def test_store_get_result():
"test whether results can be stored and retrieved"
from xtas.tasks.es import store_single, get_single_result, get_all_results
idx, typ = ES_TEST_INDEX, ES_TEST_TYPE
with clean_es() as es:
id = es.index(index=idx, doc_type=typ, body={"text": "test"})['_id']
assert_equal(get_single_result("task1", idx, typ, id), None)
assert_equal(get_all_results(idx, typ, id), {})
store_single("task1_result", "task1", idx, typ, id)
client.indices.IndicesClient(es).flush()
assert_equal(get_single_result("task1", idx, typ, id), "task1_result")
assert_equal(get_all_results(idx, typ, id), {"task1": "task1_result"})
# test second result and test non-scalar data
task2_result = {"a": {"b": ["c", "d"]}}
store_single(task2_result, "task2", idx, typ, id)
client.indices.IndicesClient(es).flush()
assert_equal(get_single_result("task1", idx, typ, id), "task1_result")
assert_equal(get_single_result("task2", idx, typ, id), task2_result)
assert_equal(get_all_results(idx, typ, id),
{"task1": "task1_result", "task2": task2_result})
# store a task result under an existing task, check that it is replaced
store_single("task1_result2", "task1", idx, typ, id)
client.indices.IndicesClient(es).flush()
assert_equal(get_single_result("task1", idx, typ, id), "task1_result2")
assert_equal(get_single_result("task2", idx, typ, id), task2_result)
assert_equal(get_all_results(idx, typ, id),
{"task1": "task1_result2", "task2": task2_result})
# check that the original document is intact
src = es.get_source(index=idx, doc_type=typ, id=id)
assert_equal(src['text'], "test")
def pipeline(doc,
pipeline,
store_final=True,
store_intermediate=False,
block=True):
"""
Get the result for a given document.
Pipeline should be a list of dicts, with members task and argument
e.g. [{"module" : "tokenize"},
{"module" : "pos_tag", "arguments" : {"model" : "nltk"}}]
@param block: if True, it will block and return the actual result.
If False, it will return an AsyncResult unless the result was
cached, in which case it returns the result immediately (!)
@param store_final: if True, store the final result
@param store_intermediate: if True, store all intermediate results as well
"""
# form basic pipeline by resolving task dictionaries to task objects
tasks = [_get_task(t) for t in pipeline]
if is_es_document(doc):
idx, typ, id, field = es_address(doc)
chain = []
input = None
# Check cache for existing documents
# Iterate over tasks in reverse order, check cached result, and
# otherwise prepend task (and cache store command) to chain
for i in range(len(tasks), 0, -1):
taskname = "__".join(t.task for t in tasks[:i])
input = get_single_result(taskname, idx, typ, id)
if input:
break
if (i == len(tasks) and store_final) or store_intermediate:
chain.insert(0, store_single.s(taskname, idx, typ, id))
chain.insert(0, tasks[i - 1])
if not chain: # final result was cached, good!
return input
elif input is None:
input = fetch(doc)
else:
# the doc is a string, so we can't use caching
chain = tasks
input = doc
chain = celery.chain(*chain).delay(input)
if block:
return chain.get()
else:
return chain
def pipeline(doc, pipeline, store_final=True, store_intermediate=False,
block=True):
"""
Get the result for a given document.
Pipeline should be a list of dicts, with members task and argument
e.g. [{"module" : "tokenize"},
{"module" : "pos_tag", "arguments" : {"model" : "nltk"}}]
@param block: if True, it will block and return the actual result.
If False, it will return an AsyncResult unless the result was
cached, in which case it returns the result immediately (!)
@param store_final: if True, store the final result
@param store_intermediate: if True, store all intermediate results as well
"""
# form basic pipeline by resolving task dictionaries to task objects
tasks = [_get_task(t) for t in pipeline]
if is_es_document(doc):
idx, typ, id, field = es_address(doc)
chain = []
input = None
# Check cache for existing documents
# Iterate over tasks in reverse order, check cached result, and
# otherwise prepend task (and cache store command) to chain
for i in range(len(tasks), 0, -1):
taskname = "__".join(t.task for t in tasks[:i])
input = get_single_result(taskname, idx, typ, id)
if input:
break
if (i == len(tasks) and store_final) or store_intermediate:
chain.insert(0, store_single.s(taskname, idx, typ, id))
chain.insert(0, tasks[i-1])
if not chain: # final result was cached, good!
return input
elif input is None:
input = fetch(doc)
else:
# the doc is a string, so we can't use caching
chain = tasks
input = doc
chain = celery.chain(*chain).delay(input)
if block:
return chain.get()
else:
return chain
def test_store_get_result():
"test whether results can be stored and retrieved"
from xtas.tasks.es import (
store_single,
get_single_result,
get_tasks_per_index,
fetch_documents_by_task,
fetch_results_by_document,
fetch_query_details_batch
)
idx, typ = ES_TEST_INDEX, ES_TEST_TYPE
with clean_es() as es:
id = es.index(index=idx, doc_type=typ, body={"text": "test"})['_id']
assert_equal(get_single_result("task1", idx, typ, id), None)
store_single("task1_result", "task1", idx, typ, id)
client.indices.IndicesClient(es).flush()
assert_equal(get_single_result("task1", idx, typ, id), "task1_result")
assert_in("task1", get_tasks_per_index(idx, typ))
# test second result and test non-scalar data
task2_result = {"a": {"b": ["c", "d"]}}
store_single(task2_result, "task2", idx, typ, id)
client.indices.IndicesClient(es).flush()
assert_equal(get_single_result("task1", idx, typ, id), "task1_result")
assert_equal(get_single_result("task2", idx, typ, id), task2_result)
query = {"match": {"b": {"query": "c"}}}
assert_equal(len(fetch_documents_by_task(idx, typ, query, "task2")),
1)
query = {"match": {"text": {"query": "test"}}}
results = fetch_results_by_document(idx, typ, query, "task2")
assert_equal(len(results), 1)
results = fetch_query_details_batch(idx, typ, query, True)
assert_in("task1", results[0][1])
assert_in("task2", results[0][1])
results = fetch_query_details_batch(idx, typ, query,
tasknames=["task2"])
assert_in("task2", results[0][1])
# store a task result under an existing task, check that it is replaced
store_single("task1_result2", "task1", idx, typ, id)
client.indices.IndicesClient(es).flush()
assert_equal(get_single_result("task1", idx, typ, id), "task1_result2")
assert_equal(get_single_result("task2", idx, typ, id), task2_result)
# check that the original document is intact
src = es.get_source(index=idx, doc_type=typ, id=id)
assert_equal(src['text'], "test")
def test_store_get_result():
"test whether results can be stored and retrieved"
from xtas.tasks.es import store_single, get_single_result, get_all_results
idx, typ = ES_TEST_INDEX, ES_TEST_TYPE
with clean_es() as es:
id = es.index(index=idx, doc_type=typ, body={"text": "test"})['_id']
assert_equal(get_single_result("task1", idx, typ, id), None)
assert_equal(get_all_results(idx, typ, id), {})
r = store_single("task1_result",
"task1",
idx,
typ,
id,
return_data=False)
assert_equal(r, None)
client.indices.IndicesClient(es).flush()
assert_equal(get_single_result("task1", idx, typ, id), "task1_result")
assert_equal(get_all_results(idx, typ, id), {"task1": "task1_result"})
# test second result and test non-scalar data
task2_result = {"a": {"b": ["c", "d"]}}
store_single(task2_result, "task2", idx, typ, id)
client.indices.IndicesClient(es).flush()
assert_equal(get_single_result("task1", idx, typ, id), "task1_result")
assert_equal(get_single_result("task2", idx, typ, id), task2_result)
assert_equal(get_all_results(idx, typ, id), {
"task1": "task1_result",
"task2": task2_result
})
# store a task result under an existing task, check that it is replaced
store_single("task1_result2", "task1", idx, typ, id)
client.indices.IndicesClient(es).flush()
assert_equal(get_single_result("task1", idx, typ, id), "task1_result2")
assert_equal(get_single_result("task2", idx, typ, id), task2_result)
assert_equal(get_all_results(idx, typ, id), {
"task1": "task1_result2",
"task2": task2_result
})
# check that the original document is intact
src = es.get_source(index=idx, doc_type=typ, id=id)
assert_equal(src['text'], "test")
def test_store_get_result():
"test whether results can be stored and retrieved"
from xtas.tasks.es import (store_single, get_single_result,
get_tasks_per_index, fetch_documents_by_task,
fetch_results_by_document,
fetch_query_details_batch)
idx, typ = ES_TEST_INDEX, ES_TEST_TYPE
with clean_es() as es:
id = es.index(index=idx, doc_type=typ, body={"text": "test"})['_id']
assert_equal(get_single_result("task1", idx, typ, id), None)
store_single("task1_result", "task1", idx, typ, id)
client.indices.IndicesClient(es).flush()
assert_equal(get_single_result("task1", idx, typ, id), "task1_result")
assert_in("task1", get_tasks_per_index(idx, typ))
# test second result and test non-scalar data
task2_result = {"a": {"b": ["c", "d"]}}
store_single(task2_result, "task2", idx, typ, id)
client.indices.IndicesClient(es).flush()
assert_equal(get_single_result("task1", idx, typ, id), "task1_result")
assert_equal(get_single_result("task2", idx, typ, id), task2_result)
query = {"match": {"b": {"query": "c"}}}
assert_equal(len(fetch_documents_by_task(idx, typ, query, "task2")), 1)
query = {"match": {"text": {"query": "test"}}}
results = fetch_results_by_document(idx, typ, query, "task2")
assert_equal(len(results), 1)
results = fetch_query_details_batch(idx, typ, query, True)
assert_in("task1", results[0][1])
assert_in("task2", results[0][1])
results = fetch_query_details_batch(idx,
typ,
query,
tasknames=["task2"])
assert_in("task2", results[0][1])
# store a task result under an existing task, check that it is replaced
store_single("task1_result2", "task1", idx, typ, id)
client.indices.IndicesClient(es).flush()
assert_equal(get_single_result("task1", idx, typ, id), "task1_result2")
assert_equal(get_single_result("task2", idx, typ, id), task2_result)
# check that the original document is intact
src = es.get_source(index=idx, doc_type=typ, id=id)
assert_equal(src['text'], "test")