def __init__(self, data, twitterSession, fromCache=False):
Timestamped.__init__(self)
Hashable.__init__(self)
if twitterSession is not None:
assert isinstance(twitterSession, TwitterSession)
self.data = Tree.make(data)
if not fromCache:
self.data.applyFunctionInTree(reverse_list, ['coordinates', 'coordinates']) # for use with leaflet.
self.isDataNew = not fromCache
twitterPlaceData = self.data.getFromTree(['place'])
if twitterPlaceData is not None:
self.twitter_place = Place(twitterPlaceData)
else:
self.twitter_place = None
userJson = self.data.getFromTree(['user'])
if userJson is None:
self._user = None
else:
self._user = User(userJson, twitterSession=twitterSession, isAssociatedWithTweet=True, twitterPlace=self.twitter_place, currentLocationCoordinate=self.coordinate)
if twitterSession is not None:
self.instance_key = twitterSession.instance_key
else:
self.instance_key = None
self.twitter_session = twitterSession
def __init__(self, data, twitterSession, fromCache=False):
Timestamped.__init__(self)
Hashable.__init__(self)
if twitterSession is not None:
assert isinstance(twitterSession, TwitterSession)
self.data = Tree.make(data)
if not fromCache:
self.data.applyFunctionInTree(reverse_list, ['coordinates', 'coordinates']) # for use with leaflet.
self.isDataNew = not fromCache
twitterPlaceData = self.data.getFromTree(['place'])
if twitterPlaceData is not None:
self.twitter_place = Place(twitterPlaceData)
else:
self.twitter_place = None
userJson = self.data.getFromTree(['user'])
if userJson is None:
self._user = None
else:
self._user = User(userJson, twitterSession=twitterSession, isAssociatedWithTweet=True, twitterPlace=self.twitter_place, currentLocationCoordinate=self.coordinate)
if twitterSession is not None:
self.instance_key = twitterSession.instance_key
else:
self.instance_key = None
self.twitter_session = twitterSession
def __init__(self, userJson, twitterSession, fromCache=False, isFollowee=False, isAssociatedWithTweet=False, twitterPlace=None, currentLocationCoordinate=None, geocodeBias=None, knownFollowees=None):
Hashable.__init__(self)
Timestamped.__init__(self)
if twitterSession is not None:
assert isinstance(twitterSession, TwitterSession)
if twitterPlace is not None:
assert isinstance(twitterPlace, Place)
if knownFollowees is None:
knownFollowees = set()
self.allow_geocode_external = True
if userJson is None:
self.data = Tree.make()
else:
self.data = Tree.make(userJson)
# If false indicates that self.data is already in the cache,
# so no point readding.
self.isDataNew = not fromCache
self.is_followee = isFollowee
# This does not contain all followees, only followees known to our application
# through follower enrichment.
self.known_followees = knownFollowees
self.is_associated_with_tweet = isAssociatedWithTweet
self.twitter_session = twitterSession
if twitterSession is not None:
self.instance_key = twitterSession.instance_key
else:
self.instance_key = None
self.queued_for_follower_enrichment = False
self.current_location_coordinate = currentLocationCoordinate
self.twitter_place = twitterPlace
self.last_follower_enrichment_error = None
self.follower_enrichment_progress = UserFollowerEnrichmentProgress(self)
if self.num_followers is not None:
self.twitter_calls_to_retrieve_follower_ids = math.ceil(float(self.num_followers) / float(TwitterSession.GET_FOLLOWER_IDS_QUANTITY_PER_TWITTER_CALL))
else:
self.twitter_calls_to_retrieve_follower_ids = 1
self.geocoded_from = None
self.geocode_bias = None
self.analysers = None
def __init__(self, userJson, twitterSession, fromCache=False, isFollowee=False, isAssociatedWithTweet=False, twitterPlace=None, currentLocationCoordinate=None, geocodeBias=None, knownFollowees=None):
Hashable.__init__(self)
Timestamped.__init__(self)
if twitterSession is not None:
assert isinstance(twitterSession, TwitterSession)
if twitterPlace is not None:
assert isinstance(twitterPlace, Place)
if knownFollowees is None:
knownFollowees = set()
self.allow_geocode_external = True
if userJson is None:
self.data = Tree.make()
else:
self.data = Tree.make(userJson)
# If false indicates that self.data is already in the cache,
# so no point readding.
self.isDataNew = not fromCache
self.is_followee = isFollowee
# This does not contain all followees, only followees known to our application
# through follower enrichment.
self.known_followees = knownFollowees
self.is_associated_with_tweet = isAssociatedWithTweet
self.twitter_session = twitterSession
if twitterSession is not None:
self.instance_key = twitterSession.instance_key
else:
self.instance_key = None
self.queued_for_follower_enrichment = False
self.current_location_coordinate = currentLocationCoordinate
self.twitter_place = twitterPlace
self.last_follower_enrichment_error = None
self.follower_enrichment_progress = UserFollowerEnrichmentProgress(self)
if self.num_followers is not None:
self.twitter_calls_to_retrieve_follower_ids = math.ceil(float(self.num_followers) / float(TwitterSession.GET_FOLLOWER_IDS_QUANTITY_PER_TWITTER_CALL))
else:
self.twitter_calls_to_retrieve_follower_ids = 1
self.geocoded_from = None
self.geocode_bias = None
self.analysers = None
"""
Hash based on value of elements.
>>> m = pmap({pbag([1, 2]): "it's here!"})
>>> m[pbag([2, 1])]
"it's here!"
>>> pbag([1, 1, 2]) in m
False
"""
return hash(self._counts)
Container.register(PBag)
Iterable.register(PBag)
Sized.register(PBag)
Hashable.register(PBag)
def b(*elements):
"""
Construct a persistent bag.
Takes an arbitrary number of arguments to insert into the new persistent
bag.
>>> b(1, 2, 3, 2)
pbag([1, 2, 2, 3])
"""
return pbag(elements)
pmap({'a': 1, 'b': 2})
The changes are kept in the evolver. An updated pmap can be created using the
persistent() function on the evolver.
>>> m2 = e.persistent()
>>> m2
pmap({'c': 3, 'b': 2})
The new pmap will share data with the original pmap in the same way that would have
been done if only using operations on the pmap.
"""
return self._Evolver(self)
Mapping.register(PMap)
Hashable.register(PMap)
def _turbo_mapping(initial, pre_size):
if pre_size:
size = pre_size
else:
try:
size = 2 * len(initial) or 8
except Exception:
# Guess we can't figure out the length. Give up on length hinting,
# we can always reallocate later.
size = 8
buckets = size * [None]
def get_vmc_version():
import os
from subprocess import check_output, CalledProcessError
original_directory = os.getcwd()
try:
os.chdir(os.path.dirname(__file__))
try:
return check_output(["git", "describe", "--always"])
except CalledProcessError:
return None
finally:
os.chdir(original_directory)
import six
if six.PY3:
import numpy
from collections import Hashable
from numbers import Integral
# FIXME: track down why we are passing around these int64's anyway
if not isinstance(numpy.int64, Integral):
Integral.register(numpy.int64)
if not isinstance(numpy.int64, Hashable):
Hashable.register(numpy.int64)
# FIXME: numpy.ndarray is Hashable in python2 but not python3. Honestly, I
# don't think it should be in either...
Hashable.register(numpy.ndarray)
pmap({'a': 1, 'b': 2})
The changes are kept in the evolver. An updated pmap can be created using the
persistent() function on the evolver.
>>> m2 = e.persistent()
>>> m2
pmap({'c': 3, 'b': 2})
The new pmap will share data with the original pmap in the same way that would have
been done if only using operations on the pmap.
"""
return self._Evolver(self)
Mapping.register(PMap)
Hashable.register(PMap)
def _turbo_mapping(initial, pre_size):
size = pre_size or (2 * len(initial)) or 8
buckets = size * [None]
if not isinstance(initial, Mapping):
# Make a dictionary of the initial data if it isn't already,
# that will save us some job further down since we can assume no
# key collisions
initial = dict(initial)
for k, v in six.iteritems(initial):
h = hash(k)
index = h % size
return result
class NamedspaceMeta(type):
"Metaclass for namedspace classes"
@property
def _field_names(self):
return self._all_fields
@property
def _field_names_iter(self):
return iter(self._all_fields)
_class_template = """\
class {typename}(object):
__metaclass__ = NamedspaceMeta
"{typename}({arg_list})"
class FieldNameError(AttributeError, KeyError): pass
class ReadOnlyNamedspaceError(TypeError): pass
class ReadOnlyFieldError(TypeError): pass
class MutableNamedspaceError(TypeError): pass
_all_fields = all_fields
_all_fields_set = all_fields_set
_required_fields_set = required_fields_set
_mutable_fields_set = mutable_fields_set
_default_values = default_values
_default_value_factories = default_value_factories
"""
Hash based on value of elements.
>>> m = pmap({pbag([1, 2]): "it's here!"})
>>> m[pbag([2, 1])]
"it's here!"
>>> pbag([1, 1, 2]) in m
False
"""
return hash(self._counts)
Container.register(PBag)
Iterable.register(PBag)
Sized.register(PBag)
Hashable.register(PBag)
def b(*elements):
"""
Construct a persistent bag.
Takes an arbitrary number of arguments to insert into the new persistent
bag.
>>> b(1, 2, 3, 2)
pbag([1, 2, 2, 3])
"""
return pbag(elements)
__slots__ = ('first', 'rest')
def __new__(cls, first, rest):
instance = super(PList, cls).__new__(cls)
instance.first = first
instance.rest = rest
return instance
def __bool__(self):
return True
__nonzero__ = __bool__
Sequence.register(PList)
Hashable.register(PList)
class _EmptyPList(_PListBase):
__slots__ = ()
def __bool__(self):
return False
__nonzero__ = __bool__
@property
def first(self):
raise AttributeError("Empty PList has no first")
@property
type(index).__name__)
if index >= 0:
return self.popleft(index).left
shifted = len(self) + index
if shifted < 0:
raise IndexError(
"pdeque index {0} out of range {1}".format(index, len(self)), )
return self.popleft(shifted).left
index = Sequence.index
Sequence.register(PDeque)
Hashable.register(PDeque)
def pdeque(iterable=(), maxlen=None):
"""
Return deque containing the elements of iterable. If maxlen is specified then
len(iterable) - maxlen elements are discarded from the left to if len(iterable) > maxlen.
>>> pdeque([1, 2, 3])
pdeque([1, 2, 3])
>>> pdeque([1, 2, 3, 4], maxlen=2)
pdeque([3, 4], maxlen=2)
"""
t = tuple(iterable)
if maxlen is not None:
t = t[-maxlen:]
result = result.pop(self._length - (index.stop % self._length))
return result
if not isinstance(index, Integral):
raise TypeError("'%s' object cannot be interpreted as an index" % type(index).__name__)
if index >= 0:
return self.popleft(index).left
return self.pop(index).right
index = Sequence.index
Sequence.register(PDeque)
Hashable.register(PDeque)
def pdeque(iterable=(), maxlen=None):
"""
Return deque containing the elements of iterable. If maxlen is specified then
len(iterable) - maxlen elements are discarded from the left to if len(iterable) > maxlen.
>>> pdeque([1, 2, 3])
pdeque([1, 2, 3])
>>> pdeque([1, 2, 3, 4], maxlen=2)
pdeque([3, 4], maxlen=2)
"""
t = tuple(iterable)
if maxlen is not None:
t = t[-maxlen:]
4
"""
return self._tolist().index(value, *args, **kwargs)
def count(self, value):
"""
Return the number of times that value appears in the vector.
>>> v1 = v(1, 4, 3, 4)
>>> v1.count(4)
2
"""
return self._tolist().count(value)
Sequence.register(PVector)
Hashable.register(PVector)
_EMPTY_VECTOR = PVector(0, SHIFT, [], [])
def _pvector(sequence=()):
"""
Factory function, returns a new PVector object containing the elements in sequence.
>>> v1 = pvector([1, 2, 3])
>>> v1
(1, 2, 3)
"""
return _EMPTY_VECTOR.extend(sequence)
print "Container Abstract Base Class"
from collections import Container
print(Container.__subclasshook__(list))
print(Container.__subclasshook__(dict))
print(Container.__subclasshook__(set))
print(Container.__subclasshook__(tuple))
import string
print(Container.__subclasshook__(string))
class WorldContainer(Container):
def __contains__(self, item):
return False
print(Container.__subclasshook__(WorldContainer))
print(WorldContainer().__contains__(4))
print "Hashable Abstract Base Class"
from collections import Hashable
print(Hashable.__subclasshook__(string))
class WorldCHashable(Hashable):
def __hash__(self, item):
return id(item)
print(Hashable.__subclasshook__(WorldCHashable))
print(WorldCHashable().__hash__(4))
# to read more details https://docs.python.org/2/library/collections.html
__and__ = Set.__and__
__or__ = Set.__or__
__sub__ = Set.__sub__
__xor__ = Set.__xor__
issubset = __le__
issuperset = __ge__
union = __or__
intersection = __and__
difference = __sub__
symmetric_difference = __xor__
isdisjoint = Set.isdisjoint
Set.register(PSet)
Hashable.register(PSet)
_EMPTY_PSET = PSet(pmap())
def pset(iterable=(), pre_size=8):
"""
Creates a persistent set from iterable. Optionally takes a sizing parameter equivalent to that
used for :py:func:`pmap`.
>>> s1 = pset([1, 2, 3, 2])
>>> s1
pset([1, 2, 3])
"""
if not iterable:
return _EMPTY_PSET
__and__ = Set.__and__
__or__ = Set.__or__
__sub__ = Set.__sub__
__xor__ = Set.__xor__
issubset = __le__
issuperset = __ge__
union = __or__
intersection = __and__
difference = __sub__
symmetric_difference = __xor__
isdisjoint = Set.isdisjoint
Set.register(PSet)
Hashable.register(PSet)
_EMPTY_PSET = PSet(pmap())
def pset(iterable=(), pre_size=8):
"""
Creates a persistent set from iterable. Optionally takes a sizing parameter equivalent to that
used for :py:func:`pmap`.
>>> s1 = pset([1, 2, 3, 2])
>>> s1
pset([1, 2, 3])
"""
if not iterable:
return _EMPTY_PSET
@abstractmethod
def delete(self, index, stop=None):
"""
Delete a portion of the vector by index or range.
>>> v1 = v(1, 2, 3, 4, 5)
>>> v1.delete(1)
pvector([1, 3, 4, 5])
>>> v1.delete(1, 3)
pvector([1, 4, 5])
"""
_EMPTY_PVECTOR = PythonPVector(0, SHIFT, [], [])
PVector.register(PythonPVector)
Sequence.register(PVector)
Hashable.register(PVector)
def python_pvector(iterable=()):
"""
Create a new persistent vector containing the elements in iterable.
>>> v1 = pvector([1, 2, 3])
>>> v1
pvector([1, 2, 3])
"""
return _EMPTY_PVECTOR.extend(iterable)
try:
# Use the C extension as underlying trie implementation if it is available
import os
if os.environ.get('PYRSISTENT_NO_C_EXTENSION'):
"""
__slots__ = ('first', 'rest')
def __new__(cls, first, rest):
instance = super(PList, cls).__new__(cls)
instance.first = first
instance.rest = rest
return instance
def __bool__(self):
return True
__nonzero__ = __bool__
Sequence.register(PList)
Hashable.register(PList)
class _EmptyPList(_PListBase):
__slots__ = ()
def __bool__(self):
return False
__nonzero__ = __bool__
@property
def first(self):
raise AttributeError("Empty PList has no first")
@property
def rest(self):
def delete(self, index, stop=None):
"""
Delete a portion of the vector by index or range.
>>> v1 = v(1, 2, 3, 4, 5)
>>> v1.delete(1)
pvector([1, 3, 4, 5])
>>> v1.delete(1, 3)
pvector([1, 4, 5])
"""
_EMPTY_PVECTOR = PythonPVector(0, SHIFT, [], [])
PVector.register(PythonPVector)
Sequence.register(PVector)
Hashable.register(PVector)
def python_pvector(iterable=()):
"""
Create a new persistent vector containing the elements in iterable.
>>> v1 = pvector([1, 2, 3])
>>> v1
pvector([1, 2, 3])
"""
return _EMPTY_PVECTOR.extend(iterable)
try:
# Use the C extension as underlying trie implementation if it is available
