docs of result set as primitive

README.md

@@ -119,12 +119,11 @@ Session Pool comes with the following assumptions:
 
 For more details, see [SessionPoolExample.py](example/SessionPoolExample.py).
 
-## Example: Server-Side evaluated parameters
+## Example: Server-Side Evaluated Parameters
 
-To enable parameterize the query, see this example:
-
-> Note not all tokes of a query could be paramterized, you could verify it with iPython quickly.
+To enable parameterization of the query, refer to the following example:
 
+> Note: Not all tokens of a query can be parameterized. You can quickly verify which ones can be with iPython.
 ```python
 params = {
     "p1": 3,
@@ -145,6 +144,9 @@ resp = client.execute_parameter(
 )
 ```
 
+For further information, consult [Params.py](example/Params.py).
+
+
 ## Example: Extracting Edge and Vertex Lists from Query Results
 
 For graph visualization purposes, the following code snippet demonstrates how to effortlessly extract lists of edges and vertices from any query result by utilizing the `ResultSet.dict_for_vis()` method.
@@ -232,6 +234,23 @@ The dict/JSON structure with `dict_for_vis()` is as follows:
 
 </details>
 
+## Example: Retrieve Primitive Typed Results
+
+The executed result is typed as `ResultSet`, and you can inspect its structure using `dir()`.
+
+For each data cell in the `ResultSet`, you can use `.cast()` to retrieve raw wrapped data (with sugar) such as a Vertex (Node), Edge (Relationship), Path, Value (Int, Float, etc.). Alternatively, you can use `.cast_primitive()` to obtain values in primitive types like dict, int, or float, depending on your needs.
+
+For more details, refer to [FromResp.py](example/FromResp.py).
+
+Additionally, `ResultSet.as_primitive()` provides a convenient method to convert the result set into a list of dictionaries (similar to JSONL format) containing primitive values for each row.
+
+```python
+result = session.execute('<your query>')
+
+result_dict = result.as_primitive()
+print(result_dict)
+```
+
 ## Example: Fetching Query Results into a Pandas DataFrame
 
 > For `nebula3-python>=3.6.0`:

nebula3/gclient/net/Connection.py

@@ -245,7 +245,7 @@ def _build_byte_param(params: dict) -> dict:
         for k, v in params.items():
             if isinstance(v, Value):
                 byte_params[k] = v
-            elif type(v).startswith("nebula3.common.ttypes"):
+            elif str(type(v)).startswith("nebula3.common.ttypes"):
                 byte_params[k] = v
             elif isinstance(v, list):
                 byte_list = []