Lists & Tuples

Course: CSCI 1250

Lists

• Ordered and mutable
• Can be heterogenous
• Used for data that’s dynamic
• Defined with square brackets

my_list = [1, 2, 3]
my_list[0] = 4
 
for item in my_list:
	print(item) # 4 -> 2 -> 3

List Comprehensions

• Offers a shorter syntax when you want to create a list based on another list.
  • IE: creating a list of strings from a list of numbers
• Can be used to map and filter lists.

Map

• List comprehensions can be used to map lists, which convert some T to another value, U.
  • IE: list[str] → list[int]

nums = [1, 2, 3]
stringified_nums = [str(n) for n in nums]
 
# Without list comprehension:
stringified_nums = []
for n in nums:
	stringified_nums.append(str(n))

Filter

• List comprehensions can also be used to filter lists, which remove values from a list based on a predicate (a function that returns a boolean)

fruits = ["apple", "orange", "banana", "apple"]
apple_basket = [x for x in fruits if x == "apple"] # ["apple", "apple"]

Tuple

• Ordered and immutable
• Can be heterogenous
• Used for fixed data/records
  • Defined with parentheses

coordinates = (69, 420)

Unpacking

• Since lists and tuples are both iterators, they’re able to be unpacked.
• Unpacking offers a way to assign variables from values within an iterator.
  • IE: assigning x and y variables from a coordinate
• It can be used within loops.
  • IE: looping over a list of coordinates, you could unpack those values.

coordinates = [(1, 2), (3, 4)]
 
for x, y in coordinates:
	print(f"x: {x}, y: {y}") # x: 1, y: 2 -> x: 3, y: 4