def parser(stream, objconf, tuples, **kwargs):
""" Parses the pipe content
Args:
stream (Iter[dict]): The source. Note: this shares the `tuples`
iterator, so consuming it will consume `tuples` as well.
objconf (obj): the item independent configuration (an Objectify
instance).
tuples (Iter[(dict, obj)]): Iterable of tuples of (item, objconf)
`item` is an element in the source stream and `objconf` is the item
configuration (an Objectify instance). Note: this shares the
`stream` iterator, so consuming it will consume `stream` as well.
kwargs (dict): Keyword arguments.
Kwargs:
others (List[Iter(dict)]): List of streams to join
Returns:
Iter(dict): The output stream
Examples:
>>> from itertools import repeat
>>>
>>> stream = ({'x': x} for x in range(5))
>>> other1 = ({'x': x + 5} for x in range(5))
>>> other2 = ({'x': x + 10} for x in range(5))
>>> kwargs = {'others': [other1, other2]}
>>> tuples = zip(stream, repeat(None))
>>> len(list(parser(stream, None, tuples, **kwargs)))
15
"""
return chain(stream, multiplex(kwargs['others']))
def output(self):
source = yield self.source
async_pipeline = partial(self.async_pipe, **self.kwargs)
if self.mapify:
args = (async_pipeline, source, self.connections)
mapped = yield ait.async_map(*args)
output = multiplex(mapped)
else:
output = yield async_pipeline(source)
return_value(output)
def output(self):
pipeline = partial(self.pipe, **self.kwargs)
if self.parallelize:
zipped = zip(self.source, repeat(pipeline))
mapped = self.map(listpipe, zipped, chunksize=self.chunksize)
elif self.mapify:
mapped = self.map(pipeline, self.source)
if self.parallelize and not self.reuse_pool:
self.pool.close()
self.pool.join()
return multiplex(mapped) if self.mapify else pipeline(self.source)
def async_fetch(self):
"""Fetch all source urls"""
args = (async_get_pipe, self.zargs, self.connections)
mapped = yield ait.async_map(*args)
return_value(multiplex(mapped))
def fetch(self):
"""Fetch all source urls"""
kwargs = {'chunksize': self.chunksize} if self.parallel else {}
mapped = self.map(getpipe, self.zargs, **kwargs)
return multiplex(mapped)
def wrapper(items=None, **kwargs):
module_name = wrapper.__module__.split('.')[-1]
wrapper.__dict__['name'] = module_name
defaults = {
'dictize': True, 'ftype': 'pass', 'ptype': 'pass',
'objectify': True, 'emit': True, 'assign': module_name}
combined = merge([self.defaults, defaults, self.opts, kwargs])
extracted = 'extract' in combined
pdictize = combined.get('listize') if extracted else True
combined.setdefault('pdictize', pdictize)
conf = {k: combined[k] for k in self.defaults}
conf.update(kwargs.get('conf', {}))
combined.update({'conf': conf})
# replace conf with dictized version so we can access its
# attributes even if we already extracted a value
updates = {'conf': DotDict(conf), 'assign': combined.get('assign')}
kwargs.update(updates)
items = items or iter([])
_INPUT = map(DotDict, items) if combined.get('dictize') else items
bfuncs = get_broadcast_funcs(**combined)
types = {combined['ftype'], combined['ptype']}
if types.difference({'pass', 'none'}):
dfuncs = get_dispatch_funcs(**combined)
else:
dfuncs = None
pairs = (_dispatch(item, bfuncs, dfuncs=dfuncs) for item in _INPUT)
parsed, _ = _dispatch(DotDict(), bfuncs, dfuncs=dfuncs)
# - operators can't skip items
# - purposely setting both variables to maps of the same iterable
# since only one is intended to be used at any given time
# - `tuples` is an iterator of tuples of the first two `parsed`
# elements
tuples = ((p[0][0], p[0][1]) for p in pairs)
orig_stream = (p[0][0] for p in pairs)
objconf = parsed[1]
if self.async:
stream = yield pipe(orig_stream, objconf, tuples, **kwargs)
else:
stream = pipe(orig_stream, objconf, tuples, **kwargs)
sub_type = 'aggregator' if hasattr(stream, 'keys') else 'composer'
wrapper.__dict__['sub_type'] = sub_type
# operators can only assign one value per item and can't skip items
_, assignment = get_assignment(stream, **combined)
if combined.get('emit'):
stream = assignment
else:
singles = (iter([v]) for v in assignment)
key = combined.get('assign')
assigned = (assign({}, s, key, one=True) for s in singles)
stream = multiplex(assigned)
if self.async:
return_value(stream)
else:
for s in stream:
yield s
def wrapper(items=None, **kwargs):
module_name = wrapper.__module__.split('.')[-1]
wrapper.__dict__['name'] = module_name
defaults = {
'dictize': True, 'ftype': 'pass', 'ptype': 'pass',
'objectify': True, 'emit': True, 'assign': module_name}
combined = merge([self.defaults, defaults, self.opts, kwargs])
extracted = 'extract' in combined
pdictize = combined.get('listize') if extracted else True
combined.setdefault('pdictize', pdictize)
conf = {k: combined[k] for k in self.defaults}
conf.update(kwargs.get('conf', {}))
combined.update({'conf': conf})
uconf = DotDict(conf) if combined.get('dictize') else conf
updates = {'conf': uconf, 'assign': combined.get('assign')}
kwargs.update(updates)
items = items or iter([])
_INPUT = map(DotDict, items) if combined.get('dictize') else items
bfuncs = get_broadcast_funcs(**combined)
types = {combined['ftype'], combined['ptype']}
if types.difference({'pass', 'none'}):
dfuncs = get_dispatch_funcs(**combined)
else:
dfuncs = None
pairs = (_dispatch(item, bfuncs, dfuncs=dfuncs) for item in _INPUT)
parsed, _ = _dispatch(DotDict(), bfuncs, dfuncs=dfuncs)
# - operators can't skip items
# - purposely setting both variables to maps of the same iterable
# since only one is intended to be used at any given time
# - `tuples` is an iterator of tuples of the first two `parsed`
# elements
tuples = ((p[0][0], p[0][1]) for p in pairs)
orig_stream = (p[0][0] for p in pairs)
objconf = parsed[1]
if self.async:
stream = yield pipe(orig_stream, objconf, tuples, **kwargs)
else:
stream = pipe(orig_stream, objconf, tuples, **kwargs)
sub_type = 'aggregator' if hasattr(stream, 'keys') else 'composer'
wrapper.__dict__['sub_type'] = sub_type
# operators can only assign one value per item and can't skip items
_, assignment = get_assignment(stream, **combined)
if combined.get('emit'):
stream = assignment
else:
singles = (iter([v]) for v in assignment)
assigned = (
assign({}, s, one=True, **combined) for s in singles)
stream = multiplex(assigned)
if self.async:
return_value(stream)
else:
for s in stream:
yield s
