Implement keywords filter for Tabulator (#3298)

holoviz · Apr 1, 2022 · d7a6b66 · d7a6b66
1 parent 070b0c4
commit d7a6b66
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diff --git a/panel/tests/widgets/test_tables.py b/panel/tests/widgets/test_tables.py
@@ -1327,6 +1327,47 @@ def test_tabulator_constant_list_filter_client_side(document, comm):
         np.testing.assert_array_equal(values, expected[col])
 
 
+def test_tabulator_keywords_filter_client_side(document, comm):
+    df = makeMixedDataFrame()
+    table = Tabulator(df)
+
+    model = table.get_root(document, comm)
+
+    table.filters = [{'field': 'C', 'type': 'keywords', 'value': 'foo3 foo5'}]
+
+    expected = {
+        'index': np.array([2, 4]),
+        'A': np.array([2, 4]),
+        'B': np.array([0, 0]),
+        'C': np.array(['foo3', 'foo5']),
+        'D': np.array(['2009-01-05T00:00:00.000000000',
+                       '2009-01-07T00:00:00.000000000'],
+                      dtype='datetime64[ns]').astype(np.int64) / 10e5
+    }
+    for col, values in model.source.data.items():
+        np.testing.assert_array_equal(values, expected[col])
+
+
+def test_tabulator_keywords_match_all_filter_client_side(document, comm):
+    df = makeMixedDataFrame()
+    table = Tabulator(df, header_filters={'C': {'type': 'input', 'func': 'keywords', 'matchAll': True}})
+
+    model = table.get_root(document, comm)
+
+    table.filters = [{'field': 'C', 'type': 'keywords', 'value': 'f oo 3'}]
+
+    expected = {
+        'index': np.array([2]),
+        'A': np.array([2]),
+        'B': np.array([0]),
+        'C': np.array(['foo3']),
+        'D': np.array(['2009-01-05T00:00:00.000000000'],
+                      dtype='datetime64[ns]').astype(np.int64) / 10e5
+    }
+    for col, values in model.source.data.items():
+        np.testing.assert_array_equal(values, expected[col])
+
+
 def test_tabulator_widget_scalar_filter(document, comm):
     df = makeMixedDataFrame()
     table = Tabulator(df)

diff --git a/panel/widgets/tables.py b/panel/widgets/tables.py
@@ -309,6 +309,7 @@ def _filter_dataframe(self, df):
             col_name = filt['field']
             op = filt['type']
             val = filt['value']
+            filt_def = getattr(self, 'header_filters', {}) or {}
             if col_name in df.columns:
                 col = df[col_name]
             elif col_name in self.indexes:
@@ -345,6 +346,18 @@ def _filter_dataframe(self, df):
                 filters.append(col.str.startsWith(val))
             elif op == 'ends':
                 filters.append(col.str.endsWith(val))
+            elif op == 'keywords':
+                match_all = filt_def.get(col_name, {}).get('matchAll', False)
+                sep = filt_def.get(col_name, {}).get('separator', ' ')
+                matches = val.lower().split(sep)
+                if match_all:
+                    for match in matches:
+                        filters.append(col.str.lower().str.contains(match))
+                else:
+                    filt = col.str.lower().str.contains(matches[0])
+                    for match in matches[1:]:
+                        filt |= col.str.lower().str.contains(match)
+                    filters.append(filt)
             elif op == 'regex':
                 raise ValueError("Regex filtering not supported.")
             else: