2017-02-19 Python

Python collections

Python: Collections and Containers#

List and strings are collections
Lists are mutable
Strings, tuples, floats and integers are immutable
Are iterable

Strings are immutable you cannot change them in place … a new spot is needed in memory

Adding things#

You can use .append() but will put a list within a list

With the + sign they both have to be lists

favourite_things += ["new element"]

extend() - Extend list by appending elements from the iterable

my_list = [1, 2, 3]
my_list.extend([4, 5])

my_list
>>> [1, 2, 3, 4, 5]

insert(<index to insert>, <thing to insert>) - add a element at specific index

Delete an element#

del favourite_things[-1]

Last item in a list is always index -1

Deleting an element by value#

Use remove() - only removes the first instance

my_list.remove(1)

sometimes doesn’t exist it will return a ValueError

To get the information you remove#

Use pop()

Without arguments: my_list.pop() it returns the last item

Can have an index: my_list.pop(0)

Can’t pop an empty list, need a try and an except

Slice#

A list or string that is a portion of another list or string

favourite_things = ['a', 'b', 'c', 'd', 'e']

#Slice
favourite_things[1:5]

Remember the second parameter it exclusive, it does not include the last element

Always returns same type

No outofbounds error is thrown

Start slice as beginning: favourite_things(:2) Start slice at end: favourite_things(2:)

Sort#

my_list.sort()

This sorts in place, it does not return a sorted list.

Range#

You can create a range with range(10)

Which you can cast to a list with: my_list = list(range(10))

The list will contain 0 to 9

List steps slices#

Format is: `my_list[::]

For the whole list: mylist[::2]

Can apply to any ordered iterable: lists and strings Eg. “Johannesburg”[::2]

Default step is +1

But you can use a negative step to move backwards:

So to reverse the entire list: mylist[::-1]

Mutating a list#

Lists are mutable so you can specify what a specific slice should be

eg. my_list[2:4] = ["red", "blue"]

Delete a portion

del my_list[5:8]

Slices and replacements don’t have to be the same size

Dictionary#

Lets you name data. In other languages known as hashes or associative array
key-value pair
they are mutable
unsorted - cannot use an index
keys dont have to be strings
seperate more fields with ,
Can have a dictionary within a dictionary
+ concatenate is not supported (python does not know priority)

Usages: my_dict = {"title": "Surfer190"}

Can create with dict keyword: a = dict([['Title', 'Surfer190']])

Get an element#

my_dict["title"]

Can subditionary: my_dict["teacher"]["title"]

If you request an element that does not exist you get a KeyError because the key does not exist

Create a new key / Update#

my_dict["new_val"] = 4

Updating several values at once#

my_dict.update({...})

duplicate keys, it will take the value of the last occurance

Packing#

With argument to a function with **

eg. def packer(**kwargs):

Python will pack all the arguments sent in, into a dictionary

kwargs stands for keyword argument eg. name = "kenneth", grade=2

You can exclude a certain key with:

def packer(name=None, **kwargs)

Unpacking#

Giving a dictionary to a function and the arguments to that function derived from the dictionary

def unpacker(first_name=None, second_name=None):
    if first_name and last_name:
        print("Hi {} {}".format(first_name, last_name))
    else:
        print("Hi no name!")

unpacker(**{first_name: "surfer", last_name: "190"})

Call function with single dictionary as the only argument

because of ** python took each key from the dict and sent to function

Iterating through Dictionaries#

Can loop same as list, but will only get keys not values

get keys: course_minutes.keys() optimised to give keys

get values: course_minutes.values()

get items: course_minutes.items() returns a tuple

Tuples#

Like lists, each element has an index and can be looped over and any data type.
Cannot be changed n place - immutable
More memory efficient - fixed size in memory

String: ‘’ Lists: [,] - brackets Dictionaries: {:} - braces Tuples: (,,) - parenthesis

But parenthesis don’t make a tuple, the , does

That is why a tuple needs a , even if it is a single item

Eg. my_tuple = 1, 2, 3

or my_tuple = (1, 2, 3)

my_tuple = tuple([1, 2, 3])

Does not support Item Assignment Can add, remove elements

But you can change the data inside of mutable tuple members

Tuples have simulataneous assignment

a = 5
b = 20

a, b = b, a

a = 20
b = 5

tuples unpacks into variable on left side of equal sign

single asterisk * to pack a tuple

mostly called: *args always before **kwargs** and after others

Upack tuple from dictionary#

for course, minutes in course_minutes.items():
    print("{} is {} minutes long".format(course, minutes))

enumerate takes an ordered iterable and returns a tuple for each item, with index

enumerate("abc")

for index, letter in enumerate("abcdef"):

enumerate takes a second argument which is where to start

Sets#

Set of unique items

sets can be compared
no indexes
mutable - updates in place

Used to create with: set([1,2,3])

Can now create with: {1, 3, 5} (but has to atleast have 1 value)

python sorts the sets in the way it makes sense to python

low_primes = {1, 3, 5, 7, 11}

Adding: low_primes.add(7)

Remove: low_primes.remove(15)

Update (with mutiple sets): low_primes.update({19, 23}, {2, 29})

Union - Combination of 2 or more sets
Difference - Everything in first set that isn’t in the second
Symmetric difference - Unique to either set
Intersection - Items in both sets

set1.union(set2) or set1 | set2

set1.difference(set2) or set2 - set1

set2.symmetric_difference(set1) or set1 ^ set2

set1.intersection(set2) or set1 & set2

Python collections