!A?h2 d Z g dZddlZddlZddlmZ ddlmZ ddlm
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lm Z n # e $ r Y nw xY w G d dej Z! G d dej" Z# G d dej$ Z% G d de& Z' G d de( Z) ddlm)Z) n # e $ r Y nw xY w ddlm*Z* n# e $ r d Z*Y nw xY wdddd d Z+d Z, dd lm,Z, n # e $ r Y nw xY w G d d!e( Z- G d" d#ej. Z/ G d$ d%ej. Z0 G d& d'ej Z1 G d( d)ej2 Z3dS )*a? This module implements specialized container datatypes providing
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* deque list-like container with fast appends and pops on either end
* ChainMap dict-like class for creating a single view of multiple mappings
* Counter dict subclass for counting hashable objects
* OrderedDict dict subclass that remembers the order entries were added
* defaultdict dict subclass that calls a factory function to supply missing values
* UserDict wrapper around dictionary objects for easier dict subclassing
* UserList wrapper around list objects for easier list subclassing
* UserString wrapper around string objects for easier string subclassing
) ChainMapCounter OrderedDictUserDictUserList
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r$ )r; iterablerD r r) s r fromkeyszOrderedDict.fromkeys) s. suu C DII r c t |t r>t | | o"t t t | | S t | | S )zod.__eq__(y) <==> od==y. Comparison to another OD is order-sensitive
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j d j! " d$d% }n# tF t f$ r Y nw xY w|||_$ |S )&aC Returns a new subclass of tuple with named fields.
>>> Point = namedtuple('Point', ['x', 'y'])
>>> Point.__doc__ # docstring for the new class
'Point(x, y)'
>>> p = Point(11, y=22) # instantiate with positional args or keywords
>>> p[0] + p[1] # indexable like a plain tuple
33
>>> x, y = p # unpack like a regular tuple
>>> x, y
(11, 22)
>>> p.x + p.y # fields also accessible by name
33
>>> d = p._asdict() # convert to a dictionary
>>> d['x']
11
>>> Point(**d) # convert from a dictionary
Point(x=11, y=22)
>>> p._replace(x=100) # _replace() is like str.replace() but targets named fields
Point(x=100, y=22)
, _z*Type names and field names must be stringsz6Type names and field names must be valid identifiers: z0Type names and field names cannot be a keyword: z-Field names cannot start with an underscore: z"Encountered duplicate field name: Nz(Got more default values than field names, r` rz c 3 K | ] }| d V
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Zd Zd Zd Zd Zd Zd Zd Zd Zd Zd Zd Zd Zd Z d Z d Z d Z d Z d Z! xZ"S )!r a Dict subclass for counting hashable items. Sometimes called a bag
or multiset. Elements are stored as dictionary keys and their counts
are stored as dictionary values.
>>> c = Counter('abcdeabcdabcaba') # count elements from a string
>>> c.most_common(3) # three most common elements
[('a', 5), ('b', 4), ('c', 3)]
>>> sorted(c) # list all unique elements
['a', 'b', 'c', 'd', 'e']
>>> ''.join(sorted(c.elements())) # list elements with repetitions
'aaaaabbbbcccdde'
>>> sum(c.values()) # total of all counts
15
>>> c['a'] # count of letter 'a'
5
>>> for elem in 'shazam': # update counts from an iterable
... c[elem] += 1 # by adding 1 to each element's count
>>> c['a'] # now there are seven 'a'
7
>>> del c['b'] # remove all 'b'
>>> c['b'] # now there are zero 'b'
0
>>> d = Counter('simsalabim') # make another counter
>>> c.update(d) # add in the second counter
>>> c['a'] # now there are nine 'a'
9
>>> c.clear() # empty the counter
>>> c
Counter()
Note: If a count is set to zero or reduced to zero, it will remain
in the counter until the entry is deleted or the counter is cleared:
>>> c = Counter('aaabbc')
>>> c['b'] -= 2 # reduce the count of 'b' by two
>>> c.most_common() # 'b' is still in, but its count is zero
[('a', 3), ('c', 1), ('b', 0)]
Nc d t | j |fi | dS )a Create a new, empty Counter object. And if given, count elements
from an input iterable. Or, initialize the count from another mapping
of elements to their counts.
>>> c = Counter() # a new, empty counter
>>> c = Counter('gallahad') # a new counter from an iterable
>>> c = Counter({'a': 4, 'b': 2}) # a new counter from a mapping
>>> c = Counter(a=4, b=2) # a new counter from keyword args
N)superrB r )r r r= r| s r rB zCounter.__init__K s; H%%%%%%%r c dS )z1The count of elements not in the Counter is zero.r r$ r( s r __missing__zCounter.__missing__Y s qr c D t | S )zSum of the counts)sumro r s r totalz
Counter.total^ s 4;;==!!!r c |1t | t d d S ddl}| || t d S )zList the n most common elements and their counts from the most
common to the least. If n is None, then list all element counts.
>>> Counter('abracadabra').most_common(3)
[('a', 5), ('b', 2), ('r', 2)]
Nr` T)r) reverser )r) )sortedrm r heapqnlargest)r rg r s r most_commonzCounter.most_commonb s]
9$**,,KNNDIII I ~~a ;q>>~BBBr c t t j t t | S )a Iterator over elements repeating each as many times as its count.
>>> c = Counter('ABCABC')
>>> sorted(c.elements())
['A', 'A', 'B', 'B', 'C', 'C']
# Knuth's example for prime factors of 1836: 2**2 * 3**3 * 17**1
>>> import math
>>> prime_factors = Counter({2: 2, 3: 3, 17: 1})
>>> math.prod(prime_factors.elements())
1836
Note, if an element's count has been set to zero or is a negative
number, elements() will ignore it.
)_chain
from_iterable_starmap_repeatrm r s r elementszCounter.elementsr s' $ #HWdjjll$C$CDDDr c t d )Nz@Counter.fromkeys() is undefined. Use Counter(iterable) instead.)NotImplementedError)r; r vs r r zCounter.fromkeys s " NP P Pr c B |t |t j rX| r4| j }| D ]\ }}| ||d z | |< n2t | nt | | |r| | dS dS )a Like dict.update() but add counts instead of replacing them.
Source can be an iterable, a dictionary, or another Counter instance.
>>> c = Counter('which')
>>> c.update('witch') # add elements from another iterable
>>> d = Counter('watch')
>>> c.update(d) # add elements from another counter
>>> c['h'] # four 'h' in which, witch, and watch
4
Nr )r r Mappingr rm r r r )r r r= self_getr countr| s r r zCounter.update s ( ($4$<==
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| |< |r| | dS dS )a Like dict.update() but subtracts counts instead of replacing them.
Counts can be reduced below zero. Both the inputs and outputs are
allowed to contain zero and negative counts.
Source can be an iterable, a dictionary, or another Counter instance.
>>> c = Counter('which')
>>> c.subtract('witch') # subtract elements from another iterable
>>> c.subtract(Counter('watch')) # subtract elements from another counter
>>> c['h'] # 2 in which, minus 1 in witch, minus 1 in watch
0
>>> c['w'] # 1 in which, minus 1 in witch, minus 1 in watch
-1
Nr r` )r r r r rm subtract)r r r= r r r s r r zCounter.subtract s xH($4$<==
7#+>>#3#3 ; ;KD%!)$!2!2U!:DJJ; % 7 7D!)$!2!2Q!6DJJ MM$ r c , | | S )zReturn a shallow copy.r r s r r z Counter.copy r r c 0 | j t | ffS r )r| r5 r s r r zCounter.__reduce__ s ~T
},,r c V || v r#t | dS dS )zGLike dict.__delitem__() but does not raise KeyError for missing values.N)r rO )r r r| s r rO zCounter.__delitem__ s1 4<< GG % % % % % . = II1qII!47eAh&IIIIIIIr r r r r r s ``r r zCounter.__eq__
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IIIIIIr c H t |t st S | |k S )z@True if any counts disagree. Missing counts are treated as zero.r r r r s r r zCounter.__ne__ s' %)) "! !5= r c z t t st S t fd fD S )z:True if all counts in self are a subset of those in other.c 3 F K | ]}|D ]}| | k V d S r r$ r s r r z!Counter.__le__.. r r r r s ``r __le__zCounter.__le__ r! r c R t |t st S | |k o| |k S )zATrue if all counts in self are a proper subset of those in other.r# r s r __lt__zCounter.__lt__ - %)) "! !u}. .r c z t t st S t fd fD S )z.& r r r r s ``r __ge__zCounter.__ge__" r! r c R t |t st S | |k o| |k S )zCTrue if all counts in self are a proper superset of those in other.r# r s r __gt__zCounter.__gt__( r) r c t |t st S t }| D ]\ }}||| z }|dk r|||< | D ]\ }}|| vr |dk r|||< |S )zAdd counts from two counters.
>>> Counter('abbb') + Counter('bcc')
Counter({'b': 4, 'c': 2, 'a': 1})
r r r r rm r rA rt r r newcounts r __add__zCounter.__add__. s %)) "! ! ::<< ( (KD% uT{*H!|| 't ;;== % %KD%4 EAII $t
r c t |t st S t }| D ]\ }}||| z
}|dk r|||< | D ]\ }}|| vr|dk rd|z
||< |S )z Subtract count, but keep only results with positive counts.
>>> Counter('abbbc') - Counter('bccd')
Counter({'b': 2, 'a': 1})
r r0 r1 s r __sub__zCounter.__sub__A s %)) "! ! ::<< ( (KD% uT{*H!|| 't ;;== ) )KD%4 EAII 5yt
r c t |t st S t }| D ]"\ }}|| }||k r|n|}|dk r|||< #| D ]\ }}|| vr |dk r|||< |S )zUnion is the maximum of value in either of the input counters.
>>> Counter('abbb') | Counter('bcc')
Counter({'b': 3, 'c': 2, 'a': 1})
r r0 r rA rt r r other_countr2 s r r zCounter.__or__T s %)) "! ! ::<< ( (KD% +K&+k&9&9{{uH!|| 't ;;== % %KD%4 EAII $t
r c t |t st S t }| D ]"\ }}|| }||k r|n|}|dk r|||< #|S )z Intersection is the minimum of corresponding counts.
>>> Counter('abbb') & Counter('bcc')
Counter({'b': 1})
r r0 r7 s r __and__zCounter.__and__h st %)) "! ! ::<< ( (KD% +K % 3 3uuH!|| 't
r c l t }| D ]\ }}|dk r|||< |S )zEAdds an empty counter, effectively stripping negative and zero countsr r rm r rt r r s r __pos__zCounter.__pos__y s> ::<< % %KD%qyy $t
r c r t }| D ]\ }}|dk rd|z
||< |S )z{Subtracts from an empty counter. Strips positive and zero counts,
and flips the sign on negative counts.
r r< r= s r __neg__zCounter.__neg__ sD
::<< ) )KD%qyy 5yt
r c R d | D }|D ]}| |= | S )z?Internal method to strip elements with a negative or zero countc $ g | ]
\ }}|d k |S )r r$ )r r r s r
z*Counter._keep_positive.. s! MMM e5199t999r )rm )r nonpositiver s r _keep_positivezCounter._keep_positive s: MMtzz||MMM DT
r c ~ | D ]\ }}| |xx |z
cc< | S )zInplace add from another counter, keeping only positive counts.
>>> c = Counter('abbb')
>>> c += Counter('bcc')
>>> c
Counter({'b': 4, 'c': 2, 'a': 1})
rm rE r rA r r s r __iadd__zCounter.__iadd__ I !;;== KD% JJJ% JJJJ""$$$r c ~ | D ]\ }}| |xx |z cc< | S )zInplace subtract counter, but keep only results with positive counts.
>>> c = Counter('abbbc')
>>> c -= Counter('bccd')
>>> c
Counter({'b': 2, 'a': 1})
rG rH s r __isub__zCounter.__isub__ rJ r c | D ]\ }}| | }||k r|| |< | S )zInplace union is the maximum of value from either counter.
>>> c = Counter('abbb')
>>> c |= Counter('bcc')
>>> c
Counter({'b': 3, 'c': 2, 'a': 1})
rG )r rA r r8 r s r r zCounter.__ior__ sP "' ) ) D+JEU"" (T
""$$$r c | D ]\ }}|| }||k r|| |< | S )zInplace intersection is the minimum of corresponding counts.
>>> c = Counter('abbb')
>>> c &= Counter('bcc')
>>> c
Counter({'b': 1})
rG )r rA r r r8 s r __iand__zCounter.__iand__ sO ::<< ) )KD% +KU"" (T
""$$$r r )#r! r" r# r rB r r r r r r r r r r rO r~ r r r& r( r, r. r3 r5 r r: r> r@ rE rI rL r rO
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to create a single, updateable view.
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state.
Lookups search the underlying mappings successively until a key is found.
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