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Diffstat (limited to 'stanza/tests/test_server_request.py')
| -rw-r--r-- | stanza/tests/test_server_request.py | 223 |
1 files changed, 223 insertions, 0 deletions
diff --git a/stanza/tests/test_server_request.py b/stanza/tests/test_server_request.py new file mode 100644 index 00000000..6edf670a --- /dev/null +++ b/stanza/tests/test_server_request.py @@ -0,0 +1,223 @@ +""" +Tests for setting request properties of servers +""" + +import json +import pytest +import stanza.server as corenlp + +from stanza.protobuf import Document +from stanza.tests import TEST_WORKING_DIR, compare_ignoring_whitespace + +pytestmark = pytest.mark.client + +EN_DOC = "Joe Smith lives in California." + +# results with an example properties file +EN_DOC_GOLD = """ +Sentence #1 (6 tokens): +Joe Smith lives in California. + +Tokens: +[Text=Joe CharacterOffsetBegin=0 CharacterOffsetEnd=3 PartOfSpeech=NNP] +[Text=Smith CharacterOffsetBegin=4 CharacterOffsetEnd=9 PartOfSpeech=NNP] +[Text=lives CharacterOffsetBegin=10 CharacterOffsetEnd=15 PartOfSpeech=VBZ] +[Text=in CharacterOffsetBegin=16 CharacterOffsetEnd=18 PartOfSpeech=IN] +[Text=California CharacterOffsetBegin=19 CharacterOffsetEnd=29 PartOfSpeech=NNP] +[Text=. CharacterOffsetBegin=29 CharacterOffsetEnd=30 PartOfSpeech=.] +""" + +GERMAN_DOC = "Angela Merkel ist seit 2005 Bundeskanzlerin der Bundesrepublik Deutschland." + +GERMAN_DOC_GOLD = """ +Sentence #1 (10 tokens): +Angela Merkel ist seit 2005 Bundeskanzlerin der Bundesrepublik Deutschland. + +Tokens: +[Text=Angela CharacterOffsetBegin=0 CharacterOffsetEnd=6 PartOfSpeech=PROPN] +[Text=Merkel CharacterOffsetBegin=7 CharacterOffsetEnd=13 PartOfSpeech=PROPN] +[Text=ist CharacterOffsetBegin=14 CharacterOffsetEnd=17 PartOfSpeech=AUX] +[Text=seit CharacterOffsetBegin=18 CharacterOffsetEnd=22 PartOfSpeech=ADP] +[Text=2005 CharacterOffsetBegin=23 CharacterOffsetEnd=27 PartOfSpeech=NUM] +[Text=Bundeskanzlerin CharacterOffsetBegin=28 CharacterOffsetEnd=43 PartOfSpeech=NOUN] +[Text=der CharacterOffsetBegin=44 CharacterOffsetEnd=47 PartOfSpeech=DET] +[Text=Bundesrepublik CharacterOffsetBegin=48 CharacterOffsetEnd=62 PartOfSpeech=PROPN] +[Text=Deutschland CharacterOffsetBegin=63 CharacterOffsetEnd=74 PartOfSpeech=PROPN] +[Text=. CharacterOffsetBegin=74 CharacterOffsetEnd=75 PartOfSpeech=PUNCT] +""" + +FRENCH_CUSTOM_PROPS = {'annotators': 'tokenize,ssplit,mwt,pos,parse', + 'tokenize.language': 'fr', + 'pos.model': 'edu/stanford/nlp/models/pos-tagger/french-ud.tagger', + 'parse.model': 'edu/stanford/nlp/models/srparser/frenchSR.ser.gz', + 'mwt.mappingFile': 'edu/stanford/nlp/models/mwt/french/french-mwt.tsv', + 'mwt.pos.model': 'edu/stanford/nlp/models/mwt/french/french-mwt.tagger', + 'mwt.statisticalMappingFile': 'edu/stanford/nlp/models/mwt/french/french-mwt-statistical.tsv', + 'mwt.preserveCasing': 'false', + 'outputFormat': 'text'} + +FRENCH_EXTRA_PROPS = {'annotators': 'tokenize,ssplit,mwt,pos,depparse', + 'tokenize.language': 'fr', + 'pos.model': 'edu/stanford/nlp/models/pos-tagger/french-ud.tagger', + 'mwt.mappingFile': 'edu/stanford/nlp/models/mwt/french/french-mwt.tsv', + 'mwt.pos.model': 'edu/stanford/nlp/models/mwt/french/french-mwt.tagger', + 'mwt.statisticalMappingFile': 'edu/stanford/nlp/models/mwt/french/french-mwt-statistical.tsv', + 'mwt.preserveCasing': 'false', + 'depparse.model': 'edu/stanford/nlp/models/parser/nndep/UD_French.gz'} + +FRENCH_DOC = "Cette enquête préliminaire fait suite aux révélations de l’hebdomadaire quelques jours plus tôt." + +FRENCH_CUSTOM_GOLD = """ +Sentence #1 (16 tokens): +Cette enquête préliminaire fait suite aux révélations de l’hebdomadaire quelques jours plus tôt. + +Tokens: +[Text=Cette CharacterOffsetBegin=0 CharacterOffsetEnd=5 PartOfSpeech=DET] +[Text=enquête CharacterOffsetBegin=6 CharacterOffsetEnd=13 PartOfSpeech=NOUN] +[Text=préliminaire CharacterOffsetBegin=14 CharacterOffsetEnd=26 PartOfSpeech=ADJ] +[Text=fait CharacterOffsetBegin=27 CharacterOffsetEnd=31 PartOfSpeech=VERB] +[Text=suite CharacterOffsetBegin=32 CharacterOffsetEnd=37 PartOfSpeech=NOUN] +[Text=à CharacterOffsetBegin=38 CharacterOffsetEnd=41 PartOfSpeech=ADP] +[Text=les CharacterOffsetBegin=38 CharacterOffsetEnd=41 PartOfSpeech=DET] +[Text=révélations CharacterOffsetBegin=42 CharacterOffsetEnd=53 PartOfSpeech=NOUN] +[Text=de CharacterOffsetBegin=54 CharacterOffsetEnd=56 PartOfSpeech=ADP] +[Text=l’ CharacterOffsetBegin=57 CharacterOffsetEnd=59 PartOfSpeech=NOUN] +[Text=hebdomadaire CharacterOffsetBegin=59 CharacterOffsetEnd=71 PartOfSpeech=ADJ] +[Text=quelques CharacterOffsetBegin=72 CharacterOffsetEnd=80 PartOfSpeech=DET] +[Text=jours CharacterOffsetBegin=81 CharacterOffsetEnd=86 PartOfSpeech=NOUN] +[Text=plus CharacterOffsetBegin=87 CharacterOffsetEnd=91 PartOfSpeech=ADV] +[Text=tôt CharacterOffsetBegin=92 CharacterOffsetEnd=95 PartOfSpeech=ADV] +[Text=. CharacterOffsetBegin=95 CharacterOffsetEnd=96 PartOfSpeech=PUNCT] + +Constituency parse: +(ROOT + (SENT + (NP (DET Cette) + (MWN (NOUN enquête) (ADJ préliminaire))) + (VN + (MWV (VERB fait) (NOUN suite))) + (PP (ADP à) + (NP (DET les) (NOUN révélations) + (PP (ADP de) + (NP (NOUN l’) + (AP (ADJ hebdomadaire)))))) + (NP (DET quelques) (NOUN jours)) + (AdP (ADV plus) (ADV tôt)) + (PUNCT .))) +""" + +FRENCH_EXTRA_GOLD = """ +Sentence #1 (16 tokens): +Cette enquête préliminaire fait suite aux révélations de l’hebdomadaire quelques jours plus tôt. + +Tokens: +[Text=Cette CharacterOffsetBegin=0 CharacterOffsetEnd=5 PartOfSpeech=DET] +[Text=enquête CharacterOffsetBegin=6 CharacterOffsetEnd=13 PartOfSpeech=NOUN] +[Text=préliminaire CharacterOffsetBegin=14 CharacterOffsetEnd=26 PartOfSpeech=ADJ] +[Text=fait CharacterOffsetBegin=27 CharacterOffsetEnd=31 PartOfSpeech=VERB] +[Text=suite CharacterOffsetBegin=32 CharacterOffsetEnd=37 PartOfSpeech=NOUN] +[Text=à CharacterOffsetBegin=38 CharacterOffsetEnd=41 PartOfSpeech=ADP] +[Text=les CharacterOffsetBegin=38 CharacterOffsetEnd=41 PartOfSpeech=DET] +[Text=révélations CharacterOffsetBegin=42 CharacterOffsetEnd=53 PartOfSpeech=NOUN] +[Text=de CharacterOffsetBegin=54 CharacterOffsetEnd=56 PartOfSpeech=ADP] +[Text=l’ CharacterOffsetBegin=57 CharacterOffsetEnd=59 PartOfSpeech=NOUN] +[Text=hebdomadaire CharacterOffsetBegin=59 CharacterOffsetEnd=71 PartOfSpeech=ADJ] +[Text=quelques CharacterOffsetBegin=72 CharacterOffsetEnd=80 PartOfSpeech=DET] +[Text=jours CharacterOffsetBegin=81 CharacterOffsetEnd=86 PartOfSpeech=NOUN] +[Text=plus CharacterOffsetBegin=87 CharacterOffsetEnd=91 PartOfSpeech=ADV] +[Text=tôt CharacterOffsetBegin=92 CharacterOffsetEnd=95 PartOfSpeech=ADV] +[Text=. CharacterOffsetBegin=95 CharacterOffsetEnd=96 PartOfSpeech=PUNCT] + +Dependency Parse (enhanced plus plus dependencies): +root(ROOT-0, fait-4) +det(enquête-2, Cette-1) +nsubj(fait-4, enquête-2) +amod(enquête-2, préliminaire-3) +obj(fait-4, suite-5) +case(révélations-8, à-6) +det(révélations-8, les-7) +obl:à(fait-4, révélations-8) +case(l’-10, de-9) +nmod:de(révélations-8, l’-10) +amod(révélations-8, hebdomadaire-11) +det(jours-13, quelques-12) +obl(fait-4, jours-13) +advmod(tôt-15, plus-14) +advmod(jours-13, tôt-15) +punct(fait-4, .-16) +""" + +FRENCH_JSON_GOLD = json.loads(open(f'{TEST_WORKING_DIR}/out/example_french.json').read()) + +ES_DOC = 'Andrés Manuel López Obrador es el presidente de México.' + +ES_PROPS = {'annotators': 'tokenize,ssplit,mwt,pos,depparse', 'tokenize.language': 'es', + 'pos.model': 'edu/stanford/nlp/models/pos-tagger/spanish-ud.tagger', + 'mwt.mappingFile': 'edu/stanford/nlp/models/mwt/spanish/spanish-mwt.tsv', + 'depparse.model': 'edu/stanford/nlp/models/parser/nndep/UD_Spanish.gz'} + +ES_PROPS_GOLD = """ +Sentence #1 (10 tokens): +Andrés Manuel López Obrador es el presidente de México. + +Tokens: +[Text=Andrés CharacterOffsetBegin=0 CharacterOffsetEnd=6 PartOfSpeech=PROPN] +[Text=Manuel CharacterOffsetBegin=7 CharacterOffsetEnd=13 PartOfSpeech=PROPN] +[Text=López CharacterOffsetBegin=14 CharacterOffsetEnd=19 PartOfSpeech=PROPN] +[Text=Obrador CharacterOffsetBegin=20 CharacterOffsetEnd=27 PartOfSpeech=PROPN] +[Text=es CharacterOffsetBegin=28 CharacterOffsetEnd=30 PartOfSpeech=AUX] +[Text=el CharacterOffsetBegin=31 CharacterOffsetEnd=33 PartOfSpeech=DET] +[Text=presidente CharacterOffsetBegin=34 CharacterOffsetEnd=44 PartOfSpeech=NOUN] +[Text=de CharacterOffsetBegin=45 CharacterOffsetEnd=47 PartOfSpeech=ADP] +[Text=México CharacterOffsetBegin=48 CharacterOffsetEnd=54 PartOfSpeech=PROPN] +[Text=. CharacterOffsetBegin=54 CharacterOffsetEnd=55 PartOfSpeech=PUNCT] + +Dependency Parse (enhanced plus plus dependencies): +root(ROOT-0, presidente-7) +nsubj(presidente-7, Andrés-1) +flat(Andrés-1, Manuel-2) +flat(Andrés-1, López-3) +flat(Andrés-1, Obrador-4) +cop(presidente-7, es-5) +det(presidente-7, el-6) +case(México-9, de-8) +nmod:de(presidente-7, México-9) +punct(presidente-7, .-10) +""" + + +@pytest.fixture(scope="module") +def corenlp_client(): + """ Client to run tests on """ + client = corenlp.CoreNLPClient(annotators='tokenize,ssplit,pos', server_id='stanza_request_tests_server') + yield client + client.stop() + + +def test_basic(corenlp_client): + """ Basic test of making a request, test default output format is a Document """ + ann = corenlp_client.annotate(EN_DOC, output_format="text") + assert ann.strip() == EN_DOC_GOLD.strip() + ann = corenlp_client.annotate(EN_DOC) + assert isinstance(ann, Document) + + +def test_python_dict(corenlp_client): + """ Test using a Python dictionary to specify all request properties """ + ann = corenlp_client.annotate(ES_DOC, properties=ES_PROPS, output_format="text") + assert ann.strip() == ES_PROPS_GOLD.strip() + ann = corenlp_client.annotate(FRENCH_DOC, properties=FRENCH_CUSTOM_PROPS) + assert ann.strip() == FRENCH_CUSTOM_GOLD.strip() + + +def test_lang_setting(corenlp_client): + """ Test using a Stanford CoreNLP supported languages as a properties key """ + ann = corenlp_client.annotate(GERMAN_DOC, properties="german", output_format="text") + compare_ignoring_whitespace(ann, GERMAN_DOC_GOLD) + + +def test_annotators_and_output_format(corenlp_client): + """ Test setting the annotators and output_format """ + ann = corenlp_client.annotate(FRENCH_DOC, properties=FRENCH_EXTRA_PROPS, + annotators="tokenize,ssplit,mwt,pos", output_format="json") + assert FRENCH_JSON_GOLD == ann |