CS2304: Sequences and Collections - Virginia Techcourses.cs.vt.edu/~cs2304/spring2014/Notes/T05... · • A list is an ordered sequence of zero or more object references. • Very

CS2304: Python for Java Programmers

Monti 2014

CS2304: Sequences and Collections


Monti 2014

Sequences In Python

•  A sequence type in python supports: •  The in membership operator. •  The len() function. •  Slicing like we saw with strings, s[1:3]. •  And is iterable (for item in mylist:).

•  Python has 5 built-in sequence types. •  In this set of slides we’ll talk about:

•  The str, tuple, and list sequences/collections. •  There are also bytearray and bytes sequence

types. •  We may discuss these later in the semester.


Monti 2014

First Some Review: Strings

•  A collection of characters ex. “Hello World”. •  Single and double quotes are pretty much

interchangeable: •  So ‘Hello World’ is the same as “Hello World”. •  While ‘’ or “” are acceptable, they do need to “match” so ‘ ”

won’t work. •  Remember “”” “”” can be used for multi-line comments.

•  Strings in Python are for the most part very flexible. •  “+” Will concatenate two or more strings. •  “*” Can be used as well, ex. “hello”*3.


Monti 2014

Review: String Basics

•  Strings can use bracket notation like arrays/strings in other languages.

•  Oddly, at least coming from another language, you can also use negative indices.

•  You start at the end of the string and count backwards:

>>> s = “Hello World” >>> s[0] ‘H’ >>> s[3] ‘l’

>>> s[-1] ‘d’


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Review: String Slicing

•  String “slicing” is supported, giving you substrings:

•  Strings are immutable, so trying to modify an individual cell will cause an error:

•  You can always create another string though.

>>> s = “Hello World” >>> s[0:3] ‘Hel’ >>> s[3:6] ‘lo ’

>>> s[0] = “L” # TypeError


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Review: Iterating Through Strings

•  Recall: We can use a for loop to move through a string.

•  The loop will iterate through the characters, printing them one by one:

H e l …

for x in s: print(x)


Monti 2014

Our Next Sequence: Tuples

•  You can think of a tuple as being kind of a like a C struct. •  Or like a Java class with only data items and without

member functions.

•  You can group several different types together into a collection. •  So, you can have a tuple with a string, a number, and a

boolean value. Or tuple made up of lists and other tuples.

•  Each item in the tuple is an object reference. •  Tuples are built-in into Python and can be created

without formally defining a new data type. •  Tuples, like strings, are also immutable.


Monti 2014

Creating And Using Tuples

•  To create a tuple you just list values separated by commas:

•  Parentheses are often used but not required: •  You can return tuples:

•  You can also capture the individual values:

>>> t = “hello”, 1, True

>>> t = (“hello”, 1, True)

# at the end of a function return (“hello”, 1, True) # elsewhere t = func()

x, y, z = func()


Monti 2014

Tuples: Accessing The Items

•  Like strings, you can use bracket notation:

•  Negative indexes work too, you count from the

back or end of the tuple:

>>> t = (“Hello”, 1, True) >>> t[0] ‘Hello’ >>> t[2] True

>>> t[-1] True


Monti 2014

Tuple Slicing

•  Slicing is supported, giving you sub-tuples:

•  Like strings, tuples are immutable, so trying to

modify an individual item will cause an error:

•  You can always create another tuple though:

>>> t = (“hello”, 1, True) >>> t[0:1] ('hello',) >>> t[1:3] (1, True)

>>> t[0] = “L” # TypeError

>>> t = t[0:1] # Works fine


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Iterating Through Tuples

•  These work just like they did with strings:

•  The loop will iterate through the items, printing them one by one:

hello 1 True

for x in t: print(x)


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Other Useful Tuple Information

•  Tuples support a few useful functions: •  t.count(x) - gives you the number times x

occurs in the tuple. •  t.index(x) - gives you the index of the left most

occurrence of x.

>>> t = (“hello”, 1, True) >>> t.count(“hello”) 1 >>> t.index(True) 1  # because 1 counts as true >>> t = (“hello”, 0, True) >>> t.index(True) 2


Monti 2014

More (Hopefully) Useful Information

•  You can use the + operator with tuples as well:

•  Of course, this is actually creating another tuple. •  The membership operator works with tuples:

>>> t = (“hello”, 1, True) >>> f = t[0:1] + (“balloons”,) + t[1:3] >>> f ('hello', 'balloons', 0, True)

>>> if “hello” in t: ... print(“We found it.”) We found it. >>> if “world” in t: ... print(“We found it.”) >>>


Monti 2014

Passing Tuples To Functions

•  There are a few ways to pass tuples to functions, one is fairly straightforward:

>>> t = (“hello”, 1, True) >>> func(t) # elsewhere def func(var):

# break apart the tuple here msg = var[0]+ str(var[1]) # use the pieces of the tuple


Monti 2014

Passing Tuples To Functions

•  You can also expand the tuple automatically using the *:

•  Trying this with the tuple f(which has 4 items) will result in an error.

# note this function has 3 parameters def func2(x, y, z):

# do something x, y, and z pass

# call the function using the tuple # remember the tuple has 3 elements >>> func2(*t)


Monti 2014

Now We Move On To… Lists

•  A list is an ordered sequence of zero or more object references.

•  Very flexible, if performance isn’t crucial lists will often take the place of what we traditionally think of as an arrays job. •  There is an array type we will examine later.

•  Since each item is an object reference, elements don’t have to be the same type.

•  Lists, like tuples, are built-in into Python and can be created very easily.

•  Lists are mutable, unlike like strings and tuples.


Monti 2014

Basic List Usage

•  We’ve seen this in class before, but this creates an empty list:

•  We’ve also seen examples like this in projects:

•  You can have different data types in the same list as well as nested lists:

>>> l = []

>>> l = [“hello”, 1, True, [.10, .15, .25]]

>>> rates = [.10, .15, .25]


Monti 2014

List Slicing

•  Slicing is supported, giving you sub-lists:

•  Lists are mutable, so trying to modify an individual cell works as you would expect:

>>> l = [“hello”, 1, True, [.10, .15, .25]] >>> l[0:3] ['hello', 1, True] >>> l[2:4] [True, [0.1, 0.15, 0.25]]

>>> l[0] = “L” # Works fine >>> l[2] = “W” # Also works fine >>> l ['L', 1, 'W', [0.1, 0.15, 0.25]]


Monti 2014

Iterating Through Lists

•  Recall: We can use a for loop to move through a list.

•  The loop will iterate through the items, printing them one by one:

L 1 W …

for x in l: print(x)


Monti 2014

List Functions

•  Like tuples, lists support count and index: •  l.count(x) - gives you the number times x

occurs in the list. •  l.index(x) - gives you the index of the left most

occurrence of x.

>>> l = [“hello”, 1, True] >>> l.count(“hello”) 1 >>> l.index(True) 1  # because 1 counts as true >>> l = [“hello”, 0, True] >>> l.index(True) 2


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More List Functions

•  Lists support far more functions than just count and index.

•  l.append(x) - appends item x at the end of l. •  l.insert(i, x) - inserts item x at index i. •  l.pop() - removes the right most value in l. •  l.remove(x) - removes the left most occurrence

of x. •  l.reverse() - reverses the order of l in-place.

•  Take a look at the book or resources online for more functions.


Monti 2014

More (Hopefully) Useful Information

•  You can use the + operator with lists as well:

•  The membership operator works with lists:

>>> l = [] >>> l += [1, “hello”] >>> l += [[1, 2, 3]] >>> l [1, 'hello', [1, 2, 3]]

>>> if “hello” in l: ... print(“We found it.”) We found it. >>> if “world” in l: ... print(“We found it.”) >>>


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List Comprehensions

•  Let’s say you’d like to quickly create a list filed with data, you could do something like this:

•  This accomplishes the same thing:

l = [] for x in range(10):

l.append(x**2) >>> l [0, 1, 4, 9, 16, 25, 36, 49, 64, 81]

l =[x**2 for x in range(10)]


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More List Comprehensions •  You can do far more interesting things with list

comprehensions: •  This (more complex code) accomplishes the

same thing: l = [] for x in [1, 2, 3]:

for y in [3, 1, 4]: if x != y: l.append((x,y))

>>> l [(1, 3), (1, 4), (2, 3), (2, 1), (2, 4), (3, 1), (3, 4)]

[(x, y) for x in [1,2,3] for y in [3,1,4] if x != y]


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Other Uses For List Comprehensions

•  As filters:

•  They also work with functions, and types other than numbers:

l = [-1, -2, 0, 2, 4] pos = [x for x in l if x >=0] >>> pos [0, 2, 4]

>>> from math import pi >>> [str(round(pi, i)) for i in range(1, 6)] ['3.1', '3.14', '3.142', '3.1416', '3.14159']


Monti 2014

One More Collection: Dictionaries

•  The types we’ve looked at are groupings of values that you could access via l[0] or t[0]. •  Regardless of type, an index (a number) is a common way to

access the collections we’ve seen so far.

•  Python also has a mapping or associative array type called a dictionary.

•  Instead of being indexed by numbers, a dictionary is indexed using “keys”. •  So a dictionary is made up of (unordered) key & value pairs.

•  A key can be any immutable type, so strings, numbers, and tuples (if they don’t contain any mutable objects).


Monti 2014

Creating And Using Dictionaries

•  To create an empty dictionary you use curly brackets or braces:

•  To create dictionary a with some starting values: •  You can then use m kind of like an array:

•  You can add new items using the same method:

>>> m = {}

>>> m[“hello”] 1

m[“foobar”] = 3

>>> m = {“hello”:1, “world”:2}


Monti 2014

Dictionaries: Other Useful Functions •  If you want to test whether something is the

dictionary you can use get:

•  There are functions to get the keys and the

values:

# “j” is not a key in the map, get will # return None if doesn’t find the key >>> m.get(“j”) is None True >>> m.get(“hello”) is not None True

>>> list(m.keys()) >>> list(m.values())


Monti 2014

Iterating Through Dictionaries

•  You can use for loops to iterate through all of the key, value pairs

•  If you want to delete a individual piece of the dictionary:

for k, v in m.items(): print(k, v)

hello 1 world 2 foobar 3

del m[“hello”]

Documents

CS2304: Sequences and Collections - Virginia Techcourses.cs.vt.edu/~cs2304/spring2014/Notes/T05... · • A list is an ordered sequence of zero or more object references. • Very