def test_text_search(table):
from bigchaindb.backend import connect, query
conn = connect()
# Example data and tests cases taken from the mongodb documentation
# https://docs.mongodb.com/manual/reference/operator/query/text/
objects = [{
'id': 1,
'subject': 'coffee',
'author': 'xyz',
'views': 50
}, {
'id': 2,
'subject': 'Coffee Shopping',
'author': 'efg',
'views': 5
}, {
'id': 3,
'subject': 'Baking a cake',
'author': 'abc',
'views': 90
}, {
'id': 4,
'subject': 'baking',
'author': 'xyz',
'views': 100
}, {
'id': 5,
'subject': 'Café Con Leche',
'author': 'abc',
'views': 200
}, {
'id': 6,
'subject': 'Сырники',
'author': 'jkl',
'views': 80
}, {
'id': 7,
'subject': 'coffee and cream',
'author': 'efg',
'views': 10
}, {
'id': 8,
'subject': 'Cafe con Leche',
'author': 'xyz',
'views': 10
}]
# insert the assets
conn.db[table].insert_many(deepcopy(objects), ordered=False)
# test search single word
assert list(query.text_search(conn, 'coffee', table=table)) == [
{
'id': 1,
'subject': 'coffee',
'author': 'xyz',
'views': 50
},
{
'id': 2,
'subject': 'Coffee Shopping',
'author': 'efg',
'views': 5
},
{
'id': 7,
'subject': 'coffee and cream',
'author': 'efg',
'views': 10
},
]
# match any of the search terms
assert list(query.text_search(conn, 'bake coffee cake', table=table)) == [{
'author':
'abc',
'id':
3,
'subject':
'Baking a cake',
'views':
90
}, {
'author':
'xyz',
'id':
1,
'subject':
'coffee',
'views':
50
}, {
'author':
'xyz',
'id':
4,
'subject':
'baking',
'views':
100
}, {
'author':
'efg',
'id':
2,
'subject':
'Coffee Shopping',
'views':
5
}, {
'author':
'efg',
'id':
7,
'subject':
'coffee and cream',
'views':
10
}]
# search for a phrase
assert list(query.text_search(conn, '\"coffee shop\"', table=table)) == [
{
'id': 2,
'subject': 'Coffee Shopping',
'author': 'efg',
'views': 5
},
]
# exclude documents that contain a term
assert list(query.text_search(conn, 'coffee -shop', table=table)) == [
{
'id': 1,
'subject': 'coffee',
'author': 'xyz',
'views': 50
},
{
'id': 7,
'subject': 'coffee and cream',
'author': 'efg',
'views': 10
},
]
# search different language
assert list(query.text_search(conn, 'leche', language='es',
table=table)) == [{
'id': 5,
'subject': 'Café Con Leche',
'author': 'abc',
'views': 200
}, {
'id': 8,
'subject': 'Cafe con Leche',
'author': 'xyz',
'views': 10
}]
# case and diacritic insensitive search
assert list(query.text_search(conn, 'сы́рники CAFÉS', table=table)) == [{
'id':
6,
'subject':
'Сырники',
'author':
'jkl',
'views':
80
}, {
'id':
5,
'subject':
'Café Con Leche',
'author':
'abc',
'views':
200
}, {
'id':
8,
'subject':
'Cafe con Leche',
'author':
'xyz',
'views':
10
}]
# case sensitive search
assert list(
query.text_search(conn, 'Coffee', case_sensitive=True,
table=table)) == [
{
'id': 2,
'subject': 'Coffee Shopping',
'author': 'efg',
'views': 5
},
]
# diacritic sensitive search
assert list(
query.text_search(conn, 'CAFÉ', diacritic_sensitive=True,
table=table)) == [
{
'id': 5,
'subject': 'Café Con Leche',
'author': 'abc',
'views': 200
},
]
# return text score
assert list(query.text_search(conn, 'coffee', text_score=True,
table=table)) == [
{
'id': 1,
'subject': 'coffee',
'author': 'xyz',
'views': 50,
'score': 1.0
},
{
'id': 2,
'subject': 'Coffee Shopping',
'author': 'efg',
'views': 5,
'score': 0.75
},
{
'id': 7,
'subject': 'coffee and cream',
'author': 'efg',
'views': 10,
'score': 0.75
},
]
# limit search result
assert list(query.text_search(conn, 'coffee', limit=2, table=table)) == [
{
'id': 1,
'subject': 'coffee',
'author': 'xyz',
'views': 50
},
{
'id': 2,
'subject': 'Coffee Shopping',
'author': 'efg',
'views': 5
},
]
def test_text_search(table):
from bigchaindb.backend import connect, query
conn = connect()
# Example data and tests cases taken from the mongodb documentation
# https://docs.mongodb.com/manual/reference/operator/query/text/
objects = [
{'id': 1, 'subject': 'coffee', 'author': 'xyz', 'views': 50},
{'id': 2, 'subject': 'Coffee Shopping', 'author': 'efg', 'views': 5},
{'id': 3, 'subject': 'Baking a cake', 'author': 'abc', 'views': 90},
{'id': 4, 'subject': 'baking', 'author': 'xyz', 'views': 100},
{'id': 5, 'subject': 'Café Con Leche', 'author': 'abc', 'views': 200},
{'id': 6, 'subject': 'Сырники', 'author': 'jkl', 'views': 80},
{'id': 7, 'subject': 'coffee and cream', 'author': 'efg', 'views': 10},
{'id': 8, 'subject': 'Cafe con Leche', 'author': 'xyz', 'views': 10}
]
# insert the assets
conn.db[table].insert_many(deepcopy(objects), ordered=False)
# test search single word
assert list(query.text_search(conn, 'coffee', table=table)) == [
{'id': 1, 'subject': 'coffee', 'author': 'xyz', 'views': 50},
{'id': 2, 'subject': 'Coffee Shopping', 'author': 'efg', 'views': 5},
{'id': 7, 'subject': 'coffee and cream', 'author': 'efg', 'views': 10},
]
# match any of the search terms
assert list(query.text_search(conn, 'bake coffee cake', table=table)) == [
{'author': 'abc', 'id': 3, 'subject': 'Baking a cake', 'views': 90},
{'author': 'xyz', 'id': 1, 'subject': 'coffee', 'views': 50},
{'author': 'xyz', 'id': 4, 'subject': 'baking', 'views': 100},
{'author': 'efg', 'id': 2, 'subject': 'Coffee Shopping', 'views': 5},
{'author': 'efg', 'id': 7, 'subject': 'coffee and cream', 'views': 10}
]
# search for a phrase
assert list(query.text_search(conn, '\"coffee shop\"', table=table)) == [
{'id': 2, 'subject': 'Coffee Shopping', 'author': 'efg', 'views': 5},
]
# exclude documents that contain a term
assert list(query.text_search(conn, 'coffee -shop', table=table)) == [
{'id': 1, 'subject': 'coffee', 'author': 'xyz', 'views': 50},
{'id': 7, 'subject': 'coffee and cream', 'author': 'efg', 'views': 10},
]
# search different language
assert list(query.text_search(conn, 'leche', language='es', table=table)) == [
{'id': 5, 'subject': 'Café Con Leche', 'author': 'abc', 'views': 200},
{'id': 8, 'subject': 'Cafe con Leche', 'author': 'xyz', 'views': 10}
]
# case and diacritic insensitive search
assert list(query.text_search(conn, 'сы́рники CAFÉS', table=table)) == [
{'id': 6, 'subject': 'Сырники', 'author': 'jkl', 'views': 80},
{'id': 5, 'subject': 'Café Con Leche', 'author': 'abc', 'views': 200},
{'id': 8, 'subject': 'Cafe con Leche', 'author': 'xyz', 'views': 10}
]
# case sensitive search
assert list(query.text_search(conn, 'Coffee', case_sensitive=True, table=table)) == [
{'id': 2, 'subject': 'Coffee Shopping', 'author': 'efg', 'views': 5},
]
# diacritic sensitive search
assert list(query.text_search(conn, 'CAFÉ', diacritic_sensitive=True, table=table)) == [
{'id': 5, 'subject': 'Café Con Leche', 'author': 'abc', 'views': 200},
]
# return text score
assert list(query.text_search(conn, 'coffee', text_score=True, table=table)) == [
{'id': 1, 'subject': 'coffee', 'author': 'xyz', 'views': 50, 'score': 1.0},
{'id': 2, 'subject': 'Coffee Shopping', 'author': 'efg', 'views': 5, 'score': 0.75},
{'id': 7, 'subject': 'coffee and cream', 'author': 'efg', 'views': 10, 'score': 0.75},
]
# limit search result
assert list(query.text_search(conn, 'coffee', limit=2, table=table)) == [
{'id': 1, 'subject': 'coffee', 'author': 'xyz', 'views': 50},
{'id': 2, 'subject': 'Coffee Shopping', 'author': 'efg', 'views': 5},
]
