class TestBuilderBuild:
def setup_method(self, method):
self.builder = Builder()
doc = {"id": "id", "title": "test", "body": "missing"}
self.builder.ref("id")
self.builder.field("title")
self.builder.add(doc)
self.index = self.builder.build()
def test_adds_tokens_to_inverted_index(self):
_assert_deep_keys(self.builder.inverted_index, "test.title.id")
def test_builds_vector_space_of_the_document_fields(self):
assert "title/id" in self.builder.field_vectors
assert isinstance(self.builder.field_vectors["title/id"], Vector)
def test_skips_fields_not_defined_for_indexing(self):
assert "missing" not in self.builder.inverted_index
def test_builds_a_token_set_for_the_corpus(self):
needle = TokenSet.from_string("test")
assert "test" in self.builder.token_set.intersect(needle).to_list()
def test_calculates_document_count(self):
assert self.builder.average_field_length["title"] == 1
def test_index_is_returned(self):
assert isinstance(self.index, Index)
def test_define_fields_to_index(self):
builder = Builder()
builder.field("foo")
assert len(builder._fields) == 1
assert builder._fields["foo"].name == "foo"
assert builder._fields["foo"].boost == 1
assert builder._fields["foo"].extractor is None
assert repr(builder._fields["foo"]) == '<Field "foo" boost="1">'
assert hash(builder._fields["foo"]) == hash("foo")
class TestBuilderAdd:
def test_builder_casts_docrefs_to_strings(self):
self.builder = Builder()
self.builder.ref("id")
self.builder.field("title")
self.builder.add(dict(id=123, title="test", body="missing"))
_assert_deep_keys(self.builder.inverted_index, "test.title.123")
def test_builder_metadata_whitelist_includes_metadata_in_index(self):
self.builder = Builder()
self.builder.ref("id")
self.builder.field("title")
self.builder.metadata_whitelist = ["position"]
self.builder.add(dict(id="a", title="test", body="missing"))
self.builder.add(dict(id="b", title="another test", body="missing"))
assert self.builder.inverted_index["test"]["title"]["a"] == {
"position": [[0, 4]]
}
assert self.builder.inverted_index["test"]["title"]["b"] == {
"position": [[8, 4]]
}
def test_builder_field_raises_if_contains_slash(self):
self.builder = Builder()
with pytest.raises(ValueError):
self.builder.field("foo/bar")
def test_builder_extracts_nested_properties_from_document(self):
self.builder = Builder()
self.builder.field("name", extractor=lambda d: d["person"]["name"])
self.builder.add({"id": "id", "person": {"name": "bob"}})
assert self.builder.inverted_index["bob"]["name"]["id"] == {}
def test_builder_field_term_frequency_and_length(self):
self.builder = Builder()
self.builder.ref("id")
self.builder.field("title")
self.builder.add(
dict(id="a", title="test a testing test", body="missing"))
assert self.builder.field_term_frequencies == {
"title/a": {
"test": 2,
"a": 1,
"testing": 1
}
}
assert self.builder.field_lengths == {"title/a": 4}
def lunr_builder(ref, fields):
"""A convenience function to configure and construct a lunr.Builder.
Returns:
Index: The populated Index ready to search against.
"""
builder = Builder()
builder.pipeline.add(trimmer, stop_word_filter, stemmer)
builder.search_pipeline.add(stemmer)
builder.ref(ref)
for field in fields:
builder.field(field)
return builder
def lunr(ref, fields, documents, languages=None):
"""A convenience function to configure and construct a lunr.Index.
Args:
ref (str): The key in the documents to be used a the reference.
fields (list): A list of strings defining fields in the documents to
index. Optionally a list of dictionaries with three keys:
`field_name` defining the document's field, `boost` an integer
defining a boost to be applied to the field, and `extractor`
a callable taking the document as a single argument and returning
a string located in the document in a particular way.
documents (list): The list of dictonaries representing the documents
to index. Optionally a 2-tuple of dicts, the first one being
the document and the second the associated attributes to it.
languages (str or list, optional): The languages to use if using
NLTK language support, ignored if NLTK is not available.
Returns:
Index: The populated Index ready to search against.
"""
if languages is not None and lang.LANGUAGE_SUPPORT:
if isinstance(languages, basestring):
languages = [languages]
unsupported_languages = set(languages) - set(lang.SUPPORTED_LANGUAGES)
if unsupported_languages:
raise RuntimeError("The specified languages {} are not supported, "
"please choose one of {}".format(
", ".join(unsupported_languages),
", ".join(lang.SUPPORTED_LANGUAGES.keys()),
))
builder = lang.get_nltk_builder(languages)
else:
builder = Builder()
builder.pipeline.add(trimmer, stop_word_filter) #, stemmer)
#builder.search_pipeline.add(stemmer)
builder.ref(ref)
for field in fields:
if isinstance(field, dict):
builder.field(**field)
else:
builder.field(field)
for document in documents:
if isinstance(document, (tuple, list)):
builder.add(document[0], attributes=document[1])
else:
builder.add(document)
return builder.build()
def generate_output(self, writer):
pages = [self.create_node(x) for x in self.context['articles']]
path = os.path.join(self.output_path, 'search_index.json')
pages_to_index = [{
'id': x['id'],
'title': x['title'],
'text': x['text']
} for x in pages]
additional_data = {
x['id']: {
'url': x['url'],
'title': x['title'],
'summary': x['summary'],
}
for x in pages
}
Pipeline.register_function(special_chars_remover,
'specialCharsRemover')
bldr = Builder()
bldr.pipeline.add(trimmer, stop_word_filter, stemmer,
special_chars_remover)
bldr.search_pipeline.add(stemmer)
bldr.ref('id')
bldr.field('title', 10)
bldr.field('text')
for page in pages_to_index:
bldr.add(page)
idx = bldr.build().serialize()
with open(path, 'w') as idxfile:
json.dump({
'index': idx,
'data': additional_data,
}, idxfile)