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Add backports version for collections for 2.6

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Re-enable home platform stat
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Tim 2015-06-22 11:05:50 +02:00
parent db492d8408
commit 8e8a98b78b
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lib/backport_abcoll.py Normal file
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# Copyright 2007 Google, Inc. All Rights Reserved.
# Licensed to PSF under a Contributor Agreement.
"""Abstract Base Classes (ABCs) for collections, according to PEP 3119.
DON'T USE THIS MODULE DIRECTLY! The classes here should be imported
via collections; they are defined here only to alleviate certain
bootstrapping issues. Unit tests are in test_collections.
"""
from abc import ABCMeta, abstractmethod
import sys
__all__ = ["Hashable", "Iterable", "Iterator",
"Sized", "Container", "Callable",
"Set", "MutableSet",
"Mapping", "MutableMapping",
"MappingView", "KeysView", "ItemsView", "ValuesView",
"Sequence", "MutableSequence",
]
### ONE-TRICK PONIES ###
def _hasattr(C, attr):
try:
return any(attr in B.__dict__ for B in C.__mro__)
except AttributeError:
# Old-style class
return hasattr(C, attr)
class Hashable:
__metaclass__ = ABCMeta
@abstractmethod
def __hash__(self):
return 0
@classmethod
def __subclasshook__(cls, C):
if cls is Hashable:
try:
for B in C.__mro__:
if "__hash__" in B.__dict__:
if B.__dict__["__hash__"]:
return True
break
except AttributeError:
# Old-style class
if getattr(C, "__hash__", None):
return True
return NotImplemented
class Iterable:
__metaclass__ = ABCMeta
@abstractmethod
def __iter__(self):
while False:
yield None
@classmethod
def __subclasshook__(cls, C):
if cls is Iterable:
if _hasattr(C, "__iter__"):
return True
return NotImplemented
Iterable.register(str)
class Iterator(Iterable):
@abstractmethod
def next(self):
'Return the next item from the iterator. When exhausted, raise StopIteration'
raise StopIteration
def __iter__(self):
return self
@classmethod
def __subclasshook__(cls, C):
if cls is Iterator:
if _hasattr(C, "next") and _hasattr(C, "__iter__"):
return True
return NotImplemented
class Sized:
__metaclass__ = ABCMeta
@abstractmethod
def __len__(self):
return 0
@classmethod
def __subclasshook__(cls, C):
if cls is Sized:
if _hasattr(C, "__len__"):
return True
return NotImplemented
class Container:
__metaclass__ = ABCMeta
@abstractmethod
def __contains__(self, x):
return False
@classmethod
def __subclasshook__(cls, C):
if cls is Container:
if _hasattr(C, "__contains__"):
return True
return NotImplemented
class Callable:
__metaclass__ = ABCMeta
@abstractmethod
def __call__(self, *args, **kwds):
return False
@classmethod
def __subclasshook__(cls, C):
if cls is Callable:
if _hasattr(C, "__call__"):
return True
return NotImplemented
### SETS ###
class Set(Sized, Iterable, Container):
"""A set is a finite, iterable container.
This class provides concrete generic implementations of all
methods except for __contains__, __iter__ and __len__.
To override the comparisons (presumably for speed, as the
semantics are fixed), redefine __le__ and __ge__,
then the other operations will automatically follow suit.
"""
def __le__(self, other):
if not isinstance(other, Set):
return NotImplemented
if len(self) > len(other):
return False
for elem in self:
if elem not in other:
return False
return True
def __lt__(self, other):
if not isinstance(other, Set):
return NotImplemented
return len(self) < len(other) and self.__le__(other)
def __gt__(self, other):
if not isinstance(other, Set):
return NotImplemented
return len(self) > len(other) and self.__ge__(other)
def __ge__(self, other):
if not isinstance(other, Set):
return NotImplemented
if len(self) < len(other):
return False
for elem in other:
if elem not in self:
return False
return True
def __eq__(self, other):
if not isinstance(other, Set):
return NotImplemented
return len(self) == len(other) and self.__le__(other)
def __ne__(self, other):
return not (self == other)
@classmethod
def _from_iterable(cls, it):
'''Construct an instance of the class from any iterable input.
Must override this method if the class constructor signature
does not accept an iterable for an input.
'''
return cls(it)
def __and__(self, other):
if not isinstance(other, Iterable):
return NotImplemented
return self._from_iterable(value for value in other if value in self)
__rand__ = __and__
def isdisjoint(self, other):
'Return True if two sets have a null intersection.'
for value in other:
if value in self:
return False
return True
def __or__(self, other):
if not isinstance(other, Iterable):
return NotImplemented
chain = (e for s in (self, other) for e in s)
return self._from_iterable(chain)
__ror__ = __or__
def __sub__(self, other):
if not isinstance(other, Set):
if not isinstance(other, Iterable):
return NotImplemented
other = self._from_iterable(other)
return self._from_iterable(value for value in self
if value not in other)
def __rsub__(self, other):
if not isinstance(other, Set):
if not isinstance(other, Iterable):
return NotImplemented
other = self._from_iterable(other)
return self._from_iterable(value for value in other
if value not in self)
def __xor__(self, other):
if not isinstance(other, Set):
if not isinstance(other, Iterable):
return NotImplemented
other = self._from_iterable(other)
return (self - other) | (other - self)
__rxor__ = __xor__
# Sets are not hashable by default, but subclasses can change this
__hash__ = None
def _hash(self):
"""Compute the hash value of a set.
Note that we don't define __hash__: not all sets are hashable.
But if you define a hashable set type, its __hash__ should
call this function.
This must be compatible __eq__.
All sets ought to compare equal if they contain the same
elements, regardless of how they are implemented, and
regardless of the order of the elements; so there's not much
freedom for __eq__ or __hash__. We match the algorithm used
by the built-in frozenset type.
"""
MAX = sys.maxint
MASK = 2 * MAX + 1
n = len(self)
h = 1927868237 * (n + 1)
h &= MASK
for x in self:
hx = hash(x)
h ^= (hx ^ (hx << 16) ^ 89869747) * 3644798167
h &= MASK
h = h * 69069 + 907133923
h &= MASK
if h > MAX:
h -= MASK + 1
if h == -1:
h = 590923713
return h
Set.register(frozenset)
class MutableSet(Set):
"""A mutable set is a finite, iterable container.
This class provides concrete generic implementations of all
methods except for __contains__, __iter__, __len__,
add(), and discard().
To override the comparisons (presumably for speed, as the
semantics are fixed), all you have to do is redefine __le__ and
then the other operations will automatically follow suit.
"""
@abstractmethod
def add(self, value):
"""Add an element."""
raise NotImplementedError
@abstractmethod
def discard(self, value):
"""Remove an element. Do not raise an exception if absent."""
raise NotImplementedError
def remove(self, value):
"""Remove an element. If not a member, raise a KeyError."""
if value not in self:
raise KeyError(value)
self.discard(value)
def pop(self):
"""Return the popped value. Raise KeyError if empty."""
it = iter(self)
try:
value = next(it)
except StopIteration:
raise KeyError
self.discard(value)
return value
def clear(self):
"""This is slow (creates N new iterators!) but effective."""
try:
while True:
self.pop()
except KeyError:
pass
def __ior__(self, it):
for value in it:
self.add(value)
return self
def __iand__(self, it):
for value in (self - it):
self.discard(value)
return self
def __ixor__(self, it):
if it is self:
self.clear()
else:
if not isinstance(it, Set):
it = self._from_iterable(it)
for value in it:
if value in self:
self.discard(value)
else:
self.add(value)
return self
def __isub__(self, it):
if it is self:
self.clear()
else:
for value in it:
self.discard(value)
return self
MutableSet.register(set)
### MAPPINGS ###
class Mapping(Sized, Iterable, Container):
"""A Mapping is a generic container for associating key/value
pairs.
This class provides concrete generic implementations of all
methods except for __getitem__, __iter__, and __len__.
"""
@abstractmethod
def __getitem__(self, key):
raise KeyError
def get(self, key, default=None):
'D.get(k[,d]) -> D[k] if k in D, else d. d defaults to None.'
try:
return self[key]
except KeyError:
return default
def __contains__(self, key):
try:
self[key]
except KeyError:
return False
else:
return True
def iterkeys(self):
'D.iterkeys() -> an iterator over the keys of D'
return iter(self)
def itervalues(self):
'D.itervalues() -> an iterator over the values of D'
for key in self:
yield self[key]
def iteritems(self):
'D.iteritems() -> an iterator over the (key, value) items of D'
for key in self:
yield (key, self[key])
def keys(self):
"D.keys() -> list of D's keys"
return list(self)
def items(self):
"D.items() -> list of D's (key, value) pairs, as 2-tuples"
return [(key, self[key]) for key in self]
def values(self):
"D.values() -> list of D's values"
return [self[key] for key in self]
# Mappings are not hashable by default, but subclasses can change this
__hash__ = None
def __eq__(self, other):
if not isinstance(other, Mapping):
return NotImplemented
return dict(self.items()) == dict(other.items())
def __ne__(self, other):
return not (self == other)
class MappingView(Sized):
def __init__(self, mapping):
self._mapping = mapping
def __len__(self):
return len(self._mapping)
def __repr__(self):
return '{0.__class__.__name__}({0._mapping!r})'.format(self)
class KeysView(MappingView, Set):
@classmethod
def _from_iterable(self, it):
return set(it)
def __contains__(self, key):
return key in self._mapping
def __iter__(self):
for key in self._mapping:
yield key
class ItemsView(MappingView, Set):
@classmethod
def _from_iterable(self, it):
return set(it)
def __contains__(self, item):
key, value = item
try:
v = self._mapping[key]
except KeyError:
return False
else:
return v == value
def __iter__(self):
for key in self._mapping:
yield (key, self._mapping[key])
class ValuesView(MappingView):
def __contains__(self, value):
for key in self._mapping:
if value == self._mapping[key]:
return True
return False
def __iter__(self):
for key in self._mapping:
yield self._mapping[key]
class MutableMapping(Mapping):
"""A MutableMapping is a generic container for associating
key/value pairs.
This class provides concrete generic implementations of all
methods except for __getitem__, __setitem__, __delitem__,
__iter__, and __len__.
"""
@abstractmethod
def __setitem__(self, key, value):
raise KeyError
@abstractmethod
def __delitem__(self, key):
raise KeyError
__marker = object()
def pop(self, key, default=__marker):
'''D.pop(k[,d]) -> v, remove specified key and return the corresponding value.
If key is not found, d is returned if given, otherwise KeyError is raised.
'''
try:
value = self[key]
except KeyError:
if default is self.__marker:
raise
return default
else:
del self[key]
return value
def popitem(self):
'''D.popitem() -> (k, v), remove and return some (key, value) pair
as a 2-tuple; but raise KeyError if D is empty.
'''
try:
key = next(iter(self))
except StopIteration:
raise KeyError
value = self[key]
del self[key]
return key, value
def clear(self):
'D.clear() -> None. Remove all items from D.'
try:
while True:
self.popitem()
except KeyError:
pass
def update(*args, **kwds):
''' D.update([E, ]**F) -> None. Update D from mapping/iterable E and F.
If E present and has a .keys() method, does: for k in E: D[k] = E[k]
If E present and lacks .keys() method, does: for (k, v) in E: D[k] = v
In either case, this is followed by: for k, v in F.items(): D[k] = v
'''
if len(args) > 2:
raise TypeError("update() takes at most 2 positional "
"arguments ({args} given)".format(args=len(args)))
elif not args:
raise TypeError("update() takes at least 1 argument (0 given)")
self = args[0]
other = args[1] if len(args) >= 2 else ()
if isinstance(other, Mapping):
for key in other:
self[key] = other[key]
elif hasattr(other, "keys"):
for key in other.keys():
self[key] = other[key]
else:
for key, value in other:
self[key] = value
for key, value in kwds.items():
self[key] = value
def setdefault(self, key, default=None):
'D.setdefault(k[,d]) -> D.get(k,d), also set D[k]=d if k not in D'
try:
return self[key]
except KeyError:
self[key] = default
return default
MutableMapping.register(dict)
### SEQUENCES ###
class Sequence(Sized, Iterable, Container):
"""All the operations on a read-only sequence.
Concrete subclasses must override __new__ or __init__,
__getitem__, and __len__.
"""
@abstractmethod
def __getitem__(self, index):
raise IndexError
def __iter__(self):
i = 0
try:
while True:
v = self[i]
yield v
i += 1
except IndexError:
return
def __contains__(self, value):
for v in self:
if v == value:
return True
return False
def __reversed__(self):
for i in reversed(range(len(self))):
yield self[i]
def index(self, value):
'''S.index(value) -> integer -- return first index of value.
Raises ValueError if the value is not present.
'''
for i, v in enumerate(self):
if v == value:
return i
raise ValueError
def count(self, value):
'S.count(value) -> integer -- return number of occurrences of value'
return sum(1 for v in self if v == value)
Sequence.register(tuple)
Sequence.register(basestring)
Sequence.register(buffer)
Sequence.register(xrange)
class MutableSequence(Sequence):
"""All the operations on a read-only sequence.
Concrete subclasses must provide __new__ or __init__,
__getitem__, __setitem__, __delitem__, __len__, and insert().
"""
@abstractmethod
def __setitem__(self, index, value):
raise IndexError
@abstractmethod
def __delitem__(self, index):
raise IndexError
@abstractmethod
def insert(self, index, value):
'S.insert(index, object) -- insert object before index'
raise IndexError
def append(self, value):
'S.append(object) -- append object to the end of the sequence'
self.insert(len(self), value)
def reverse(self):
'S.reverse() -- reverse *IN PLACE*'
n = len(self)
for i in range(n//2):
self[i], self[n-i-1] = self[n-i-1], self[i]
def extend(self, values):
'S.extend(iterable) -- extend sequence by appending elements from the iterable'
for v in values:
self.append(v)
def pop(self, index=-1):
'''S.pop([index]) -> item -- remove and return item at index (default last).
Raise IndexError if list is empty or index is out of range.
'''
v = self[index]
del self[index]
return v
def remove(self, value):
'''S.remove(value) -- remove first occurrence of value.
Raise ValueError if the value is not present.
'''
del self[self.index(value)]
def __iadd__(self, values):
self.extend(values)
return self
MutableSequence.register(list)

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__all__ = ['Counter', 'deque', 'defaultdict', 'namedtuple', 'OrderedDict']
# For bootstrapping reasons, the collection ABCs are defined in _abcoll.py.
# They should however be considered an integral part of collections.py.
from backport_abcoll import *
import backport_abcoll
__all__ += backport_abcoll.__all__
from _collections import defaultdict
from collections import deque as _deque
from operator import itemgetter as _itemgetter, eq as _eq
from keyword import iskeyword as _iskeyword
import sys as _sys
import heapq as _heapq
from itertools import repeat as _repeat, chain as _chain, starmap as _starmap
from itertools import imap as _imap
try:
from thread import get_ident as _get_ident
except ImportError:
from dummy_thread import get_ident as _get_ident
if _sys.version_info >= (2, 7):
import warnings as _warnings
_warnings.warn('Use the stock collections modules instead.', DeprecationWarning)
################################################################################
### OrderedDict
################################################################################
class OrderedDict(dict):
'Dictionary that remembers insertion order'
# An inherited dict maps keys to values.
# The inherited dict provides __getitem__, __len__, __contains__, and get.
# The remaining methods are order-aware.
# Big-O running times for all methods are the same as regular dictionaries.
# The internal self.__map dict maps keys to links in a doubly linked list.
# The circular doubly linked list starts and ends with a sentinel element.
# The sentinel element never gets deleted (this simplifies the algorithm).
# Each link is stored as a list of length three: [PREV, NEXT, KEY].
def __init__(self, *args, **kwds):
'''Initialize an ordered dictionary. The signature is the same as
regular dictionaries, but keyword arguments are not recommended because
their insertion order is arbitrary.
'''
if len(args) > 1:
raise TypeError('expected at most 1 arguments, got %d' % len(args))
try:
self.__root
except AttributeError:
self.__root = root = [] # sentinel node
root[:] = [root, root, None]
self.__map = {}
self.__update(*args, **kwds)
def __setitem__(self, key, value, dict_setitem=dict.__setitem__):
'od.__setitem__(i, y) <==> od[i]=y'
# Setting a new item creates a new link at the end of the linked list,
# and the inherited dictionary is updated with the new key/value pair.
if key not in self:
root = self.__root
last = root[0]
last[1] = root[0] = self.__map[key] = [last, root, key]
return dict_setitem(self, key, value)
def __delitem__(self, key, dict_delitem=dict.__delitem__):
'od.__delitem__(y) <==> del od[y]'
# Deleting an existing item uses self.__map to find the link which gets
# removed by updating the links in the predecessor and successor nodes.
dict_delitem(self, key)
link_prev, link_next, _ = self.__map.pop(key)
link_prev[1] = link_next # update link_prev[NEXT]
link_next[0] = link_prev # update link_next[PREV]
def __iter__(self):
'od.__iter__() <==> iter(od)'
# Traverse the linked list in order.
root = self.__root
curr = root[1] # start at the first node
while curr is not root:
yield curr[2] # yield the curr[KEY]
curr = curr[1] # move to next node
def __reversed__(self):
'od.__reversed__() <==> reversed(od)'
# Traverse the linked list in reverse order.
root = self.__root
curr = root[0] # start at the last node
while curr is not root:
yield curr[2] # yield the curr[KEY]
curr = curr[0] # move to previous node
def clear(self):
'od.clear() -> None. Remove all items from od.'
root = self.__root
root[:] = [root, root, None]
self.__map.clear()
dict.clear(self)
# -- the following methods do not depend on the internal structure --
def keys(self):
'od.keys() -> list of keys in od'
return list(self)
def values(self):
'od.values() -> list of values in od'
return [self[key] for key in self]
def items(self):
'od.items() -> list of (key, value) pairs in od'
return [(key, self[key]) for key in self]
def iterkeys(self):
'od.iterkeys() -> an iterator over the keys in od'
return iter(self)
def itervalues(self):
'od.itervalues -> an iterator over the values in od'
for k in self:
yield self[k]
def iteritems(self):
'od.iteritems -> an iterator over the (key, value) pairs in od'
for k in self:
yield (k, self[k])
update = MutableMapping.update
__update = update # let subclasses override update without breaking __init__
__marker = object()
def pop(self, key, default=__marker):
'''od.pop(k[,d]) -> v, remove specified key and return the corresponding
value. If key is not found, d is returned if given, otherwise KeyError
is raised.
'''
if key in self:
result = self[key]
del self[key]
return result
if default is self.__marker:
raise KeyError(key)
return default
def setdefault(self, key, default=None):
'od.setdefault(k[,d]) -> od.get(k,d), also set od[k]=d if k not in od'
if key in self:
return self[key]
self[key] = default
return default
def popitem(self, last=True):
'''od.popitem() -> (k, v), return and remove a (key, value) pair.
Pairs are returned in LIFO order if last is true or FIFO order if false.
'''
if not self:
raise KeyError('dictionary is empty')
key = next(reversed(self) if last else iter(self))
value = self.pop(key)
return key, value
def __repr__(self, _repr_running={}):
'od.__repr__() <==> repr(od)'
call_key = id(self), _get_ident()
if call_key in _repr_running:
return '...'
_repr_running[call_key] = 1
try:
if not self:
return '%s()' % (self.__class__.__name__,)
return '%s(%r)' % (self.__class__.__name__, self.items())
finally:
del _repr_running[call_key]
def __reduce__(self):
'Return state information for pickling'
items = [[k, self[k]] for k in self]
inst_dict = vars(self).copy()
for k in vars(OrderedDict()):
inst_dict.pop(k, None)
if inst_dict:
return (self.__class__, (items,), inst_dict)
return self.__class__, (items,)
def copy(self):
'od.copy() -> a shallow copy of od'
return self.__class__(self)
@classmethod
def fromkeys(cls, iterable, value=None):
'''OD.fromkeys(S[, v]) -> New ordered dictionary with keys from S.
If not specified, the value defaults to None.
'''
self = cls()
for key in iterable:
self[key] = value
return self
def __eq__(self, other):
'''od.__eq__(y) <==> od==y. Comparison to another OD is order-sensitive
while comparison to a regular mapping is order-insensitive.
'''
if isinstance(other, OrderedDict):
return dict.__eq__(self, other) and all(_imap(_eq, self, other))
return dict.__eq__(self, other)
def __ne__(self, other):
'od.__ne__(y) <==> od!=y'
return not self == other
# -- the following methods support python 3.x style dictionary views --
def viewkeys(self):
"od.viewkeys() -> a set-like object providing a view on od's keys"
return KeysView(self)
def viewvalues(self):
"od.viewvalues() -> an object providing a view on od's values"
return ValuesView(self)
def viewitems(self):
"od.viewitems() -> a set-like object providing a view on od's items"
return ItemsView(self)
################################################################################
### namedtuple
################################################################################
_class_template = '''\
class {typename}(tuple):
'{typename}({arg_list})'
__slots__ = ()
_fields = {field_names!r}
def __new__(_cls, {arg_list}):
'Create new instance of {typename}({arg_list})'
return _tuple.__new__(_cls, ({arg_list}))
@classmethod
def _make(cls, iterable, new=tuple.__new__, len=len):
'Make a new {typename} object from a sequence or iterable'
result = new(cls, iterable)
if len(result) != {num_fields:d}:
raise TypeError('Expected {num_fields:d} arguments, got %d' % len(result))
return result
def __repr__(self):
'Return a nicely formatted representation string'
return '{typename}({repr_fmt})' % self
def _asdict(self):
'Return a new OrderedDict which maps field names to their values'
return OrderedDict(zip(self._fields, self))
def _replace(_self, **kwds):
'Return a new {typename} object replacing specified fields with new values'
result = _self._make(map(kwds.pop, {field_names!r}, _self))
if kwds:
raise ValueError('Got unexpected field names: %r' % kwds.keys())
return result
def __getnewargs__(self):
'Return self as a plain tuple. Used by copy and pickle.'
return tuple(self)
__dict__ = _property(_asdict)
def __getstate__(self):
'Exclude the OrderedDict from pickling'
pass
{field_defs}
'''
_repr_template = '{name}=%r'
_field_template = '''\
{name} = _property(_itemgetter({index:d}), doc='Alias for field number {index:d}')
'''
def namedtuple(typename, field_names, verbose=False, rename=False):
"""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 accessable 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)
"""
# Validate the field names. At the user's option, either generate an error
# message or automatically replace the field name with a valid name.
if isinstance(field_names, basestring):
field_names = field_names.replace(',', ' ').split()
field_names = map(str, field_names)
typename = str(typename)
if rename:
seen = set()
for index, name in enumerate(field_names):
if (not all(c.isalnum() or c=='_' for c in name)
or _iskeyword(name)
or not name
or name[0].isdigit()
or name.startswith('_')
or name in seen):
field_names[index] = '_%d' % index
seen.add(name)
for name in [typename] + field_names:
if type(name) != str:
raise TypeError('Type names and field names must be strings')
if not all(c.isalnum() or c=='_' for c in name):
raise ValueError('Type names and field names can only contain '
'alphanumeric characters and underscores: %r' % name)
if _iskeyword(name):
raise ValueError('Type names and field names cannot be a '
'keyword: %r' % name)
if name[0].isdigit():
raise ValueError('Type names and field names cannot start with '
'a number: %r' % name)
seen = set()
for name in field_names:
if name.startswith('_') and not rename:
raise ValueError('Field names cannot start with an underscore: '
'%r' % name)
if name in seen:
raise ValueError('Encountered duplicate field name: %r' % name)
seen.add(name)
# Fill-in the class template
class_definition = _class_template.format(
typename = typename,
field_names = tuple(field_names),
num_fields = len(field_names),
arg_list = repr(tuple(field_names)).replace("'", "")[1:-1],
repr_fmt = ', '.join(_repr_template.format(name=name)
for name in field_names),
field_defs = '\n'.join(_field_template.format(index=index, name=name)
for index, name in enumerate(field_names))
)
if verbose:
print class_definition
# Execute the template string in a temporary namespace and support
# tracing utilities by setting a value for frame.f_globals['__name__']
namespace = dict(_itemgetter=_itemgetter, __name__='namedtuple_%s' % typename,
OrderedDict=OrderedDict, _property=property, _tuple=tuple)
try:
exec class_definition in namespace
except SyntaxError as e:
raise SyntaxError(e.message + ':\n' + class_definition)
result = namespace[typename]
# For pickling to work, the __module__ variable needs to be set to the frame
# where the named tuple is created. Bypass this step in environments where
# sys._getframe is not defined (Jython for example) or sys._getframe is not
# defined for arguments greater than 0 (IronPython).
try:
result.__module__ = _sys._getframe(1).f_globals.get('__name__', '__main__')
except (AttributeError, ValueError):
pass
return result
########################################################################
### Counter
########################################################################
class Counter(dict):
'''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)]
'''
# References:
# http://en.wikipedia.org/wiki/Multiset
# http://www.gnu.org/software/smalltalk/manual-base/html_node/Bag.html
# http://www.demo2s.com/Tutorial/Cpp/0380__set-multiset/Catalog0380__set-multiset.htm
# http://code.activestate.com/recipes/259174/
# Knuth, TAOCP Vol. II section 4.6.3
def __init__(self, iterable=None, **kwds):
'''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
'''
super(Counter, self).__init__()
self.update(iterable, **kwds)
def __missing__(self, key):
'The count of elements not in the Counter is zero.'
# Needed so that self[missing_item] does not raise KeyError
return 0
def most_common(self, n=None):
'''List 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('abcdeabcdabcaba').most_common(3)
[('a', 5), ('b', 4), ('c', 3)]
'''
# Emulate Bag.sortedByCount from Smalltalk
if n is None:
return sorted(self.iteritems(), key=_itemgetter(1), reverse=True)
return _heapq.nlargest(n, self.iteritems(), key=_itemgetter(1))
def elements(self):
'''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
>>> prime_factors = Counter({2: 2, 3: 3, 17: 1})
>>> product = 1
>>> for factor in prime_factors.elements(): # loop over factors
... product *= factor # and multiply them
>>> product
1836
Note, if an element's count has been set to zero or is a negative
number, elements() will ignore it.
'''
# Emulate Bag.do from Smalltalk and Multiset.begin from C++.
return _chain.from_iterable(_starmap(_repeat, self.iteritems()))
# Override dict methods where necessary
@classmethod
def fromkeys(cls, iterable, v=None):
# There is no equivalent method for counters because setting v=1
# means that no element can have a count greater than one.
raise NotImplementedError(
'Counter.fromkeys() is undefined. Use Counter(iterable) instead.')
def update(self, iterable=None, **kwds):
'''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
'''
# The regular dict.update() operation makes no sense here because the
# replace behavior results in the some of original untouched counts
# being mixed-in with all of the other counts for a mismash that
# doesn't have a straight-forward interpretation in most counting
# contexts. Instead, we implement straight-addition. Both the inputs
# and outputs are allowed to contain zero and negative counts.
if iterable is not None:
if isinstance(iterable, Mapping):
if self:
self_get = self.get
for elem, count in iterable.iteritems():
self[elem] = self_get(elem, 0) + count
else:
super(Counter, self).update(iterable) # fast path when counter is empty
else:
self_get = self.get
for elem in iterable:
self[elem] = self_get(elem, 0) + 1
if kwds:
self.update(kwds)
def subtract(self, iterable=None, **kwds):
'''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
'''
if iterable is not None:
self_get = self.get
if isinstance(iterable, Mapping):
for elem, count in iterable.items():
self[elem] = self_get(elem, 0) - count
else:
for elem in iterable:
self[elem] = self_get(elem, 0) - 1
if kwds:
self.subtract(kwds)
def copy(self):
'Return a shallow copy.'
return self.__class__(self)
def __reduce__(self):
return self.__class__, (dict(self),)
def __delitem__(self, elem):
'Like dict.__delitem__() but does not raise KeyError for missing values.'
if elem in self:
super(Counter, self).__delitem__(elem)
def __repr__(self):
if not self:
return '%s()' % self.__class__.__name__
items = ', '.join(map('%r: %r'.__mod__, self.most_common()))
return '%s({%s})' % (self.__class__.__name__, items)
# Multiset-style mathematical operations discussed in:
# Knuth TAOCP Volume II section 4.6.3 exercise 19
# and at http://en.wikipedia.org/wiki/Multiset
#
# Outputs guaranteed to only include positive counts.
#
# To strip negative and zero counts, add-in an empty counter:
# c += Counter()
def __add__(self, other):
'''Add counts from two counters.
>>> Counter('abbb') + Counter('bcc')
Counter({'b': 4, 'c': 2, 'a': 1})
'''
if not isinstance(other, Counter):
return NotImplemented
result = Counter()
for elem, count in self.items():
newcount = count + other[elem]
if newcount > 0:
result[elem] = newcount
for elem, count in other.items():
if elem not in self and count > 0:
result[elem] = count
return result
def __sub__(self, other):
''' Subtract count, but keep only results with positive counts.
>>> Counter('abbbc') - Counter('bccd')
Counter({'b': 2, 'a': 1})
'''
if not isinstance(other, Counter):
return NotImplemented
result = Counter()
for elem, count in self.items():
newcount = count - other[elem]
if newcount > 0:
result[elem] = newcount
for elem, count in other.items():
if elem not in self and count < 0:
result[elem] = 0 - count
return result
def __or__(self, other):
'''Union is the maximum of value in either of the input counters.
>>> Counter('abbb') | Counter('bcc')
Counter({'b': 3, 'c': 2, 'a': 1})
'''
if not isinstance(other, Counter):
return NotImplemented
result = Counter()
for elem, count in self.items():
other_count = other[elem]
newcount = other_count if count < other_count else count
if newcount > 0:
result[elem] = newcount
for elem, count in other.items():
if elem not in self and count > 0:
result[elem] = count
return result
def __and__(self, other):
''' Intersection is the minimum of corresponding counts.
>>> Counter('abbb') & Counter('bcc')
Counter({'b': 1})
'''
if not isinstance(other, Counter):
return NotImplemented
result = Counter()
for elem, count in self.items():
other_count = other[elem]
newcount = count if count < other_count else other_count
if newcount > 0:
result[elem] = newcount
return result
if __name__ == '__main__':
# verify that instances can be pickled
from cPickle import loads, dumps
Point = namedtuple('Point', 'x, y', True)
p = Point(x=10, y=20)
assert p == loads(dumps(p))
# test and demonstrate ability to override methods
class Point(namedtuple('Point', 'x y')):
__slots__ = ()
@property
def hypot(self):
return (self.x ** 2 + self.y ** 2) ** 0.5
def __str__(self):
return 'Point: x=%6.3f y=%6.3f hypot=%6.3f' % (self.x, self.y, self.hypot)
for p in Point(3, 4), Point(14, 5/7.):
print p
class Point(namedtuple('Point', 'x y')):
'Point class with optimized _make() and _replace() without error-checking'
__slots__ = ()
_make = classmethod(tuple.__new__)
def _replace(self, _map=map, **kwds):
return self._make(_map(kwds.get, ('x', 'y'), self))
print Point(11, 22)._replace(x=100)
Point3D = namedtuple('Point3D', Point._fields + ('z',))
print Point3D.__doc__
import doctest
TestResults = namedtuple('TestResults', 'failed attempted')
print TestResults(*doctest.testmod())
########################################################################
### deque
########################################################################
class deque(_deque):
"""Extension of deque to support Python 2.7's operations."""
def __init__(self, iterable=[], maxlen=None):
_deque.__init__(self, iterable, maxlen)
self._maxlen = maxlen
@property
def maxlen(self):
return self._maxlen
def reverse(self):
data = []
while self:
data.append(self.pop())
self.extend(data)
def count(self, value):
return sum(1 for element in self if element == value)

14
plexpy/plexwatch.py
View file

@ -15,7 +15,11 @@
from plexpy import logger, helpers, request, datatables, config, db
from xml.dom import minidom
# from collections import defaultdict, Counter
import sys
if sys.version_info < (2, 7):
from backport_collections import defaultdict, Counter
else:
from collections import defaultdict, Counter
import plexpy
import json
@ -633,7 +637,7 @@ class PlexWatch(object):
home_stats.append({'stat_id': stat,
'rows': top_users})
'''
elif 'top_platforms' in stat:
top_platform = []
query = 'SELECT platform, COUNT(id) as total_plays, MAX(time) as last_watch, xml ' \
@ -672,12 +676,11 @@ class PlexWatch(object):
home_stats.append({'stat_id': stat,
'rows': top_platform_aggr})
'''
return home_stats
# Taken from:
# https://stackoverflow.com/questions/18066269/group-by-and-aggregate-the-values-of-a-list-of-dictionaries-in-python
'''
@staticmethod
def group_and_sum_dataset(dataset, group_by_key, sum_value_keys, sort_by_key):
@ -694,5 +697,4 @@ class PlexWatch(object):
]
new_dataset.sort(key=lambda item: item[sort_by_key], reverse=True)
return new_dataset
'''
return new_dataset