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104 lines
2.0 KiB
Plaintext
104 lines
2.0 KiB
Plaintext
-> Common function used in python:
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map, filter, zip, and replace
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-> map:
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Prototype:
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map(<function>, <iterable>)
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Whatever the first argument, i.e., function can do, map will do
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the same logic for each item in the iterable and return the
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iterable with same structure.
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for ex:
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my_list = [1,2,3]
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def multiply_by2(item):
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return item*2
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print(list(map(multiply_by2, my_list)))
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print(my_list)
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-> filter:
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Prototype:
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filter(<function>, <iterable>)
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To filter some items from the iterable based on the condition
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defined in the function which return some boolean value.
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for ex:
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my_list = [1,2,3]
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def only_odd(item):
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return item % 2 == 0
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print(list(filter(only_odd, my_list)))
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print(my_list)
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-> zip:
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Prototype:
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zip(<iterable1> , <iterable2>)
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combine each items from both iterable together.
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for ex:
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my_list = [1, 2, 3]
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your_list = [10, 20, 30]
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print(list(zip(my_list, your_list)))
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print(my_list)
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Output:
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[(1,10), (2,20), (3,30)]
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-> reduce:
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to use reduce add the below line:
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from functools import reduce
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# What reduce does?
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# reduce take the function given and take item from the
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# iterable and pass to function given to it. The first
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# parameter is the value initialized as the 3rd argument
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# to the reduce function. It do the processing and returns
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# a value which is used as next initialiizing value for the
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# first argument of the function provided in the reduce function
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# and so on for all items in iterable.
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-> lambda expressions:
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one time anonymous function.
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Prototype:
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lambda item: <action on param>
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for ex:
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my_list = [1,2,3]
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print(list(map(lambda item: item*2, my_list)))
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-> list comprehension:
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for ex:
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my_list = [char for char in 'hello']
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print(my_list) |