kopia lustrzana https://github.com/simonw/datasette
637 wiersze
22 KiB
Python
637 wiersze
22 KiB
Python
from datasette.app import Datasette
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from datasette.database import Database
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from datasette.facets import ColumnFacet, ArrayFacet, DateFacet
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from datasette.utils.asgi import Request
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from datasette.utils import detect_json1
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from .fixtures import app_client, make_app_client # noqa
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import json
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import pytest
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@pytest.mark.asyncio
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async def test_column_facet_suggest(app_client):
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facet = ColumnFacet(
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app_client.ds,
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Request.fake("/"),
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database="fixtures",
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sql="select * from facetable",
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table="facetable",
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)
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suggestions = await facet.suggest()
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assert [
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{"name": "created", "toggle_url": "http://localhost/?_facet=created"},
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{"name": "planet_int", "toggle_url": "http://localhost/?_facet=planet_int"},
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{"name": "on_earth", "toggle_url": "http://localhost/?_facet=on_earth"},
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{"name": "state", "toggle_url": "http://localhost/?_facet=state"},
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{"name": "_city_id", "toggle_url": "http://localhost/?_facet=_city_id"},
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{
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"name": "_neighborhood",
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"toggle_url": "http://localhost/?_facet=_neighborhood",
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},
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{"name": "tags", "toggle_url": "http://localhost/?_facet=tags"},
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{
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"name": "complex_array",
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"toggle_url": "http://localhost/?_facet=complex_array",
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},
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] == suggestions
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@pytest.mark.asyncio
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async def test_column_facet_suggest_skip_if_already_selected(app_client):
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facet = ColumnFacet(
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app_client.ds,
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Request.fake("/?_facet=planet_int&_facet=on_earth"),
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database="fixtures",
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sql="select * from facetable",
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table="facetable",
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)
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suggestions = await facet.suggest()
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assert [
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{
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"name": "created",
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"toggle_url": "http://localhost/?_facet=planet_int&_facet=on_earth&_facet=created",
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},
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{
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"name": "state",
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"toggle_url": "http://localhost/?_facet=planet_int&_facet=on_earth&_facet=state",
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},
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{
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"name": "_city_id",
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"toggle_url": "http://localhost/?_facet=planet_int&_facet=on_earth&_facet=_city_id",
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},
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{
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"name": "_neighborhood",
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"toggle_url": "http://localhost/?_facet=planet_int&_facet=on_earth&_facet=_neighborhood",
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},
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{
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"name": "tags",
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"toggle_url": "http://localhost/?_facet=planet_int&_facet=on_earth&_facet=tags",
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},
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{
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"name": "complex_array",
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"toggle_url": "http://localhost/?_facet=planet_int&_facet=on_earth&_facet=complex_array",
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},
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] == suggestions
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@pytest.mark.asyncio
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async def test_column_facet_suggest_skip_if_enabled_by_metadata(app_client):
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facet = ColumnFacet(
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app_client.ds,
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Request.fake("/"),
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database="fixtures",
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sql="select * from facetable",
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table="facetable",
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metadata={"facets": ["_city_id"]},
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)
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suggestions = [s["name"] for s in await facet.suggest()]
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assert [
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"created",
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"planet_int",
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"on_earth",
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"state",
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"_neighborhood",
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"tags",
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"complex_array",
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] == suggestions
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@pytest.mark.asyncio
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async def test_column_facet_results(app_client):
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facet = ColumnFacet(
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app_client.ds,
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Request.fake("/?_facet=_city_id"),
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database="fixtures",
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sql="select * from facetable",
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table="facetable",
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)
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buckets, timed_out = await facet.facet_results()
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assert [] == timed_out
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assert [
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{
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"name": "_city_id",
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"type": "column",
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"hideable": True,
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"toggle_url": "/",
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"results": [
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{
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"value": 1,
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"label": "San Francisco",
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"count": 6,
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"toggle_url": "http://localhost/?_facet=_city_id&_city_id__exact=1",
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"selected": False,
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},
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{
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"value": 2,
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"label": "Los Angeles",
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"count": 4,
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"toggle_url": "http://localhost/?_facet=_city_id&_city_id__exact=2",
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"selected": False,
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},
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{
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"value": 3,
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"label": "Detroit",
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"count": 4,
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"toggle_url": "http://localhost/?_facet=_city_id&_city_id__exact=3",
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"selected": False,
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},
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{
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"value": 4,
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"label": "Memnonia",
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"count": 1,
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"toggle_url": "http://localhost/?_facet=_city_id&_city_id__exact=4",
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"selected": False,
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},
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],
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"truncated": False,
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}
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] == buckets
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@pytest.mark.asyncio
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async def test_column_facet_results_column_starts_with_underscore(app_client):
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facet = ColumnFacet(
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app_client.ds,
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Request.fake("/?_facet=_neighborhood"),
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database="fixtures",
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sql="select * from facetable",
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table="facetable",
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)
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buckets, timed_out = await facet.facet_results()
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assert [] == timed_out
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assert buckets == [
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{
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"name": "_neighborhood",
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"type": "column",
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"hideable": True,
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"toggle_url": "/",
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"results": [
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{
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"value": "Downtown",
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"label": "Downtown",
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"count": 2,
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"toggle_url": "http://localhost/?_facet=_neighborhood&_neighborhood__exact=Downtown",
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"selected": False,
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},
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{
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"value": "Arcadia Planitia",
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"label": "Arcadia Planitia",
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"count": 1,
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"toggle_url": "http://localhost/?_facet=_neighborhood&_neighborhood__exact=Arcadia+Planitia",
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"selected": False,
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},
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{
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"value": "Bernal Heights",
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"label": "Bernal Heights",
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"count": 1,
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"toggle_url": "http://localhost/?_facet=_neighborhood&_neighborhood__exact=Bernal+Heights",
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"selected": False,
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},
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{
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"value": "Corktown",
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"label": "Corktown",
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"count": 1,
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"toggle_url": "http://localhost/?_facet=_neighborhood&_neighborhood__exact=Corktown",
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"selected": False,
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},
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{
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"value": "Dogpatch",
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"label": "Dogpatch",
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"count": 1,
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"toggle_url": "http://localhost/?_facet=_neighborhood&_neighborhood__exact=Dogpatch",
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"selected": False,
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},
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{
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"value": "Greektown",
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"label": "Greektown",
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"count": 1,
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"toggle_url": "http://localhost/?_facet=_neighborhood&_neighborhood__exact=Greektown",
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"selected": False,
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},
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{
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"value": "Hayes Valley",
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"label": "Hayes Valley",
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"count": 1,
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"toggle_url": "http://localhost/?_facet=_neighborhood&_neighborhood__exact=Hayes+Valley",
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"selected": False,
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},
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{
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"value": "Hollywood",
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"label": "Hollywood",
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"count": 1,
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"toggle_url": "http://localhost/?_facet=_neighborhood&_neighborhood__exact=Hollywood",
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"selected": False,
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},
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{
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"value": "Koreatown",
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"label": "Koreatown",
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"count": 1,
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"toggle_url": "http://localhost/?_facet=_neighborhood&_neighborhood__exact=Koreatown",
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"selected": False,
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},
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{
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"value": "Los Feliz",
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"label": "Los Feliz",
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"count": 1,
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"toggle_url": "http://localhost/?_facet=_neighborhood&_neighborhood__exact=Los+Feliz",
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"selected": False,
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},
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{
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"value": "Mexicantown",
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"label": "Mexicantown",
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"count": 1,
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"toggle_url": "http://localhost/?_facet=_neighborhood&_neighborhood__exact=Mexicantown",
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"selected": False,
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},
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{
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"value": "Mission",
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"label": "Mission",
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"count": 1,
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"toggle_url": "http://localhost/?_facet=_neighborhood&_neighborhood__exact=Mission",
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"selected": False,
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},
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{
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"value": "SOMA",
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"label": "SOMA",
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"count": 1,
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"toggle_url": "http://localhost/?_facet=_neighborhood&_neighborhood__exact=SOMA",
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"selected": False,
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},
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{
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"value": "Tenderloin",
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"label": "Tenderloin",
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"count": 1,
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"toggle_url": "http://localhost/?_facet=_neighborhood&_neighborhood__exact=Tenderloin",
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"selected": False,
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},
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],
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"truncated": False,
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}
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]
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@pytest.mark.asyncio
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async def test_column_facet_from_metadata_cannot_be_hidden(app_client):
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facet = ColumnFacet(
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app_client.ds,
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Request.fake("/"),
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database="fixtures",
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sql="select * from facetable",
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table="facetable",
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metadata={"facets": ["_city_id"]},
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)
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buckets, timed_out = await facet.facet_results()
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assert [] == timed_out
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assert [
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{
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"name": "_city_id",
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"type": "column",
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"hideable": False,
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"toggle_url": "/",
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"results": [
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{
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"value": 1,
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"label": "San Francisco",
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"count": 6,
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"toggle_url": "http://localhost/?_city_id__exact=1",
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"selected": False,
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},
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{
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"value": 2,
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"label": "Los Angeles",
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"count": 4,
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"toggle_url": "http://localhost/?_city_id__exact=2",
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"selected": False,
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},
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{
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"value": 3,
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"label": "Detroit",
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"count": 4,
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"toggle_url": "http://localhost/?_city_id__exact=3",
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"selected": False,
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},
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{
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"value": 4,
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"label": "Memnonia",
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"count": 1,
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"toggle_url": "http://localhost/?_city_id__exact=4",
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"selected": False,
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},
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],
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"truncated": False,
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}
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] == buckets
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@pytest.mark.asyncio
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@pytest.mark.skipif(not detect_json1(), reason="Requires the SQLite json1 module")
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async def test_array_facet_suggest(app_client):
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facet = ArrayFacet(
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app_client.ds,
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Request.fake("/"),
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database="fixtures",
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sql="select * from facetable",
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table="facetable",
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)
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suggestions = await facet.suggest()
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assert [
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{
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"name": "tags",
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"type": "array",
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"toggle_url": "http://localhost/?_facet_array=tags",
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}
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] == suggestions
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@pytest.mark.asyncio
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@pytest.mark.skipif(not detect_json1(), reason="Requires the SQLite json1 module")
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async def test_array_facet_suggest_not_if_all_empty_arrays(app_client):
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facet = ArrayFacet(
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app_client.ds,
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Request.fake("/"),
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database="fixtures",
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sql="select * from facetable where tags = '[]'",
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table="facetable",
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)
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suggestions = await facet.suggest()
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assert [] == suggestions
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@pytest.mark.asyncio
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@pytest.mark.skipif(not detect_json1(), reason="Requires the SQLite json1 module")
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async def test_array_facet_results(app_client):
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facet = ArrayFacet(
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app_client.ds,
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Request.fake("/?_facet_array=tags"),
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database="fixtures",
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sql="select * from facetable",
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table="facetable",
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)
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buckets, timed_out = await facet.facet_results()
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assert [] == timed_out
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assert [
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{
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"name": "tags",
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"type": "array",
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"results": [
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{
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"value": "tag1",
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"label": "tag1",
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"count": 2,
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"toggle_url": "http://localhost/?_facet_array=tags&tags__arraycontains=tag1",
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"selected": False,
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},
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{
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"value": "tag2",
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"label": "tag2",
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"count": 1,
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"toggle_url": "http://localhost/?_facet_array=tags&tags__arraycontains=tag2",
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"selected": False,
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},
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{
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"value": "tag3",
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"label": "tag3",
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"count": 1,
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"toggle_url": "http://localhost/?_facet_array=tags&tags__arraycontains=tag3",
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"selected": False,
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},
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],
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"hideable": True,
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"toggle_url": "/",
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"truncated": False,
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}
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] == buckets
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@pytest.mark.asyncio
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@pytest.mark.skipif(not detect_json1(), reason="Requires the SQLite json1 module")
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async def test_array_facet_handle_duplicate_tags():
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ds = Datasette([], memory=True)
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db = ds.add_database(Database(ds, memory_name="test_array_facet"))
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await db.execute_write("create table otters(name text, tags text)")
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for name, tags in (
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("Charles", ["friendly", "cunning", "friendly"]),
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("Shaun", ["cunning", "empathetic", "friendly"]),
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("Tracy", ["empathetic", "eager"]),
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):
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await db.execute_write(
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"insert into otters (name, tags) values (?, ?)", [name, json.dumps(tags)]
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)
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response = await ds.client.get("/test_array_facet/otters.json?_facet_array=tags")
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assert response.json()["facet_results"]["tags"] == {
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"name": "tags",
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"type": "array",
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"results": [
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{
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"value": "cunning",
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"label": "cunning",
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"count": 2,
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"toggle_url": "http://localhost/test_array_facet/otters.json?_facet_array=tags&tags__arraycontains=cunning",
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"selected": False,
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},
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{
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"value": "empathetic",
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"label": "empathetic",
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"count": 2,
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"toggle_url": "http://localhost/test_array_facet/otters.json?_facet_array=tags&tags__arraycontains=empathetic",
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"selected": False,
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},
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{
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"value": "friendly",
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"label": "friendly",
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"count": 2,
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"toggle_url": "http://localhost/test_array_facet/otters.json?_facet_array=tags&tags__arraycontains=friendly",
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"selected": False,
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},
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{
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"value": "eager",
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"label": "eager",
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"count": 1,
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"toggle_url": "http://localhost/test_array_facet/otters.json?_facet_array=tags&tags__arraycontains=eager",
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"selected": False,
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},
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],
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"hideable": True,
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"toggle_url": "/test_array_facet/otters.json",
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"truncated": False,
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}
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@pytest.mark.asyncio
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async def test_date_facet_results(app_client):
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facet = DateFacet(
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app_client.ds,
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Request.fake("/?_facet_date=created"),
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database="fixtures",
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sql="select * from facetable",
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table="facetable",
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)
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buckets, timed_out = await facet.facet_results()
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assert [] == timed_out
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assert [
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{
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"name": "created",
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"type": "date",
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"results": [
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{
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"value": "2019-01-14",
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"label": "2019-01-14",
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"count": 4,
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"toggle_url": "http://localhost/?_facet_date=created&created__date=2019-01-14",
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"selected": False,
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},
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{
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"value": "2019-01-15",
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"label": "2019-01-15",
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"count": 4,
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"toggle_url": "http://localhost/?_facet_date=created&created__date=2019-01-15",
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"selected": False,
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},
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{
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"value": "2019-01-17",
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"label": "2019-01-17",
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"count": 4,
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"toggle_url": "http://localhost/?_facet_date=created&created__date=2019-01-17",
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"selected": False,
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},
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{
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"value": "2019-01-16",
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"label": "2019-01-16",
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"count": 3,
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"toggle_url": "http://localhost/?_facet_date=created&created__date=2019-01-16",
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"selected": False,
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},
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],
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"hideable": True,
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"toggle_url": "/",
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"truncated": False,
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}
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] == buckets
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@pytest.mark.asyncio
|
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async def test_json_array_with_blanks_and_nulls():
|
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ds = Datasette([], memory=True)
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db = ds.add_database(Database(ds, memory_name="test_json_array"))
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await db.execute_write("create table foo(json_column text)")
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for value in ('["a", "b", "c"]', '["a", "b"]', "", None):
|
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await db.execute_write("insert into foo (json_column) values (?)", [value])
|
|
response = await ds.client.get("/test_json_array/foo.json")
|
|
data = response.json()
|
|
assert data["suggested_facets"] == [
|
|
{
|
|
"name": "json_column",
|
|
"type": "array",
|
|
"toggle_url": "http://localhost/test_json_array/foo.json?_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")
|
|
data = response.json()
|
|
assert data["suggested_facets"] == [
|
|
{
|
|
"name": "neighbourhood",
|
|
"toggle_url": "http://localhost/test_facet_size/neighbourhoods.json?_facet=neighbourhood",
|
|
}
|
|
]
|
|
# Bump up _facet_size= to suggest city too
|
|
response2 = await ds.client.get(
|
|
"/test_facet_size/neighbourhoods.json?_facet_size=50"
|
|
)
|
|
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&_facet=city",
|
|
},
|
|
{
|
|
"name": "neighbourhood",
|
|
"toggle_url": "http://localhost/test_facet_size/neighbourhoods.json?_facet_size=50&_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"]["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"]["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"]["city"]["results"]) == 20
|
|
# Now try messing with facet_size in the table metadata
|
|
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"]["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"]["city"]["results"]) == 20
|
|
|
|
|
|
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
|
|
|
|
|
|
def test_conflicting_facet_names_json(app_client):
|
|
response = app_client.get(
|
|
"/fixtures/facetable.json?_facet=created&_facet_date=created"
|
|
"&_facet=tags&_facet_array=tags"
|
|
)
|
|
assert set(response.json["facet_results"].keys()) == {
|
|
"created",
|
|
"tags",
|
|
"created_2",
|
|
"tags_2",
|
|
}
|