cs_lec_10

#r/lecture

Lecture notes: link

Lecture: 10/3

print("Hello world i am cool")

HMWK 4 is out Iterators A container can provide an iterator that provides access to its elements in order iter(iterable): Return an iterator over the elements of an interable value next(iterator): Returns next element in iterator

>>>s = [3,4,5]
>>>t = iter(s)
>>>next(t)
3

So here its kinda like the first, the $t$ thingy, points to something. The first $next(t)$ will return the first element of the list. The following $next(t)$ will return the subsequent elements of the list, one by one.

>>>s = [[1,2],3,4,5]
>>>t = iter(s)
>>>next(s)
LIST not iterator
>>>s
[[1,2],3,4,5]
>>>

![[chrome_UeB89kZuGq.png]]

An iterable value is any value that can be passed to iter to produce an iterator ![[chrome_F8TUN0xXED.png]] Objects like lists, tuples, sets, dictionaries, strings, etc. are called iterables. In short and simpler terms, iterable is anything that you can loop over.

An iterator is returned from iter and can be passed to next; all iterators are mutable

Example of errors: ![[pythonw_3fKNhKEPlv.png]] We see that from this example, the (iterable value) that is passed into the iterator shouldn't change.

Can't change the order of a dictionary in python.

![[pythonw_taOCYuv6e4.png]] However, above example shows that you can change the values within the dictionary (or iterable item that is being changed) freely, without causing an error.

For statements Turns out you can go through the contents of a list using an interator using a for statement ![[pythonw_nwAb4iTf3O.png]] So basically you can use an iterator with for statement, which will use up certain elements of the iterator (so if you for the iterator twice it wouldn't work), or u can direcly pass an iterable to for, which will auto create an iterator for the iterable.

Built-in Iterator Functions

![[pythonw_oyE2FvM565.png]] Just like the int, list,string functions, passing in an iterator into the iter function will just return the original iterator.

Iterator knows what it is iterating over and where the iterator itself is.

Many built-in Python sequence operations return iterators that compute results lazily 1) map(func,iterable): Iterate over func(x) for x in iterable 2) filter(func,iterable): Iterate over x in iterable if func(x) 3) zip(first_iter,second_iter): Iterate over co-indexed (x,y) pairs 4) reversed(sequence): Iterate over x in a sequence in reverse order

To view contents of iterator, place resulting elements in a container

list(iterable). Create list containing all x in iterable
tuple(iterable). Create tuple containing all x in iterable

![[pythonw_kz9UWCo26a.png]]

![[pythonw_lc9y9fwxPu.png]] This shows what filter(x) exactly does, it filters certain elements of the iterator away that do not satisfy some mentioined condition.

The Zip Function The built-in zip function returns an iterator over co-indexed tuples. ![[chrome_rVNMgtOxtz.png]]

![[chrome_4h2mNCKqPN.png]] Two distinct ways of writing a function palindrome that takes in a list s and returns whether the list is a palindrome or not.

Reasons for using Iterators Code that processes an iterator (via next) or iterable(via for or iter) makes few assumptions about the data itself

Changing the data representation from a list to a tuple, map object or dict_keys doesn't require rewriting code.

Example: Casino Blackjack 1) The dealing of the card can be dealt with by a list containing a random order of the cards being passed into the iter function 2) So then the dealing of the card uses the customised next() function for the dealer.