Dictionary¶
Get All Keys¶
>>> a = {"1":1, "2":2, "3":3}
>>> b = {"2":2, "3":3, "4":4}
>>> a.keys()
['1', '3', '2']
Get Key and Value¶
>>> a = {"1":1, "2":2, "3":3}
>>> a.items()
Find Same Keys¶
>>> a = {"1":1, "2":2, "3":3}
>>> b = {"2":2, "3":3, "4":4}
>>> [_ for _ in a.keys() if _ in b.keys()]
['3', '2']
>>> # better way
>>> c = set(a).intersection(set(b))
>>> list(c)
['3', '2']
>>> # or
>>> [_ for _ in a if _ in b]
['3', '2']
[('1', 1), ('3', 3), ('2', 2)]
Set a Default Value¶
>>> # intuitive but not recommend
>>> d = {}
>>> key = "foo"
>>> if key not in d:
... d[key] = []
...
# using d.setdefault(key[, default])
>>> d = {}
>>> key = "foo"
>>> d.setdefault(key, [])
[]
>>> d[key] = 'bar'
>>> d
{'foo': 'bar'}
# using collections.defaultdict
>>> from collections import defaultdict
>>> d = defaultdict(list)
>>> d["key"]
[]
>>> d["foo"]
[]
>>> d["foo"].append("bar")
>>> d
defaultdict(<class 'list'>, {'key': [], 'foo': ['bar']})
dict.setdefault(key[, default])
returns its default value if key is not in
the dictionary. However, if the key exists in the dictionary, the function will
return its value.
>>> d = {}
>>> d.setdefault("key", [])
[]
>>> d["key"] = "bar"
>>> d.setdefault("key", [])
'bar'
Update Dictionary¶
>>> a = {"1":1, "2":2, "3":3}
>>> b = {"2":2, "3":3, "4":4}
>>> a.update(b)
>>> a
{'1': 1, '3': 3, '2': 2, '4': 4}
Merge Two Dictionaries¶
Python 3.4 or lower
>>> a = {"x": 55, "y": 66}
>>> b = {"a": "foo", "b": "bar"}
>>> c = a.copy()
>>> c.update(b)
>>> c
{'y': 66, 'x': 55, 'b': 'bar', 'a': 'foo'}
Python 3.5 or above
>>> a = {"x": 55, "y": 66}
>>> b = {"a": "foo", "b": "bar"}
>>> c = {**a, **b}
>>> c
{'x': 55, 'y': 66, 'a': 'foo', 'b': 'bar'}
Emulating a Dictionary¶
>>> class EmuDict(object):
... def __init__(self, dict_):
... self._dict = dict_
... def __repr__(self):
... return "EmuDict: " + repr(self._dict)
... def __getitem__(self, key):
... return self._dict[key]
... def __setitem__(self, key, val):
... self._dict[key] = val
... def __delitem__(self, key):
... del self._dict[key]
... def __contains__(self, key):
... return key in self._dict
... def __iter__(self):
... return iter(self._dict.keys())
...
>>> _ = {"1":1, "2":2, "3":3}
>>> emud = EmuDict(_)
>>> emud # __repr__
EmuDict: {'1': 1, '2': 2, '3': 3}
>>> emud['1'] # __getitem__
1
>>> emud['5'] = 5 # __setitem__
>>> emud
EmuDict: {'1': 1, '2': 2, '3': 3, '5': 5}
>>> del emud['2'] # __delitem__
>>> emud
EmuDict: {'1': 1, '3': 3, '5': 5}
>>> for _ in emud:
... print(emud[_], end=' ') # __iter__
... else:
... print()
...
1 3 5
>>> '1' in emud # __contains__
True
LRU Cache¶
from collections import OrderedDict
class LRU(object):
def __init__(self, maxsize=128):
self._maxsize = maxsize
self._cache = OrderedDict()
def get(self, k):
if k not in self._cache:
return None
self._cache.move_to_end(k)
return self._cache[k]
def put(self, k, v):
if k in self._cache:
self._cache.move_to_end(k)
self._cache[k] = v
if len(self._cache) > self._maxsize:
self._cache.popitem(last=False)
def __str__(self):
return str(self._cache)
def __repr__(self):
return self.__str__()
Note that dictionaries preserve insertion order from Python 3.7. Moreover, updating a key does not affect the order. Therefore, a dictionary can also simulate an LRU cache, which is similar to using an OrderedDict.
class LRU(object):
def __init__(self, maxsize=128):
self._maxsize = maxsize
self._cache = {}
def get(self, k):
if k not in self._cache:
return None
self.move_to_end(k)
return self._cache[k]
def put(self, k, v):
if k in self._cache:
self.move_to_end(k)
self._cache[k] = v
if len(self._cache) > self._maxsize:
self.pop()
def pop(self):
it = iter(self._cache.keys())
del self._cache[next(it)]
def move_to_end(self, k):
if k not in self._cache:
return
v = self._cache[k]
del self._cache[k]
self._cache[k] = v
def __str__(self):
return str(self._cache)
def __repr__(self):
return self.__str__()