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 test_pipeline_cache():
"Does the cache work correctly?"
import json
import nltk
from xtas.tasks.single import tokenize
from xtas.tasks.pipeline import pipeline
from xtas.tasks.es import es_document
text = "The cat is happy"
expected_tokens = [{
u'token': u'The'
}, {
u'token': u'cat'
}, {
u'token': u'is'
}, {
u'token': u'happy'
}]
expected_pos = [[u'The', u'DT'], [u'cat', u'NN'], [u'is', u'VBZ'],
[u'happy', u'JJ']]
with eager_celery(), clean_es() as es:
idx, typ = ES_TEST_INDEX, ES_TEST_TYPE
id = es.index(index=idx, doc_type=typ, body={"text": text})['_id']
doc = es_document(idx, typ, id, "text")
# test a single task 'pipeline'
pipe = [{"module": tokenize}]
r = pipeline(doc, pipe, store_intermediate=True)
assert_equal(r, expected_tokens)
# second time result should come from cache.
# Test with block=False which returns async object if not cached
r = pipeline(doc, pipe, store_intermediate=True, block=False)
assert_equal(r, expected_tokens)
# add pos_tag to pipeline. Check that tokenize is not called
# (anyone has a more elegant way to check that?)
pipe = [{
"module": "xtas.tasks.single.tokenize"
}, {
"module": "xtas.tasks.single.pos_tag",
"arguments": {
"model": "nltk"
}
}]
OLD_TOKENIZE = nltk.word_tokenize
nltk.word_tokenize = None
try:
r = pipeline(doc, pipe, store_intermediate=True)
# compare json to ignore tuple/list difference
assert_equal(json.dumps(r), json.dumps(expected_pos))
finally:
nltk.word_tokenize = OLD_TOKENIZE
# whole pipeline should now be skipped
r = pipeline(doc, pipe, store_intermediate=True, block=False)
assert_equal(json.dumps(r), json.dumps(expected_pos))
def test_pipeline_cache():
"Does the cache work correctly?"
import json
import nltk
from xtas.tasks.single import tokenize
from xtas.tasks.pipeline import pipeline
from xtas.tasks.es import es_document
text = "The cat is happy"
expected_tokens = [u"The", u"cat", u"is", u"happy"]
expected_pos = [[u"The", u"DT"], [u"cat", u"NN"], [u"is", u"VBZ"], [u"happy", u"JJ"]]
with eager_celery(), clean_es() as es:
idx, typ = ES_TEST_INDEX, ES_TEST_TYPE
id = es.index(index=idx, doc_type=typ, body={"text": text})["_id"]
doc = es_document(idx, typ, id, "text")
# test a single task 'pipeline'
pipe = [{"module": tokenize}]
r = pipeline(doc, pipe, store_intermediate=True)
assert_equal(r, expected_tokens)
# second time result should come from cache.
# Test with block=False which returns async object if not cached
client.indices.IndicesClient(es).flush()
r = pipeline(doc, pipe, store_intermediate=True, block=False)
assert_equal(r, expected_tokens)
# add pos_tag to pipeline. Check that tokenize is not called
# (anyone has a more elegant way to check that?)
pipe = [
{"module": "xtas.tasks.single.tokenize"},
{"module": "xtas.tasks.single.pos_tag", "arguments": {"model": "nltk"}},
]
OLD_TOKENIZE = nltk.word_tokenize
nltk.word_tokenize = None
try:
client.indices.IndicesClient(es).flush()
r = pipeline(doc, pipe, store_intermediate=True)
# compare json to ignore tuple/list difference
assert_equal(json.dumps(r), json.dumps(expected_pos))
finally:
nltk.word_tokenize = OLD_TOKENIZE
# whole pipeline should now be skipped
client.indices.IndicesClient(es).flush()
r = pipeline(doc, pipe, store_intermediate=True, block=False)
assert_equal(json.dumps(r), json.dumps(expected_pos))
# Simple example of how to construct a pipeline of operations from Python
# and apply them to an ES document, storing the result back into ES.
from celery import chain
from xtas.tasks.es import es_document, store_single
from xtas.tasks.single import pos_tag, tokenize
doc = es_document('blog', 'post', 1, 'body')
# The following is Celery syntax for a pipeline of operations.
ch = chain(tokenize.s(doc)
| pos_tag.s('nltk')
| store_single.s('pipeline', 'blog', 'post', 1)
)
r = ch.delay()
print(r.get())
from xtas.celery import app
app.conf['CELERY_ALWAYS_EAGER'] = True
pipe = [{"module" : x} for x in args.modules]
doctype = "__".join([args.parent_doctype] + [m['module'] for m in pipe])
es = Elasticsearch(hosts=[{"host":args.host, "port": 9200}], timeout=600)
check_mapping(es, args.index, doctype, args.parent_doctype)
while True:
if args.single:
n, aids = 1, [args.set]
else:
logging.warn("Retrieving {args.n} articles".format(**locals()))
try:
n, aids = list(get_articles(es, args.index, doctype, args.parent_doctype, args.set, size=args.n))
except:
logging.exception("Error on get_articles, retrying in 10 seconds")
time.sleep(10)
continue
if not aids:
logging.warn("DONE")
break
docs = [es_document(args.index, args.parent_doctype, aid, "text")
for aid in aids]
cache_many(pipe, docs)
if args.norepeat or args.single:
break
