pipe 1.5.0

Module enablig a sh like infix syntax (using pipes)

Infix programming toolkit

Module enabling a sh like infix syntax (using pipes).

Introduction

As an example, here is the solution for the 2nd Euler Project exercise:

Find the sum of all the even-valued terms in Fibonacci which do not exceed four million.

Given fib a generator of fibonacci numbers:

euler2 = (fib() | where(lambda x: x % 2 == 0)
                | take_while(lambda x: x < 4000000)
                | add)

Vocabulary

• A Pipe: a Pipe is a 'pipeable' function, somthing that you can pipe to, In the code '[1, 2, 3] | add' add is a Pipe
• A Pipe function: A standard function returning a Pipe so it can be used like a normal Pipe but called like in : [1, 2, 3] | concat("#")

Syntax

I don't like import * but for the following examples in an REPL it will be OK, so:

>>> from pipe import *

The basic syntax is to use a Pipe like in a shell:

>>> [1, 2, 3] | add
6

A Pipe can be a function call, for exemple the Pipe function 'where':

>>> [1, 2, 3] | where(lambda x: x % 2 == 0) #doctest: +ELLIPSIS
<generator object ...>

A Pipe as a function is nothing more than a function returning a specialized Pipe.

Constructing your own

You can construct your pipes using Pipe classe initialized with lambdas like:

stdout = Pipe(lambda x: sys.stdout.write(str(x)))
select = Pipe(lambda iterable, pred: (pred(x) for x in iterable))

Or using decorators:

@Pipe
def stdout(x):
    sys.stdout.write(str(x))

Existing Pipes in this module

stdout
    Outputs anything to the standard output
    >>> "42" | stdout
    42

lineout
    Outputs anything to the standard output followed by a line break
    >>> 42 | lineout
    42

tee
    tee outputs to the standard output and yield unchanged items, usefull for
    debugging
    >>> [1, 2, 3, 4, 5] | tee | add
    1
    2
    3
    4
    5
    15

as_list
    Outputs an iterable as a list
    >>> (0, 1, 2) | as_list
    [0, 1, 2]

as_tuple
    Outputs an iterable as a tuple
    >>> [1, 2, 3] | as_tuple
    (1, 2, 3)

as_dict
    Outputs an iterable of tuples as a dictionary
    [('a', 1), ('b', 2), ('c', 3)] | as_dict
    {'a': 1, 'b': 2, 'c': 3}

as_set
    Outputs an iterable as a set
    >>> [1, 2, 3, 1, 2, 3] | as_set
    {1, 2, 3}

concat()
    Aggregates strings using given separator, or ", " by default
    >>> [1, 2, 3, 4] | concat
    '1, 2, 3, 4'
    >>> [1, 2, 3, 4] | concat("#")
    '1#2#3#4'

average
    Returns the average of the given iterable
    >>> [1, 2, 3, 4, 5, 6] | average
    3.5

netcat
    Open a socket on the given host and port, and send data to it,
    Yields host reponse as it come.
    netcat apply traverse to its input so it can take a string or
    any iterable.

    "GET / HTTP/1.0\r\nHost: google.fr\r\n\r\n" \
        | netcat('google.fr', 80)               \
        | concat                                \
        | stdout

netwrite
    Like netcat but don't read the socket after sending data

count
    Returns the length of the given iterable, counting elements one by one
    >>> [1, 2, 3, 4, 5, 6] | count
    6

add
    Returns the sum of all elements in the preceding iterable
    >>> (1, 2, 3, 4, 5, 6) | add
    21

first
    Returns the first element of the given iterable
    >>> (1, 2, 3, 4, 5, 6) | first
    1

chain
    Unfold preceding Iterable of Iterables
    >>> [[1, 2], [3, 4], [5]] | chain | concat
    '1, 2, 3, 4, 5'

    Warning : chain only unfold iterable containing ONLY iterables :
      [1, 2, [3]] | chain
          Gives a TypeError: chain argument #1 must support iteration
          Consider using traverse

traverse
    Recursively unfold iterables
    >>> [[1, 2], [[[3], [[4]]], [5]]] | traverse | concat
    '1, 2, 3, 4, 5'
    >>> squares = (i * i for i in range(3))
    >>> [[0, 1, 2], squares] | traverse | as_list
    [0, 1, 2, 0, 1, 4]

select()
    Apply a conversion expression given as parameter
    to each element of the given iterable
    >>> [1, 2, 3] | select(lambda x: x * x) | concat
    '1, 4, 9'

where()
    Only yields the matching items of the given iterable
    >>> [1, 2, 3] | where(lambda x: x % 2 == 0) | concat
    '2'

take_while()
    Like itertools.takewhile, yields elements of the
    given iterable while the predicat is true
    >>> [1, 2, 3, 4] | take_while(lambda x: x < 3) | concat
    '1, 2'

skip_while()
    Like itertools.dropwhile, skips elements of the given iterable
    while the predicat is true, then yields others
    >>> [1, 2, 3, 4] | skip_while(lambda x: x < 3) | concat
    '3, 4'

chain_with()
    Like itertools.chain, yields elements of the given iterable,
    then yields elements of its parameters
    >>> (1, 2, 3) | chain_with([4, 5], [6]) | concat
    '1, 2, 3, 4, 5, 6'

take()
    Yields the given quantity of elemenets from the given iterable, like head
    in shell script.
    >>> (1, 2, 3, 4, 5) | take(2) | concat
    '1, 2'

tail()
    Yiels the given quantity of the last elements of the given iterable.
    >>> (1, 2, 3, 4, 5) | tail(3) | concat
    '3, 4, 5'

skip()
    Skips the given quantity of elements from the given iterable, then yields
    >>> (1, 2, 3, 4, 5) | skip(2) | concat
    '3, 4, 5'

islice()
    Just the itertools.islice
    >>> (1, 2, 3, 4, 5, 6, 7, 8, 9) | islice(2, 8, 2) | concat
    '3, 5, 7'

izip()
    Just the itertools.izip
    >>> (1, 2, 3, 4, 5, 6, 7, 8, 9) \
    ...  | izip([9, 8, 7, 6, 5, 4, 3, 2, 1]) \
    ...  | concat
    '(1, 9), (2, 8), (3, 7), (4, 6), (5, 5), (6, 4), (7, 3), (8, 2), (9, 1)'

aggregate()
    Works as python reduce, the optional initializer must be passed as a
    keyword argument
    >>> (1, 2, 3, 4, 5, 6, 7, 8, 9) | aggregate(lambda x, y: x * y)
    362880

    >>> () | aggregate(lambda x, y: x + y, initializer=0)
    0

    Simulate concat :
    >>> (1, 2, 3, 4, 5, 6, 7, 8, 9) \
    ... | aggregate(lambda x, y: str(x) + ', ' + str(y))
    '1, 2, 3, 4, 5, 6, 7, 8, 9'

any()
    Returns True if any element of the given iterable satisfies the predicate
    >>> (1, 3, 5, 6, 7) | any(lambda x: x >= 7)
    True

    >>> (1, 3, 5, 6, 7) | any(lambda x: x > 7)
    False

all()
    Returns True if all elements of the given iterable
    satisfies the given predicate
    >>> (1, 3, 5, 6, 7) | all(lambda x: x < 7)
    False

    >>> (1, 3, 5, 6, 7) | all(lambda x: x <= 7)
    True

max()
    Returns the biggest element, using the given key function if
    provided (or else the identity)

    >>> ('aa', 'b', 'foo', 'qwerty', 'bar', 'zoog') | max(key=len)
    'qwerty'
    >>> ('aa', 'b', 'foo', 'qwerty', 'bar', 'zoog') | max()
    'zoog'
    >>> ('aa', 'b', 'foo', 'qwerty', 'bar', 'zoog') | max
    'zoog'

min()
    Returns the smallest element, using the key function if provided
    (or else the identity)

    >>> ('aa', 'b', 'foo', 'qwerty', 'bar', 'zoog') | min(key=len)
    'b'
    >>> ('aa', 'b', 'foo', 'qwerty', 'bar', 'zoog') | min
    'aa'

groupby()
    Like itertools.groupby(sorted(iterable, key = keyfunc), keyfunc)
    (1, 2, 3, 4, 5, 6, 7, 8, 9) \
            | groupby(lambda x: x % 2 and "Even" or "Odd")
            | select(lambda x: "%s : %s" % (x[0], (x[1] | concat(', '))))
            | concat(' / ')
    'Even : 1, 3, 5, 7, 9 / Odd : 2, 4, 6, 8'

sort()
    Like Python's built-in "sorted" primitive. Allows cmp (Python 2.x
    only), key, and reverse arguments. By default sorts using the
    identity function as the key.

    >>> "python" | sort | concat("")
    'hnopty'
    >>> [5, -4, 3, -2, 1] | sort(key=abs) | concat
    '1, -2, 3, -4, 5'

dedup()
    Deduplicate values

    >>> [1,1,2,2,3,3,1,2,3] | dedup | as_list
    [1, 2, 3]

uniq()
    Like dedup() but only deduplicate consecutive values.

    >>> [1,1,2,2,3,3,1,2,3] | uniq | as_list
    [1, 2, 3, 1, 2, 3]

reverse
    Like Python's built-in "reversed" primitive.
    >>> [1, 2, 3] | reverse | concat
    '3, 2, 1'

passed
    Like Python's pass.
    >>> "something" | passed


index
    Returns index of value in iterable
    >>> [1,2,3,2,1] | index(2)
    1
    >>> [1,2,3,2,1] | index(1,1)
    4

strip
    Like Python's strip-method for str.
    >>> '  abc   ' | strip
    'abc'
    >>> '.,[abc] ] ' | strip('.,[] ')
    'abc'

rstrip
    Like Python's rstrip-method for str.
    >>> '  abc   ' | rstrip
    '  abc'
    >>> '.,[abc] ] ' | rstrip('.,[] ')
    '.,[abc'

lstrip
    Like Python's lstrip-method for str.
    >>> 'abc   ' | lstrip
    'abc   '
    >>> '.,[abc] ] ' | lstrip('.,[] ')
    'abc] ] '

run_with
    >>> (1,10,2) | run_with(range) | as_list
    [1, 3, 5, 7, 9]

t
    Like Haskell's operator ":"
    >>> 0 | t(1) | t(2) == range(3) | as_list
    True

to_type
    Typecast
    >>> range(5) | add | to_type(str) | t(' is summ!') | concat('')
    '10 is summ!'

permutations()
    Returns all possible permutations
    >>> 'ABC' | permutations(2) | concat(' ')
    "('A', 'B') ('A', 'C') ('B', 'A') ('B', 'C') ('C', 'A') ('C', 'B')"

    >>> range(3) | permutations | concat('-')
    '(0, 1, 2)-(0, 2, 1)-(1, 0, 2)-(1, 2, 0)-(2, 0, 1)-(2, 1, 0)'

transpose()
    Transposes the rows and columns of a matrix
    >>> [[1, 2, 3], [4, 5, 6], [7, 8, 9]] | transpose
    [(1, 4, 7), (2, 5, 8), (3, 6, 9)]

Euler project samples

Find the sum of all the multiples of 3 or 5 below 1000.

euler1 = (itertools.count() | select(lambda x: x * 3) | take_while(lambda x: x < 1000) | add) \
       + (itertools.count() | select(lambda x: x * 5) | take_while(lambda x: x < 1000) | add) \
       - (itertools.count() | select(lambda x: x * 15) | take_while(lambda x: x < 1000) | add)
assert euler1 == 233168

Find the sum of all the even-valued terms in Fibonacci which do not exceed four million.

euler2 = fib() | where(lambda x: x % 2 == 0) | take_while(lambda x: x < 4000000) | add
assert euler2 == 4613732

Find the difference between the sum of the squares of the first one hundred natural numbers and the square of the sum.

square = lambda x: x * x
euler6 = square(itertools.count(1) | take(100) | add) - (itertools.count(1) | take(100) | select(square) | add)
assert euler6 == 25164150