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datasette/tests/test_facets.py

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from datasette.app import Datasette
from datasette.database import Database
from datasette.facets import ColumnFacet, ArrayFacet, DateFacet
from datasette.utils.asgi import Request
from datasette.utils import detect_json1
from .fixtures import make_app_client
import json
import pytest
@pytest.mark.asyncio
async def test_column_facet_suggest(ds_client):
facet = ColumnFacet(
ds_client.ds,
Request.fake("/"),
database="fixtures",
sql="select * from facetable",
table="facetable",
)
suggestions = await facet.suggest()
assert [
{"name": "created", "toggle_url": "http://localhost/?_facet=created"},
{"name": "planet_int", "toggle_url": "http://localhost/?_facet=planet_int"},
{"name": "on_earth", "toggle_url": "http://localhost/?_facet=on_earth"},
{"name": "state", "toggle_url": "http://localhost/?_facet=state"},
{"name": "_city_id", "toggle_url": "http://localhost/?_facet=_city_id"},
{
"name": "_neighborhood",
"toggle_url": "http://localhost/?_facet=_neighborhood",
},
{"name": "tags", "toggle_url": "http://localhost/?_facet=tags"},
{
"name": "complex_array",
"toggle_url": "http://localhost/?_facet=complex_array",
},
] == suggestions
@pytest.mark.asyncio
async def test_column_facet_suggest_skip_if_already_selected(ds_client):
facet = ColumnFacet(
ds_client.ds,
Request.fake("/?_facet=planet_int&_facet=on_earth"),
database="fixtures",
sql="select * from facetable",
table="facetable",
)
suggestions = await facet.suggest()
assert [
{
"name": "created",
"toggle_url": "http://localhost/?_facet=planet_int&_facet=on_earth&_facet=created",
},
{
"name": "state",
"toggle_url": "http://localhost/?_facet=planet_int&_facet=on_earth&_facet=state",
},
{
"name": "_city_id",
"toggle_url": "http://localhost/?_facet=planet_int&_facet=on_earth&_facet=_city_id",
},
{
"name": "_neighborhood",
"toggle_url": "http://localhost/?_facet=planet_int&_facet=on_earth&_facet=_neighborhood",
},
{
"name": "tags",
"toggle_url": "http://localhost/?_facet=planet_int&_facet=on_earth&_facet=tags",
},
{
"name": "complex_array",
"toggle_url": "http://localhost/?_facet=planet_int&_facet=on_earth&_facet=complex_array",
},
] == suggestions
@pytest.mark.asyncio
async def test_column_facet_suggest_skip_if_enabled_by_metadata(ds_client):
facet = ColumnFacet(
ds_client.ds,
Request.fake("/"),
database="fixtures",
sql="select * from facetable",
table="facetable",
table_config={"facets": ["_city_id"]},
)
suggestions = [s["name"] for s in await facet.suggest()]
assert [
"created",
"planet_int",
"on_earth",
"state",
"_neighborhood",
"tags",
"complex_array",
] == suggestions
@pytest.mark.asyncio
async def test_column_facet_results(ds_client):
facet = ColumnFacet(
ds_client.ds,
Request.fake("/?_facet=_city_id"),
database="fixtures",
sql="select * from facetable",
table="facetable",
)
buckets, timed_out = await facet.facet_results()
assert [] == timed_out
assert [
{
"name": "_city_id",
"type": "column",
"hideable": True,
"toggle_url": "/",
"results": [
{
"value": 1,
"label": "San Francisco",
"count": 6,
"toggle_url": "http://localhost/?_facet=_city_id&_city_id__exact=1",
"selected": False,
},
{
"value": 2,
"label": "Los Angeles",
"count": 4,
"toggle_url": "http://localhost/?_facet=_city_id&_city_id__exact=2",
"selected": False,
},
{
"value": 3,
"label": "Detroit",
"count": 4,
"toggle_url": "http://localhost/?_facet=_city_id&_city_id__exact=3",
"selected": False,
},
{
"value": 4,
"label": "Memnonia",
"count": 1,
"toggle_url": "http://localhost/?_facet=_city_id&_city_id__exact=4",
"selected": False,
},
],
"truncated": False,
}
] == buckets
@pytest.mark.asyncio
async def test_column_facet_results_column_starts_with_underscore(ds_client):
facet = ColumnFacet(
ds_client.ds,
Request.fake("/?_facet=_neighborhood"),
database="fixtures",
sql="select * from facetable",
table="facetable",
)
buckets, timed_out = await facet.facet_results()
assert [] == timed_out
assert buckets == [
{
"name": "_neighborhood",
"type": "column",
"hideable": True,
"toggle_url": "/",
"results": [
{
"value": "Downtown",
"label": "Downtown",
"count": 2,
"toggle_url": "http://localhost/?_facet=_neighborhood&_neighborhood__exact=Downtown",
"selected": False,
},
{
"value": "Arcadia Planitia",
"label": "Arcadia Planitia",
"count": 1,
"toggle_url": "http://localhost/?_facet=_neighborhood&_neighborhood__exact=Arcadia+Planitia",
"selected": False,
},
{
"value": "Bernal Heights",
"label": "Bernal Heights",
"count": 1,
"toggle_url": "http://localhost/?_facet=_neighborhood&_neighborhood__exact=Bernal+Heights",
"selected": False,
},
{
"value": "Corktown",
"label": "Corktown",
"count": 1,
"toggle_url": "http://localhost/?_facet=_neighborhood&_neighborhood__exact=Corktown",
"selected": False,
},
{
"value": "Dogpatch",
"label": "Dogpatch",
"count": 1,
"toggle_url": "http://localhost/?_facet=_neighborhood&_neighborhood__exact=Dogpatch",
"selected": False,
},
{
"value": "Greektown",
"label": "Greektown",
"count": 1,
"toggle_url": "http://localhost/?_facet=_neighborhood&_neighborhood__exact=Greektown",
"selected": False,
},
{
"value": "Hayes Valley",
"label": "Hayes Valley",
"count": 1,
"toggle_url": "http://localhost/?_facet=_neighborhood&_neighborhood__exact=Hayes+Valley",
"selected": False,
},
{
"value": "Hollywood",
"label": "Hollywood",
"count": 1,
"toggle_url": "http://localhost/?_facet=_neighborhood&_neighborhood__exact=Hollywood",
"selected": False,
},
{
"value": "Koreatown",
"label": "Koreatown",
"count": 1,
"toggle_url": "http://localhost/?_facet=_neighborhood&_neighborhood__exact=Koreatown",
"selected": False,
},
{
"value": "Los Feliz",
"label": "Los Feliz",
"count": 1,
"toggle_url": "http://localhost/?_facet=_neighborhood&_neighborhood__exact=Los+Feliz",
"selected": False,
},
{
"value": "Mexicantown",
"label": "Mexicantown",
"count": 1,
"toggle_url": "http://localhost/?_facet=_neighborhood&_neighborhood__exact=Mexicantown",
"selected": False,
},
{
"value": "Mission",
"label": "Mission",
"count": 1,
"toggle_url": "http://localhost/?_facet=_neighborhood&_neighborhood__exact=Mission",
"selected": False,
},
{
"value": "SOMA",
"label": "SOMA",
"count": 1,
"toggle_url": "http://localhost/?_facet=_neighborhood&_neighborhood__exact=SOMA",
"selected": False,
},
{
"value": "Tenderloin",
"label": "Tenderloin",
"count": 1,
"toggle_url": "http://localhost/?_facet=_neighborhood&_neighborhood__exact=Tenderloin",
"selected": False,
},
],
"truncated": False,
}
]
@pytest.mark.asyncio
async def test_column_facet_from_metadata_cannot_be_hidden(ds_client):
facet = ColumnFacet(
ds_client.ds,
Request.fake("/"),
database="fixtures",
sql="select * from facetable",
table="facetable",
table_config={"facets": ["_city_id"]},
)
buckets, timed_out = await facet.facet_results()
assert [] == timed_out
assert [
{
"name": "_city_id",
"type": "column",
"hideable": False,
"toggle_url": "/",
"results": [
{
"value": 1,
"label": "San Francisco",
"count": 6,
"toggle_url": "http://localhost/?_city_id__exact=1",
"selected": False,
},
{
"value": 2,
"label": "Los Angeles",
"count": 4,
"toggle_url": "http://localhost/?_city_id__exact=2",
"selected": False,
},
{
"value": 3,
"label": "Detroit",
"count": 4,
"toggle_url": "http://localhost/?_city_id__exact=3",
"selected": False,
},
{
"value": 4,
"label": "Memnonia",
"count": 1,
"toggle_url": "http://localhost/?_city_id__exact=4",
"selected": False,
},
],
"truncated": False,
}
] == buckets
@pytest.mark.asyncio
@pytest.mark.skipif(not detect_json1(), reason="Requires the SQLite json1 module")
async def test_array_facet_suggest(ds_client):
facet = ArrayFacet(
ds_client.ds,
Request.fake("/"),
database="fixtures",
sql="select * from facetable",
table="facetable",
)
suggestions = await facet.suggest()
assert [
{
"name": "tags",
"type": "array",
"toggle_url": "http://localhost/?_facet_array=tags",
}
] == suggestions
@pytest.mark.asyncio
@pytest.mark.skipif(not detect_json1(), reason="Requires the SQLite json1 module")
async def test_array_facet_suggest_not_if_all_empty_arrays(ds_client):
facet = ArrayFacet(
ds_client.ds,
Request.fake("/"),
database="fixtures",
sql="select * from facetable where tags = '[]'",
table="facetable",
)
suggestions = await facet.suggest()
assert [] == suggestions
@pytest.mark.asyncio
@pytest.mark.skipif(not detect_json1(), reason="Requires the SQLite json1 module")
async def test_array_facet_results(ds_client):
facet = ArrayFacet(
ds_client.ds,
Request.fake("/?_facet_array=tags"),
database="fixtures",
sql="select * from facetable",
table="facetable",
)
buckets, timed_out = await facet.facet_results()
assert [] == timed_out
assert [
{
"name": "tags",
"type": "array",
"results": [
{
"value": "tag1",
"label": "tag1",
"count": 2,
"toggle_url": "http://localhost/?_facet_array=tags&tags__arraycontains=tag1",
"selected": False,
},
{
"value": "tag2",
"label": "tag2",
"count": 1,
"toggle_url": "http://localhost/?_facet_array=tags&tags__arraycontains=tag2",
"selected": False,
},
{
"value": "tag3",
"label": "tag3",
"count": 1,
"toggle_url": "http://localhost/?_facet_array=tags&tags__arraycontains=tag3",
"selected": False,
},
],
"hideable": True,
"toggle_url": "/",
"truncated": False,
}
] == buckets
@pytest.mark.asyncio
@pytest.mark.skipif(not detect_json1(), reason="Requires the SQLite json1 module")
async def test_array_facet_handle_duplicate_tags():
ds = Datasette([], memory=True)
db = ds.add_database(Database(ds, memory_name="test_array_facet"))
await db.execute_write("create table otters(name text, tags text)")
for name, tags in (
("Charles", ["friendly", "cunning", "friendly"]),
("Shaun", ["cunning", "empathetic", "friendly"]),
("Tracy", ["empathetic", "eager"]),
):
await db.execute_write(
"insert into otters (name, tags) values (?, ?)", [name, json.dumps(tags)]
)
response = await ds.client.get("/test_array_facet/otters.json?_facet_array=tags")
assert response.json()["facet_results"]["results"]["tags"] == {
"name": "tags",
"type": "array",
"results": [
{
"value": "cunning",
"label": "cunning",
"count": 2,
"toggle_url": "http://localhost/test_array_facet/otters.json?_facet_array=tags&tags__arraycontains=cunning",
"selected": False,
},
{
"value": "empathetic",
"label": "empathetic",
"count": 2,
"toggle_url": "http://localhost/test_array_facet/otters.json?_facet_array=tags&tags__arraycontains=empathetic",
"selected": False,
},
{
"value": "friendly",
"label": "friendly",
"count": 2,
"toggle_url": "http://localhost/test_array_facet/otters.json?_facet_array=tags&tags__arraycontains=friendly",
"selected": False,
},
{
"value": "eager",
"label": "eager",
"count": 1,
"toggle_url": "http://localhost/test_array_facet/otters.json?_facet_array=tags&tags__arraycontains=eager",
"selected": False,
},
],
"hideable": True,
"toggle_url": "/test_array_facet/otters.json",
"truncated": False,
}
@pytest.mark.asyncio
async def test_date_facet_results(ds_client):
facet = DateFacet(
ds_client.ds,
Request.fake("/?_facet_date=created"),
database="fixtures",
sql="select * from facetable",
table="facetable",
)
buckets, timed_out = await facet.facet_results()
assert [] == timed_out
assert [
{
"name": "created",
"type": "date",
"results": [
{
"value": "2019-01-14",
"label": "2019-01-14",
"count": 4,
"toggle_url": "http://localhost/?_facet_date=created&created__date=2019-01-14",
"selected": False,
},
{
"value": "2019-01-15",
"label": "2019-01-15",
"count": 4,
"toggle_url": "http://localhost/?_facet_date=created&created__date=2019-01-15",
"selected": False,
},
{
"value": "2019-01-17",
"label": "2019-01-17",
"count": 4,
"toggle_url": "http://localhost/?_facet_date=created&created__date=2019-01-17",
"selected": False,
},
{
"value": "2019-01-16",
"label": "2019-01-16",
"count": 3,
"toggle_url": "http://localhost/?_facet_date=created&created__date=2019-01-16",
"selected": False,
},
],
"hideable": True,
"toggle_url": "/",
"truncated": False,
}
] == buckets
@pytest.mark.asyncio
async def test_json_array_with_blanks_and_nulls():
ds = Datasette([], memory=True)
db = ds.add_database(Database(ds, memory_name="test_json_array"))
await db.execute_write("create table foo(json_column text)")
for value in ('["a", "b", "c"]', '["a", "b"]', "", None):
await db.execute_write("insert into foo (json_column) values (?)", [value])
response = await ds.client.get("/test_json_array/foo.json?_extra=suggested_facets")
data = response.json()
assert data["suggested_facets"] == [
{
"name": "json_column",
"type": "array",
"toggle_url": "http://localhost/test_json_array/foo.json?_extra=suggested_facets&_facet_array=json_column",
}
]
@pytest.mark.asyncio
async def test_facet_size():
ds = Datasette([], memory=True, settings={"max_returned_rows": 50})
db = ds.add_database(Database(ds, memory_name="test_facet_size"))
await db.execute_write("create table neighbourhoods(city text, neighbourhood text)")
for i in range(1, 51):
for j in range(1, 4):
await db.execute_write(
"insert into neighbourhoods (city, neighbourhood) values (?, ?)",
["City {}".format(i), "Neighbourhood {}".format(j)],
)
response = await ds.client.get(
"/test_facet_size/neighbourhoods.json?_extra=suggested_facets"
)
data = response.json()
assert data["suggested_facets"] == [
{
"name": "neighbourhood",
"toggle_url": "http://localhost/test_facet_size/neighbourhoods.json?_extra=suggested_facets&_facet=neighbourhood",
}
]
# Bump up _facet_size= to suggest city too
response2 = await ds.client.get(
"/test_facet_size/neighbourhoods.json?_facet_size=50&_extra=suggested_facets"
)
data2 = response2.json()
assert sorted(data2["suggested_facets"], key=lambda f: f["name"]) == [
{
"name": "city",
"toggle_url": "http://localhost/test_facet_size/neighbourhoods.json?_facet_size=50&_extra=suggested_facets&_facet=city",
},
{
"name": "neighbourhood",
"toggle_url": "http://localhost/test_facet_size/neighbourhoods.json?_facet_size=50&_extra=suggested_facets&_facet=neighbourhood",
},
]
# Facet by city should return expected number of results
response3 = await ds.client.get(
"/test_facet_size/neighbourhoods.json?_facet_size=50&_facet=city"
)
data3 = response3.json()
assert len(data3["facet_results"]["results"]["city"]["results"]) == 50
# Reduce max_returned_rows and check that it's respected
ds._settings["max_returned_rows"] = 20
response4 = await ds.client.get(
"/test_facet_size/neighbourhoods.json?_facet_size=50&_facet=city"
)
data4 = response4.json()
assert len(data4["facet_results"]["results"]["city"]["results"]) == 20
# Test _facet_size=max
response5 = await ds.client.get(
"/test_facet_size/neighbourhoods.json?_facet_size=max&_facet=city"
)
data5 = response5.json()
assert len(data5["facet_results"]["results"]["city"]["results"]) == 20
# Now try messing with facet_size in the table metadata
orig_metadata = ds._metadata_local
try:
ds._metadata_local = {
"databases": {
"test_facet_size": {"tables": {"neighbourhoods": {"facet_size": 6}}}
}
}
response6 = await ds.client.get(
"/test_facet_size/neighbourhoods.json?_facet=city"
)
data6 = response6.json()
assert len(data6["facet_results"]["results"]["city"]["results"]) == 6
# Setting it to max bumps it up to 50 again
ds._metadata_local["databases"]["test_facet_size"]["tables"]["neighbourhoods"][
"facet_size"
] = "max"
data7 = (
await ds.client.get("/test_facet_size/neighbourhoods.json?_facet=city")
).json()
assert len(data7["facet_results"]["results"]["city"]["results"]) == 20
finally:
ds._metadata_local = orig_metadata
def test_other_types_of_facet_in_metadata():
with make_app_client(
metadata={
"databases": {
"fixtures": {
"tables": {
"facetable": {
"facets": ["state", {"array": "tags"}, {"date": "created"}]
}
}
}
}
}
) as client:
response = client.get("/fixtures/facetable")
for fragment in (
"<strong>created (date)\n",
"<strong>tags (array)\n",
"<strong>state\n",
):
assert fragment in response.text
@pytest.mark.asyncio
async def test_conflicting_facet_names_json(ds_client):
response = await ds_client.get(
"/fixtures/facetable.json?_facet=created&_facet_date=created"
"&_facet=tags&_facet_array=tags"
)
assert set(response.json()["facet_results"]["results"].keys()) == {
"created",
"tags",
"created_2",
"tags_2",
}
@pytest.mark.asyncio
async def test_facet_against_in_memory_database():
ds = Datasette()
db = ds.add_memory_database("mem")
await db.execute_write(
"create table t (id integer primary key, name text, name2 text)"
)
to_insert = [{"name": "one", "name2": "1"} for _ in range(800)] + [
{"name": "two", "name2": "2"} for _ in range(300)
]
print(to_insert)
await db.execute_write_many(
"insert into t (name, name2) values (:name, :name2)", to_insert
)
response1 = await ds.client.get("/mem/t")
assert response1.status_code == 200
response2 = await ds.client.get("/mem/t?_facet=name&_facet=name2")
assert response2.status_code == 200
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