The entirety of pipey's functionality can be captured in the pipey.Pipeable class, which can be passed a function to create a Pipeable-compatible function or used as a decorator around a new function. Both of these functionalities are shown below.

pipey is meant to be flexible, and therefore can accept (almost) anything as input. Creating custom functions compatible with the pipey framework is therefore quite easy, as long as an existing __rshift__ method doesn't exist for the object being passed to Pipeable.

Extended usage

We support keyword arguments (and decorators, for convenience) to extend the basic piping functionality.

See extended.py for the full set of decorators.

Accept multiple inputs

By default, the input is passed as the first argument of the receiving function, but Pipeable allows multiple inputs to be passed in as a tuple or list through the keyword argument unpack_input, as shown below.

Print = Pipeable(print, unpack_input=True)

('hello', 'world') >> Print

> hello world

Use only first input

Often functions will return a tuple of outputs, and when chaining Pipeable-compatible functions together, it's convenient to only take the first argument. This can be accomplished with the keyword argument use_first_arg_only as follows:

Print = Pipeable(print, use_first_arg_only=True)

('hello', 'world') >> Print

> hello

Enable calling

To remain unambiguous, by default we disable Pipeable-decorated objects to be called normally -- i.e. they can only be called through the piping syntax, with >>. This prevents unintended behavior when a function only has optional named parameters, in which case the Pipeable function would be called before the >> operation had a chance to pipe an input.

Nonetheless, we support traditional calling of our Pipeable functions using the keyword argument use_first_arg_only, though we urge you to have at least one required positional argument in your function definition to ensure this behaves as intended. Moreover, all other named parameters should always be explicitly (not positionally) passed to ensure the function fails without the unnamed argument -- the decorator enables a try/except to determine whether you mean to call the function or pass the piped argument to it, so the function call needs to fail in order for the piping argument to be passed.

This behavior can be enables as follows:

Print = Pipeable(print, try_normal_call_first=True)

Print('hello world')

> hello world

Append docstring

We supply an append_docstring decorator to allow docstrings from other functions to be bolted onto Pipeable docstrings. This can be invoked as a decorator, as follows:

@append_docstring(print)
@Pipeable
def Print(*args, **kwargs):
    print(*args, **kwargs)