kopia lustrzana https://github.com/simonw/datasette
Removed ManyToManyFacet for the moment, closes #550
Simon Willison
rodzic
9998f92cc0
commit
c5542abba5
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@ -60,7 +60,7 @@ def load_facet_configs(request, table_metadata):
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@hookimpl
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def register_facet_classes():
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classes = [ColumnFacet, DateFacet, ManyToManyFacet]
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classes = [ColumnFacet, DateFacet]
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if detect_json1():
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classes.append(ArrayFacet)
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return classes
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@ -476,190 +476,3 @@ class DateFacet(Facet):
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facets_timed_out.append(column)
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return facet_results, facets_timed_out
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class ManyToManyFacet(Facet):
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type = "m2m"
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async def suggest(self):
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# This is calculated based on foreign key relationships to this table
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# Are there any many-to-many tables pointing here?
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suggested_facets = []
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db = self.ds.databases[self.database]
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all_foreign_keys = await db.get_all_foreign_keys()
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if not all_foreign_keys.get(self.table):
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# It's probably a view
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return []
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args = set(self.get_querystring_pairs())
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incoming = all_foreign_keys[self.table]["incoming"]
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# Do any of these incoming tables have exactly two outgoing keys?
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for fk in incoming:
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other_table = fk["other_table"]
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other_table_outgoing_foreign_keys = all_foreign_keys[other_table][
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"outgoing"
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]
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if len(other_table_outgoing_foreign_keys) == 2:
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destination_table = [
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t
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for t in other_table_outgoing_foreign_keys
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if t["other_table"] != self.table
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][0]["other_table"]
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# Only suggest if it's not selected already
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if ("_facet_m2m", destination_table) in args:
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continue
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suggested_facets.append(
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{
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"name": destination_table,
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"type": "m2m",
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"toggle_url": self.ds.absolute_url(
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self.request,
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path_with_added_args(
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self.request, {"_facet_m2m": destination_table}
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),
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),
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}
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)
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return suggested_facets
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async def facet_results(self):
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facet_results = {}
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facets_timed_out = []
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args = set(self.get_querystring_pairs())
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facet_size = self.ds.config("default_facet_size")
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db = self.ds.databases[self.database]
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all_foreign_keys = await db.get_all_foreign_keys()
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if not all_foreign_keys.get(self.table):
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return [], []
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# We care about three tables: self.table, middle_table and destination_table
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incoming = all_foreign_keys[self.table]["incoming"]
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for source_and_config in self.get_configs():
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config = source_and_config["config"]
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source = source_and_config["source"]
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# The destination_table is specified in the _facet_m2m=xxx parameter
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destination_table = config.get("column") or config["simple"]
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# Find middle table - it has fks to self.table AND destination_table
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fks = None
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middle_table = None
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for fk in incoming:
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other_table = fk["other_table"]
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other_table_outgoing_foreign_keys = all_foreign_keys[other_table][
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"outgoing"
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]
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if (
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any(
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o
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for o in other_table_outgoing_foreign_keys
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if o["other_table"] == destination_table
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)
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and len(other_table_outgoing_foreign_keys) == 2
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):
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fks = other_table_outgoing_foreign_keys
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middle_table = other_table
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break
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if middle_table is None or fks is None:
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return [], []
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# Now that we have determined the middle_table, we need to figure out the three
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# columns on that table which are relevant to us. These are:
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# column_to_table - the middle_table column with a foreign key to self.table
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# table_pk - the primary key column on self.table that is referenced
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# column_to_destination - the column with a foreign key to destination_table
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#
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# It turns out we don't actually need the fourth obvious column:
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# destination_pk = the primary key column on destination_table which is referenced
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#
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# These are both in the fks array - which now contains 2 foreign key relationships, e.g:
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# [
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# {'other_table': 'characteristic', 'column': 'characteristic_id', 'other_column': 'pk'},
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# {'other_table': 'attractions', 'column': 'attraction_id', 'other_column': 'pk'}
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# ]
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column_to_table = None
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table_pk = None
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column_to_destination = None
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for fk in fks:
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if fk["other_table"] == self.table:
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table_pk = fk["other_column"]
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column_to_table = fk["column"]
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elif fk["other_table"] == destination_table:
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column_to_destination = fk["column"]
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assert all((column_to_table, table_pk, column_to_destination))
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facet_sql = """
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select
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{middle_table}.{column_to_destination} as value,
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count(distinct {middle_table}.{column_to_table}) as count
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from {middle_table}
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where {middle_table}.{column_to_table} in (
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select {table_pk} from ({sql})
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)
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group by {middle_table}.{column_to_destination}
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order by count desc limit {limit}
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""".format(
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sql=self.sql,
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limit=facet_size + 1,
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middle_table=escape_sqlite(middle_table),
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column_to_destination=escape_sqlite(column_to_destination),
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column_to_table=escape_sqlite(column_to_table),
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table_pk=escape_sqlite(table_pk),
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)
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try:
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facet_rows_results = await self.ds.execute(
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self.database,
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facet_sql,
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self.params,
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truncate=False,
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custom_time_limit=self.ds.config("facet_time_limit_ms"),
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)
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facet_results_values = []
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facet_results[destination_table] = {
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"name": destination_table,
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"type": self.type,
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"results": facet_results_values,
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"hideable": source != "metadata",
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"toggle_url": path_with_removed_args(
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self.request, {"_facet_m2m": destination_table}
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),
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"truncated": len(facet_rows_results) > facet_size,
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}
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facet_rows = facet_rows_results.rows[:facet_size]
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# Attempt to expand foreign keys into labels
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values = [row["value"] for row in facet_rows]
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expanded = await self.ds.expand_foreign_keys(
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self.database, middle_table, column_to_destination, values
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)
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for row in facet_rows:
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through = json.dumps(
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{
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"table": middle_table,
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"column": column_to_destination,
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"value": str(row["value"]),
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},
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separators=(",", ":"),
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sort_keys=True,
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)
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selected = ("_through", through) in args
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if selected:
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toggle_path = path_with_removed_args(
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self.request, {"_through": through}
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)
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else:
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toggle_path = path_with_added_args(
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self.request, {"_through": through}
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)
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facet_results_values.append(
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{
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"value": row["value"],
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"label": expanded.get(
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(column_to_destination, row["value"]), row["value"]
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),
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"count": row["count"],
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"toggle_url": self.ds.absolute_url(
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self.request, toggle_path
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),
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"selected": selected,
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}
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)
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except QueryInterrupted:
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facets_timed_out.append(destination_table)
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return facet_results, facets_timed_out
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@ -1,8 +1,7 @@
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from datasette.facets import ColumnFacet, ArrayFacet, DateFacet, ManyToManyFacet
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from datasette.facets import ColumnFacet, ArrayFacet, DateFacet
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from datasette.utils import detect_json1
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from .fixtures import app_client # noqa
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from .utils import MockRequest
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from collections import namedtuple
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import pytest
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@ -303,60 +302,3 @@ async def test_date_facet_results(app_client):
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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_m2m_facet_suggest(app_client):
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facet = ManyToManyFacet(
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app_client.ds,
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MockRequest("http://localhost/"),
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database="fixtures",
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sql="select * from roadside_attractions",
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table="roadside_attractions",
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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": "attraction_characteristic",
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"type": "m2m",
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"toggle_url": "http://localhost/?_facet_m2m=attraction_characteristic",
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}
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] == suggestions
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@pytest.mark.asyncio
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async def test_m2m_facet_results(app_client):
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facet = ManyToManyFacet(
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app_client.ds,
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MockRequest("http://localhost/?_facet_m2m=attraction_characteristic"),
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database="fixtures",
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sql="select * from roadside_attractions",
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table="roadside_attractions",
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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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"attraction_characteristic": {
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"name": "attraction_characteristic",
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"type": "m2m",
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"results": [
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{
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"value": 2,
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"label": "Paranormal",
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"count": 3,
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"toggle_url": "http://localhost/?_facet_m2m=attraction_characteristic&_through=%7B%22column%22%3A%22characteristic_id%22%2C%22table%22%3A%22roadside_attraction_characteristics%22%2C%22value%22%3A%222%22%7D",
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"selected": False,
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},
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{
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"value": 1,
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"label": "Museum",
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"count": 2,
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"toggle_url": "http://localhost/?_facet_m2m=attraction_characteristic&_through=%7B%22column%22%3A%22characteristic_id%22%2C%22table%22%3A%22roadside_attraction_characteristics%22%2C%22value%22%3A%221%22%7D",
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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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