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]
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
bucket = buckets[index]
if bucket:
bucket.append((k, v))
else:
buckets[index] = [(k, v)]
return PMap(len(initial), pvector().extend(buckets))
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]
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 initial.items():
h = hash(k)
index = h % size
bucket = buckets[index]
if bucket:
bucket.append((k, v))
else:
buckets[index] = [(k, v)]
return PMap(len(initial), pvector().extend(buckets))
def freeze(o):
"""
Recursively convert simple Python containers into pyrsistent versions
of those containers.
- list is converted to pvector, recursively
- dict is converted to pmap, recursively on values (but not keys)
- set is converted to pset, but not recursively
- tuple is converted to tuple, recursively.
Sets and dict keys are not recursively frozen because they do not contain
mutable data by convention. The main exception to this rule is that
dict keys and set elements are often instances of mutable objects that
support hash-by-id, which this function can't convert anyway.
>>> freeze(set([1, 2]))
pset([1, 2])
>>> freeze([1, {'a': 3}])
pvector([1, pmap({'a': 3})])
>>> freeze((1, []))
(1, pvector([]))
"""
typ = type(o)
if typ is dict:
return pmap(dict((k, freeze(v)) for k, v in six.iteritems(o)))
if typ is list:
return pvector(map(freeze, o))
if typ is tuple:
return tuple(map(freeze, o))
if typ is set:
return pset(o)
return o
def freeze(o):
"""
Recursively convert simple Python containers into pyrsistent versions
of those containers.
- list is converted to pvector, recursively
- dict is converted to pmap, recursively on values (but not keys)
- set is converted to pset, but not recursively
- tuple is converted to tuple, recursively.
Sets and dict keys are not recursively frozen because they do not contain
mutable data by convention. The main exception to this rule is that
dict keys and set elements are often instances of mutable objects that
support hash-by-id, which this function can't convert anyway.
>>> freeze(set([1, 2]))
pset([1, 2])
>>> freeze([1, {'a': 3}])
pvector([1, pmap({'a': 3})])
>>> freeze((1, []))
(1, pvector([]))
"""
typ = type(o)
if typ is dict:
return pmap(dict((k, freeze(v)) for k, v in six.iteritems(o)))
if typ is list:
return pvector(map(freeze, o))
if typ is tuple:
return tuple(map(freeze, o))
if typ is set:
return pset(o)
return o
def _reallocate(self, new_size):
new_list = new_size * [None]
buckets = self._buckets_evolver.persistent()
for k, v in chain.from_iterable(x for x in buckets if x):
index = hash(k) % new_size
if new_list[index]:
new_list[index].append((k, v))
else:
new_list[index] = [(k, v)]
self._buckets_evolver = pvector().extend(new_list).evolver()
def _reallocate(self, new_size):
new_list = new_size * [None]
buckets = self._buckets_evolver.persistent()
for k, v in chain.from_iterable(x for x in buckets if x):
index = hash(k) % new_size
if new_list[index]:
new_list[index].append((k, v))
else:
new_list[index] = [(k, v)]
self._buckets_evolver = pvector().extend(new_list).evolver()
def _reallocate(self, new_size):
new_list = new_size * [None]
buckets = self._buckets_evolver.persistent()
for k, v in chain.from_iterable(x for x in buckets if x):
index = hash(k) % new_size
if new_list[index]:
new_list[index].append((k, v))
else:
new_list[index] = [(k, v)]
# A reallocation should always result in a dirty buckets evolver to avoid
# possible loss of elements when doing the reallocation.
self._buckets_evolver = pvector().evolver()
self._buckets_evolver.extend(new_list)
def _reallocate(self, new_size):
new_list = new_size * [None]
buckets = self._buckets_evolver.persistent()
for k, v in chain.from_iterable(x for x in buckets if x):
index = hash(k) % new_size
if new_list[index]:
new_list[index].append((k, v))
else:
new_list[index] = [(k, v)]
# A reallocation should always result in a dirty buckets evolver to avoid
# possible loss of elements when doing the reallocation.
self._buckets_evolver = pvector().evolver()
self._buckets_evolver.extend(new_list)
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
bucket = buckets[index]
if bucket:
bucket.append((k, v))
else:
buckets[index] = [(k, v)]
return PMap(len(initial), pvector().extend(buckets))
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
bucket = buckets[index]
if bucket:
bucket.append((k, v))
else:
buckets[index] = [(k, v)]
return PMap(len(initial), pvector().extend(buckets))
def freeze(o, strict=True):
"""
Recursively convert simple Python containers into pyrsistent versions
of those containers.
- list is converted to pvector, recursively
- dict is converted to pmap, recursively on values (but not keys)
- set is converted to pset, but not recursively
- tuple is converted to tuple, recursively.
If strict == True (default):
- freeze is called on elements of pvectors
- freeze is called on values of pmaps
Sets and dict keys are not recursively frozen because they do not contain
mutable data by convention. The main exception to this rule is that
dict keys and set elements are often instances of mutable objects that
support hash-by-id, which this function can't convert anyway.
>>> freeze(set([1, 2]))
pset([1, 2])
>>> freeze([1, {'a': 3}])
pvector([1, pmap({'a': 3})])
>>> freeze((1, []))
(1, pvector([]))
"""
typ = type(o)
if typ is dict or (strict and isinstance(o, PMap)):
return pmap({k: freeze(v, strict) for k, v in o.items()})
if typ is list or (strict and isinstance(o, PVector)):
curried_freeze = lambda x: freeze(x, strict)
return pvector(map(curried_freeze, o))
if typ is tuple:
curried_freeze = lambda x: freeze(x, strict)
return tuple(map(curried_freeze, o))
if typ is set:
# impossible to have anything that needs freezing inside a set or pset
return pset(o)
return o
def items(self):
return pvector(self.iteritems())
def items(self):
return pvector(self.iteritems())
def keys(self):
return pvector(self.iterkeys())
def values(self):
return pvector(self.itervalues())
def keys(self):
return pvector(self.iterkeys())
def values(self):
return pvector(self.itervalues())
