Python语法速查：数据类型

<list> = <list>[<slice>]       # Or: <list>[from_inclusive : to_exclusive : ±step]

<list>.append(<el>)            # Or: <list> += [<el>]
<list>.extend(<collection>)    # Or: <list> += <collection>

<list>.sort()                  # Sorts in ascending order.
<list>.reverse()               # Reverses the list in-place.
<list> = sorted(<collection>)  # Returns a new sorted list.
<iter> = reversed(<list>)      # Returns reversed iterator.

sum_of_elements  = sum(<collection>)
elementwise_sum  = [sum(pair) for pair in zip(list_a, list_b)]
sorted_by_second = sorted(<collection>, key=lambda el: el[1])
sorted_by_both   = sorted(<collection>, key=lambda el: (el[1], el[0]))
flatter_list     = list(itertools.chain.from_iterable(<list>))
product_of_elems = functools.reduce(lambda out, el: out * el, <collection>)
list_of_chars    = list(<str>)

<list>.insert(<int>, <el>)     # Inserts item at index and moves the rest to the right.
<el>  = <list>.pop([<int>])    # Removes and returns item at index or from the end.
<int> = <list>.count(<el>)     # Returns number of occurrences. Also works on strings.
<int> = <list>.index(<el>)     # Returns index of the first occurrence or raises ValueError.
<list>.remove(<el>)            # Removes first occurrence of the item or raises ValueError.
<list>.clear()                 # Removes all items. Also works on dictionary and set.

<view> = <dict>.keys()                          # Coll. of keys that reflects changes.
<view> = <dict>.values()                        # Coll. of values that reflects changes.
<view> = <dict>.items()                         # Coll. of key-value tuples that reflects chgs.

value  = <dict>.get(key, default=None)          # Returns default if key is missing.
value  = <dict>.setdefault(key, default=None)   # Returns and writes default if key is missing.
<dict> = collections.defaultdict(<type>)        # Returns a dict with default value of type.
<dict> = collections.defaultdict(lambda: 1)     # Returns a dict with default value 1.

<dict> = dict(<collection>)                     # Creates a dict from coll. of key-value pairs.
<dict> = dict(zip(keys, values))                # Creates a dict from two collections.
<dict> = dict.fromkeys(keys [, value])          # Creates a dict from collection of keys.

<dict>.update(<dict>)                           # Adds items. Replaces ones with matching keys.
value = <dict>.pop(key)                         # Removes item or raises KeyError.
{k for k, v in <dict>.items() if v == value}    # Returns set of keys that point to the value.
{k: v for k, v in <dict>.items() if k in keys}  # Returns a dictionary, filtered by keys.

>>> from collections import Counter
>>> colors = ['blue', 'blue', 'blue', 'red', 'red']
>>> counter = Counter(colors)
>>> counter['yellow'] += 1
Counter({'blue': 3, 'red': 2, 'yellow': 1})
>>> counter.most_common()[0]
('blue', 3)

<set> = set()                                   # `{}` returns a dictionary.

<set>.add(<el>)                                 # Or: <set> |= {<el>}
<set>.update(<collection> [, ...])              # Or: <set> |= <set>

<set>  = <set>.union(<coll.>)                   # Or: <set> | <set>
<set>  = <set>.intersection(<coll.>)            # Or: <set> & <set>
<set>  = <set>.difference(<coll.>)              # Or: <set> - <set>
<set>  = <set>.symmetric_difference(<coll.>)    # Or: <set> ^ <set>
<bool> = <set>.issubset(<coll.>)                # Or: <set> <= <set>
<bool> = <set>.issuperset(<coll.>)              # Or: <set> >= <set>

<el> = <set>.pop()                              # Raises KeyError if empty.
<set>.remove(<el>)                              # Raises KeyError if missing.
<set>.discard(<el>)                             # Doesn't raise an error.

<frozenset> = frozenset(<collection>)

<tuple> = ()                                # Empty tuple.
<tuple> = (<el>,)                           # Or: <el>,
<tuple> = (<el_1>, <el_2> [, ...])          # Or: <el_1>, <el_2> [, ...]

>>> from collections import namedtuple
>>> Point = namedtuple('Point', 'x y')
>>> p = Point(1, y=2)
Point(x=1, y=2)
>>> p[0]
1
>>> p.x
1
>>> getattr(p, 'y')
2

<range> = range(stop)                       # range(to_exclusive)
<range> = range(start, stop)                # range(from_inclusive, to_exclusive)
<range> = range(start, stop, ±step)         # range(from_inclusive, to_exclusive, ±step_size)

>>> [i for i in range(3)]
[0, 1, 2]

for i, el in enumerate(<collection> [, i_start]):
    ...

<iter> = iter(<collection>)                 # `iter(<iter>)` returns unmodified iterator.
<iter> = iter(<function>, to_exclusive)     # A sequence of return values until 'to_exclusive'.
<el>   = next(<iter> [, default])           # Raises StopIteration or returns 'default' on end.
<list> = list(<iter>)                       # Returns a list of iterator's remaining elements.

import itertools as it

<iter> = it.count(start=0, step=1)          # Returns updated value endlessly. Accepts floats.
<iter> = it.repeat(<el> [, times])          # Returns element endlessly or 'times' times.
<iter> = it.cycle(<collection>)             # Repeats the sequence endlessly.

<iter> = it.chain(<coll>, <coll> [, ...])   # Empties collections in order (figuratively).
<iter> = it.chain.from_iterable(<coll>)     # Empties collections inside a collection in order.

<iter> = it.islice(<coll>, to_exclusive)    # Only returns first 'to_exclusive' elements.
<iter> = it.islice(<coll>, from_inc, …)     # `to_exclusive, +step_size`. Indices can be None.

def count(start, step):
    while True:
        yield start
        start += step

>>> counter = count(10, 2)
>>> next(counter), next(counter), next(counter)
(10, 12, 14)