forked from JulienPalard/Pipe
-
Notifications
You must be signed in to change notification settings - Fork 0
rcludwick/Pipe
This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository.
Folders and files
Name | Name | Last commit message | Last commit date | |
---|---|---|---|---|
Repository files navigation
Help on module pipe: NAME pipe - Infix programming toolkit FILE /home/mandark/doc/code/python/pipe/pipe.py DESCRIPTION Module enablig a sh like infix syntax (using pipes). = Introduction = As an exemple, 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 = The basic symtax 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 <genexpr> at ...> 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 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) 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 Host: google.fr " | 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' 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 >>> (1, 2, 3, 4, 5, 6, 7, 8, 9) | aggregate(lambda x, y: x * y) 362880 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' reverse Like Python's built-in "reversed" primitive. >>> [1, 2, 3] | reverse | concat '3, 2, 1' 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)' 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 CLASSES Pipe class Pipe | Represent a Pipeable Element : | Described as : | first = Pipe(lambda iterable: next(iter(iterable))) | and used as : | print [1, 2, 3] | first | printing 1 | | Or represent a Pipeable Function : | It's a function returning a Pipe | Described as : | select = Pipe(lambda iterable, pred: (pred(x) for x in iterable)) | and used as : | print [1, 2, 3] | select(lambda x: x * 2) | # 2, 4, 6 | | Methods defined here: | | __call__(self, *args, **kwargs) | | __init__(self, function) | | __ror__(self, other) FUNCTIONS reduce(...) reduce(function, sequence[, initial]) -> value Apply a function of two arguments cumulatively to the items of a sequence, from left to right, so as to reduce the sequence to a single value. For example, reduce(lambda x, y: x+y, [1, 2, 3, 4, 5]) calculates ((((1+2)+3)+4)+5). If initial is present, it is placed before the items of the sequence in the calculation, and serves as a default when the sequence is empty. DATA __author__ = 'Julien Palard <julien@eeple.fr>' __credits__ = 'Jerome Schneider, for its Python skillz,\nand dalexande... __date__ = '10 Nov 2010' __version__ = '1.3' add = <pipe.Pipe instance> aggregate = <pipe.Pipe instance> all = <pipe.Pipe instance> any = <pipe.Pipe instance> as_list = <pipe.Pipe instance> as_tuple = <pipe.Pipe instance> average = <pipe.Pipe instance> chain = <pipe.Pipe instance> chain_with = <pipe.Pipe instance> concat = <pipe.Pipe instance> count = <pipe.Pipe instance> first = <pipe.Pipe instance> groupby = <pipe.Pipe instance> islice = <pipe.Pipe instance> izip = <pipe.Pipe instance> lineout = <pipe.Pipe instance> max = <pipe.Pipe instance> min = <pipe.Pipe instance> netcat = <pipe.Pipe instance> netwrite = <pipe.Pipe instance> permutations = <pipe.Pipe instance> reverse = <pipe.Pipe instance> select = <pipe.Pipe instance> skip = <pipe.Pipe instance> skip_while = <pipe.Pipe instance> sort = <pipe.Pipe instance> stdout = <pipe.Pipe instance> take = <pipe.Pipe instance> take_while = <pipe.Pipe instance> traverse = <pipe.Pipe instance> where = <pipe.Pipe instance> VERSION 1.3 DATE 10 Nov 2010 AUTHOR Julien Palard <julien@eeple.fr> CREDITS Jerome Schneider, for its Python skillz, and dalexander for contributing
About
A Python library to use infix notation in Python
Resources
Stars
Watchers
Forks
Releases
No releases published
Packages 0
No packages published