reduce docs

src/natsbridge.py

@@ -71,8 +71,9 @@ def _serialize_data(data: Any, payload_type: str) -> bytes:
     
     Args:
         data: Data to serialize (string for "text", JSON-serializable for "dictionary",
-              table-like for "table", binary for "image", "audio", "video", "binary")
-        payload_type: Target format: "text", "dictionary", "table", "image", "audio", "video", "binary"
+              table-like for "arrowtable"/"jsontable", binary for "image", "audio", "video", "binary")
+        payload_type: Target format: "text", "dictionary", "arrowtable", "jsontable",
+                      "image", "audio", "video", "binary"
     
     Returns:
         Binary representation of the serialized data
@@ -80,7 +81,8 @@ def _serialize_data(data: Any, payload_type: str) -> bytes:
     Raises:
         Error: If payload_type is not one of the supported types
         Error: If payload_type is "image", "audio", or "video" but data is not bytes
-        Error: If payload_type is "table" but data is not a pandas DataFrame or pyarrow Table
+        Error: If payload_type is "arrowtable" but data is not a pandas DataFrame or pyarrow Table
+        Error: If payload_type is "jsontable" but data is not a list of dicts
     """
     if payload_type == 'text':
         if isinstance(data, str):
@@ -90,9 +92,9 @@ def _serialize_data(data: Any, payload_type: str) -> bytes:
     elif payload_type == 'dictionary':
         json_str = json.dumps(data)
         return json_str.encode('utf-8')
-    elif payload_type == 'table':
+    elif payload_type == 'arrowtable':
         if not ARROW_AVAILABLE:
-            raise RuntimeError('pyarrow not available for table serialization')
+            raise RuntimeError('pyarrow not available for arrowtable serialization')
         
         import io
         buf = io.BytesIO()
@@ -110,7 +112,14 @@ def _serialize_data(data: Any, payload_type: str) -> bytes:
             sink.close()
             return buf.getvalue()
         else:
-            raise ValueError('Table data must be a pandas DataFrame or pyarrow Table')
+            raise ValueError('Arrow table data must be a pandas DataFrame or pyarrow Table')
+    elif payload_type == 'jsontable':
+        # Serialize list of dicts to JSON format
+        if isinstance(data, list) and all(isinstance(row, dict) for row in data):
+            json_str = json.dumps(data)
+            return json_str.encode('utf-8')
+        else:
+            raise ValueError('JSON table data must be a list of dicts')
     elif payload_type == 'image':
         if isinstance(data, (bytes, bytearray)):
             return bytes(data)
@@ -141,12 +150,13 @@ def _deserialize_data(data: bytes, payload_type: str, correlation_id: str) -> An
     
     Args:
         data: Serialized data as bytes
-        payload_type: Data type ("text", "dictionary", "table", "image", "audio", "video", "binary")
+        payload_type: Data type ("text", "dictionary", "arrowtable", "jsontable",
+                      "image", "audio", "video", "binary")
         correlation_id: Correlation ID for logging
     
     Returns:
-        Deserialized data (String for "text", DataFrame for "table", JSON data for "dictionary",
-        bytes for "image", "audio", "video", "binary")
+        Deserialized data (String for "text", DataFrame for "arrowtable",
+        Vector{Dict} for "jsontable"/"dictionary", bytes for "image", "audio", "video", "binary")
     
     Raises:
         Error: If payload_type is not one of the supported types
@@ -156,14 +166,18 @@ def _deserialize_data(data: bytes, payload_type: str, correlation_id: str) -> An
     elif payload_type == 'dictionary':
         json_str = data.decode('utf-8')
         return json.loads(json_str)
-    elif payload_type == 'table':
+    elif payload_type == 'arrowtable':
         if not ARROW_AVAILABLE:
-            raise RuntimeError('pyarrow not available for table deserialization')
+            raise RuntimeError('pyarrow not available for arrowtable deserialization')
         
         import io
         buf = io.BytesIO(data)
         reader = ipc.open_file(buf)
         return reader.read_all().to_pandas()
+    elif payload_type == 'jsontable':
+        # Deserialize JSON to list of dicts
+        json_str = data.decode('utf-8')
+        return json.loads(json_str)
     elif payload_type == 'image':
         return data
     elif payload_type == 'audio':
@@ -317,7 +331,7 @@ class NATSClient:
             self._client = nats.connect(self.url)
             await self._client
         else:
-            raise Error('nats-py not available')
+            raise RuntimeError('nats-py not available')
         return self._client
     
     async def publish(self, subject: str, message: str, correlation_id: str = "") -> None:
@@ -397,12 +411,19 @@ def _build_payload(
     Returns:
         Payload object
     """
+    # Determine encoding based on payload type (matching Julia/JS implementation)
+    encoding = 'base64'
+    if payload_type == 'jsontable':
+        encoding = 'json'
+    elif payload_type == 'arrowtable':
+        encoding = 'arrow-ipc'
+    
     return {
         'id': str(uuid.uuid4()),
         'dataname': dataname,
         'payload_type': payload_type,
         'transport': transport,
-        'encoding': 'base64' if transport == 'direct' else 'none',
+        'encoding': encoding,
         'size': len(payload_bytes),
         'data': data,
         'metadata': {'payload_bytes': len(payload_bytes)} if transport == 'direct' else {}
@@ -476,7 +497,7 @@ async def smartsend(
         data: List of (dataname, data, type) tuples to send
             - dataname: Name of the payload
             - data: The actual data to send
-            - type: Payload type: "text", "dictionary", "table", "image", "audio", "video", "binary"
+            - type: Payload type: "text", "dictionary", "arrowtable", "jsontable", "image", "audio", "video", "binary"
         broker_url: URL of the NATS server
         fileserver_url: URL of the HTTP file server for large payloads
         fileserver_upload_handler: Function to handle fileserver uploads (must return Dict with "status",
@@ -514,14 +535,21 @@ async def smartsend(
         >>> data2 = [1, 2, 3, 4, 5]
         >>> env, env_json_str = await smartsend(
         ...     "my.subject",
-        ...     [("dataname1", data1, "dictionary"), ("dataname2", data2, "table")]
+        ...     [("dataname1", data1, "dictionary"), ("dataname2", data2, "arrowtable")]
         ... )
         >>>
         >>> # Send a large array using fileserver upload
         >>> data = list(range(10_000_000))  # ~80 MB
         >>> env, env_json_str = await smartsend(
         ...     "large.data",
-        ...     [("large_table", data, "table")]
+        ...     [("large_table", data, "arrowtable")]
+        ... )
+        >>>
+        >>> # Send jsontable (JSON format for human-readable tabular data)
+        >>> users = [{"id": 1, "name": "Alice"}, {"id": 2, "name": "Bob"}]
+        >>> env, env_json_str = await smartsend(
+        ...     "json.data",
+        ...     [("users", users, "jsontable")]
         ... )
         >>>
         >>> # Mixed content (e.g., chat with text and image)