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        "author": "Julien Palard",
        "author_email": "julien@palard.fr",
        "bugtrack_url": null,
        "classifiers": [
            "Development Status :: 5 - Production/Stable",
            "Intended Audience :: Developers",
            "License :: OSI Approved :: BSD License",
            "Operating System :: OS Independent",
            "Programming Language :: Python",
            "Programming Language :: Python :: 3",
            "Topic :: Software Development",
            "Topic :: Software Development :: Libraries :: Python Modules"
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        "description": "# Infix programming toolkit\n\nModule enabling a sh like infix syntax (using pipes).\n\n\n# Introduction\n\nAs an example, here is the solution for the 2nd Euler Project exercise:\n\n> Find the sum of all the even-valued terms in Fibonacci which do not\n  exceed four million.\n\nGiven fib a generator of Fibonacci numbers:\n\n    euler2 = (fib() | where(lambda x: x % 2 == 0)\n                    | take_while(lambda x: x < 4000000)\n                    | add)\n\n\n# Deprecations of pipe 1.x\n\nIn pipe 1.x a lot of functions were returning iterables and a lot\nother functions were returning non-iterables, causing confusion. The\none returning non-iterables could only be used as the last function of\na pipe expression, so they are in fact useless:\n\n    range(100) | where(lambda x: x % 2 == 0) | add\n\ncan be rewritten with no less readability as:\n\n    sum(range(100) | where(lambda x: x % 2 == 0))\n\nso all pipes returning a non-pipe are now deprecated and will be removed in pipe 2.0.\n\n\n# Vocabulary\n\n- A Pipe: a Pipe is a 'pipeable' function, something that you can pipe to,\n  In the code '[1, 2, 3] | add' add is a Pipe\n- A Pipe function: A standard function returning a Pipe so it can be used like\n  a normal Pipe but called like in : [1, 2, 3] | concat(\"#\")\n\n\n# Syntax\n\nI don't like `import * `but for the following examples in an REPL it\nwill be OK, so:\n\n    >>> from pipe import *\n\nThe basic syntax is to use a Pipe like in a shell:\n\n    >>> sum(range(100) | select(lambda x: x ** 2) | where(lambda x: x < 100))\n    285\n\nSome pipes take an argument, some do not need one:\n\n    >>> sum([1, 2, 3, 4] | where(lambda x: x % 2 == 0))\n    6\n\n    >>> sum([1, [2, 3], 4] | traverse)\n    10\n\nA Pipe as a function is nothing more than a function returning\na specialized Pipe.\n\n\n# Constructing your own\n\nYou can construct your pipes using Pipe class initialized with lambdas like:\n\n    stdout = Pipe(lambda x: sys.stdout.write(str(x)))\n    select = Pipe(lambda iterable, pred: (pred(x) for x in iterable))\n\nOr using decorators:\n\n    @Pipe\n    def stdout(x):\n        sys.stdout.write(str(x))\n\n\n# Existing Pipes in this module\n\n    tee\n        tee outputs to the standard output and yield unchanged items, usefull for\n        debugging\n        >>> sum([1, 2, 3, 4, 5] | tee)\n        1\n        2\n        3\n        4\n        5\n        15\n\n    chain\n        Chain a sequence of iterables:\n        >>> list([[1, 2], [3, 4], [5]] | chain)\n        [1, 2, 3, 4, 5]\n\n        Warning : chain only unfold iterable containing ONLY iterables:\n          [1, 2, [3]] | chain\n        Gives a TypeError: chain argument #1 must support iteration\n        Consider using traverse.\n\n    traverse\n        Recursively unfold iterables:\n        >>> list([[1, 2], [[[3], [[4]]], [5]]] | traverse)\n        [1, 2, 3, 4, 5]\n        >>> squares = (i * i for i in range(3))\n        >>> list([[0, 1, 2], squares] | traverse)\n        [0, 1, 2, 0, 1, 4]\n\n    map()\n        Apply a conversion expression given as parameter\n        to each element of the given iterable\n        >>> list([1, 2, 3] | map(lambda x: x * x))\n        [1, 4, 9]\n\n    select()\n        An alias for map().\n        >>> list([1, 2, 3] | select(lambda x: x * x))\n        [1, 4, 9]\n\n    where()\n        Only yields the matching items of the given iterable:\n        >>> list([1, 2, 3] | where(lambda x: x % 2 == 0))\n        [2]\n\n    take_while()\n        Like itertools.takewhile, yields elements of the\n        given iterable while the predicat is true:\n        >>> list([1, 2, 3, 4] | take_while(lambda x: x < 3))\n        [1, 2]\n\n    skip_while()\n        Like itertools.dropwhile, skips elements of the given iterable\n        while the predicat is true, then yields others:\n        >>> list([1, 2, 3, 4] | skip_while(lambda x: x < 3))\n        [3, 4]\n\n    chain_with()\n        Like itertools.chain, yields elements of the given iterable,\n        then yields elements of its parameters\n        >>> list((1, 2, 3) | chain_with([4, 5], [6]))\n        [1, 2, 3, 4, 5, 6]\n\n    take()\n        Yields the given quantity of elemenets from the given iterable, like head\n        in shell script.\n        >>> list((1, 2, 3, 4, 5) | take(2))\n        [1, 2]\n\n    tail()\n        Yiels the given quantity of the last elements of the given iterable.\n        >>> list((1, 2, 3, 4, 5) | tail(3))\n        [3, 4, 5]\n\n    skip()\n        Skips the given quantity of elements from the given iterable, then yields\n        >>> list((1, 2, 3, 4, 5) | skip(2))\n        [3, 4, 5]\n\n    islice()\n        Just the itertools.islice\n        >>> list((1, 2, 3, 4, 5, 6, 7, 8, 9) | islice(2, 8, 2))\n        [3, 5, 7]\n\n    izip()\n        Just the itertools.izip\n        >>> list((1, 2, 3, 4, 5, 6, 7, 8, 9)\n        ...  | izip([9, 8, 7, 6, 5, 4, 3, 2, 1]))\n        [(1, 9), (2, 8), (3, 7), (4, 6), (5, 5), (6, 4), (7, 3), (8, 2), (9, 1)]\n\n    groupby()\n        Like itertools.groupby(sorted(iterable, key = keyfunc), keyfunc)\n        (1, 2, 3, 4, 5, 6, 7, 8, 9) \\\n                | groupby(lambda x: x % 2 and \"Even\" or \"Odd\")\n                | select(lambda x: \"%s : %s\" % (x[0], (x[1] | concat(', '))))\n                | concat(' / ')\n        'Even : 1, 3, 5, 7, 9 / Odd : 2, 4, 6, 8'\n\n    sort()\n        Like Python's built-in \"sorted\" primitive. Allows cmp (Python 2.x\n        only), key, and reverse arguments. By default sorts using the\n        identity function as the key.\n\n        >>> ''.join(\"python\" | sort)\n        'hnopty'\n        >>> list([5, -4, 3, -2, 1] | sort(key=abs))\n        [1, -2, 3, -4, 5]\n\n    dedup()\n        Deduplicate values, using the given key function if provided (or else\n        the identity)\n\n        >>> list([1, 1, 2, 2, 3, 3, 1, 2, 3] | dedup)\n        [1, 2, 3]\n        >>> list([1, 1, 2, 2, 3, 3, 1, 2, 3] | dedup(key=lambda n:n % 2))\n        [1, 2]\n\n    uniq()\n        Like dedup() but only deduplicate consecutive values, using the given\n        key function if provided (or else the identity)\n\n        >>> list([1, 1, 2, 2, 3, 3, 1, 2, 3] | uniq)\n        [1, 2, 3, 1, 2, 3]\n        >>> list([1, 1, 2, 2, 3, 3, 1, 2, 3] | uniq(key=lambda n:n % 2))\n        [1, 2, 3, 2, 3]\n\n    reverse\n        Like Python's built-in \"reversed\" primitive.\n        >>> list([1, 2, 3] | reverse)\n        [3, 2, 1]\n\n    strip\n        Like Python's strip-method for str.\n        >>> '  abc   ' | strip\n        'abc'\n        >>> '.,[abc] ] ' | strip('.,[] ')\n        'abc'\n\n    rstrip\n        Like Python's rstrip-method for str.\n        >>> '  abc   ' | rstrip\n        '  abc'\n        >>> '.,[abc] ] ' | rstrip('.,[] ')\n        '.,[abc'\n\n    lstrip\n        Like Python's lstrip-method for str.\n        >>> 'abc   ' | lstrip\n        'abc   '\n        >>> '.,[abc] ] ' | lstrip('.,[] ')\n        'abc] ] '\n\n    t\n        Like Haskell's operator \":\"\n        >>> list(0 | t(1) | t(2)) == list(range(3))\n        True\n\n    permutations()\n        Returns all possible permutations\n        >>> list('ABC' | permutations(2))\n        [('A', 'B'), ('A', 'C'), ('B', 'A'), ('B', 'C'), ('C', 'A'), ('C', 'B')]\n\n        >>> list(range(3) | permutations)\n        [(0, 1, 2), (0, 2, 1), (1, 0, 2), (1, 2, 0), (2, 0, 1), (2, 1, 0)]\n\n    transpose()\n        Transposes the rows and columns of a matrix\n        >>> [[1, 2, 3], [4, 5, 6], [7, 8, 9]] | transpose\n        [(1, 4, 7), (2, 5, 8), (3, 6, 9)]\n\n\n# Euler project samples\n\n> Find the sum of all the multiples of 3 or 5 below 1000.\n\n    euler1 = (itertools.count() | select(lambda x: x * 3) | take_while(lambda x: x < 1000) | add) \\\n           + (itertools.count() | select(lambda x: x * 5) | take_while(lambda x: x < 1000) | add) \\\n           - (itertools.count() | select(lambda x: x * 15) | take_while(lambda x: x < 1000) | add)\n    assert euler1 == 233168\n\n> Find the sum of all the even-valued terms in Fibonacci which do not exceed four million.\n\n    euler2 = fib() | where(lambda x: x % 2 == 0) | take_while(lambda x: x < 4000000) | add\n    assert euler2 == 4613732\n\n> Find the difference between the sum of the squares of the first one hundred natural numbers and the square of the sum.\n\n    square = lambda x: x * x\n    euler6 = square(itertools.count(1) | take(100) | add) - (itertools.count(1) | take(100) | select(square) | add)\n    assert euler6 == 25164150\n\n\n",
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