Fix some linting warnings

mlserver/registry.py

@@ -230,7 +230,7 @@ async def _unload_model(self, model: MLModel):
             self._clear_default()
 
         model.ready = not await model.unload()
-        
+
         sys_tracer.tp_model_unload(model.name, model.version)
 
     def _find_model(self, version: Optional[str] = None) -> Optional[MLModel]:

mlserver/settings.py

@@ -140,7 +140,7 @@ class TracepointSettings(BaseSettings):
 
     configured_tracepoints: Optional[List[Tracepoint]] = Tracepoint.all()
     """
-    When tracing is enabled (via `enable_tracepoints`), this controls the 
+    When tracing is enabled (via `enable_tracepoints`), this controls the
     list of tracepoints exposed by MLServer
     """
 

mlserver/sys_tracing/provider.py

@@ -9,14 +9,14 @@
 functions) whenever application-specific events take place, such as starting to
 process an inference request, loading/unloading a model, etc:
 
-``` 
+```
 sys_trace = SystemTracingProvider()
-sys_trace.generate_native_sdt_tracepoints(settings.tracepoint_settings) 
-... 
+sys_trace.generate_native_sdt_tracepoints(settings.tracepoint_settings)
+...
 # A new model gets loaded
-ext_trace.tp_model_load_begin(...) 
-model.ready = await model.load() 
-ext_trace.tp_model_load_end(...) 
+sys_trace.tp_model_load_begin(...)
+model.ready = await model.load()
+sys_trace.tp_model_load_end(...)
 ```
 
 Sometimes, the arguments that we want to pass to a tracepoint are obtained by
@@ -25,18 +25,18 @@
 first call the `is_active` member function, which only returns true if the
 passed tracepoint has an external probe attached:
 
-``` 
+```
 if sys_trace.is_active(Tracepoint.inference_begin):
-    # compute arguments 
+    # compute arguments
     pipeline = parse_headers(...)
 
-    # fire tracepoint 
+    # fire tracepoint
     sys_trace.tp_inference_begin(..., pipeline, ...)
 ```
 
 Each tp_* function calls into a native shared library that is generated on the
 fly and dynamically loaded inside the process when calling
-`ext_trace.generate_native_sdt_tracepoints(...)`. In the shared library, a
+`sys_trace.generate_native_sdt_tracepoints(...)`. In the shared library, a
 tracepoint is just a hook function (a series of nop instructions followed by a
 ret). The code of this hook can be modified at runtime to jump into code
 provided from outside the process (e.g. SystemTap or BPF probes running in
@@ -95,7 +95,7 @@ def create_native_sdt_tracepoints(self, tracepoint_settings: TracepointSettings)
                 # native ELF library containing the tracepoint functions to
                 # which external probes can be attached to.
                 import stapsdt
-            except:
+            except Exception:
                 logger.warning(
                     "Could not enable tracing. Ensure python-stapsdt and libstapsdt.so are installed"
                 )
@@ -110,7 +110,7 @@ def create_native_sdt_tracepoints(self, tracepoint_settings: TracepointSettings)
             # provider, while disabled ones remain as stubs
             for tp in self._configured_tracepoints:
                 arg_types, status = tp.get_arg_types()
-                if arg_types != None:
+                if arg_types is not None:
                     self._num_native_tracepoints += 1
                     self._tracepoint_definition[tp] = self._provider.add_probe(
                         tp.name, *arg_types

mlserver/system_tracing.py

@@ -1,4 +1,3 @@
-from .logging import logger
 from .settings import TracepointSettings
 from .sys_tracing import SystemTracingProvider
 

mlserver/types/tracepoints.py

@@ -1,6 +1,6 @@
 """
 A tracepoint is a statically defined marker placed in code to identify
-application-level events. 
+application-level events.
 
 From the perspective of the python application, each tracepoint acts like a
 normal function call. When a tracepoint is initialized by the tracing provider,
@@ -15,7 +15,7 @@
 `ArgTypeMap._prototypes`.
 
 The subset of tracepoints visible to external tracing users can be restricted in
-the MLServer settings, via the `tracepoint_settings.configured_tracepoints` 
+the MLServer settings, via the `tracepoint_settings.configured_tracepoints`
 option.
 
 See `system_tracing.provider` for more details about the actual tracepoint