chapter 4 and 5 section06: sequences. general description "normal" variables x = 19 the...
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General Description
"Normal" variablesx = 19
The name "x" is associated with a single valueSequence variables:
L = (5, 17, 19, -1) A name which is associated with a group of values.
Python sequences
Immutable types (Ch. 4) Strings: a group of characters Tuples: a group of other python objects
Mutables types (Ch. 5) Lists: a group of other python objects Dictionaries: a group of key-value pairs (the value is a
python object), indentified by key.
Length of sequences
Returns the number of "things" in the sequence.S = "ABCDEF"T = (1, 2, 3)U = (4, 5, (6, 7, 8), 9)len(S) # 6len(T) # 3len(U) # 4
Indexing Sequences (except Dictionaries)
Index number identifies a position.s = "Oranges"
Examples:>>> s[0] # 'O'>>> s[2] # 'a'>>> s[-1] # 's'>>> s[-2] # 'e'
The indexed value can be used anywhere a "normal" variable / constant would
O r a n g e s
0 1 2 3 4 5 6-7 -6 -5 -4 -3 -2 -1
Slicing SequencesReturns a section of a sequence
Doesn't work for Dictionaries.
>>> s = "Apples-Oranges"
>>> s[1:4] # "ppl">>> s[5:9] # "s-Or">>> s[-6:-1] # "range">>> s[-5:-7] # "">>> s[10:] # "nges">>> s[:6] # "Apples">>> s[1:10:2] # "plsOa">>> s[12:8:-1] # "egna">>> s[-1::-1] # "segnarO-selppA" (backward)
-14
-13
-12
-11
-10
-9 -8 -7 -6 -5 -4 -3 -2 -1
0 1 2 3 4 5 6 7 8 9 10
11
12
13
A p p l e s - O r a n g e s
for loops
A type of repetition, but tied to a sequence.Syntax:
for var in seq: # for-loop block
The number of items in seq controls the number of iterations.
var is a variable, created / updated by python A reference to the "current" item in the sequence.
Equivalent to: i = 0while i < len(seq): var = seq[i] i += 1 # for-loop block
for loop example
s = "ABCDE"for c in s:
print(c)
Outputs:ABCDE
# Doing the same thing with a while loopi = 0while i < len(s):
c = s[i]print(c)i += 1
range objects
range([start,] end [, step])Treated as a sequence (sort of)Useful when used with for loopsExample:
for i in range(1, 6,2): # prints 1, 3, then 5print(i)
s = "ABCDE"for i in range(len(s)): # prints 0,1,2,3, then 4
print(i, s[i])
a new random function
random.choice(sequence)Returns a random element of sequence.s = "ABCDEFG"print(random.choice(s))
Here's how we could do this ourself:Indx = random.randint(0,len(s)-1)X = s[Indx] # Same as x = random.choice(s)
count method
All sequences have this method.Returns the # of times that value appearsS = "ABCDEFGBH"S.count("B") # returns 2S.count("AB") # returns 1S.count("I") # returns 0
in operator
val in seqReturns True or False if the given value
appears in the sequence.Examples:
S = "ABCD""B" in S # True"X" in S # False"AB" in S # True
Review
A few "quiz-ish" problems: Write a function which takes a string as an argument
and returns true if this string is a palindrome. Write another function which also takes a string as an
argument and returns the odd characters, in reverse sequence. Example: func2("ABCDEFGHI") would return "HFDB"
Tuples
A (possibly) heterogenous group of python objects.
Deliminted by parentheses (when creating)Examples:
T1 = (1, 2, 3, 4, 5)T2 = ("ABC", "DEF", "GHI")T2[1] # "DEF"T2[1][0] # "D"T3 = (1.7, "XYZ", 19)T4 = () # Empty tupleT5 = (5,) # Tuple with only 1 elem.T6 = (10, 11, (12, 13), 14) # NestedT7 = (screen, marioSurf, luigiSurf)
Tuples, cont.
All the previous operations, work with tuples[Try it!]Where have we seen tuples already?
Colors (pygame.draw.xxx, screen.fill) Positions (pygame.draw.xxx) Window Dimensions (pygame.display.set_mode) Point-lists (pygame.draw.polygon) Rectangles (pygame.draw.rect) Multiple return values from functions
2D Tuples
A common name for a tuple with tuple (sub-)elements
Example:T = ((15,8,7), (3,2,9), (1,-2,10))T[0] # (15,8,7)T[0][1] # 8T[0:2] # ((15,8,7), (3,2,9))T[0][1:]# (8,7)T[1] + T[2] # (3,2,9,1,-2,10)T[1] + T[1] # (3,2,9,3,2,9)T[1][1] + T[2][-1] # 12
Tuple un-packing
Another way to extract values from a sequence.T = (1, 2, 3)
x,y,z = T # x is 1, y is 2, z is 3One catch: #variables on left must be == len(T)Look familiar?
We've seen this with functions returning multiple valuesdef foo():x = random.randint(1,10)y = random.randint(1,10)return x, y # Equivalent to return (x, y)a, b = foo()# or…t = foo()a = t[0]b = t[1]
Review
Write a function which takes a tuple of numbers as an arugment and returns the average of this tuple: e.g. print(avg((3, 5, 15, 9))) would print 8.0 Make sure it will work with tuples of any size
Use a for loop to "traverse" a tuple of this form:example = (("A", 5), ("joe", 3), ("!", 4))
and produce this output (make it work with tuples of any size): AAAAA
joejoejoe!!!!
Lists
Like a tuple, but they are mutable. You can add elements You can remove elements You can change elements You can share references to the same thing.
Delimited by square brackets. Note: All sequences use square brackets for slicing /
indexing. The delimiters are only relevant when creating.
Lists
Adding an element:L = [4, 5]G = [1.0, 2.0, 3.0]H = L + G # H is now [4, 5, 1.0, 2.0, 3.0]
G.append(9.0) # G is now [1.0, 2.0, 3.0, 9.0]G.insert(0, 11.0) # G is [11.0,1.0,2.0,3.0,9.0]G.insert(2, 0.0) # G is [11.0,1.0,0.0,2.0,3.0,9.0]
Note: these are both methods of all list objects.
Lists, cont.
Removing an elementL = [1.3, 9.2, 5.8, 1.7, 1.3, 2.1]
Using the remove method
L.remove(9.2) # L is [1.3,5.8,1.7,1.3,2.1]L.remove(1.3) # L is [5.8, 1.7, 1.3, 2.1]L.remove(L[0]) # L is [1.7, 1.3, 2.1]L.remove(2.2) # ERROR!
Using the del operatordel L[0] Note: del can be used to "un-define" any variable, not just
mutable seq. variables.
Lists, cont.Changing elementsL = [1.1, 2.2, 3.3, 4.4, 5.5]L[0] = 9.9 # L is [9.9, 2.2, 3.3, 4.4, 5.5]L[1:3] = [10.1, 11.11, 12.12]print(L) # [9.9, 10.1, 11.1, 12.12, 4.4, 5.5]You can only do this to mutable objects. Even
though tuples allow indexing, they don't allow changing. A work around:T = (1.1, 2.2, 3.3, 4.4, 5.5)T = (9.9,) + T[1:]T = (T[0],) + (10.1, 11.1, 12.12) + T[3:]Note: has the same effect for lists, but we're re-creating the tuple (could be slow for large tuples)
Lists & Mutability, cont.
Mutability also means a variable of a mutable type is a reference (or pointer) to the memory location.
Address Value
This is L 1024 8000
… …
… …
This is the actual
8000 1.2
list data. 8004 3.7
(4 bytes per float)
8008 5.0
8012 9.9
8016 10.3
… …
… …
… …
L = [1.2, 3.7, 5.0, 9.9, 10.3]
Lists & Mutability, cont.This is important because assigning a new
variable = to the mutable object simply copies the reference.
Address Value
This is L 1024 8000
… …
… …
This is the actual
8000 1.2
list data. 8004 3.7
(4 bytes per float)
8008 5.0
8012 9.9
8016 10.3
… …
>>> L = [1.2, 3.7, 5.0, 9.9, 10.3]
>>> K = L
This is K 12100 8000
… …
>>> K[2] = 1000
Address Value
This is L 1024 8000
… …
… …
This is the actual
8000 1.2
list data. 8004 3.7
(4 bytes per float)
8008 99
8012 9.9
8016 10.3
… …
>>> print(K)[1.2, 3.7, 1000, 9.9, 10.3]
>>> print(L)[1.2, 3.7, 1000, 9.9, 10.3]
Mutable objects as function parameters
Recall: when you have a function call, the argument is copied to the parameter.
This is still true, but with mutable objects (e.g. Lists), you're copying the reference.
This means that when we change elements of the list in the function those changes are also reflected in the argument (in the caller).
We'll take advantage of this…a lot.
Mutable objects as parameters
Example:def func(a):
""" a is a list of integers """for i in range(len(a)):
a[i] -= 1L = [3.1, 2.9, 7.6, 4.0, 1.3, 10.4]H = [0.0, 12.3, 6.5]func(L)func(H)print(L) # Prints [2.1, 1.9, 6.6, 3.0, 0.3, 9.4]Print(H) # Prints [-1.0, 11.3, 5.5]
Lists & Mutability
We’ll see other mutable objects in python: Dictionaries Objects (from Object-Oriented Programming)