Merge branch 'master' into master

Makefile

@@ -34,7 +34,7 @@ clean:
 
 clean-all: clean
 	docker image rm --force \
-		redash/redash:10.1.0.b50633 redis:7-alpine maildev/maildev:latest \
+		redash/redash:latest redis:7-alpine maildev/maildev:latest \
 		pgautoupgrade/pgautoupgrade:15-alpine3.8 pgautoupgrade/pgautoupgrade:latest
 
 down:

client/app/pages/queries/hooks/useAutocompleteFlags.js

@@ -1,16 +1,11 @@
 import { useCallback, useMemo, useState } from "react";
-import { reduce } from "lodash";
 import localOptions from "@/lib/localOptions";
 
-function calculateTokensCount(schema) {
-  return reduce(schema, (totalLength, table) => totalLength + table.columns.length, 0);
-}
-
 export default function useAutocompleteFlags(schema) {
-  const isAvailable = useMemo(() => calculateTokensCount(schema) <= 5000, [schema]);
+  const isAvailable = true;
   const [isEnabled, setIsEnabled] = useState(localOptions.get("liveAutocomplete", true));
 
-  const toggleAutocomplete = useCallback(state => {
+  const toggleAutocomplete = useCallback((state) => {
     setIsEnabled(state);
     localOptions.set("liveAutocomplete", state);
   }, []);

pyproject.toml

@@ -88,6 +88,7 @@ tzlocal = "4.3.1"
 pyodbc = "5.1.0"
 debugpy = "^1.8.9"
 paramiko = "3.4.1"
+oracledb = "2.5.1"
 
 [tool.poetry.group.all_ds]
 optional = true
@@ -113,7 +114,6 @@ nzalchemy = "^11.0.2"
 nzpy = ">=1.15"
 oauth2client = "4.1.3"
 openpyxl = "3.0.7"
-oracledb = "2.1.2"
 pandas = "1.3.4"
 phoenixdb = "0.7"
 pinotdb = ">=0.4.5"

redash/models/__init__.py

@@ -908,6 +908,7 @@ def next_state(op, value, threshold):
         # boolean value is Python specific and most likely will be confusing to
         # users.
         value = str(value).lower()
+        value_is_number = False
     else:
         try:
             value = float(value)

redash/utils/__init__.py

@@ -6,6 +6,7 @@
 import hashlib
 import io
 import json
+import math
 import os
 import random
 import re
@@ -120,6 +121,17 @@ def json_loads(data, *args, **kwargs):
     return json.loads(data, *args, **kwargs)
 
 
+# Convert NaN, Inf, and -Inf to None, as they are not valid JSON values.
+def _sanitize_data(data):
+    if isinstance(data, dict):
+        return {k: _sanitize_data(v) for k, v in data.items()}
+    if isinstance(data, list):
+        return [_sanitize_data(v) for v in data]
+    if isinstance(data, float) and (math.isnan(data) or math.isinf(data)):
+        return None
+    return data
+
+
 def json_dumps(data, *args, **kwargs):
     """A custom JSON dumping function which passes all parameters to the
     json.dumps function."""
@@ -128,7 +140,7 @@ def json_dumps(data, *args, **kwargs):
     # Float value nan or inf in Python should be render to None or null in json.
     # Using allow_nan = True will make Python render nan as NaN, leading to parse error in front-end
     kwargs.setdefault("allow_nan", False)
-    return json.dumps(data, *args, **kwargs)
+    return json.dumps(_sanitize_data(data), *args, **kwargs)
 
 
 def mustache_render(template, context=None, **kwargs):

redash/utils/query_order.py

@@ -33,7 +33,7 @@
 from sqlalchemy.orm.properties import ColumnProperty
 from sqlalchemy.orm.query import _ColumnEntity
 from sqlalchemy.orm.util import AliasedInsp
-from sqlalchemy.sql.expression import asc, desc
+from sqlalchemy.sql.expression import asc, desc, nullslast
 
 
 def get_query_descriptor(query, entity, attr):
@@ -225,7 +225,7 @@ def __init__(self, silent=True, separator="-"):
     def assign_order_by(self, entity, attr, func):
         expr = get_query_descriptor(self.query, entity, attr)
         if expr is not None:
-            return self.query.order_by(func(expr))
+            return self.query.order_by(nullslast(func(expr)))
         if not self.silent:
             raise QuerySorterException("Could not sort query with expression '%s'" % attr)
         return self.query

tests/utils/test_json_dumps.py

@@ -0,0 +1,31 @@
+from redash.utils import json_dumps, json_loads
+from tests import BaseTestCase
+
+
+class TestJsonDumps(BaseTestCase):
+    """
+    NaN, Inf, and -Inf are sanitized to None.
+    """
+
+    def test_data_with_nan_is_sanitized(self):
+        input_data = {
+            "columns": [
+                {"name": "_col0", "friendly_name": "_col0", "type": "float"},
+                {"name": "_col1", "friendly_name": "_col1", "type": "float"},
+                {"name": "_col2", "friendly_name": "_col1", "type": "float"},
+                {"name": "_col3", "friendly_name": "_col1", "type": "float"},
+            ],
+            "rows": [{"_col0": 1.0, "_col1": float("nan"), "_col2": float("inf"), "_col3": float("-inf")}],
+        }
+        expected_output_data = {
+            "columns": [
+                {"name": "_col0", "friendly_name": "_col0", "type": "float"},
+                {"name": "_col1", "friendly_name": "_col1", "type": "float"},
+                {"name": "_col2", "friendly_name": "_col1", "type": "float"},
+                {"name": "_col3", "friendly_name": "_col1", "type": "float"},
+            ],
+            "rows": [{"_col0": 1.0, "_col1": None, "_col2": None, "_col3": None}],
+        }
+        json_data = json_dumps(input_data)
+        actual_output_data = json_loads(json_data)
+        self.assertEquals(actual_output_data, expected_output_data)

viz-lib/src/visualizations/chart/plotly/prepareDefaultData.ts

@@ -99,36 +99,29 @@ function prepareSeries(series: any, options: any, numSeries: any, additionalOpti
       };
 
   const sourceData = new Map();
-
-  const labelsValuesMap = new Map();
+  const xValues: any[] = [];
+  const yValues: any[] = [];
 
   const yErrorValues: any = [];
   each(data, row => {
     const x = normalizeValue(row.x, options.xAxis.type); // number/datetime/category
     const y = cleanYValue(row.y, seriesYAxis === "y2" ? options.yAxis[1].type : options.yAxis[0].type); // depends on series type!
     const yError = cleanNumber(row.yError); // always number
     const size = cleanNumber(row.size); // always number
-    if (labelsValuesMap.has(x)) {
-      labelsValuesMap.set(x, labelsValuesMap.get(x) + y);
-    } else {
-      labelsValuesMap.set(x, y);
-    }
-    const aggregatedY = labelsValuesMap.get(x);
 
     sourceData.set(x, {
       x,
-      y: aggregatedY,
+      y,
       yError,
       size,
       yPercent: null, // will be updated later
       row,
     });
+    xValues.push(x);
+    yValues.push(y);
     yErrorValues.push(yError);
   });
 
-  const xValues = Array.from(labelsValuesMap.keys());
-  const yValues = Array.from(labelsValuesMap.values());
-
   const plotlySeries = {
     visible: true,
     hoverinfo: hoverInfoPattern,