[fix] Re-cleanup legacy filters

superset/examples/birth_names.py

@@ -126,7 +126,6 @@ def load_birth_names(only_metadata=False, force=False):
         "since": "100 years ago",
         "until": "now",
         "viz_type": "table",
-        "where": "",
         "markup_type": "markdown",
     }
 

superset/examples/country_map.py

@@ -90,7 +90,6 @@ def load_country_map_data(only_metadata=False, force=False):
         "granularity_sqla": "",
         "since": "",
         "until": "",
-        "where": "",
         "viz_type": "country_map",
         "entity": "DEPT_ID",
         "metric": {

superset/examples/deck.py

@@ -173,10 +173,8 @@ def load_deck_dash():
         "spatial": {"type": "latlong", "lonCol": "LON", "latCol": "LAT"},
         "color_picker": COLOR_RED,
         "datasource": "5__table",
-        "filters": [],
         "granularity_sqla": None,
         "groupby": [],
-        "having": "",
         "mapbox_style": "mapbox://styles/mapbox/light-v9",
         "multiplier": 10,
         "point_radius_fixed": {"type": "metric", "value": "count"},
@@ -195,7 +193,6 @@ def load_deck_dash():
             "zoom": 12.729132798697304,
         },
         "viz_type": "deck_scatter",
-        "where": "",
     }
 
     print("Creating Scatterplot slice")
@@ -211,7 +208,6 @@ def load_deck_dash():
 
     slice_data = {
         "point_unit": "square_m",
-        "filters": [],
         "row_limit": 5000,
         "spatial": {"type": "latlong", "lonCol": "LON", "latCol": "LAT"},
         "mapbox_style": "mapbox://styles/mapbox/dark-v9",
@@ -222,8 +218,6 @@ def load_deck_dash():
         "point_radius": "Auto",
         "color_picker": {"a": 1, "r": 14, "b": 0, "g": 255},
         "grid_size": 20,
-        "where": "",
-        "having": "",
         "viewport": {
             "zoom": 14.161641703941438,
             "longitude": -122.41827069521386,
@@ -249,7 +243,6 @@ def load_deck_dash():
 
     slice_data = {
         "spatial": {"type": "latlong", "lonCol": "LON", "latCol": "LAT"},
-        "filters": [],
         "row_limit": 5000,
         "mapbox_style": "mapbox://styles/mapbox/streets-v9",
         "granularity_sqla": None,
@@ -261,15 +254,13 @@ def load_deck_dash():
         "color_picker": {"a": 1, "r": 14, "b": 0, "g": 255},
         "grid_size": 40,
         "extruded": True,
-        "having": "",
         "viewport": {
             "latitude": 37.789795085160335,
             "pitch": 54.08961642447763,
             "zoom": 13.835465702403654,
             "longitude": -122.40632230075536,
             "bearing": -2.3984797349335167,
         },
-        "where": "",
         "point_radius_fixed": {"type": "fix", "value": 2000},
         "datasource": "5__table",
         "time_grain_sqla": None,
@@ -288,7 +279,6 @@ def load_deck_dash():
 
     slice_data = {
         "spatial": {"type": "latlong", "lonCol": "LON", "latCol": "LAT"},
-        "filters": [],
         "row_limit": 5000,
         "mapbox_style": "mapbox://styles/mapbox/satellite-streets-v9",
         "granularity_sqla": None,
@@ -300,15 +290,13 @@ def load_deck_dash():
         "color_picker": {"a": 1, "r": 14, "b": 0, "g": 255},
         "grid_size": 120,
         "extruded": True,
-        "having": "",
         "viewport": {
             "longitude": -122.42066918995666,
             "bearing": 155.80099696026355,
             "zoom": 12.699690845482069,
             "latitude": 37.7942314882596,
             "pitch": 53.470800300695146,
         },
-        "where": "",
         "point_radius_fixed": {"type": "fix", "value": 2000},
         "datasource": "5__table",
         "time_grain_sqla": None,
@@ -403,9 +391,6 @@ def load_deck_dash():
         "js_onclick_href": "",
         "legend_format": ".1s",
         "legend_position": "tr",
-        "where": "",
-        "having": "",
-        "filters": [],
     }
 
     print("Creating Polygon slice")
@@ -456,9 +441,6 @@ def load_deck_dash():
         },
         "color_picker": {"r": 0, "g": 122, "b": 135, "a": 1},
         "stroke_width": 1,
-        "where": "",
-        "having": "",
-        "filters": [],
     }
 
     print("Creating Arc slice")
@@ -508,9 +490,6 @@ def load_deck_dash():
         "}));",
         "js_tooltip": "",
         "js_onclick_href": "",
-        "where": "",
-        "having": "",
-        "filters": [],
     }
 
     print("Creating Path slice")

superset/examples/energy.py

@@ -77,12 +77,10 @@ def load_energy(only_metadata=False, force=False):
                 "source",
                 "target"
             ],
-            "having": "",
             "metric": "sum__value",
             "row_limit": "5000",
             "slice_name": "Energy Sankey",
-            "viz_type": "sankey",
-            "where": ""
+            "viz_type": "sankey"
         }
         """
         ),
@@ -104,13 +102,11 @@ def load_energy(only_metadata=False, force=False):
                 "source",
                 "target"
             ],
-            "having": "",
             "link_length": "200",
             "metric": "sum__value",
             "row_limit": "5000",
             "slice_name": "Force",
-            "viz_type": "directed_force",
-            "where": ""
+            "viz_type": "directed_force"
         }
         """
         ),
@@ -130,13 +126,11 @@ def load_energy(only_metadata=False, force=False):
             "all_columns_y": "target",
             "canvas_image_rendering": "pixelated",
             "collapsed_fieldsets": "",
-            "having": "",
             "linear_color_scheme": "blue_white_yellow",
             "metric": "sum__value",
             "normalize_across": "heatmap",
             "slice_name": "Heatmap",
             "viz_type": "heatmap",
-            "where": "",
             "xscale_interval": "1",
             "yscale_interval": "1"
         }

superset/examples/long_lat.py

@@ -96,7 +96,6 @@ def load_long_lat_data(only_metadata=False, force=False):
         "granularity_sqla": "day",
         "since": "2014-01-01",
         "until": "now",
-        "where": "",
         "viz_type": "mapbox",
         "all_columns_x": "LON",
         "all_columns_y": "LAT",

superset/examples/multiformat_time_series.py

@@ -98,7 +98,6 @@ def load_multiformat_time_series(only_metadata=False, force=False):
             "row_limit": config["ROW_LIMIT"],
             "since": "2015",
             "until": "2016",
-            "where": "",
             "viz_type": "cal_heatmap",
             "domain_granularity": "month",
             "subdomain_granularity": "day",

superset/examples/random_time_series.py

@@ -62,7 +62,6 @@ def load_random_time_series_data(only_metadata=False, force=False):
         "since": "1 year ago",
         "until": "now",
         "metric": "count",
-        "where": "",
         "viz_type": "cal_heatmap",
         "domain_granularity": "month",
         "subdomain_granularity": "day",

superset/examples/unicode_test_data.py

@@ -90,7 +90,6 @@ def load_unicode_test_data(only_metadata=False, force=False):
         "row_limit": config["ROW_LIMIT"],
         "since": "100 years ago",
         "until": "now",
-        "where": "",
         "viz_type": "word_cloud",
         "size_from": "10",
         "series": "short_phrase",

superset/examples/world_bank.py

@@ -108,7 +108,6 @@ def load_world_bank_health_n_pop(only_metadata=False, force=False):
         "since": "2014-01-01",
         "until": "2014-01-02",
         "time_range": "2014-01-01 : 2014-01-02",
-        "where": "",
         "markup_type": "markdown",
         "country_fieldtype": "cca3",
         "secondary_metric": {
@@ -226,10 +225,12 @@ def load_world_bank_health_n_pop(only_metadata=False, force=False):
                 y="sum__SP_DYN_LE00_IN",
                 size="sum__SP_POP_TOTL",
                 max_bubble_size="50",
-                filters=[
+                adhoc_filters=[
                     {
-                        "col": "country_code",
-                        "val": [
+                        "clause": "WHERE",
+                        "expressionType": "SIMPLE",
+                        "filterOptionName": "2745eae5",
+                        "comparator": [
                             "TCA",
                             "MNP",
                             "DMA",
@@ -245,7 +246,8 @@ def load_world_bank_health_n_pop(only_metadata=False, force=False):
                             "AMA",
                             "PLW",
                         ],
-                        "op": "not in",
+                        "operator": "not in",
+                        "subject": "country_code",
                     }
                 ],
             ),

superset/migrations/versions/78ee127d0d1d_reconvert_legacy_filters_into_adhoc.py

@@ -0,0 +1,76 @@
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements.  See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership.  The ASF licenses this file
+# to you under the Apache License, Version 2.0 (the
+# "License"); you may not use this file except in compliance
+# with the License.  You may obtain a copy of the License at
+#
+#   http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing,
+# software distributed under the License is distributed on an
+# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+# KIND, either express or implied.  See the License for the
+# specific language governing permissions and limitations
+# under the License.
+"""reconvert legacy filters into adhoc
+
+Revision ID: 78ee127d0d1d
+Revises: c2acd2cf3df2
+Create Date: 2019-11-06 15:23:26.497876
+
+"""
+
+# revision identifiers, used by Alembic.
+revision = "78ee127d0d1d"
+down_revision = "c2acd2cf3df2"
+
+import copy
+import json
+import logging
+import uuid
+from collections import defaultdict
+
+from alembic import op
+from sqlalchemy import Column, Integer, Text
+from sqlalchemy.ext.declarative import declarative_base
+
+from superset import db
+from superset.utils.core import (
+    convert_legacy_filters_into_adhoc,
+    split_adhoc_filters_into_base_filters,
+)
+
+Base = declarative_base()
+
+
+class Slice(Base):
+    __tablename__ = "slices"
+
+    id = Column(Integer, primary_key=True)
+    params = Column(Text)
+
+
+def upgrade():
+    bind = op.get_bind()
+    session = db.Session(bind=bind)
+
+    for slc in session.query(Slice).all():
+        if slc.params:
+            try:
+                source = json.loads(slc.params)
+                target = copy.deepcopy(source)
+                convert_legacy_filters_into_adhoc(target)
+
+                if source != target:
+                    slc.params = json.dumps(target, sort_keys=True)
+            except Exception as ex:
+                logging.warn(ex)
+
+    session.commit()
+    session.close()
+
+
+def downgrade():
+    pass