loops condition - Pythonic way to combine FOR loop and IF statement





while combining (8)


Use intersection or intersection_update

  • intersection :

    a = [2,3,4,5,6,7,8,9,0]
    xyz = [0,12,4,6,242,7,9]
    ans = sorted(set(a).intersection(set(xyz)))
    
  • intersection_update:

    a = [2,3,4,5,6,7,8,9,0]
    xyz = [0,12,4,6,242,7,9]
    b = set(a)
    b.intersection_update(xyz)
    

    then b is your answer

I know how to use both for loops and if statements on separate lines, such as:

>>> a = [2,3,4,5,6,7,8,9,0]
... xyz = [0,12,4,6,242,7,9]
... for x in xyz:
...     if x in a:
...         print(x)
0,4,6,7,9

And I know I can use a list comprehension to combine these when the statements are simple, such as:

print([x for x in xyz if x in a])

But what I can't find is a good example anywhere (to copy and learn from) demonstrating a complex set of commands (not just "print x") that occur following a combination of a for loop and some if statements. Something that I would expect looks like:

for x in xyz if x not in a:
    print(x...)

Is this just not the way python is supposed to work?




You can use generators too, if generator expressions become too involved or complex:

def gen():
    for x in xyz:
        if x in a:
            yield x

for x in gen():
    print x



The following is a simplification/one liner from the accepted answer:

a = [2,3,4,5,6,7,8,9,0]
xyz = [0,12,4,6,242,7,9]

for x in (x for x in xyz if x not in a):
    print(x)

12
242

Notice that the generator was kept inline. This was tested on python2.7 and python3.6 (notice the parens in the print ;) )







I personally think this is the prettiest version:

a = [2,3,4,5,6,7,8,9,0]
xyz = [0,12,4,6,242,7,9]
for x in filter(lambda w: w in a, xyz):
  print x

Edit

if you are very keen on avoiding to use lambda you can use partial function application and use the operator module (that provides functions of most operators).

https://docs.python.org/2/library/operator.html#module-operator

from operator import contains
from functools import partial
print(list(filter(partial(contains, a), xyz)))



a = [2,3,4,5,6,7,8,9,0]
xyz = [0,12,4,6,242,7,9]  
set(a) & set(xyz)  
set([0, 9, 4, 6, 7])



As per The Zen of Python (if you are wondering whether your code is "Pythonic", that's the place to go):

  • Beautiful is better than ugly.
  • Explicit is better than implicit.
  • Simple is better than complex.
  • Flat is better than nested.
  • Readability counts.

The Pythonic way of getting the sorted intersection of two sets is:

>>> sorted(set(a).intersection(xyz))
[0, 4, 6, 7, 9]

Or those elements that are xyz but not in a:

>>> sorted(set(xyz).difference(a))
[12, 242]

But for a more complicated loop you may want to flatten it by iterating over a well-named generator expression and/or calling out to a well-named function. Trying to fit everything on one line is rarely "Pythonic".


Update following additional comments on your question and the accepted answer

I'm not sure what you are trying to do with enumerate, but if a is a dictionary, you probably want to use the keys, like this:

>>> a = {
...     2: 'Turtle Doves',
...     3: 'French Hens',
...     4: 'Colly Birds',
...     5: 'Gold Rings',
...     6: 'Geese-a-Laying',
...     7: 'Swans-a-Swimming',
...     8: 'Maids-a-Milking',
...     9: 'Ladies Dancing',
...     0: 'Camel Books',
... }
>>>
>>> xyz = [0, 12, 4, 6, 242, 7, 9]
>>>
>>> known_things = sorted(set(a.iterkeys()).intersection(xyz))
>>> unknown_things = sorted(set(xyz).difference(a.iterkeys()))
>>>
>>> for thing in known_things:
...     print 'I know about', a[thing]
...
I know about Camel Books
I know about Colly Birds
I know about Geese-a-Laying
I know about Swans-a-Swimming
I know about Ladies Dancing
>>> print '...but...'
...but...
>>>
>>> for thing in unknown_things:
...     print "I don't know what happened on the {0}th day of Christmas".format(thing)
...
I don't know what happened on the 12th day of Christmas
I don't know what happened on the 242th day of Christmas



A metaclass is a class that tells how (some) other class should be created.

This is a case where I saw metaclass as a solution to my problem: I had a really complicated problem, that probably could have been solved differently, but I chose to solve it using a metaclass. Because of the complexity, it is one of the few modules I have written where the comments in the module surpass the amount of code that has been written. Here it is...

#!/usr/bin/env python

# Copyright (C) 2013-2014 Craig Phillips.  All rights reserved.

# This requires some explaining.  The point of this metaclass excercise is to
# create a static abstract class that is in one way or another, dormant until
# queried.  I experimented with creating a singlton on import, but that did
# not quite behave how I wanted it to.  See now here, we are creating a class
# called GsyncOptions, that on import, will do nothing except state that its
# class creator is GsyncOptionsType.  This means, docopt doesn't parse any
# of the help document, nor does it start processing command line options.
# So importing this module becomes really efficient.  The complicated bit
# comes from requiring the GsyncOptions class to be static.  By that, I mean
# any property on it, may or may not exist, since they are not statically
# defined; so I can't simply just define the class with a whole bunch of
# properties that are @property @staticmethods.
#
# So here's how it works:
#
# Executing 'from libgsync.options import GsyncOptions' does nothing more
# than load up this module, define the Type and the Class and import them
# into the callers namespace.  Simple.
#
# Invoking 'GsyncOptions.debug' for the first time, or any other property
# causes the __metaclass__ __getattr__ method to be called, since the class
# is not instantiated as a class instance yet.  The __getattr__ method on
# the type then initialises the class (GsyncOptions) via the __initialiseClass
# method.  This is the first and only time the class will actually have its
# dictionary statically populated.  The docopt module is invoked to parse the
# usage document and generate command line options from it.  These are then
# paired with their defaults and what's in sys.argv.  After all that, we
# setup some dynamic properties that could not be defined by their name in
# the usage, before everything is then transplanted onto the actual class
# object (or static class GsyncOptions).
#
# Another piece of magic, is to allow command line options to be set in
# in their native form and be translated into argparse style properties.
#
# Finally, the GsyncListOptions class is actually where the options are
# stored.  This only acts as a mechanism for storing options as lists, to
# allow aggregation of duplicate options or options that can be specified
# multiple times.  The __getattr__ call hides this by default, returning the
# last item in a property's list.  However, if the entire list is required,
# calling the 'list()' method on the GsyncOptions class, returns a reference
# to the GsyncListOptions class, which contains all of the same properties
# but as lists and without the duplication of having them as both lists and
# static singlton values.
#
# So this actually means that GsyncOptions is actually a static proxy class...
#
# ...And all this is neatly hidden within a closure for safe keeping.
def GetGsyncOptionsType():
    class GsyncListOptions(object):
        __initialised = False

    class GsyncOptionsType(type):
        def __initialiseClass(cls):
            if GsyncListOptions._GsyncListOptions__initialised: return

            from docopt import docopt
            from libgsync.options import doc
            from libgsync import __version__

            options = docopt(
                doc.__doc__ % __version__,
                version = __version__,
                options_first = True
            )

            paths = options.pop('<path>', None)
            setattr(cls, "destination_path", paths.pop() if paths else None)
            setattr(cls, "source_paths", paths)
            setattr(cls, "options", options)

            for k, v in options.iteritems():
                setattr(cls, k, v)

            GsyncListOptions._GsyncListOptions__initialised = True

        def list(cls):
            return GsyncListOptions

        def __getattr__(cls, name):
            cls.__initialiseClass()
            return getattr(GsyncListOptions, name)[-1]

        def __setattr__(cls, name, value):
            # Substitut option names: --an-option-name for an_option_name
            import re
            name = re.sub(r'^__', "", re.sub(r'-', "_", name))
            listvalue = []

            # Ensure value is converted to a list type for GsyncListOptions
            if isinstance(value, list):
                if value:
                    listvalue = [] + value
                else:
                    listvalue = [ None ]
            else:
                listvalue = [ value ]

            type.__setattr__(GsyncListOptions, name, listvalue)

    # Cleanup this module to prevent tinkering.
    import sys
    module = sys.modules[__name__]
    del module.__dict__['GetGsyncOptionsType']

    return GsyncOptionsType

# Our singlton abstract proxy class.
class GsyncOptions(object):
    __metaclass__ = GetGsyncOptionsType()




python loops if-statement for-loop