Revised error codes and functional PlaybackEngine

All internal and public errors have been revised (GPT 5.6 Sol) to return
more detail without horrendously long error classes, this has reduced
the number of error types but each now carries a reason and a code for
differentiation if needed

PlaybackEngine has been implemented and is functional, core mode changes
what signal descriptors are returned to avoid duplicates, the playback
engine currently discards the derived signals that would be recorded in
the DLPak and derived signals are reprocessed live

Future will require the behavior listed above to be selectable so one of
two options are possible:
A - Derived signals are reprocessed live by the relevant derive units
(current behavior
B - Derived signals are played back directly from the PlaybackEngine,
this requires turning off the routing to the live derive units to avoid
duplicate values

This will also require the option to perform offline processing with
derive units to be able to create derived signals after the fact, this
will likely incur a new 'offline' mode in the core to gate things
correctly, this will likely be useful for heavier processing that cannot
be done live, filters that require a lookahead, or more precise derived
signals using interpolated signals for higher acurracy which also brings
the ability to offline process on a fixed timebase instead of following
either input signal to the derived signal

test/manual/peer.py

@@ -3,6 +3,7 @@ import logging
 import threading
 from concurrent.futures import CancelledError as FutureCancelledError
 from concurrent.futures import TimeoutError as FutureTimeoutError
+from math import sin, tau
 from statistics import mean
 from time import monotonic, monotonic_ns, perf_counter
 from uuid import UUID, uuid4
@@ -27,6 +28,7 @@ PORT = 8765
 # Set to None to send as quickly as possible.
 # For a controlled rate, use something like 5_000.0.
 TARGET_FREQUENCY_HZ: float | None = 1000
+SINE_FREQUENCY_HZ = 0.5
 
 FREQUENCY_SAMPLE_SIZE = 20000
 
@@ -88,6 +90,7 @@ def value_sender_thread(
     """
     intervals: list[float] = []
     previous_send_time: float | None = None
+    sine_start_time = perf_counter()
 
     if TARGET_FREQUENCY_HZ is not None:
         period = 1.0 / TARGET_FREQUENCY_HZ
@@ -117,16 +120,20 @@ def value_sender_thread(
 
                 next_send_time += period
 
+            sine_value = sin(
+                tau * SINE_FREQUENCY_HZ * (perf_counter() - sine_start_time)
+            )
+            timestamp = monotonic_ns()
             message = ValueBatch(values=[])
             value1 = ValueDescriptor(
                 signal_id=signal_id_1,
-                value=2.0,
-                timestamp=monotonic_ns(),
+                value=2.0 * sine_value,
+                timestamp=timestamp,
             )
             value2 = ValueDescriptor(
                 signal_id=signal_id_2,
-                value=1.0,
-                timestamp=monotonic_ns(),
+                value=sine_value,
+                timestamp=timestamp,
             )
             message.values.append(value1)
             message.values.append(value2)