spaCy/spacy/tests/lang/de/test_parser.py
Ines Montani 75f3234404
💫 Refactor test suite (#2568)
## Description

Related issues: #2379 (should be fixed by separating model tests)

* **total execution time down from > 300 seconds to under 60 seconds** 🎉
* removed all model-specific tests that could only really be run manually anyway – those will now live in a separate test suite in the [`spacy-models`](https://github.com/explosion/spacy-models) repository and are already integrated into our new model training infrastructure
* changed all relative imports to absolute imports to prepare for moving the test suite from `/spacy/tests` to `/tests` (it'll now always test against the installed version)
* merged old regression tests into collections, e.g. `test_issue1001-1500.py` (about 90% of the regression tests are very short anyways)
* tidied up and rewrote existing tests wherever possible

### Todo

- [ ] move tests to `/tests` and adjust CI commands accordingly
- [x] move model test suite from internal repo to `spacy-models`
- [x] ~~investigate why `pipeline/test_textcat.py` is flakey~~
- [x] review old regression tests (leftover files) and see if they can be merged, simplified or deleted
- [ ] update documentation on how to run tests


### Types of change
enhancement, tests

## Checklist
<!--- Before you submit the PR, go over this checklist and make sure you can
tick off all the boxes. [] -> [x] -->
- [x] I have submitted the spaCy Contributor Agreement.
- [x] I ran the tests, and all new and existing tests passed.
- [ ] My changes don't require a change to the documentation, or if they do, I've added all required information.
2018-07-24 23:38:44 +02:00

32 lines
1.3 KiB
Python

# coding: utf-8
from __future__ import unicode_literals
from ...util import get_doc
def test_de_parser_noun_chunks_standard_de(de_tokenizer):
text = "Eine Tasse steht auf dem Tisch."
heads = [1, 1, 0, -1, 1, -2, -4]
tags = ['ART', 'NN', 'VVFIN', 'APPR', 'ART', 'NN', '$.']
deps = ['nk', 'sb', 'ROOT', 'mo', 'nk', 'nk', 'punct']
tokens = de_tokenizer(text)
doc = get_doc(tokens.vocab, words=[t.text for t in tokens], tags=tags, deps=deps, heads=heads)
chunks = list(doc.noun_chunks)
assert len(chunks) == 2
assert chunks[0].text_with_ws == "Eine Tasse "
assert chunks[1].text_with_ws == "dem Tisch "
def test_de_extended_chunk(de_tokenizer):
text = "Die Sängerin singt mit einer Tasse Kaffee Arien."
heads = [1, 1, 0, -1, 1, -2, -1, -5, -6]
tags = ['ART', 'NN', 'VVFIN', 'APPR', 'ART', 'NN', 'NN', 'NN', '$.']
deps = ['nk', 'sb', 'ROOT', 'mo', 'nk', 'nk', 'nk', 'oa', 'punct']
tokens = de_tokenizer(text)
doc = get_doc(tokens.vocab, words=[t.text for t in tokens], tags=tags, deps=deps, heads=heads)
chunks = list(doc.noun_chunks)
assert len(chunks) == 3
assert chunks[0].text_with_ws == "Die Sängerin "
assert chunks[1].text_with_ws == "einer Tasse Kaffee "
assert chunks[2].text_with_ws == "Arien "