def buffiter(obj, chunk=10, max_chunk=1000, factor=2):
"""Buffered iterator - reads the remote iterator in chunks starting with
*chunk*, multiplying the chunk size by *factor* every time, as an
exponential-backoff, up to a chunk of *max_chunk* size.
``buffiter`` is very useful for tight loops, where you fetch an element
from the other side with every iterator. Instead of being limited by the
network's latency after every iteration, ``buffiter`` fetches a "chunk"
of elements every time, reducing the amount of network I/Os.
:param obj: An iterable object (supports ``iter()``)
:param chunk: the initial chunk size
:param max_chunk: the maximal chunk size
:param factor: the factor by which to multiply the chunk size after every
iterator (up to *max_chunk*). Must be >= 1.
:returns: an iterator
Example::
cursor = db.get_cursor()
for id, name, dob in buffiter(cursor.select("Id", "Name", "DoB")):
print id, name, dob
"""
if factor < 1:
raise ValueError("factor must be >= 1, got %r" % (factor, ))
it = iter(obj)
count = chunk
while True:
items = syncreq(it, HANDLE_BUFFITER, count)
count = min(count * factor, max_chunk)
if not items:
break
for elem in items:
yield elem
def buffiter(obj, chunk = 10, max_chunk = 1000, factor = 2):
"""Buffered iterator - reads the remote iterator in chunks starting with
*chunk*, multiplying the chunk size by *factor* every time, as an
exponential-backoff, up to a chunk of *max_chunk* size.
``buffiter`` is very useful for tight loops, where you fetch an element
from the other side with every iterator. Instead of being limited by the
network's latency after every iteration, ``buffiter`` fetches a "chunk"
of elements every time, reducing the amount of network I/Os.
:param obj: An iterable object (supports ``iter()``)
:param chunk: the initial chunk size
:param max_chunk: the maximal chunk size
:param factor: the factor by which to multiply the chunk size after every
iterator (up to *max_chunk*). Must be >= 1.
:returns: an iterator
Example::
cursor = db.get_cursor()
for id, name, dob in buffiter(cursor.select("Id", "Name", "DoB")):
print id, name, dob
"""
if factor < 1:
raise ValueError("factor must be >= 1, got %r" % (factor,))
it = iter(obj)
count = chunk
while True:
items = syncreq(it, HANDLE_BUFFITER, count)
count = min(count * factor, max_chunk)
if not items:
break
for elem in items:
yield elem
def __array__(self, dtype=None):
# Note that protocol=-1 will only work between python
# interpreters of the same version.
res = netref.pickle.loads(
netref.syncreq(
self,
netref.consts.HANDLE_PICKLE,
netref.pickle.HIGHEST_PROTOCOL,
)
)
if dtype is not None:
res = numpy.asarray(res, dtype=dtype)
return res
def buffiter(obj, chunk = 10, max_chunk = 1000, factor = 2):
"""buffering iterator - reads the remote iterator in chunks starting with
`chunk` up to `max_chunk`, multiplying by `factor` as an exponential
backoff"""
if factor < 1:
raise ValueError("factor must be >= 1, got %r" % (factor,))
it = iter(obj)
count = chunk
while True:
items = syncreq(it, HANDLE_BUFFITER, count)
count = min(count * factor, max_chunk)
if not items:
break
for elem in items:
yield elem
