wip

crates/re_sdk_comms/src/buffered_client.rs

@@ -202,6 +202,10 @@ fn msg_encode(
                         re_log::error!("Failed to send message to tcp_sender thread. Likely a shutdown race-condition.");
                         return;
                     }
+                    // TODO: this is incorrect and dangerous: flush() can return before this
+                    // thread is done with its workload, which means the python process might be
+                    // dead before this thread is dead, which means we call a C callback that has
+                    // been dunload().
                     if msg_drop_tx.send(msg_msg).is_err() {
                         re_log::error!("Failed to send message to msg_drop thread. Likely a shutdown race-condition");
                         return;

examples/python/clock/main.py

@@ -59,9 +59,9 @@ def rotate(angle: float, len: float) -> Tuple[float, float, float]:
 
         scaled_h = (t_secs % 43200) / 43200.0
         point_h = np.array(rotate(math.tau * scaled_h, LENGTH_H))
-        color_h = (int(255 - (scaled_h * 255)), int(scaled_h * 255), 255, 255)
+        color_h = (int(255 - (scaled_h * 255)), int(scaled_h * 255), 255, 128)
         rr.log_point("world/hours_pt", position=point_h, color=color_h)
-        rr.log_arrow("world/hours_hand", origin=[0.0, 0.0, 0.0], vector=point_h, color=color_h, width_scale=WIDTH_M)
+        rr.log_arrow("world/hours_hand", origin=[0.0, 0.0, 0.0], vector=point_h, color=color_h, width_scale=WIDTH_H)
 
 
 if __name__ == "__main__":

examples/python/minimal/main.py

@@ -9,7 +9,7 @@
 _, unknown = __import__("argparse").ArgumentParser().parse_known_args()
 [__import__("logging").warning(f"unknown arg: {arg}") for arg in unknown]
 
-rr.spawn()
+rr.init("minimal", spawn=True)
 
 positions = np.vstack([xyz.ravel() for xyz in np.mgrid[3 * [slice(-5, 5, 10j)]]]).T
 colors = np.vstack([rgb.ravel() for rgb in np.mgrid[3 * [slice(0, 255, 10j)]]]).astype(np.uint8).T

examples/python/multiprocessing/main.py

@@ -14,6 +14,7 @@ def task(title: str) -> None:
     # All processes spawned with `multiprocessing` will automatically
     # be assigned the same default recording_id.
     # We just need to connect each process to the the rerun viewer:
+    rr.init("multiprocessing")
     rr.connect()
 
     rr.log_text_entry(

rerun_py/rerun_sdk/rerun/__init__.py

@@ -29,8 +29,6 @@
     "ClassDescription",
     "LoggingHandler",
     "bindings",
-    "components",
-    "inline_show",
     "ImageFormat",
     "log_annotation_context",
     "log_arrow",
@@ -58,7 +56,6 @@
     "log_text_entry",
     "log_unknown_transform",
     "log_view_coordinates",
-    "notebook",
     "LogLevel",
     "MeshFormat",
     "RectFormat",
@@ -109,29 +106,13 @@ def get_recording_id() -> str:
     return str(bindings.get_recording_id())
 
 
-def set_recording_id(value: str) -> None:
-    """
-    Set the recording ID that this process is logging to, as a UUIDv4.
-
-    The default recording_id is based on `multiprocessing.current_process().authkey`
-    which means that all processes spawned with `multiprocessing`
-    will have the same default recording_id.
-
-    If you are not using `multiprocessing` and still want several different Python
-    processes to log to the same Rerun instance (and be part of the same recording),
-    you will need to manually assign them all the same recording_id.
-    Any random UUIDv4 will work, or copy the recording id for the parent process.
-
-    Parameters
-    ----------
-    value : str
-        The recording ID to use for this process.
-
-    """
-    bindings.set_recording_id(value)
-
-
-def init(application_id: str, spawn: bool = False, default_enabled: bool = True, strict: bool = False) -> None:
+def init(
+    application_id: str,
+    recording_id: Optional[str] = None,
+    spawn: bool = False,
+    default_enabled: bool = True,
+    strict: bool = False,
+) -> None:
     """
     Initialize the Rerun SDK with a user-chosen application id (name).
 
@@ -144,6 +125,17 @@ def init(application_id: str, spawn: bool = False, default_enabled: bool = True,
         For example, if you have one application doing object detection
         and another doing camera calibration, you could have
         `rerun.init("object_detector")` and `rerun.init("calibrator")`.
+    recording_id : Optional[str]
+        Set the recording ID that this process is logging to, as a UUIDv4.
+
+        The default recording_id is based on `multiprocessing.current_process().authkey`
+        which means that all processes spawned with `multiprocessing`
+        will have the same default recording_id.
+
+        If you are not using `multiprocessing` and still want several different Python
+        processes to log to the same Rerun instance (and be part of the same recording),
+        you will need to manually assign them all the same recording_id.
+        Any random UUIDv4 will work, or copy the recording id for the parent process.
     spawn : bool
         Spawn a Rerun Viewer and stream logging data to it.
         Short for calling `spawn` separately.
@@ -189,6 +181,7 @@ def init(application_id: str, spawn: bool = False, default_enabled: bool = True,
 
     bindings.init(
         application_id=application_id,
+        recording_id=recording_id,
         application_path=application_path,
         default_enabled=default_enabled,
     )

rerun_py/src/lib.rs

@@ -15,4 +15,3 @@ static GLOBAL: AccountingAllocator<mimalloc::MiMalloc> =
 
 mod arrow;
 mod python_bridge;
-mod python_session;