funcoperators 0.8.2

Allow natural function notations like (1,2) /dot/ (3,4) for dot((1,2), (3,4)) or 1 /frac/ 3 for Fraction(1,3), pipes and other useful operators to functions.

Always wanted to add custom operators ?

a = (1,2,3) /dot/ (4,5,6) # a = 32

infix

Infix operators can be created using the infix class.

It works for existing functions, like numpy.dot:

import numpy
dot = infix(numpy.dot)
a = (1,2,3) /dot/ (4,5,6) # use as an infix

If you already have dot in your namespace, don't worry, it still work as a function:

a = dot((1,2,3), (4,5,6)) # still works as a function

Or for custom functions as a decorator:

@infix
def crunch(x,y):
    """
    Do a super crunchy operation between two numbers.
    """
    return x + 2 * y

a = 1 |crunch| 2 # a = crunch(1, 2)
a = crunch(1, 2) # still works
help(crunch.function) # to get help about the initial function

Any binary operator can be used like 1 *f* 2, 1 %f% 2 or 1 << f << 2 but / or | should be clean for all use cases. Beware if you use **, the operator is right to left:

b = 1 **f** 2 # a = f(2, 1)

dot and cross product

Dot and cross products are used heavily in mathematics and physics as an infix operator · or ×.

a = (1,2,3) /dot/ (4,5,6)
a = (1,2,3) |dot| (4,5,6) # same 
r = 2 + (1,2,3) /dot/ (4,5,6) # here "/" has priority over + like in normal python
r = 2 + (1,2,3) *dot* (4,5,6) # for a dot PRODUCT, '*' seems logical
r = 2 + dot((1,2,3), (4,5,6)) # still works as a function

using '|' for low priority

In some use cases, one want to mix classic operators with function operators, the | operator may be used as a low priority operator.

Y = A + B |dot| C # is parsed as Y = (A + B) |dot| C
Y = A + B /dot/ C # is parsed as Y = A + (B /dot/ C)

fractions

When using the fractions module, often you want to transition from floats to Fraction. Your current code uses / for division and you can just replace the slashes with /frac/, the mathematical stays natural to read!

from fractions import Fraction
frac = infix(Fraction)
a = 1 + 1 / 3 # 1.3333...
a = 1 + 1 /frac/ 3 # Fraction(4, 3)
b = 2 * (a + 3) /frac/ (a + 1) # nicer complex expressions

ranges, 2..5 in ruby ?

In many languages, iterating over a range has a notational shortcut, like 2..5 in ruby. Now you can even write for i in 1 /inclusive/ 5 in python.

@infix
def inclusive(a,b):
    return range(a, b+1)

for i in 2 /inclusive/ 5:
    print(i) # 2 3 4 5

for i in inclusive(2, 5):
    print(i) # 2 3 4 5

pipes : postfix

In bash, a functionality called pipes is useful to reuse an expression and change the behavior by just adding code at the end. The library can be used for that.

@postfix
def no_zero(L):
    return [x for x in L if x != 0]

@postfix
def plus_one(L):
    return [x+1 for x in L]

Y = [1,2,7,0,2,0] |no_zero |plus_one # Y == [2,3,8,3]
Y = plus_one(no_zero([1,2,7,0,2,0])) # Y == [2,3,8,3]

pipe factory

Sometimes, pipes want extra information, for example in our last example, no_zero is a special case of a pipe that filters out a value, use the pipe factory recipe like so:

def filter_out(x):
    @postfix
    def f(L):
        return [y for y in L if y != x]
    return f

L = [1,2,7,0,2,0] | filter_out(0) # Y == [2,3,8,3]

function compose (alias circle)

In mathematics and functional programming languages, function composition is naturally used using a circle operator to write things like h = f ∘ g.

s = hex(ord('A')) # s = '0x41'

from funcoperators import compose
display = hex /compose/ ord
s = display('A') # s = '0x41'

display = hex *circle* ord 

partial syntax

The library adds sugar to functools, called curry, the names comes from other languages.

def f(x,y):
    return x + y

from funcoperators import curry
g = f /curry/ 5
y = f(2) # y = 7

from funcoperators import partially
@partially
def f(x,y,z):
    return x + y + z

r = f(1,2,3)
r = f[1](2,3)
r = f[1][2][3]()
# NOT: f[1,2] which will give one argument: a tuple

partiallyauto

In functional languages, function composition is sometimes not dissociable from function call, partiallyauto only works for methods with N fixed positional arguments.

@partiallyauto
def f(x,y,z):
    return x + y + z

r = f(1,2,3)   # r = 6
r = f(1)(2)(3) # r = 6
r = f(1)(2,3)  # r = 6
g = f(1)   # g = a function with two arguments 
r = g(2,3) # r = 6
k = g(2)   # k = a function with one argument

elipartial, elicurry (alias with_arguments and deferredcall)

Python's functools.partial only works for arguments that will be provided later, one must use keywords arguments. However, not all functions do keywords arguments.

square = curryright(pow, 2) # square(x) = x ** 2

The library also proposes to use Python's ... (Ellipsis) as a natural placeholder for arguments.

tenexp = elipartial(pow, 10) # = pow(10, something)
y = tenexp(2) # 10 ** 2
square = elipartial(pow, ..., 2) # = pow(something, 2)
y = square(5) # 5 ** 2

Here as a more complex example, we define show to be the print function with arguments 1, something, 3 and keyword argument sep='.'.

show = print | elicurry(1, ..., 3, sep='/')
show(2) # prints 1/2/3

see more examples in the test cases in source code