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https://github.com/simonw/datasette.git
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Continue sketching out new facet design, refs #427
Includes various new partially implemented facet classes, to help exercise the API design.
This commit is contained in:
Simon Willison
parent
538d91c44a
commit
62810f8f7a
5 changed files with 524 additions and 30 deletions
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@ -579,6 +579,7 @@ class Datasette:
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truncate=False,
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custom_time_limit=None,
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page_size=None,
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log_sql_errors=True,
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):
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"""Executes sql against db_name in a thread"""
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page_size = page_size or self.page_size
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@ -605,11 +606,12 @@ class Datasette:
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except sqlite3.OperationalError as e:
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if e.args == ('interrupted',):
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raise InterruptedError(e)
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print(
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"ERROR: conn={}, sql = {}, params = {}: {}".format(
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conn, repr(sql), params, e
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if log_sql_errors:
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print(
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"ERROR: conn={}, sql = {}, params = {}: {}".format(
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conn, repr(sql), params, e
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)
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)
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)
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raise
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if truncate:
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@ -1,17 +1,48 @@
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from sanic.request import RequestParameters
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import urllib
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import re
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from datasette import hookimpl
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from datasette.utils import (
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escape_sqlite,
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get_all_foreign_keys,
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path_with_added_args,
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path_with_removed_args,
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detect_json1
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detect_json1,
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InvalidSql,
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sqlite3,
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)
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def load_facet_configs(request, table_metadata):
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# Given a request and this tables metadata, return
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# a dict of selected facets and their configs
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# return {type, [config1, config2]...}
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facet_configs = {}
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#metadata_facets = table_metadata.get("facets", [])
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#facets = metadata_facets[:]
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args = RequestParameters(
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urllib.parse.parse_qs(request.query_string, keep_blank_values=True)
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)
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for key, values in args.items():
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if key.startswith("_facet"):
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# Figure out the facet type
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if key == "_facet":
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type = "column"
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elif key.startswith("_facet_"):
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type = key[len("_facet_"):]
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for value in values:
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# The value is the config - either JSON or not
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if value.startswith("{"):
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config = json.loads(value)
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else:
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config = {"single": value}
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facet_configs.setdefault(type, []).append(config)
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return facet_configs
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@hookimpl
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def register_facet_classes():
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return [ColumnFacet]
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return [ColumnFacet, ArrayFacet, ManyToManyFacet, DateFacet, EmojiFacet, PhrasesFacet]
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# classes = [ColumnFacet, ManyToManyFacet]
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# if detect_json1():
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# classes.append(ArrayFacet)
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@ -28,26 +59,30 @@ class Facet:
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self.table = table # can be None
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self.configs = configs
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async def suggest(self, sql, params):
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raise NotImplementedError
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async def suggest(self, sql, params, filtered_table_rows_count):
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return []
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async def facet_results(self, sql, params):
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# returns ([results], [timed_out])
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# TODO: Include "hideable" with each one somehow, which indicates if it was
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# defined in metadata (in which case you cannot turn it off)
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raise NotImplementedError
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async def get_columns(self, sql, params=None):
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return (
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await self.ds.execute(
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self.database, "select * from ({}) limit 0".format(sql),
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params or []
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)
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).columns
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class ColumnFacet(Facet):
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# This is the default so type=""
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type = ""
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type = "column"
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async def suggest(self, sql, params, filtered_table_rows_count):
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# Detect column names
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columns = (
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await self.ds.execute(
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self.database, "select * from ({}) limit 0".format(sql),
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params
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)
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).columns
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# Detect column names using the "limit 0" trick
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columns = await self.get_columns(sql, params)
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facet_size = self.ds.config("default_facet_size")
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suggested_facets = []
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for column in columns:
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@ -104,7 +139,9 @@ class ColumnFacet(Facet):
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other_args[key] = value[0]
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facet_size = self.ds.config("default_facet_size")
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for column in self.configs:
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for config in (self.configs or []):
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column = config.get("column") or config["single"]
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# TODO: does this query break if inner sql produces value or count columns?
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facet_sql = """
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select {col} as value, count(*) as count from (
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{sql}
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@ -166,6 +203,460 @@ class ColumnFacet(Facet):
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class ManyToManyFacet(Facet):
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type = "m2m"
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async def suggest(self, sql, params, filtered_table_rows_count):
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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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all_foreign_keys = await self.ds.execute_against_connection_in_thread(
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self.database, get_all_foreign_keys
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)
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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]["outgoing"]
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if len(other_table_outgoing_foreign_keys) == 2:
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suggested_facets.append({
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"name": other_table,
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"type": "m2m",
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"toggle_url": self.ds.absolute_url(
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self.request, path_with_added_args(
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self.request, {"_facet_m2m": other_table}
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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, *args, **kwargs):
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return [], []
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class ArrayFacet(Facet):
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type = "array"
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async def suggest(self, sql, params, filtered_table_rows_count):
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columns = await self.get_columns(sql, params)
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suggested_facets = []
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for column in columns:
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# Is every value in this column either null or a JSON array?
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suggested_facet_sql = """
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select distinct json_type({column})
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from ({sql})
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""".format(
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column=escape_sqlite(column),
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sql=sql,
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)
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try:
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results = await self.ds.execute(
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self.database, suggested_facet_sql, params,
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truncate=False,
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custom_time_limit=self.ds.config("facet_suggest_time_limit_ms"),
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log_sql_errors=False,
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)
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types = tuple(r[0] for r in results.rows)
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if types in (
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("array",),
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("array", None)
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):
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suggested_facets.append({
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"name": column,
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"type": "array",
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"toggle_url": self.ds.absolute_url(
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self.request, path_with_added_args(
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self.request, {"_facet_array": column}
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)
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),
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})
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except (InterruptedError, sqlite3.OperationalError):
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continue
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return suggested_facets
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async def facet_results(self, sql, params):
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# self.configs should be a plain list of columns
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facet_results = {}
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facets_timed_out = []
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# TODO: refactor this
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args = RequestParameters(
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urllib.parse.parse_qs(self.request.query_string, keep_blank_values=True)
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)
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other_args = {}
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for key, value in args.items():
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if key.startswith("_") and "__" not in key:
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pass
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else:
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other_args[key] = value[0]
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facet_size = self.ds.config("default_facet_size")
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for config in (self.configs or []):
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column = config.get("column") or config["single"]
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facet_sql = """
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select j.value as value, count(*) as count from (
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{sql}
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) join json_each({col}) j
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group by j.value order by count desc limit {limit}
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""".format(
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col=escape_sqlite(column),
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sql=sql,
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limit=facet_size+1,
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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, facet_sql, 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[column] = {
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"name": column,
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"results": facet_results_values,
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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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for row in facet_rows:
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selected = str(other_args.get(column)) == str(row["value"])
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if selected:
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toggle_path = path_with_removed_args(
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self.request, {"{}__arraycontains".format(column): str(row["value"])}
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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, {"{}__arraycontains".format(column): row["value"]}
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)
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facet_results_values.append({
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"value": row["value"],
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"label": row["value"],
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"count": row["count"],
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"toggle_url": self.ds.absolute_url(self.request, toggle_path),
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"selected": selected,
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})
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except InterruptedError:
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facets_timed_out.append(column)
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return facet_results, facets_timed_out
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class DateFacet(Facet):
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type = "date"
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async def suggest(self, sql, params, filtered_table_rows_count):
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columns = await self.get_columns(sql, params)
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suggested_facets = []
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for column in columns:
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# Does this column contain any dates in the first 100 rows?
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suggested_facet_sql = """
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select date({column}) from (
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{sql}
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) limit 100;
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""".format(
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column=escape_sqlite(column),
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sql=sql,
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)
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try:
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results = await self.ds.execute(
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self.database, suggested_facet_sql, params,
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truncate=False,
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custom_time_limit=self.ds.config("facet_suggest_time_limit_ms"),
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log_sql_errors=False,
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)
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values = tuple(r[0] for r in results.rows)
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if (any(values)):
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suggested_facets.append({
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"name": column,
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"type": "date",
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"toggle_url": self.ds.absolute_url(
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self.request, path_with_added_args(
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self.request, {"_facet_date": column}
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)
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),
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})
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except (InterruptedError, sqlite3.OperationalError):
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continue
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return suggested_facets
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async def facet_results(self, sql, params):
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# self.configs should be a plain list of columns
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facet_results = {}
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facets_timed_out = []
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# TODO: refactor this
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args = RequestParameters(
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urllib.parse.parse_qs(self.request.query_string, keep_blank_values=True)
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)
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other_args = {}
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for key, value in args.items():
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if key.startswith("_") and "__" not in key:
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pass
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else:
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other_args[key] = value[0]
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facet_size = self.ds.config("default_facet_size")
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for config in (self.configs or []):
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column = config.get("column") or config["single"]
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# TODO: does this query break if inner sql produces value or count columns?
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facet_sql = """
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select date({col}) as value, count(*) as count from (
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{sql}
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)
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where date({col}) is not null
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group by date({col}) order by date({col}) desc limit {limit}
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""".format(
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col=escape_sqlite(column),
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sql=sql,
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limit=facet_size+1,
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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, facet_sql, 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[column] = {
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"name": column,
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"results": facet_results_values,
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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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for row in facet_rows:
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selected = str(other_args.get("{}__date".format(column))) == str(row["value"])
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if selected:
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toggle_path = path_with_removed_args(
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self.request, {"{}__date".format(column): str(row["value"])}
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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, {"{}__date".format(column): row["value"]}
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)
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facet_results_values.append({
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"value": row["value"],
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"label": row["value"],
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"count": row["count"],
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"toggle_url": self.ds.absolute_url(self.request, toggle_path),
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"selected": selected,
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})
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except InterruptedError:
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facets_timed_out.append(column)
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return facet_results, facets_timed_out
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class PhrasesFacet(Facet):
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type = "phrases"
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async def facet_results(self, sql, params):
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# Hmm... for this one we actually need the column name(s) AND the word list
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# Current design supports one of the following:
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# ?_facet_phrases=column:word1,word2,word3
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# which means we could support multiple columns like so:
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# ?_facet_phrases=column1:column2:word1,word2,word3
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# As JSON:
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# ?_facet_phrases={"columns":["column1","column2"],"phrases":["word1","word2"]}
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# Urgh, the filter option when one is selected is going to be pretty nasty
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facet_results = {}
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facets_timed_out = []
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facet_size = self.ds.config("default_facet_size")
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for config in (self.configs or []):
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if isinstance(config, dict) and "single" in config:
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config = config["single"]
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if isinstance(config, str):
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columns = config.rsplit(":", 1)[0].split(":")
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phrases = config.rsplit(":", 1)[1].split(",")
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else:
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columns = config["columns"]
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phases = config["phrases"]
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# FOR THE MOMENT only support one column
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column = columns[0]
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facet_sql = """
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select count(*) as count, j.value as value
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from (
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select extract_phrases_json({col}, '{json_phrases}') as a from (
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{sql}
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)
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)
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join json_each(a) j
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group by j.value order by count desc limit {limit}
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""".format(
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col=escape_sqlite(column),
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sql=sql,
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# TODO: this will break if any phrases contain '
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json_phrases=json.dumps(phrases),
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limit=facet_size+1,
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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, facet_sql, 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[column] = {
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"name": column,
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"results": facet_results_values,
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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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for row in facet_rows:
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facet_results_values.append({
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"value": row["value"],
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"label": row["value"],
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"count": row["count"],
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# TODO: toggle_url for selected
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"toggle_url": "", # self.ds.absolute_url(self.request, toggle_path),
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# TODO: identify selected
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"selected": False,
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})
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except InterruptedError:
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facets_timed_out.append(column)
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return facet_results, facets_timed_out
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class EmojiFacet(Facet):
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type = "emoji"
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async def suggest(self, sql, params, filtered_table_rows_count):
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columns = await self.get_columns(sql, params)
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suggested_facets = []
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for column in columns:
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# Is every value in this column either null or a JSON array?
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suggested_facet_sql = """
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select extract_emoji({column}) as emojis
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from ({sql}) where emojis != "" limit 1
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""".format(
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column=escape_sqlite(column),
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sql=sql,
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)
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try:
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results = await self.ds.execute(
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self.database, suggested_facet_sql, params,
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truncate=False,
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custom_time_limit=self.ds.config("facet_suggest_time_limit_ms"),
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log_sql_errors=True,
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)
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if results.rows:
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suggested_facets.append({
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"name": column,
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"type": "emoji",
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"toggle_url": self.ds.absolute_url(
|
||||
self.request, path_with_added_args(
|
||||
self.request, {"_facet_emoji": column}
|
||||
)
|
||||
),
|
||||
})
|
||||
except (InterruptedError, sqlite3.OperationalError) as e:
|
||||
print(" oh no ", e)
|
||||
continue
|
||||
return suggested_facets
|
||||
|
||||
async def facet_results(self, *args, **kwargs):
|
||||
return [], []
|
||||
|
||||
|
||||
@hookimpl
|
||||
def prepare_connection(conn):
|
||||
conn.create_function("extract_emoji", 1, extract_emoji)
|
||||
conn.create_function("extract_emoji_json", 1, extract_emoji_json)
|
||||
conn.create_function("extract_phrases_json", 2, extract_phrases_json)
|
||||
conn.create_function("extract_name_json", 1, extract_name_json)
|
||||
conn.create_function("decode_punycode", 1, decode_punycode)
|
||||
|
||||
|
||||
import json
|
||||
|
||||
def extract_emoji(s):
|
||||
if not isinstance(s, str):
|
||||
return ""
|
||||
try:
|
||||
return "".join(emoji_re.findall(s))
|
||||
except Exception as e:
|
||||
print(e)
|
||||
raise
|
||||
|
||||
|
||||
def extract_emoji_json(s):
|
||||
try:
|
||||
if not isinstance(s, str):
|
||||
return "[]"
|
||||
return json.dumps(list(set([
|
||||
c.encode("punycode").decode("latin1") for c in emoji_re.findall(s)
|
||||
])))
|
||||
except Exception as e:
|
||||
print(e)
|
||||
raise
|
||||
|
||||
|
||||
def extract_name_json(s):
|
||||
try:
|
||||
if not isinstance(s, str):
|
||||
return "[]"
|
||||
return json.dumps(list(set([m.group(0) for m in name_re.finditer(s)])))
|
||||
except Exception as e:
|
||||
print(e)
|
||||
raise
|
||||
|
||||
|
||||
def extract_phrases_json(s, phrases):
|
||||
# phrases is a '["json", "list", "of", "phrases"]'
|
||||
if not isinstance(s, str):
|
||||
return "[]"
|
||||
phrases_list = json.loads(phrases)
|
||||
# I tried caching the regex but the performance boost was negligible
|
||||
r = re.compile(r"\b{}\b".format("|".join(phrases_list)), re.I)
|
||||
return json.dumps(list(set(w.lower() for w in r.findall(s))))
|
||||
|
||||
|
||||
name_re = re.compile("([A-Z][a-z]+)+( [A-Z][a-z]+)")
|
||||
|
||||
|
||||
|
||||
def decode_punycode(s):
|
||||
return s.encode("latin1").decode("punycode")
|
||||
|
||||
|
||||
emoji_re = re.compile(
|
||||
"[\xa9\xae\u203c\u2049\u2122\u2139\u2194-\u2199\u21a9-\u21aa\u231a-\u231b"
|
||||
"\u2328\u23cf\u23e9-\u23f3\u23f8-\u23fa\u24c2\u25aa-\u25ab\u25b6\u25c0"
|
||||
"\u25fb-\u25fe\u2600-\u2604\u260e\u2611\u2614-\u2615\u2618\u261d\u2620"
|
||||
"\u2622-\u2623\u2626\u262a\u262e-\u262f\u2638-\u263a\u2640\u2642\u2648-"
|
||||
"\u2653\u2660\u2663\u2665-\u2666\u2668\u267b\u267f\u2692-\u2697\u2699"
|
||||
"\u269b-\u269c\u26a0-\u26a1\u26aa-\u26ab\u26b0-\u26b1\u26bd-\u26be\u26c4-"
|
||||
"\u26c5\u26c8\u26ce\u26cf\u26d1\u26d3-\u26d4\u26e9-\u26ea\u26f0-\u26f5"
|
||||
"\u26f7-\u26fa\u26fd\u2702\u2705\u2708-\u2709\u270a-\u270b\u270c-\u270d"
|
||||
"\u270f\u2712\u2714\u2716\u271d\u2721\u2728\u2733-\u2734\u2744\u2747\u274c"
|
||||
"\u274e\u2753-\u2755\u2757\u2763-\u2764\u2795-\u2797\u27a1\u27b0\u27bf"
|
||||
"\u2934-\u2935\u2b05-\u2b07\u2b1b-\u2b1c\u2b50\u2b55\u3030\u303d\u3297"
|
||||
"\u3299\U0001f004\U0001f0cf\U0001f170-\U0001f171\U0001f17e\U0001f17f"
|
||||
"\U0001f18e\U0001f191-\U0001f19a\U0001f1e6-\U0001f1ff\U0001f201-\U0001f202"
|
||||
"\U0001f21a\U0001f22f\U0001f232-\U0001f23a\U0001f250-\U0001f251\U0001f300-"
|
||||
"\U0001f320\U0001f321\U0001f324-\U0001f32c\U0001f32d-\U0001f32f\U0001f330-"
|
||||
"\U0001f335\U0001f336\U0001f337-\U0001f37c\U0001f37d\U0001f37e-\U0001f37f"
|
||||
"\U0001f380-\U0001f393\U0001f396-\U0001f397\U0001f399-\U0001f39b\U0001f39e-"
|
||||
"\U0001f39f\U0001f3a0-\U0001f3c4\U0001f3c5\U0001f3c6-\U0001f3ca\U0001f3cb-"
|
||||
"\U0001f3ce\U0001f3cf-\U0001f3d3\U0001f3d4-\U0001f3df\U0001f3e0-\U0001f3f0"
|
||||
"\U0001f3f3-\U0001f3f5\U0001f3f7\U0001f3f8-\U0001f3ff\U0001f400-\U0001f43e"
|
||||
"\U0001f43f\U0001f440\U0001f441\U0001f442-\U0001f4f7\U0001f4f8\U0001f4f9-"
|
||||
"\U0001f4fc\U0001f4fd\U0001f4ff\U0001f500-\U0001f53d\U0001f549-\U0001f54a"
|
||||
"\U0001f54b-\U0001f54e\U0001f550-\U0001f567\U0001f56f-\U0001f570\U0001f573-"
|
||||
"\U0001f579\U0001f57a\U0001f587\U0001f58a-\U0001f58d\U0001f590\U0001f595-"
|
||||
"\U0001f596\U0001f5a4\U0001f5a5\U0001f5a8\U0001f5b1-\U0001f5b2\U0001f5bc"
|
||||
"\U0001f5c2-\U0001f5c4\U0001f5d1-\U0001f5d3\U0001f5dc-\U0001f5de\U0001f5e1"
|
||||
"\U0001f5e3\U0001f5e8\U0001f5ef\U0001f5f3\U0001f5fa\U0001f5fb-\U0001f5ff"
|
||||
"\U0001f600\U0001f601-\U0001f610\U0001f611\U0001f612-\U0001f614\U0001f615"
|
||||
"\U0001f616\U0001f617\U0001f618\U0001f619\U0001f61a\U0001f61b\U0001f61c-"
|
||||
"\U0001f61e\U0001f61f\U0001f620-\U0001f625\U0001f626-\U0001f627\U0001f628-"
|
||||
"\U0001f62b\U0001f62c\U0001f62d\U0001f62e-\U0001f62f\U0001f630-\U0001f633"
|
||||
"\U0001f634\U0001f635-\U0001f640\U0001f641-\U0001f642\U0001f643-\U0001f644"
|
||||
"\U0001f645-\U0001f64f\U0001f680-\U0001f6c5\U0001f6cb-\U0001f6cf\U0001f6d0"
|
||||
"\U0001f6d1-\U0001f6d2\U0001f6e0-\U0001f6e5\U0001f6e9\U0001f6eb-\U0001f6ec"
|
||||
"\U0001f6f0\U0001f6f3\U0001f6f4-\U0001f6f6\U0001f6f7-\U0001f6f8\U0001f910-"
|
||||
"\U0001f918\U0001f919-\U0001f91e\U0001f91f\U0001f920-\U0001f927\U0001f928-"
|
||||
"\U0001f92f\U0001f930\U0001f931-\U0001f932\U0001f933-\U0001f93a\U0001f93c-"
|
||||
"\U0001f93e\U0001f940-\U0001f945\U0001f947-\U0001f94b\U0001f94c\U0001f950-"
|
||||
"\U0001f95e\U0001f95f-\U0001f96b\U0001f980-\U0001f984\U0001f985-\U0001f991"
|
||||
"\U0001f992-\U0001f997\U0001f9c0\U0001f9d0-\U0001f9e6]"
|
||||
)
|
||||
|
|
|
|||
|
|
@ -110,7 +110,7 @@
|
|||
|
||||
{% if suggested_facets %}
|
||||
<p class="suggested-facets">
|
||||
Suggested facets: {% for facet in suggested_facets %}<a href="{{ facet.toggle_url }}#facet-{{ facet.name|to_css_class }}">{{ facet.name }}</a>{% if not loop.last %}, {% endif %}{% endfor %}
|
||||
Suggested facets: {% for facet in suggested_facets %}<a href="{{ facet.toggle_url }}#facet-{{ facet.name|to_css_class }}">{{ facet.name }}</a>{% if facet.type %} ({{ facet.type }}){% endif %}{% if not loop.last %}, {% endif %}{% endfor %}
|
||||
</p>
|
||||
{% endif %}
|
||||
|
||||
|
|
|
|||
|
|
@ -363,7 +363,9 @@ class BaseView(RenderMixin):
|
|||
SQL query took too long. The time limit is controlled by the
|
||||
<a href="https://datasette.readthedocs.io/en/stable/config.html#sql-time-limit-ms">sql_time_limit_ms</a>
|
||||
configuration option.
|
||||
""", title="SQL Interrupted", status=400, messagge_is_html=True)
|
||||
|
||||
{}
|
||||
""".format(e), title="SQL Interrupted", status=400, messagge_is_html=True)
|
||||
except (sqlite3.OperationalError, InvalidSql) as e:
|
||||
raise DatasetteError(str(e), title="Invalid SQL", status=400)
|
||||
|
||||
|
|
|
|||
|
|
@ -5,6 +5,7 @@ import jinja2
|
|||
from sanic.exceptions import NotFound
|
||||
from sanic.request import RequestParameters
|
||||
|
||||
from datasette.facets import load_facet_configs
|
||||
from datasette.plugins import pm
|
||||
from datasette.utils import (
|
||||
CustomRow,
|
||||
|
|
@ -479,15 +480,12 @@ class TableView(RowTableShared):
|
|||
)
|
||||
|
||||
# facets support
|
||||
# pylint: disable=no-member
|
||||
metadata_facets = table_metadata.get("facets", [])
|
||||
facets = metadata_facets[:]
|
||||
if request.args.get("_facet") and not self.ds.config("allow_facet"):
|
||||
if not self.ds.config("allow_facet") and any(arg.startswith("_facet") for arg in request.args):
|
||||
raise DatasetteError("_facet= is not allowed", status=400)
|
||||
try:
|
||||
facets.extend(request.args["_facet"])
|
||||
except KeyError:
|
||||
pass
|
||||
facet_configs = load_facet_configs(request, table_metadata)
|
||||
print("facet_configs", facet_configs)
|
||||
|
||||
# pylint: disable=no-member
|
||||
facet_classes = list(
|
||||
itertools.chain.from_iterable(pm.hook.register_facet_classes())
|
||||
)
|
||||
|
|
@ -495,7 +493,7 @@ class TableView(RowTableShared):
|
|||
facets_timed_out = []
|
||||
facet_instances = []
|
||||
for klass in facet_classes:
|
||||
facet_instances.append(klass(self.ds, request, database, table, configs=facets))
|
||||
facet_instances.append(klass(self.ds, request, database, table, configs=facet_configs.get(klass.type)))
|
||||
|
||||
for facet in facet_instances:
|
||||
instance_facet_results, instance_facets_timed_out = await facet.facet_results(
|
||||
|
|
@ -504,6 +502,7 @@ class TableView(RowTableShared):
|
|||
facet_results.update(instance_facet_results)
|
||||
facets_timed_out.extend(instance_facets_timed_out)
|
||||
|
||||
# Figure out columns and rows for the query
|
||||
columns = [r[0] for r in results.description]
|
||||
rows = list(results.rows)
|
||||
|
||||
|
|
@ -653,7 +652,7 @@ class TableView(RowTableShared):
|
|||
),
|
||||
"extra_wheres_for_ui": extra_wheres_for_ui,
|
||||
"form_hidden_args": form_hidden_args,
|
||||
"facet_hideable": lambda facet: facet not in metadata_facets,
|
||||
"facet_hideable": lambda facet: facet not in [], # TODO: used to be metadata_facets fix this
|
||||
"is_sortable": any(c["sortable"] for c in display_columns),
|
||||
"path_with_replaced_args": path_with_replaced_args,
|
||||
"path_with_removed_args": path_with_removed_args,
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue