def stream(self, batch):
response = self.post(batch)
try:
for i, result_data in grouped(response):
result = JobResult.hydrate(assembled(result_data), batch)
log.info("<<< %s", result)
yield result
finally:
response.close()
def stream(self, batch):
response = self.post(batch)
try:
for i, result_data in grouped(response):
result = JobResult.hydrate(assembled(result_data), batch)
log.info("<<< %s", result)
yield result
finally:
response.close()
def stream(self, batch):
""" Execute a collection of jobs and yield results as received.
:arg batch: A :class:`.Batch` of jobs.
:rtype: generator
"""
response = self.post(batch)
try:
for i, result_data in grouped(response):
result = JobResult.hydrate(assembled(result_data), batch)
log.info("< %s", result)
yield result
finally:
response.close()
def stream(self, batch):
""" Execute a collection of jobs and yield results as received.
:arg batch: A :class:`.Batch` of jobs.
:rtype: generator
"""
response = self.post(batch)
try:
for i, result_data in grouped(response):
result = JobResult.hydrate(assembled(result_data), batch)
log.info("< %s", result)
yield result
finally:
response.close()
def get(self, key, value):
""" Fetch a list of all entities from the index which are associated
with the `key`:`value` pair supplied::
# obtain a reference to the "People" node index and
# get all nodes where `family_name` equals "Smith"
people = graph.get_or_create_index(neo4j.Node, "People")
smiths = people.get("family_name", "Smith")
..
"""
return [
self.graph.hydrate(assembled(result))
for i, result in grouped(self._searcher.expand(key=key, value=value).get())
]
def get(self, key, value):
""" Fetch a list of all entities from the index which are associated
with the `key`:`value` pair supplied::
# obtain a reference to the "People" node index and
# get all nodes where `family_name` equals "Smith"
people = graph.get_or_create_index(neo4j.Node, "People")
smiths = people.get("family_name", "Smith")
..
"""
return [
self.graph.hydrate(assembled(result)) for i, result in grouped(
self._searcher.expand(key=key, value=value).get())
]
def query(self, query):
""" Query the index according to the supplied query criteria, returning
a list of matched entities::
# obtain a reference to the "People" node index and
# get all nodes where `family_name` equals "Smith"
people = graph.get_or_create_index(neo4j.Node, "People")
s_people = people.query("family_name:S*")
The query syntax used should be appropriate for the configuration of
the index being queried. For indexes with default configuration, this
should be Apache Lucene query syntax.
"""
resource = self._query_template.expand(query=query)
for i, result in grouped(resource.get()):
yield self.graph.hydrate(assembled(result))
def query(self, query):
""" Query the index according to the supplied query criteria, returning
a list of matched entities::
# obtain a reference to the "People" node index and
# get all nodes where `family_name` equals "Smith"
people = graph.get_or_create_index(neo4j.Node, "People")
s_people = people.query("family_name:S*")
The query syntax used should be appropriate for the configuration of
the index being queried. For indexes with default configuration, this
should be Apache Lucene query syntax.
"""
resource = self._query_template.expand(query=query)
for i, result in grouped(resource.get()):
yield self.graph.hydrate(assembled(result))
def _query_with_score(self, query, order):
resource = self._query_template.expand(query=query, order=order)
for i, result in grouped(resource.get()):
meta = assembled(result)
yield self.graph.hydrate(meta), meta["score"]
def __iter__(self):
for i, response in grouped(self.__response):
yield BatchResponse.hydrate(assembled(response),
self.body_hydrator)
self.close()
def _query_with_score(self, query, order):
resource = self._query_template.expand(query=query, order=order)
for i, result in grouped(resource.get()):
meta = assembled(result)
yield self.graph.hydrate(meta), meta["score"]
def __iter__(self):
for i, response in grouped(self.__response):
yield BatchResponse.hydrate(assembled(response), self.body_hydrator)
self.close()
