feat: add bigframes.bigquery.json_value

bigframes/bigquery/__init__.py

@@ -38,6 +38,7 @@
     json_extract_array,
     json_extract_string_array,
     json_set,
+    json_value,
     parse_json,
 )
 from bigframes.bigquery._operations.search import create_vector_index, vector_search
@@ -61,6 +62,7 @@
     "json_extract",
     "json_extract_array",
     "json_extract_string_array",
+    "json_value",
     "parse_json",
     # search ops
     "create_vector_index",

bigframes/bigquery/_operations/json.py

@@ -231,6 +231,40 @@ def json_extract_string_array(
     return array_series
 
 
+def json_value(
+    input: series.Series,
+    json_path: str,
+) -> series.Series:
+    """Extracts a JSON scalar value and converts it to a SQL ``STRING`` value. In
+    addtion, this function:
+    - Removes the outermost quotes and unescapes the values.
+    - Returns a SQL ``NULL`` if a non-scalar value is selected.
+    - Uses double quotes to escape invalid ``JSON_PATH`` characters in JSON keys.
+
+    **Examples:**
+
+        >>> import bigframes.pandas as bpd
+        >>> import bigframes.bigquery as bbq
+        >>> bpd.options.display.progress_bar = None
+
+        >>> s = bpd.Series(['{"name": "Jakob", "age": "6"}', '{"name": "Jakob", "age": []}'])
+        >>> bbq.json_value(s, json_path="$.age")
+        0    6
+        1  <NA>
+        dtype: string
+
+    Args:
+        input (bigframes.series.Series):
+            The Series containing JSON data (as native JSON objects or JSON-formatted strings).
+        json_path (str):
+            The JSON path identifying the data that you want to obtain from the input.
+
+    Returns:
+        bigframes.series.Series: A new Series with the JSON-formatted STRING.
+    """
+    return input._apply_unary_op(ops.JSONValue(json_path=json_path))
+
+
 @utils.preview(name="The JSON-related API `parse_json`")
 def parse_json(
     input: series.Series,

tests/system/small/bigquery/test_json.py

@@ -212,6 +212,34 @@ def test_json_extract_string_array_w_invalid_series_type():
         bbq.json_extract_string_array(s)
 
 
+def test_json_value_from_json():
+    s = bpd.Series(
+        ['{"a": {"b": [1, 2]}}', '{"a": {"c": 1}}', '{"a": {"b": 0}}'],
+        dtype=dtypes.JSON_DTYPE,
+    )
+    actual = bbq.json_value(s, "$.a.b")
+    expected = bpd.Series([None, None, "0"], dtype=dtypes.STRING_DTYPE)
+
+    pd.testing.assert_series_equal(actual.to_pandas(), expected.to_pandas())
+
+
+def test_json_value_from_string():
+    s = bpd.Series(
+        ['{"a": {"b": [1, 2]}}', '{"a": {"c": 1}}', '{"a": {"b": 0}}'],
+        dtype=pd.StringDtype(storage="pyarrow"),
+    )
+    actual = bbq.json_value(s, "$.a.b")
+    expected = bpd.Series([None, None, "0"], dtype=dtypes.STRING_DTYPE)
+
+    pd.testing.assert_series_equal(actual.to_pandas(), expected.to_pandas())
+
+
+def test_json_value_w_invalid_series_type():
+    s = bpd.Series([1, 2])
+    with pytest.raises(TypeError):
+        bbq.json_value(s, "$.a")
+
+
 def test_parse_json_w_invalid_series_type():
     s = bpd.Series([1, 2])
     with pytest.raises(TypeError):