def test_fetch():
"Test whether tasks.fetch works as documented"
from xtas.tasks.es import fetch, es_document
# if doc is a string, fetching should return the string
assert_equal(fetch("Literal string"), "Literal string")
# index a document and fetch it with an es_document
with clean_es() as es:
d = es.index(index=ES_TEST_INDEX, doc_type=ES_TEST_TYPE,
body={"text": "test"})
doc = es_document(ES_TEST_INDEX, ES_TEST_TYPE, d['_id'], "text")
assert_equal(fetch(doc), "test")
def test_fetch():
"Test whether tasks.fetch works as documented"
from xtas.tasks.es import fetch, es_document
# if doc is a string, fetching should return the string
assert_equal(fetch("Literal string"), "Literal string")
# index a document and fetch it with an es_document
with clean_es() as es:
d = es.index(index=ES_TEST_INDEX,
doc_type=ES_TEST_TYPE,
body={"text": "test"})
doc = es_document(ES_TEST_INDEX, ES_TEST_TYPE, d['_id'], "text")
assert_equal(fetch(doc), "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 isinstance(doc, dict) and set(doc.keys()) == set(_ES_DOC_FIELDS):
idx, typ, id, field = [doc[k] for k in _ES_DOC_FIELDS]
chain = []
input = None
cache = get_all_results(idx, typ, id)
# 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])
if taskname in cache:
input = cache[taskname]
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
