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Suggest column facet only if at least one count > 1 

Fixes #638
plugin-load-metadata
Simon Willison 2019-11-21 16:56:55 -08:00
rodzic c16be14517
commit fd137da7f8
4 zmienionych plików z 65 dodań i 35 usunięć
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5
datasette/facets.py
Wyświetl plik

@ -143,9 +143,10 @@ class ColumnFacet(Facet):
if column in already_enabled:
continue
suggested_facet_sql = """
select distinct {column} from (
select {column}, count(*) as n from (
{sql}
) where {column} is not null
group by {column}
limit {limit}
""".format(
column=escape_sqlite(column), sql=self.sql, limit=facet_size + 1
@ -165,6 +166,8 @@ class ColumnFacet(Facet):
and num_distinct_values > 1
and num_distinct_values <= facet_size
and num_distinct_values < row_count
# And at least one has n > 1
and any(r["n"] > 1 for r in distinct_values)
):
suggested_facets.append(
{

33
tests/fixtures.py
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@ -669,26 +669,27 @@ CREATE TABLE facetable (
neighborhood text,
tags text,
complex_array text,
distinct_some_null,
FOREIGN KEY ("city_id") REFERENCES [facet_cities](id)
);
INSERT INTO facetable
(created, planet_int, on_earth, state, city_id, neighborhood, tags, complex_array)
(created, planet_int, on_earth, state, city_id, neighborhood, tags, complex_array, distinct_some_null)
VALUES
("2019-01-14 08:00:00", 1, 1, 'CA', 1, 'Mission', '["tag1", "tag2"]', '[{"foo": "bar"}]'),
("2019-01-14 08:00:00", 1, 1, 'CA', 1, 'Dogpatch', '["tag1", "tag3"]', '[]'),
("2019-01-14 08:00:00", 1, 1, 'CA', 1, 'SOMA', '[]', '[]'),
("2019-01-14 08:00:00", 1, 1, 'CA', 1, 'Tenderloin', '[]', '[]'),
("2019-01-15 08:00:00", 1, 1, 'CA', 1, 'Bernal Heights', '[]', '[]'),
("2019-01-15 08:00:00", 1, 1, 'CA', 1, 'Hayes Valley', '[]', '[]'),
("2019-01-15 08:00:00", 1, 1, 'CA', 2, 'Hollywood', '[]', '[]'),
("2019-01-15 08:00:00", 1, 1, 'CA', 2, 'Downtown', '[]', '[]'),
("2019-01-16 08:00:00", 1, 1, 'CA', 2, 'Los Feliz', '[]', '[]'),
("2019-01-16 08:00:00", 1, 1, 'CA', 2, 'Koreatown', '[]', '[]'),
("2019-01-16 08:00:00", 1, 1, 'MI', 3, 'Downtown', '[]', '[]'),
("2019-01-17 08:00:00", 1, 1, 'MI', 3, 'Greektown', '[]', '[]'),
("2019-01-17 08:00:00", 1, 1, 'MI', 3, 'Corktown', '[]', '[]'),
("2019-01-17 08:00:00", 1, 1, 'MI', 3, 'Mexicantown', '[]', '[]'),
("2019-01-17 08:00:00", 2, 0, 'MC', 4, 'Arcadia Planitia', '[]', '[]')
("2019-01-14 08:00:00", 1, 1, 'CA', 1, 'Mission', '["tag1", "tag2"]', '[{"foo": "bar"}]', 'one'),
("2019-01-14 08:00:00", 1, 1, 'CA', 1, 'Dogpatch', '["tag1", "tag3"]', '[]', 'two'),
("2019-01-14 08:00:00", 1, 1, 'CA', 1, 'SOMA', '[]', '[]', null),
("2019-01-14 08:00:00", 1, 1, 'CA', 1, 'Tenderloin', '[]', '[]', null),
("2019-01-15 08:00:00", 1, 1, 'CA', 1, 'Bernal Heights', '[]', '[]', null),
("2019-01-15 08:00:00", 1, 1, 'CA', 1, 'Hayes Valley', '[]', '[]', null),
("2019-01-15 08:00:00", 1, 1, 'CA', 2, 'Hollywood', '[]', '[]', null),
("2019-01-15 08:00:00", 1, 1, 'CA', 2, 'Downtown', '[]', '[]', null),
("2019-01-16 08:00:00", 1, 1, 'CA', 2, 'Los Feliz', '[]', '[]', null),
("2019-01-16 08:00:00", 1, 1, 'CA', 2, 'Koreatown', '[]', '[]', null),
("2019-01-16 08:00:00", 1, 1, 'MI', 3, 'Downtown', '[]', '[]', null),
("2019-01-17 08:00:00", 1, 1, 'MI', 3, 'Greektown', '[]', '[]', null),
("2019-01-17 08:00:00", 1, 1, 'MI', 3, 'Corktown', '[]', '[]', null),
("2019-01-17 08:00:00", 1, 1, 'MI', 3, 'Mexicantown', '[]', '[]', null),
("2019-01-17 08:00:00", 2, 0, 'MC', 4, 'Arcadia Planitia', '[]', '[]', null)
;
CREATE TABLE binary_data (

30
tests/test_api.py
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@ -197,6 +197,7 @@ def test_database_page(app_client):
"neighborhood",
"tags",
"complex_array",
"distinct_some_null",
],
"primary_keys": ["pk"],
"count": 15,
@ -1042,15 +1043,38 @@ def test_table_filter_json_arraycontains(app_client):
"Mission",
'["tag1", "tag2"]',
'[{"foo": "bar"}]',
"one",
],
[
2,
"2019-01-14 08:00:00",
1,
1,
"CA",
1,
"Dogpatch",
'["tag1", "tag3"]',
"[]",
"two",
],
[2, "2019-01-14 08:00:00", 1, 1, "CA", 1, "Dogpatch", '["tag1", "tag3"]', "[]"],
] == response.json["rows"]
def test_table_filter_extra_where(app_client):
response = app_client.get("/fixtures/facetable.json?_where=neighborhood='Dogpatch'")
assert [
[2, "2019-01-14 08:00:00", 1, 1, "CA", 1, "Dogpatch", '["tag1", "tag3"]', "[]"]
[
2,
"2019-01-14 08:00:00",
1,
1,
"CA",
1,
"Dogpatch",
'["tag1", "tag3"]',
"[]",
"two",
]
] == response.json["rows"]
@ -1503,6 +1527,7 @@ def test_expand_labels(app_client):
"neighborhood": "Dogpatch",
"tags": '["tag1", "tag3"]',
"complex_array": "[]",
"distinct_some_null": "two",
},
"13": {
"pk": 13,
@ -1514,6 +1539,7 @@ def test_expand_labels(app_client):
"neighborhood": "Corktown",
"tags": "[]",
"complex_array": "[]",
"distinct_some_null": None,
},
} == response.json

32
tests/test_csv.py
Wyświetl plik

@ -21,22 +21,22 @@ world
)
EXPECTED_TABLE_WITH_LABELS_CSV = """
pk,created,planet_int,on_earth,state,city_id,city_id_label,neighborhood,tags,complex_array
1,2019-01-14 08:00:00,1,1,CA,1,San Francisco,Mission,"[""tag1"", ""tag2""]","[{""foo"": ""bar""}]"
2,2019-01-14 08:00:00,1,1,CA,1,San Francisco,Dogpatch,"[""tag1"", ""tag3""]",[]
3,2019-01-14 08:00:00,1,1,CA,1,San Francisco,SOMA,[],[]
4,2019-01-14 08:00:00,1,1,CA,1,San Francisco,Tenderloin,[],[]
5,2019-01-15 08:00:00,1,1,CA,1,San Francisco,Bernal Heights,[],[]
6,2019-01-15 08:00:00,1,1,CA,1,San Francisco,Hayes Valley,[],[]
7,2019-01-15 08:00:00,1,1,CA,2,Los Angeles,Hollywood,[],[]
8,2019-01-15 08:00:00,1,1,CA,2,Los Angeles,Downtown,[],[]
9,2019-01-16 08:00:00,1,1,CA,2,Los Angeles,Los Feliz,[],[]
10,2019-01-16 08:00:00,1,1,CA,2,Los Angeles,Koreatown,[],[]
11,2019-01-16 08:00:00,1,1,MI,3,Detroit,Downtown,[],[]
12,2019-01-17 08:00:00,1,1,MI,3,Detroit,Greektown,[],[]
13,2019-01-17 08:00:00,1,1,MI,3,Detroit,Corktown,[],[]
14,2019-01-17 08:00:00,1,1,MI,3,Detroit,Mexicantown,[],[]
15,2019-01-17 08:00:00,2,0,MC,4,Memnonia,Arcadia Planitia,[],[]
pk,created,planet_int,on_earth,state,city_id,city_id_label,neighborhood,tags,complex_array,distinct_some_null
1,2019-01-14 08:00:00,1,1,CA,1,San Francisco,Mission,"[""tag1"", ""tag2""]","[{""foo"": ""bar""}]",one
2,2019-01-14 08:00:00,1,1,CA,1,San Francisco,Dogpatch,"[""tag1"", ""tag3""]",[],two
3,2019-01-14 08:00:00,1,1,CA,1,San Francisco,SOMA,[],[],
4,2019-01-14 08:00:00,1,1,CA,1,San Francisco,Tenderloin,[],[],
5,2019-01-15 08:00:00,1,1,CA,1,San Francisco,Bernal Heights,[],[],
6,2019-01-15 08:00:00,1,1,CA,1,San Francisco,Hayes Valley,[],[],
7,2019-01-15 08:00:00,1,1,CA,2,Los Angeles,Hollywood,[],[],
8,2019-01-15 08:00:00,1,1,CA,2,Los Angeles,Downtown,[],[],
9,2019-01-16 08:00:00,1,1,CA,2,Los Angeles,Los Feliz,[],[],
10,2019-01-16 08:00:00,1,1,CA,2,Los Angeles,Koreatown,[],[],
11,2019-01-16 08:00:00,1,1,MI,3,Detroit,Downtown,[],[],
12,2019-01-17 08:00:00,1,1,MI,3,Detroit,Greektown,[],[],
13,2019-01-17 08:00:00,1,1,MI,3,Detroit,Corktown,[],[],
14,2019-01-17 08:00:00,1,1,MI,3,Detroit,Mexicantown,[],[],
15,2019-01-17 08:00:00,2,0,MC,4,Memnonia,Arcadia Planitia,[],[],
""".lstrip().replace(
"\n", "\r\n"
)