Intro to Python ch8
Keypoints:
1. Dictionary is:
key can be any immutable type
dictinoary itself is mutable
name in other language for dictionaries: associative array, hashes, hashmaps
## 2. dict()
```python
>>> acme_customer = dict(first="Wile", middle="E", last="Coyote")
>>> acme_customer
{'first': 'Wile', 'middle': 'E', 'last': 'Coyote'}
this is limited because keys will need to be valid variable names(no spaces, no reserved words etc.)
dict can be also used to convert two value sequences into dictionary. example to can be converted: [["a",1]["b",2]["c",3]["d",4]]
3. Add/ changing items by its keys
my_dict["food"] = "hamburger"
If a key called food doesn’t exist, this will add a new key:value pair, but if it does exist, it will update the key value pair
4. Keys must be unique
If a key exist more than once in the dictionary, only the latest value would be reflected
5. Getting value by specifying key
my_dict["food"]
# would return an error if key is not present in the dictionary
my_dict.get("food","Not in the dictionary")
# returns None or the specified optional value if key doesn't exist
6. keys()
.keys() gets all keys in the dictionary
Python 2: keys() returns a list
Python 3: keys() returns dict_keys() - which is an iterable view object, so you’d need to use list() to convert this if you need a list instead
7. values()
similarly to keys() this returns all values in a dictionary instead of keys.
8. items()
this returns both key value pairs in a tuple:
## 9. len()
returns how many key:value pair are in the dictionary
## 10. combining dictionaries with **
```python
>>> first = {'a': 'agony', 'b': 'bliss'}
>>> second = {'b': 'bagels', 'c': 'candy'}
>>> {**first, **second}
{'a': 'agony', 'b': 'bagels', 'c': 'candy'}
you can parsed in more than two dictionaries to combine Using this method creates shallow copies!
11. update()
this adds the key:value pairs of dict_2 to dict_1, and if there is any duplicate keys, its will update it to represent dict_2's version instead.
## 12. del
removes the key:value pair from a dictionary
## 13. pop()
essentially a combination for get() followed by del
## 14. clear()
empties the dictionary
## 15. checking if key exists in a dictionary
use the membership operator ```in```
## 16. copy()
you can make a shallow copy of a dictionary with copy(), this works if the dictionary values are immutable.
If the values are mutable, you would need to use deepcopy() to ensure that everything is standalone from the original.
## 17. comparing dictionaries
using comparison operators == and !=, you can compare one dictionary to another
however, other operators like <=, >= will not works
dictionaries are compared one by one by key:value, and order doesn't matter
## 18. dictionary iteration
iterating over a dictionary return the key:
```python
>>> accusation = {'room': 'ballroom', 'weapon': 'lead pipe',
... 'person': 'Col. Mustard'}
>>> for card in accusation: # or, for card in accusation.keys():
... print(card)
...
room
weapon
person
for value, you need to iterate using .values()
19. dictionary comprehension
format: {key_expression : value_expression for expression in iterable}
example:
>>> word = 'letters'
>>> letter_counts = {letter: word.count(letter) for letter in set(word)}
>>> letter_counts
{'t': 2, 'l': 1, 'e': 2, 'r': 1, 's': 1}
20. Sets
each item in a set is unique, similarly to dictionary keys
sets are unordered
21. set()
python prints out an empty set as set(), because {} is used by dictionary
you can convert other sequences into a set to remove duplicate items
22. add()
23 remove()
24. & and intersection()
the ampersand(&) operator allows you to find the intersection(items that appears in both sets)
example:
>>> for name, contents in drinks.items():
... if contents & {'vermouth', 'orange juice'}:
... print(name)
...
screwdriver
martini
manhattan
you can also use intersection() to achieve the same effect
25. | and union()
| you can get the union(members of either set) with “ | ” (vertical bar) or union() |
example:
>>> a | b
{1, 2, 3}
>>> a.union(b)
{1, 2, 3}
26. - and difference()
you can obtain the difference of two sets (members of the first set but not the second) with - (minus) or difference()
>>> a - b
{1}
>>> a.difference(b)
{1}
27. ^ and symmetric_difference()
using ^ (carrot) or symmetric_difference() returns the exclusive (items only in one set and not the other)
28. <= and issubset()
you can check if a set is a subset(all items in the first set also belong in the second) of another set
(interestingly, all sets is a subset of itself, but to be a proper subset, the second needs to have all items in the first and this can be check with “<”)
29. >= and issuperset()
A superset is where all items of the second set also belongs in the first set - opposite of subset.
A proper superset can be checked with “>”
30. set comprehension
format: { expression for expression in iterable }
format with condition: { expression for expression in iterable if condition }
31. frozenset()
You could create an immutable set with any iterable
>>> frozenset([3, 2, 1])
frozenset({1, 2, 3})
>>> frozenset(set([2, 1, 3]))
frozenset({1, 2, 3})
>>> frozenset({3, 1, 2})
frozenset({1, 2, 3})
>>> frozenset( (2, 3, 1) )
frozenset({1, 2, 3})