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Comments from last section

• I'm hungry
  • I agree!
  • Question: who eats breakfast in the morning
  • who ate breakfast in the morning?
• Could you send out an email with answers to discussion questions so we can do on our own after.
  • Discussion solutions are always uploaded on the website! (both on cs61a.org and on teaching.rouxl.es), so you'll be able to do them on your own
• More recursion
• can y'all put down more stuff please there were only 3 things worth noting

Temperature Check

• Lists
  • List Slicing
  • List Comprehensions
• Mutability
• Data Abstractions
  • Trees

List Mutation Functions (adding)

• .append(element)
  • Adds elements to the end of the list
  • All elements go in one new box (can get nested lists if the element passed in is a list)
• .extend(iterable)
  • Concatenates two lists together (typcially iterable is a list)
• .insert(index, element)
  • Inserts element at index
  • Does not replace elements - this operation instead makes the list longer.
• All these functions return None once you use them

List Mutation Functions (removing)

• .remove(element)
  • Removes first appearance of element in list
  • Errors if it's unable to remove an element
• .pop(optional index)
  • Removes and returns element at the given index
  • If index is not provided, it defaults to the last element in the list.

Mutating Lists

• List mutation functions can modify an existing list
• Slicing will create a new list
  • Examples later
• a = a + b will create a new list
• a += b does not create a new list
• Indexing into a list and changing the element at that list will mutate the list:
  • a[0] = 7 will change the first element in a to be 7.

Identity vs Equality

• is will check whether 2 objects are the same thing (i.e. pointing to the same object)
• == will check if two objects have the same value

Identity vs Equality

• is will check whether 2 objects are the same thing (i.e. pointing to the same object)
• == will check if two objects have the same value

Mutating Lists (Example)

(For those reading the slides later, put this into tutor.cs61a.org)

Shallow Copy vs Deep Copy

• Shallow Copy
  • Only copies the first layer of a list
  • If we have a nested list, we only copy the arrow (not the list itself)
  • Create a new list where you copy over whatever is in the same box
• Deep Copy
  • Makes a complete copy of everything in a list
  • Very slow operation - no easy way to do this
• Python uses shallow copies (as do most languages) when copying lists!

Example: Shallow Copy vs Deep Copy

(For those reading the slides later, put this into tutor.cs61a.org)

What are Data Abstractions?

• Data abstractions are a super powerful way to let people treat code as objects, rather than knowing how the thing works itself
• Allows you to worry about how something works, rather than how something is implemented
• You'll see a lot of abstractions in other courses (Data 8, Data 100 are filled with abstractions of some sort)

What are Data Abstractions?

• Data abstractions have the following:
  • Constructors: Used to build the abstract data type
    • IMPORTANT: You do not need to know how the programmer decided to implement this!
  • Selectors: Used to interact with the data type

Example: Tree Data Abstraction

• Trees are recursive data structures (as in, trees contain more trees)
• Important terms:
  • Root Node
  • Branch(es)
    • This will be a list!
  • Leaf Node
  • Children
• Sort of looks like an upside-down tree compared to the real world
• Questions are generally solved using tree recursions

Tree Example:

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