diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
new file mode 100644
index 0000000..0503989
--- /dev/null
+++ b/.pre-commit-config.yaml
@@ -0,0 +1,16 @@
+# See https://pre-commit.com for more information
+# See https://pre-commit.com/hooks.html for more hooks
+repos:
+-   repo: https://github.com/charliermarsh/ruff-pre-commit
+    rev: 'v0.0.267'
+    hooks:
+    -   id: ruff
+        args: [ --fix, --exit-non-zero-on-fix ]
+-   repo: https://github.com/pre-commit/pre-commit-hooks
+    rev: v3.2.0
+    hooks:
+    -   id: trailing-whitespace
+    -   id: end-of-file-fixer
+    -   id: check-ast
+    -   id: check-yaml
+    -   id: check-added-large-files
diff --git a/.vscode/settings.json b/.vscode/settings.json
new file mode 100644
index 0000000..cee7b74
--- /dev/null
+++ b/.vscode/settings.json
@@ -0,0 +1,6 @@
+{
+    "[python]": {
+        "editor.defaultFormatter": "ms-python.black-formatter"
+    },
+    "python.formatting.provider": "none"
+}
diff --git a/deepview_profile/__main__.py b/deepview_profile/__main__.py
index 8b6e4e1..a3e2c3d 100644
--- a/deepview_profile/__main__.py
+++ b/deepview_profile/__main__.py
@@ -1,5 +1,4 @@
 import argparse
-import enum
 import sys
 
 import deepview_profile
diff --git a/deepview_profile/analysis/request_manager.py b/deepview_profile/analysis/request_manager.py
index dc8b16f..951a2a9 100644
--- a/deepview_profile/analysis/request_manager.py
+++ b/deepview_profile/analysis/request_manager.py
@@ -4,7 +4,6 @@
 from concurrent.futures import ThreadPoolExecutor
 
 from deepview_profile.analysis.runner import analyze_project
-from deepview_profile.config import Config
 from deepview_profile.exceptions import AnalysisError
 from deepview_profile.nvml import NVML
 import deepview_profile.protocol_gen.innpv_pb2 as pm
@@ -135,7 +134,7 @@ def _handle_analysis_request(self, analysis_request, context):
         except AnalysisError as ex:
             self._enqueue_response(self._send_analysis_error, ex, context)
 
-        except:
+        except Exception:
             logger.exception(
                 'Exception occurred when handling analysis request.')
             self._enqueue_response(
@@ -164,7 +163,7 @@ def _send_breakdown_response(self, breakdown, context):
         # Called from the main executor. Do not call directly!
         try:
             self._message_sender.send_breakdown_response(breakdown, context)
-        except:
+        except Exception:
             logger.exception(
                 'Exception occurred when sending a breakdown response.')
 
@@ -172,7 +171,7 @@ def _send_analysis_error(self, exception, context):
         # Called from the main executor. Do not call directly!
         try:
             self._message_sender.send_analysis_error(exception, context)
-        except:
+        except Exception:
             logger.exception(
                 'Exception occurred when sending an analysis error.')
 
@@ -180,7 +179,7 @@ def _send_throughput_response(self, throughput, context):
         # Called from the main executor. Do not call directly!
         try:
             self._message_sender.send_throughput_response(throughput, context)
-        except:
+        except Exception:
             logger.exception(
                 'Exception occurred when sending a throughput response.')
 
@@ -188,7 +187,7 @@ def _send_habitat_response(self, habitat_resp, context):
         # Called from the main executor. Do not call directly!
         try:
             self._message_sender.send_habitat_response(habitat_resp, context)
-        except:
+        except Exception:
             logger.exception(
                 'Exception occurred when sending a DeepView.Predict response.')
 
@@ -196,6 +195,6 @@ def _send_energy_response(self, energy_resp, context):
         # Called from the main executor. Do not call directly!
         try:
             self._message_sender.send_energy_response(energy_resp, context)
-        except:
+        except Exception:
             logger.exception(
-                'Exception occurred when sending an energy response.')
\ No newline at end of file
+                'Exception occurred when sending an energy response.')
diff --git a/deepview_profile/analysis/session.py b/deepview_profile/analysis/session.py
index 3e92150..2526cc4 100644
--- a/deepview_profile/analysis/session.py
+++ b/deepview_profile/analysis/session.py
@@ -43,10 +43,11 @@
 
 # Habitat variables
 Context = collections.namedtuple(
-    'Context',
-    ['origin_device', 'profiler', 'percentile'],
+    "Context",
+    ["origin_device", "profiler", "percentile"],
 )
 
+
 class AnalysisSession:
     def __init__(
         self,
@@ -57,7 +58,7 @@ def __init__(
         input_provider,
         iteration_provider,
         batch_size,
-        entry_point_static_analyzer
+        entry_point_static_analyzer,
     ):
         self._project_root = project_root
         self._entry_point = entry_point
@@ -71,7 +72,9 @@ def __init__(
         self._memory_usage_percentage = None
         self._batch_size_iteration_run_time_ms = None
         self._batch_size_peak_usage_bytes = None
-        self._energy_table_interface = EnergyTableInterface(DatabaseInterface().connection)
+        self._energy_table_interface = EnergyTableInterface(
+            DatabaseInterface().connection
+        )
 
     @classmethod
     def new_from(cls, project_root, entry_point):
@@ -92,21 +95,21 @@ def new_from(cls, project_root, entry_point):
             raise AnalysisError(
                 "The project entry point file is missing a model provider "
                 "function. Please add a model provider function named "
-                "\"{}\".".format(MODEL_PROVIDER_NAME)
+                '"{}".'.format(MODEL_PROVIDER_NAME)
             ).with_file_context(entry_point)
 
         if INPUT_PROVIDER_NAME not in scope:
             raise AnalysisError(
                 "The project entry point file is missing an input provider "
                 "function. Please add an input provider function named "
-                "\"{}\".".format(INPUT_PROVIDER_NAME)
+                '"{}".'.format(INPUT_PROVIDER_NAME)
             ).with_file_context(entry_point)
 
         if ITERATION_PROVIDER_NAME not in scope:
             raise AnalysisError(
                 "The project entry point file is missing an iteration "
                 "provider function. Please add an iteration provider function "
-                "named \"{}\".".format(ITERATION_PROVIDER_NAME)
+                'named "{}".'.format(ITERATION_PROVIDER_NAME)
             ).with_file_context(entry_point)
 
         batch_size = _validate_providers_signatures(
@@ -116,13 +119,15 @@ def new_from(cls, project_root, entry_point):
             entry_point,
         )
 
-        model_provider, input_provider, iteration_provider = (
-            _wrap_providers_with_validators(
-                scope[MODEL_PROVIDER_NAME],
-                scope[INPUT_PROVIDER_NAME],
-                scope[ITERATION_PROVIDER_NAME],
-                entry_point,
-            )
+        (
+            model_provider,
+            input_provider,
+            iteration_provider,
+        ) = _wrap_providers_with_validators(
+            scope[MODEL_PROVIDER_NAME],
+            scope[INPUT_PROVIDER_NAME],
+            scope[ITERATION_PROVIDER_NAME],
+            entry_point,
         )
 
         return cls(
@@ -138,7 +143,7 @@ def new_from(cls, project_root, entry_point):
 
     def energy_compute(self) -> pm.EnergyResponse:
         energy_measurer = EnergyMeasurer()
-        
+
         model = self._model_provider()
         inputs = self._input_provider()
         iteration = self._iteration_provider(model)
@@ -150,7 +155,7 @@ def energy_compute(self) -> pm.EnergyResponse:
             for _ in range(iterations):
                 iteration(*inputs)
             energy_measurer.end_measurement()
-            resp.total_consumption = energy_measurer.total_energy()/float(iterations)
+            resp.total_consumption = energy_measurer.total_energy() / float(iterations)
             resp.batch_size = self._batch_size
 
             components = []
@@ -159,7 +164,9 @@ def energy_compute(self) -> pm.EnergyResponse:
             if energy_measurer.cpu_energy() is not None:
                 cpu_component = pm.EnergyConsumptionComponent()
                 cpu_component.component_type = pm.ENERGY_CPU_DRAM
-                cpu_component.consumption_joules = energy_measurer.cpu_energy()/float(iterations)
+                cpu_component.consumption_joules = energy_measurer.cpu_energy() / float(
+                    iterations
+                )
                 components.append(cpu_component)
                 components_joules.append(cpu_component.consumption_joules)
             else:
@@ -168,18 +175,24 @@ def energy_compute(self) -> pm.EnergyResponse:
                 cpu_component.consumption_joules = 0.0
                 components.append(cpu_component)
                 components_joules.append(cpu_component.consumption_joules)
-            
+
             gpu_component = pm.EnergyConsumptionComponent()
             gpu_component.component_type = pm.ENERGY_NVIDIA
-            gpu_component.consumption_joules = energy_measurer.gpu_energy()/float(iterations)
+            gpu_component.consumption_joules = energy_measurer.gpu_energy() / float(
+                iterations
+            )
             components.append(gpu_component)
             components_joules.append(gpu_component.consumption_joules)
-            
+
             resp.components.extend(components)
-        
+
             # get last 10 runs if they exist
             path_to_entry_point = os.path.join(self._project_root, self._entry_point)
-            past_runs = self._energy_table_interface.get_latest_n_entries_of_entry_point(10, path_to_entry_point)
+            past_runs = (
+                self._energy_table_interface.get_latest_n_entries_of_entry_point(
+                    10, path_to_entry_point
+                )
+            )
             resp.past_measurements.extend(_convert_to_energy_responses(past_runs))
 
             # add current run to database
@@ -190,13 +203,13 @@ def energy_compute(self) -> pm.EnergyResponse:
             message = str(ex)
             logger.error(message)
             resp.analysis_error.error_message = message
-        except:
+        except Exception:
             logger.error("There was an error obtaining energy measurements")
-            resp.analysis_error.error_message = "There was an error obtaining energy measurements"
+            resp.analysis_error.error_message = (
+                "There was an error obtaining energy measurements"
+            )
         finally:
             return resp
-            
-        
 
     def habitat_compute_threshold(self, runnable, context):
         tracker = habitat.OperationTracker(context.origin_device)
@@ -214,10 +227,9 @@ def habitat_compute_threshold(self, runnable, context):
 
         return np.percentile(run_times, context.percentile)
 
-
     def habitat_predict(self):
-        resp = pm.HabitatResponse() 
-        if not habitat_found: 
+        resp = pm.HabitatResponse()
+        if not habitat_found:
             logger.debug("Skipping deepview predictions, returning empty response.")
             return resp
 
@@ -234,27 +246,34 @@ def habitat_predict(self):
                 habitat.Device.RTX3090,
                 habitat.Device.A40,
                 habitat.Device.A4000,
-                habitat.Device.RTX4000
+                habitat.Device.RTX4000,
             ]
 
             # Detect source GPU
             pynvml.nvmlInit()
             if pynvml.nvmlDeviceGetCount() == 0:
-                raise Exception("NVML failed to find a GPU. PLease ensure that you have a NVIDIA GPU installed and that the drivers are functioning correctly.")
+                raise Exception("NVML failed to find a GPU. Please ensure that you \
+                have a NVIDIA GPU installed and that the drivers are functioning \
+                correctly.")
 
             # TODO: Consider profiling on not only the first detected GPU
             nvml_handle = pynvml.nvmlDeviceGetHandleByIndex(0)
             source_device_name = pynvml.nvmlDeviceGetName(nvml_handle).decode("utf-8")
             split_source_device_name = re.split(r"-|\s|_|\\|/", source_device_name)
-            source_device = None if logging.root.level > logging.DEBUG else habitat.Device.T4
+            source_device = (
+                None if logging.root.level > logging.DEBUG else habitat.Device.T4
+            )
             for device in DEVICES:
                 if device.name in split_source_device_name:
                     source_device = device
             pynvml.nvmlShutdown()
             if not source_device:
-                logger.debug("Skipping DeepView predictions, source not in list of supported GPUs.")
+                logger.debug(
+                    "Skipping DeepView predictions,\
+                    source not in list of supported GPUs."
+                )
                 src = pm.HabitatDevicePrediction()
-                src.device_name = 'unavailable'
+                src.device_name = "unavailable"
                 src.runtime_ms = -1
                 resp.predictions.append(src)
                 return resp
@@ -272,13 +291,11 @@ def runnable():
             profiler = RunTimeProfiler()
 
             context = Context(
-                origin_device=source_device,
-                profiler=profiler,
-                percentile=99.5
+                origin_device=source_device, profiler=profiler, percentile=99.5
             )
 
             threshold = self.habitat_compute_threshold(runnable, context)
-            
+
             tracker = habitat.OperationTracker(
                 device=context.origin_device,
                 metrics=[
@@ -289,15 +306,14 @@ def runnable():
                 metrics_threshold_ms=threshold,
             )
 
-        
             with tracker.track():
                 iteration(*inputs)
-            
+
             print("deepview_predict: tracing on origin device")
             trace = tracker.get_tracked_trace()
 
             src = pm.HabitatDevicePrediction()
-            src.device_name = 'source'
+            src.device_name = "source"
             src.runtime_ms = trace.run_time_ms
             resp.predictions.append(src)
 
@@ -315,16 +331,13 @@ def runnable():
             message = str(ex)
             logger.error(message)
             resp.analysis_error.error_message = message
-        except:
+        except Exception:
             logger.error("There was an error running DeepView Predict")
-            resp.analysis_error.error_message = "There was an error running DeepView Predict"
+            resp.analysis_error.error_message = (
+                "There was an error running DeepView Predict"
+            )
         finally:
             return resp
-                
-
-        
-       
-        
 
     def measure_breakdown(self, nvml):
         # 1. Measure the breakdown entries
@@ -340,9 +353,11 @@ def measure_breakdown(self, nvml):
             if self._profiler is None:
                 self._initialize_iteration_profiler()
 
-            (self._batch_size_iteration_run_time_ms,
-             self._batch_size_peak_usage_bytes,
-             _) = self._profiler.measure_run_time_ms(self._batch_size)
+            (
+                self._batch_size_iteration_run_time_ms,
+                self._batch_size_peak_usage_bytes,
+                _,
+            ) = self._profiler.measure_run_time_ms(self._batch_size)
 
         # 3. Serialize the measured data
         bm = pm.BreakdownResponse()
@@ -354,9 +369,7 @@ def measure_breakdown(self, nvml):
         breakdown.weights.serialize_to_protobuf(bm.weight_tree)
 
         # 4. Bookkeeping for the throughput measurements
-        self._memory_usage_percentage = (
-            bm.peak_usage_bytes / bm.memory_capacity_bytes
-        )
+        self._memory_usage_percentage = bm.peak_usage_bytes / bm.memory_capacity_bytes
 
         return bm
 
@@ -381,9 +394,7 @@ def measure_throughput(self):
 
         # 2. Begin filling in the throughput response
         logger.debug("sampling results", samples)
-        measured_throughput = (
-            samples[0].batch_size / samples[0].run_time_ms * 1000
-        )
+        measured_throughput = samples[0].batch_size / samples[0].run_time_ms * 1000
         throughput = pm.ThroughputResponse()
         throughput.samples_per_second = measured_throughput
         throughput.predicted_max_samples_per_second = math.nan
@@ -396,7 +407,8 @@ def measure_throughput(self):
             throughput.batch_size_context.line_number = batch_info[0]
             throughput.can_manipulate_batch_size = batch_info[1]
             throughput.batch_size_context.file_path.components.extend(
-                self._entry_point.split(os.sep))
+                self._entry_point.split(os.sep)
+            )
 
         # 4. If we do not have enough throughput samples, we cannot build any
         #    prediction models so just return the message as-is
@@ -425,33 +437,30 @@ def measure_throughput(self):
         throughput.peak_usage_bytes.bias = peak_usage_model[1]
 
         predicted_max_throughput = 1000.0 / run_time_model[0]
-        
+
         # Our prediction can be inaccurate due to sampling error or incorrect
         # assumptions. In these cases, we ignore our prediction. At the very
         # minimum, a good linear model has a positive slope and bias.
-        #if (run_time_model[0] < 1e-3 or run_time_model[1] < 1e-3 or
-        if (run_time_model[0] < 1e-3 or
-                measured_throughput > predicted_max_throughput):
+        # if (run_time_model[0] < 1e-3 or run_time_model[1] < 1e-3 or
+        if run_time_model[0] < 1e-3 or measured_throughput > predicted_max_throughput:
             return throughput
 
         throughput.predicted_max_samples_per_second = predicted_max_throughput
         throughput.run_time_ms.slope = run_time_model[0]
         throughput.run_time_ms.bias = run_time_model[1]
-        
+
         return throughput
 
     def measure_peak_usage_bytes(self):
         self._prepare_for_memory_profiling()
         # Run one iteration to initialize the gradients
-        with user_code_environment(
-                self._path_to_entry_point_dir, self._project_root):
+        with user_code_environment(self._path_to_entry_point_dir, self._project_root):
             model = self._model_provider()
             iteration = self._iteration_provider(model)
             iteration(*self._input_provider(batch_size=self._batch_size))
 
         torch.cuda.reset_max_memory_allocated()
-        with user_code_environment(
-                self._path_to_entry_point_dir, self._project_root):
+        with user_code_environment(self._path_to_entry_point_dir, self._project_root):
             # NOTE: It's important to run at least 2 iterations here. It turns
             #       out that >= 2 iterations is the number of iterations needed
             #       to get a stable measurement of the total memory
@@ -495,12 +504,11 @@ def _get_tracker_instance(self):
             iteration_provider=self._iteration_provider,
             input_provider=self._input_provider,
             project_root=self._project_root,
-            user_code_path=self._path_to_entry_point_dir
+            user_code_path=self._path_to_entry_point_dir,
         )
 
 
-def _run_entry_point(
-        path_to_entry_point, path_to_entry_point_dir, project_root):
+def _run_entry_point(path_to_entry_point, path_to_entry_point_dir, project_root):
     with open(path_to_entry_point) as file:
         code_str = file.read()
     with exceptions_as_analysis_errors(project_root):
@@ -525,9 +533,11 @@ def _validate_providers_signatures(
         ).with_file_context(entry_point)
 
     input_sig = inspect.signature(input_provider)
-    if (len(input_sig.parameters) != 1 or
-            BATCH_SIZE_ARG not in input_sig.parameters or
-            type(input_sig.parameters[BATCH_SIZE_ARG].default) is not int):
+    if (
+        len(input_sig.parameters) != 1
+        or BATCH_SIZE_ARG not in input_sig.parameters
+        or type(input_sig.parameters[BATCH_SIZE_ARG].default) is not int
+    ):
         raise AnalysisError(
             "The input provider function must have exactly one '{}' "
             "parameter with an integral default "
@@ -576,9 +586,9 @@ def input_provider_wrapped(batch_size=None):
             ).with_file_context(entry_point)
 
         try:
-            input_iter = iter(inputs)
+            iter(inputs)
             return inputs
-        except TypeError as ex:
+        except TypeError:
             raise AnalysisError(
                 "The input provider function must return an iterable that "
                 "contains the inputs for the model."
@@ -609,7 +619,8 @@ def _fit_linear_model(x, y):
     # Linear model: y = slope * x + bias
     return slope, bias
 
-def _convert_to_energy_responses(entries: list)-> List[pm.EnergyResponse]:
+
+def _convert_to_energy_responses(entries: list) -> List[pm.EnergyResponse]:
     energy_response_list = []
     for entry in entries:
         if EnergyTableInterface.is_valid_entry_with_timestamp(entry):
@@ -617,15 +628,17 @@ def _convert_to_energy_responses(entries: list)-> List[pm.EnergyResponse]:
             cpu_component = pm.EnergyConsumptionComponent()
             cpu_component.component_type = pm.ENERGY_CPU_DRAM
             cpu_component.consumption_joules = entry[1]
-                
+
             gpu_component = pm.EnergyConsumptionComponent()
             gpu_component.component_type = pm.ENERGY_NVIDIA
             gpu_component.consumption_joules = entry[2]
-            
-            energy_response.total_consumption = gpu_component.consumption_joules+cpu_component.consumption_joules 
+
+            energy_response.total_consumption = (
+                gpu_component.consumption_joules + cpu_component.consumption_joules
+            )
             energy_response.components.extend([cpu_component, gpu_component])
 
             energy_response.batch_size = entry[3]
             energy_response_list.append(energy_response)
-            
+
     return energy_response_list
diff --git a/deepview_profile/commands/interactive.py b/deepview_profile/commands/interactive.py
index c11ce9c..9c9efa1 100644
--- a/deepview_profile/commands/interactive.py
+++ b/deepview_profile/commands/interactive.py
@@ -1,6 +1,5 @@
 import logging
 import signal
-import subprocess
 import threading
 
 from deepview_profile.initialization import (
@@ -48,7 +47,6 @@ def register_command(subparsers):
     parser.set_defaults(func=main)
 
 def actual_main(args):
-    from deepview_profile.config import Config
     from deepview_profile.server import SkylineServer
 
     should_shutdown = threading.Event()
diff --git a/deepview_profile/commands/measurements.py b/deepview_profile/commands/measurements.py
index 578e073..1aaa844 100644
--- a/deepview_profile/commands/measurements.py
+++ b/deepview_profile/commands/measurements.py
@@ -60,7 +60,6 @@ def make_measurements(session, batch_size):
 
 def actual_main(args):
     from deepview_profile.analysis.session import AnalysisSession
-    from deepview_profile.config import Config
     from deepview_profile.exceptions import AnalysisError
 
     if os.path.exists(args.output):
diff --git a/deepview_profile/commands/memory.py b/deepview_profile/commands/memory.py
index ba1f69d..55f631a 100644
--- a/deepview_profile/commands/memory.py
+++ b/deepview_profile/commands/memory.py
@@ -37,7 +37,6 @@ def register_command(subparsers):
 
 def actual_main(args):
     from deepview_profile.analysis.session import AnalysisSession
-    from deepview_profile.config import Config
     from deepview_profile.exceptions import AnalysisError
 
     if os.path.exists(args.output):
diff --git a/deepview_profile/commands/prediction_models.py b/deepview_profile/commands/prediction_models.py
index 58b7719..340331c 100644
--- a/deepview_profile/commands/prediction_models.py
+++ b/deepview_profile/commands/prediction_models.py
@@ -55,7 +55,6 @@ def get_model(session, batch_size):
 
 def actual_main(args):
     from deepview_profile.analysis.session import AnalysisSession
-    from deepview_profile.config import Config
     from deepview_profile.exceptions import AnalysisError
 
     if os.path.exists(args.output):
diff --git a/deepview_profile/commands/time.py b/deepview_profile/commands/time.py
index 0fc2c22..ef66580 100644
--- a/deepview_profile/commands/time.py
+++ b/deepview_profile/commands/time.py
@@ -38,7 +38,6 @@ def register_command(subparsers):
 
 def actual_main(args):
     from deepview_profile.analysis.session import AnalysisSession
-    from deepview_profile.config import Config
     from deepview_profile.exceptions import AnalysisError
 
     if os.path.exists(args.output):
diff --git a/deepview_profile/db/database.py b/deepview_profile/db/database.py
index 61a13d2..f168a16 100644
--- a/deepview_profile/db/database.py
+++ b/deepview_profile/db/database.py
@@ -1,4 +1,4 @@
-import datetime 
+import datetime
 import os
 import sqlite3
 
@@ -7,7 +7,9 @@
 
 class DatabaseInterface:
     def __init__(self, database_name=DB_PATH) -> None:
-        self.connection = sqlite3.connect(database_name, detect_types=sqlite3.PARSE_DECLTYPES|sqlite3.PARSE_COLNAMES)
+        self.connection = sqlite3.connect(
+            database_name, detect_types=sqlite3.PARSE_DECLTYPES|sqlite3.PARSE_COLNAMES
+        )
         self.create_energy_table()
 
     def create_energy_table(self) -> None:
@@ -46,9 +48,9 @@ def is_valid_entry_with_timestamp(entry: list) -> bool:
 
     def add_entry(self, entry: list) -> bool:
         '''
-        Validates an entry and then adds that entry into the Energy table. Note that current timestamp is added 
-        by this function. Returns False if the entry is not a valid format, or if the insertion failed. Else
-        returns True
+        Validates an entry and then adds that entry into the Energy table. Note that
+        current timestamp is added by this function. Returns False if the entry is
+        not a valid format, or if the insertion failed. Else returns True
         '''
         if self.is_valid_entry(entry):
             try:
@@ -69,5 +71,8 @@ def get_latest_n_entries_of_entry_point(self, n: int, entry_point: str) -> list:
         '''
         params = [entry_point, n]
         cursor = self.database_connection.cursor()
-        results = cursor.execute("SELECT * FROM ENERGY WHERE entry_point=? ORDER BY ts DESC LIMIT ?;", params).fetchall()
-        return results
\ No newline at end of file
+        results = cursor.execute(
+            "SELECT * FROM ENERGY WHERE entry_point=? ORDER BY ts DESC LIMIT ?;",
+            params
+        ).fetchall()
+        return results
diff --git a/deepview_profile/energy/measurer.py b/deepview_profile/energy/measurer.py
index f52a2ff..efd3223 100644
--- a/deepview_profile/energy/measurer.py
+++ b/deepview_profile/energy/measurer.py
@@ -19,13 +19,15 @@ def measurer_init(self):
             energy = self.sensor.energy()
             self.last_cpu = np.array(energy[0::2])
             self.last_dram = np.array(energy[1::2])
-        except Exception as e:
-            print("Warning. Failed to get CPU energy. You need to set the right permissions for pyRAPL")
+        except Exception:
+            print("Warning. Failed to get CPU energy. \
+                  You need to set the right permissions for pyRAPL")
             print("eg. $ sudo chmod -R a+r /sys/class/powercap/intel-rapl")
 
     def measurer_measure(self):
         # Get energy consumed so far (since last CPU reset)
-        if self.sensor is None: return
+        if self.sensor is None:
+            return
 
         energy = self.sensor.energy()
         cpu = np.array(energy[0::2])
@@ -33,8 +35,8 @@ def measurer_measure(self):
 
         # Compare against last measurement to determine energy since last measure
         diff_cpu = cpu - self.last_cpu
-        diff_dram = dram - self.last_dram
-        
+        dram - self.last_dram
+
         # 1J = 10^6 uJ
         # The cpu used this much since the last measurement
         # We have mW = 1000*J/s = 1000*(uJ/10^6)/s
@@ -49,7 +51,8 @@ def measurer_deallocate(self):
         pass
 
     def total_energy(self):
-        if len(self.power) == 0: return None
+        if len(self.power) == 0:
+            return None
 
         # J = W * s,    1W = 1000 mW
         energy = self.interval * sum(self.power) / 1000.0
@@ -123,6 +126,6 @@ def total_energy(self):
 
     def cpu_energy(self):
         return self.measurers["cpu"].total_energy()
-    
+
     def gpu_energy(self):
         return self.measurers["gpu"].total_energy()
diff --git a/deepview_profile/evaluate.py b/deepview_profile/evaluate.py
index c7d7518..dd061c1 100644
--- a/deepview_profile/evaluate.py
+++ b/deepview_profile/evaluate.py
@@ -1,5 +1,4 @@
 import argparse
-import enum
 import sys
 
 import deepview_profile.commands.measurements
diff --git a/deepview_profile/initialization.py b/deepview_profile/initialization.py
index 004e0bd..444fd7f 100644
--- a/deepview_profile/initialization.py
+++ b/deepview_profile/initialization.py
@@ -1,5 +1,4 @@
 import logging
-import os
 import sys
 
 logger = logging.getLogger(__name__)
@@ -42,11 +41,11 @@ def _validate_dependencies():
     # NOTE: If you make a change here, make sure to update the INSTALL_REQUIRES
     #       list in setup.py as well.
     try:
-        import yaml # pyyaml on PyPI
-        import pynvml # nvidia-ml-py3 on PyPI
-        import google.protobuf # protobuf on PyPI
-        import numpy
-        import torch
+        import yaml # pyyaml on PyPI # noqa: F401
+        import pynvml # nvidia-ml-py3 on PyPI # noqa: F401
+        import google.protobuf # protobuf on PyPI # noqa: F401
+        import numpy # noqa: F401
+        import torch # noqa: F401
         return True
     except ImportError as ex:
         logger.error(
diff --git a/deepview_profile/io/connection.py b/deepview_profile/io/connection.py
index f6b7008..e09af70 100644
--- a/deepview_profile/io/connection.py
+++ b/deepview_profile/io/connection.py
@@ -91,9 +91,9 @@ def _socket_read(self):
                         buffer = buffer[message_length:]
                         message_length = -1
 
-        except:
+        except Exception:
             logger.exception("Connection unexpectedly stopping...")
-    
+
     @property
     def project_root(self):
         return self._project_root
@@ -101,7 +101,7 @@ def project_root(self):
     @property
     def entry_point(self):
         return self._entry_point
-    
+
     def set_project_paths(self, project_root, entry_point):
         self._project_root = project_root
         self._entry_point = entry_point
diff --git a/deepview_profile/io/connection_acceptor.py b/deepview_profile/io/connection_acceptor.py
index 5fac0ea..e54184d 100644
--- a/deepview_profile/io/connection_acceptor.py
+++ b/deepview_profile/io/connection_acceptor.py
@@ -1,7 +1,6 @@
-import os
+import logging
 import select
 import socket
-import logging
 from threading import Thread
 
 from deepview_profile.io.sentinel import Sentinel
@@ -78,6 +77,6 @@ def _accept_connections(self):
                 host, port = address
                 logger.debug("Accepted a connection to (%s:%d).", host, port)
                 self._handler_function(socket, address)
-        except:
+        except Exception:
             logging.exception(
                 "DeepView has unexpectedly stopped accepting connections.")
diff --git a/deepview_profile/models/analysis.py b/deepview_profile/models/analysis.py
index b3d9806..d1f0ef2 100644
--- a/deepview_profile/models/analysis.py
+++ b/deepview_profile/models/analysis.py
@@ -1,4 +1,3 @@
-from deepview_profile.models.source_map import Position
 
 
 class OperationInfo:
diff --git a/deepview_profile/profiler/iteration.py b/deepview_profile/profiler/iteration.py
index 831cc11..08e832a 100644
--- a/deepview_profile/profiler/iteration.py
+++ b/deepview_profile/profiler/iteration.py
@@ -97,7 +97,8 @@ def measure(iterations):
         while repetitions <= max_repetitions:
             doubled = repetitions * 2
             greater = measure(doubled) / doubled
-            logger.debug("Iters: %d, Measured: %f (range: %f)", doubled, greater, max(lesser, greater) / min(lesser, greater))
+            logger.debug("Iters: %d, Measured: %f (range: %f)",\
+                         doubled, greater, max(lesser, greater) / min(lesser, greater))
 
             # Stop when the difference between the measurements is less than 5%
             if (max(lesser, greater) / min(lesser, greater)) < 1.05:
@@ -221,6 +222,6 @@ def _select_batch_size(self, lower, upper, is_increasing):
         # models whose initial batch size is much smaller than the maximum possible.
         tiers = [100, 20, 10, 5]
         for t in tiers:
-            if diff >= t: return base + mult * t
-
+            if diff >= t:
+                return base + mult * t
         return base + mult
diff --git a/deepview_profile/protocol/message_handler.py b/deepview_profile/protocol/message_handler.py
index 14f096d..ba7ce3e 100644
--- a/deepview_profile/protocol/message_handler.py
+++ b/deepview_profile/protocol/message_handler.py
@@ -2,7 +2,7 @@
 import logging
 import os
 
-from deepview_profile.exceptions import AnalysisError, NoConnectionError
+from deepview_profile.exceptions import NoConnectionError
 
 import deepview_profile.protocol_gen.innpv_pb2 as pm
 
@@ -80,9 +80,9 @@ def _handle_initialize_request(self, message, context):
             )
             return
 
-        
+
         if not _validate_paths(message.project_root,  message.entry_point):
-            # Change this to the error related to 
+            # Change this to the error related to
             self._message_sender.send_protocol_error(
                 pm.ProtocolError.ErrorCode.UNSUPPORTED_PROTOCOL_VERSION,
                 context,
@@ -95,7 +95,8 @@ def _handle_initialize_request(self, message, context):
         logger.info("Connection addr:(%s:%d)", *context.address)
         logger.info("Project Root:   %s", message.project_root)
         logger.info("Entry Point:    %s", message.entry_point)
-        self._connection_manager.get_connection(context.address).set_project_paths(message.project_root, message.entry_point)
+        self._connection_manager.get_connection(context.address)\
+            .set_project_paths(message.project_root, message.entry_point)
 
         context.state.initialized = True
         self._message_sender.send_initialize_response(context)
@@ -150,9 +151,8 @@ def handle_message(self, raw_data, address):
                 'connected.',
                 *address,
             )
-        except:
+        except Exception:
             logger.exception(
                 'Processing message from (%s:%d) resulted in an exception.',
                 *address,
             )
-
diff --git a/deepview_profile/protocol/message_sender.py b/deepview_profile/protocol/message_sender.py
index 318eab8..77afb84 100644
--- a/deepview_profile/protocol/message_sender.py
+++ b/deepview_profile/protocol/message_sender.py
@@ -2,9 +2,7 @@
 import logging
 import pynvml
 import platform
-from random import random
 
-from deepview_profile.config import Config
 from deepview_profile.exceptions import NoConnectionError
 
 import deepview_profile.protocol_gen.innpv_pb2 as pm
@@ -64,7 +62,7 @@ def send_throughput_response(self, throughput, context):
 
     def send_habitat_response(self, habitat_resp, context):
         self._send_message(habitat_resp, 'habitat', context)
-    
+
     def send_energy_response(self, energy_resp, context):
         self._send_message(energy_resp, 'energy', context)
 
diff --git a/deepview_profile/skyline.py b/deepview_profile/skyline.py
index fb2fa70..94e5c90 100644
--- a/deepview_profile/skyline.py
+++ b/deepview_profile/skyline.py
@@ -1,8 +1,6 @@
 import argparse
-import enum
 import sys
 
-import toml
 
 import deepview_profile
 import deepview_profile.commands.interactive
diff --git a/deepview_profile/tests/test_lru_cache.py b/deepview_profile/tests/test_lru_cache.py
index 0b31897..5acf625 100644
--- a/deepview_profile/tests/test_lru_cache.py
+++ b/deepview_profile/tests/test_lru_cache.py
@@ -118,7 +118,7 @@ def test_list_add_several(self):
     def test_list_move_three(self):
         n1 = self.list.add_to_front(1, 1)
         n2 = self.list.add_to_front(2, 2)
-        n3 = self.list.add_to_front(3, 3)
+        self.list.add_to_front(3, 3)
 
         self.list.move_to_front(n1)
         self.assertEqual(self.list_to_array(), [(1, 1), (3, 3), (2, 2)])
@@ -140,7 +140,7 @@ def test_list_move_three(self):
 
     def test_list_move_two(self):
         n1 = self.list.add_to_front(1, 1)
-        n2 = self.list.add_to_front(2, 2)
+        self.list.add_to_front(2, 2)
         self.assertEqual(self.list_to_array(), [(2, 2), (1, 1)])
 
         self.list.move_to_front(n1)
@@ -170,7 +170,7 @@ def test_list_remove_back_one(self):
 
     def test_list_remove_back_two(self):
         n1 = self.list.add_to_front(1, 1)
-        n2 = self.list.add_to_front(2, 2)
+        self.list.add_to_front(2, 2)
         self.assertEqual(self.list.size, 2)
         self.assertEqual(self.list_to_array(), [(2, 2), (1, 1)])
         removed = self.list.remove_back()
@@ -181,8 +181,8 @@ def test_list_remove_back_two(self):
 
     def test_list_remove_back_three(self):
         n1 = self.list.add_to_front(1, 1)
-        n2 = self.list.add_to_front(2, 2)
-        n3 = self.list.add_to_front(3, 3)
+        self.list.add_to_front(2, 2)
+        self.list.add_to_front(3, 3)
         self.assertEqual(self.list.size, 3)
         self.assertEqual(self.list_to_array(), [(3, 3), (2, 2), (1, 1)])
         removed = self.list.remove_back()
diff --git a/deepview_profile/tracking/memory/activations.py b/deepview_profile/tracking/memory/activations.py
index 46dd5ed..08c1473 100644
--- a/deepview_profile/tracking/memory/activations.py
+++ b/deepview_profile/tracking/memory/activations.py
@@ -179,7 +179,7 @@ def _extract_gradient_functions_in_topological_order(model_output):
     topological ordering of their gradient functions.
     """
     if isinstance(model_output, tuple) or isinstance(model_output, list):
-        tensors = _flatten_and_filter_tensors(tensor_iterable)
+        tensors = _flatten_and_filter_tensors(model_output)
     elif (isinstance(model_output, torch.Tensor) and
           model_output.grad_fn is not None):
         tensors = [model_output]
diff --git a/deepview_profile/tracking/memory/report.py b/deepview_profile/tracking/memory/report.py
index fa99223..cdaef5f 100644
--- a/deepview_profile/tracking/memory/report.py
+++ b/deepview_profile/tracking/memory/report.py
@@ -1,6 +1,5 @@
 import collections
 import enum
-import os
 
 from deepview_profile.tracking.base import ReportBase, ReportBuilderBase
 import deepview_profile.tracking.memory.report_queries as queries
diff --git a/deepview_profile/tracking/memory/weights.py b/deepview_profile/tracking/memory/weights.py
index 94e9512..ef3323c 100644
--- a/deepview_profile/tracking/memory/weights.py
+++ b/deepview_profile/tracking/memory/weights.py
@@ -1,5 +1,4 @@
 import torch
-import inspect
 import weakref
 
 from deepview_profile.tracking.base import TrackerBase
diff --git a/deepview_profile/tracking/time/operation.py b/deepview_profile/tracking/time/operation.py
index 9bf54dc..6d90c24 100644
--- a/deepview_profile/tracking/time/operation.py
+++ b/deepview_profile/tracking/time/operation.py
@@ -1,6 +1,5 @@
 import collections
 
-import torch
 
 from deepview_profile.tracking.call_stack import CallStack
 from deepview_profile.tracking.base import TrackerBase
diff --git a/deepview_profile/tracking/time/report.py b/deepview_profile/tracking/time/report.py
index 22363e4..13db70a 100644
--- a/deepview_profile/tracking/time/report.py
+++ b/deepview_profile/tracking/time/report.py
@@ -1,5 +1,4 @@
 import collections
-import os
 
 from deepview_profile.tracking.base import ReportBase, ReportBuilderBase
 import deepview_profile.tracking.time.report_queries as queries
diff --git a/deepview_profile/tracking/utils.py b/deepview_profile/tracking/utils.py
index 584ffeb..24efa40 100644
--- a/deepview_profile/tracking/utils.py
+++ b/deepview_profile/tracking/utils.py
@@ -1,6 +1,5 @@
 import re
 
-import torch
 
 DUNDER_REGEX = re.compile('__(?P<name>.+)__')
 
diff --git a/deepview_profile/user_code_utils.py b/deepview_profile/user_code_utils.py
index 245d351..0e06f5f 100644
--- a/deepview_profile/user_code_utils.py
+++ b/deepview_profile/user_code_utils.py
@@ -1,5 +1,4 @@
 import contextlib
-import os
 import sys
 
 from deepview_profile.exceptions import exceptions_as_analysis_errors
diff --git a/examples/densenet/densenet.py b/examples/densenet/densenet.py
index 4abb257..5db3214 100644
--- a/examples/densenet/densenet.py
+++ b/examples/densenet/densenet.py
@@ -1,11 +1,9 @@
-import re
 import torch
 import torch.nn as nn
 import torch.nn.functional as F
 import torch.utils.checkpoint as cp
 from collections import OrderedDict
 from torch import Tensor
-from torch.jit.annotations import List
 
 
 class _DenseLayer(nn.Module):
diff --git a/examples/densenet/entry_point.py b/examples/densenet/entry_point.py
index b4f480d..bfe34fe 100644
--- a/examples/densenet/entry_point.py
+++ b/examples/densenet/entry_point.py
@@ -1,5 +1,4 @@
 import torch
-import torch.nn as nn
 
 import densenet
 
diff --git a/examples/gnmt/entry_point.py b/examples/gnmt/entry_point.py
index 59ce534..eb6ccc6 100644
--- a/examples/gnmt/entry_point.py
+++ b/examples/gnmt/entry_point.py
@@ -4,10 +4,8 @@
 import torch
 import torch.nn as nn
 import torch.optim
-import torch.distributed as dist
 
 import seq2seq.data.config as config
-import seq2seq.utils as utils
 from seq2seq.models.gnmt import GNMT
 from seq2seq.train.fp_optimizers import Fp32Optimizer
 from seq2seq.train.lr_scheduler import WarmupMultiStepLR
diff --git a/examples/gnmt/seq2seq/data/sampler.py b/examples/gnmt/seq2seq/data/sampler.py
index 204b560..b807b1f 100644
--- a/examples/gnmt/seq2seq/data/sampler.py
+++ b/examples/gnmt/seq2seq/data/sampler.py
@@ -5,7 +5,6 @@
 
 from seq2seq.utils import get_rank
 from seq2seq.utils import get_world_size
-from seq2seq.utils import gnmt_print
 
 
 class DistributedSampler(Sampler):
diff --git a/examples/gnmt/seq2seq/data/tokenizer.py b/examples/gnmt/seq2seq/data/tokenizer.py
index b2d9549..5020ed5 100644
--- a/examples/gnmt/seq2seq/data/tokenizer.py
+++ b/examples/gnmt/seq2seq/data/tokenizer.py
@@ -56,7 +56,7 @@ def pad_vocabulary(self, vocab, pad):
         assert len(vocab) % pad == 0
 
     def get_state(self):
-        logging.info(f'Saving state of the tokenizer')
+        logging.info('Saving state of the tokenizer')
         state = {
             'separator': self.separator,
             'vocab_size': self.vocab_size,
@@ -66,7 +66,7 @@ def get_state(self):
         return state
 
     def set_state(self, state):
-        logging.info(f'Restoring state of the tokenizer')
+        logging.info('Restoring state of the tokenizer')
         self.separator = state['separator']
         self.vocab_size = state['vocab_size']
         self.tok2idx = state['tok2idx']
diff --git a/examples/gnmt/seq2seq/inference/beam_search.py b/examples/gnmt/seq2seq/inference/beam_search.py
index 11338b1..b9ff6a9 100644
--- a/examples/gnmt/seq2seq/inference/beam_search.py
+++ b/examples/gnmt/seq2seq/inference/beam_search.py
@@ -2,7 +2,6 @@
 
 from seq2seq.data.config import BOS
 from seq2seq.data.config import EOS
-from seq2seq.utils import gnmt_print
 
 
 class SequenceGenerator:
diff --git a/examples/gnmt/seq2seq/inference/inference.py b/examples/gnmt/seq2seq/inference/inference.py
index 5ec3a4b..01bac3f 100644
--- a/examples/gnmt/seq2seq/inference/inference.py
+++ b/examples/gnmt/seq2seq/inference/inference.py
@@ -113,7 +113,7 @@ def run(self, calc_bleu=True, epoch=None, iteration=None, eval_path=None,
             os.remove(detok_eval_path)
 
         rank = get_rank()
-        logging.info(f'Running evaluation on test set')
+        logging.info('Running evaluation on test set')
         self.model.eval()
         torch.cuda.empty_cache()
 
@@ -131,12 +131,12 @@ def run(self, calc_bleu=True, epoch=None, iteration=None, eval_path=None,
                     logging.info(f'BLEU on test dataset: {test_bleu[0]:.2f}')
 
                 if self.target_bleu and test_bleu[0] >= self.target_bleu:
-                    logging.info(f'Target accuracy reached')
+                    logging.info('Target accuracy reached')
                     break_training[0] = 1
 
         barrier()
         torch.cuda.empty_cache()
-        logging.info(f'Finished evaluation on test set')
+        logging.info('Finished evaluation on test set')
 
         if self.distributed:
             dist.broadcast(break_training, 0)
@@ -220,7 +220,7 @@ def evaluate(self, epoch, iteration, summary):
 
             if i % self.print_freq == 0:
                 log = []
-                log += f'TEST '
+                log += 'TEST '
                 if epoch is not None:
                     log += f'[{epoch}]'
                 if iteration is not None:
@@ -241,7 +241,7 @@ def evaluate(self, epoch, iteration, summary):
         if summary and get_rank() == 0:
             time_per_sentence = (batch_time.avg / global_batch_size)
             log = []
-            log += f'TEST SUMMARY:\n'
+            log += 'TEST SUMMARY:\n'
             log += f'Lines translated: {len(self.loader.dataset)}\t'
             log += f'Avg total tokens/s: {tot_tok_per_sec.avg:.0f}\n'
             log += f'Avg time per batch: {batch_time.avg:.3f} s\t'
diff --git a/examples/gnmt/seq2seq/models/gnmt.py b/examples/gnmt/seq2seq/models/gnmt.py
index 4832f72..c71e283 100644
--- a/examples/gnmt/seq2seq/models/gnmt.py
+++ b/examples/gnmt/seq2seq/models/gnmt.py
@@ -4,7 +4,6 @@
 from seq2seq.models.decoder import ResidualRecurrentDecoder
 from seq2seq.models.encoder import ResidualRecurrentEncoder
 from seq2seq.models.seq2seq_base import Seq2Seq
-from seq2seq.utils import gnmt_print
 
 
 class GNMT(Seq2Seq):
diff --git a/examples/gnmt/seq2seq/train/lr_scheduler.py b/examples/gnmt/seq2seq/train/lr_scheduler.py
index de1d459..e7246e1 100644
--- a/examples/gnmt/seq2seq/train/lr_scheduler.py
+++ b/examples/gnmt/seq2seq/train/lr_scheduler.py
@@ -3,7 +3,6 @@
 
 import torch
 
-from seq2seq.utils import gnmt_print
 
 
 def perhaps_convert_float(param, total):
@@ -64,8 +63,8 @@ def __init__(self, optimizer, iterations, warmup_steps=0,
         self.decay_steps = decay_steps
 
         if self.warmup_steps > self.remain_steps:
-            logging.warn(f'warmup_steps should not be larger than '
-                         f'remain_steps, setting warmup_steps=remain_steps')
+            logging.warn('warmup_steps should not be larger than '
+                         'remain_steps, setting warmup_steps=remain_steps')
             self.warmup_steps = self.remain_steps
 
         super(WarmupMultiStepLR, self).__init__(optimizer, last_epoch)
diff --git a/examples/gnmt/seq2seq/train/trainer.py b/examples/gnmt/seq2seq/train/trainer.py
index e3c2a5f..bb3ec4a 100644
--- a/examples/gnmt/seq2seq/train/trainer.py
+++ b/examples/gnmt/seq2seq/train/trainer.py
@@ -13,7 +13,6 @@
 from seq2seq.train.fp_optimizers import Fp32Optimizer
 from seq2seq.train.lr_scheduler import WarmupMultiStepLR
 from seq2seq.utils import AverageMeter
-from seq2seq.utils import gnmt_print
 from seq2seq.utils import sync_workers
 
 
diff --git a/examples/legacy/testnet2.py b/examples/legacy/testnet2.py
index 5562589..28610b0 100644
--- a/examples/legacy/testnet2.py
+++ b/examples/legacy/testnet2.py
@@ -1,4 +1,3 @@
-import torch
 import torch.nn as nn
 
 
diff --git a/examples/legacy/vgg11.py b/examples/legacy/vgg11.py
index 5344300..96c18ba 100644
--- a/examples/legacy/vgg11.py
+++ b/examples/legacy/vgg11.py
@@ -1,4 +1,3 @@
-import torch
 import torch.nn as nn
 
 
diff --git a/examples/resnet/entry_point.py b/examples/resnet/entry_point.py
index 7a3d16a..e21d1bd 100644
--- a/examples/resnet/entry_point.py
+++ b/examples/resnet/entry_point.py
@@ -1,5 +1,4 @@
 import torch
-import torch.nn as nn
 
 import resnet
 
diff --git a/examples/resnet/entry_point_resnext.py b/examples/resnet/entry_point_resnext.py
index 4f69bb0..68c5fb2 100644
--- a/examples/resnet/entry_point_resnext.py
+++ b/examples/resnet/entry_point_resnext.py
@@ -1,5 +1,4 @@
 import torch
-import torch.nn as nn
 
 import resnet
 
diff --git a/examples/testnet/testnet1.py b/examples/testnet/testnet1.py
index d99917f..4ed3a68 100644
--- a/examples/testnet/testnet1.py
+++ b/examples/testnet/testnet1.py
@@ -1,4 +1,3 @@
-import torch
 import torch.nn as nn
 
 
diff --git a/examples/transformer/transformer/Beam.py b/examples/transformer/transformer/Beam.py
index 127b14f..6a52a1f 100644
--- a/examples/transformer/transformer/Beam.py
+++ b/examples/transformer/transformer/Beam.py
@@ -6,7 +6,6 @@
 """
 
 import torch
-import numpy as np
 import transformer.Constants as Constants
 
 class Beam():
diff --git a/examples/vgg/entry_point.py b/examples/vgg/entry_point.py
index 3214b1b..1c7f8b8 100644
--- a/examples/vgg/entry_point.py
+++ b/examples/vgg/entry_point.py
@@ -1,5 +1,4 @@
 import torch
-import torch.nn as nn
 
 import vgg
 
diff --git a/poetry.lock b/poetry.lock
index 9181f6b..c7c7f1e 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -1,3 +1,130 @@
+# This file is automatically @generated by Poetry 1.4.2 and should not be changed by hand.
+
+[[package]]
+name = "cfgv"
+version = "3.3.1"
+description = "Validate configuration and produce human readable error messages."
+category = "dev"
+optional = false
+python-versions = ">=3.6.1"
+files = [
+    {file = "cfgv-3.3.1-py2.py3-none-any.whl", hash = "sha256:c6a0883f3917a037485059700b9e75da2464e6c27051014ad85ba6aaa5884426"},
+    {file = "cfgv-3.3.1.tar.gz", hash = "sha256:f5a830efb9ce7a445376bb66ec94c638a9787422f96264c98edc6bdeed8ab736"},
+]
+
+[[package]]
+name = "colorama"
+version = "0.4.6"
+description = "Cross-platform colored terminal text."
+category = "main"
+optional = false
+python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,!=3.6.*,>=2.7"
+files = [
+    {file = "colorama-0.4.6-py2.py3-none-any.whl", hash = "sha256:4f1d9991f5acc0ca119f9d443620b77f9d6b33703e51011c16baf57afb285fc6"},
+    {file = "colorama-0.4.6.tar.gz", hash = "sha256:08695f5cb7ed6e0531a20572697297273c47b8cae5a63ffc6d6ed5c201be6e44"},
+]
+
+[[package]]
+name = "deepview-predict"
+version = "0.1.0"
+description = "Cross-GPU performance predictions for PyTorch neural network training."
+category = "main"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "deepview_predict-0.1.0-py310-none-any.whl", hash = "sha256:be6ee2cc3e2e34ef2931299a5f04741317ee5e5201d1bc2c54818d2a25705f51"},
+    {file = "deepview_predict-0.1.0-py37-none-any.whl", hash = "sha256:6f448f233c112097c1c19d893cae5c7db47a7ed5e3b1ca201cd1c36d631a7fde"},
+    {file = "deepview_predict-0.1.0-py38-none-any.whl", hash = "sha256:50793705b1c538b6715e9ecd1febfd08b3ad8535c7224579c3868e4487d3341e"},
+    {file = "deepview_predict-0.1.0-py39-none-any.whl", hash = "sha256:803f07ceabe120e2a6fcb4fd3452cbcb9e1e8ddb058ad6f688434c55ec40e2f8"},
+]
+
+[package.dependencies]
+nvidia-cuda-cupti-cu11 = "11.7.101"
+nvidia-cuda-runtime-cu11 = "11.7.99"
+pandas = ">=1.1.2"
+pyyaml = "*"
+torch = ">=1.4.0"
+tqdm = ">=4.49.0"
+
+[[package]]
+name = "distlib"
+version = "0.3.6"
+description = "Distribution utilities"
+category = "dev"
+optional = false
+python-versions = "*"
+files = [
+    {file = "distlib-0.3.6-py2.py3-none-any.whl", hash = "sha256:f35c4b692542ca110de7ef0bea44d73981caeb34ca0b9b6b2e6d7790dda8f80e"},
+    {file = "distlib-0.3.6.tar.gz", hash = "sha256:14bad2d9b04d3a36127ac97f30b12a19268f211063d8f8ee4f47108896e11b46"},
+]
+
+[[package]]
+name = "filelock"
+version = "3.12.0"
+description = "A platform independent file lock."
+category = "dev"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "filelock-3.12.0-py3-none-any.whl", hash = "sha256:ad98852315c2ab702aeb628412cbf7e95b7ce8c3bf9565670b4eaecf1db370a9"},
+    {file = "filelock-3.12.0.tar.gz", hash = "sha256:fc03ae43288c013d2ea83c8597001b1129db351aad9c57fe2409327916b8e718"},
+]
+
+[package.extras]
+docs = ["furo (>=2023.3.27)", "sphinx (>=6.1.3)", "sphinx-autodoc-typehints (>=1.23,!=1.23.4)"]
+testing = ["covdefaults (>=2.3)", "coverage (>=7.2.3)", "diff-cover (>=7.5)", "pytest (>=7.3.1)", "pytest-cov (>=4)", "pytest-mock (>=3.10)", "pytest-timeout (>=2.1)"]
+
+[[package]]
+name = "identify"
+version = "2.5.24"
+description = "File identification library for Python"
+category = "dev"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "identify-2.5.24-py2.py3-none-any.whl", hash = "sha256:986dbfb38b1140e763e413e6feb44cd731faf72d1909543178aa79b0e258265d"},
+    {file = "identify-2.5.24.tar.gz", hash = "sha256:0aac67d5b4812498056d28a9a512a483f5085cc28640b02b258a59dac34301d4"},
+]
+
+[package.extras]
+license = ["ukkonen"]
+
+[[package]]
+name = "importlib-metadata"
+version = "6.6.0"
+description = "Read metadata from Python packages"
+category = "dev"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "importlib_metadata-6.6.0-py3-none-any.whl", hash = "sha256:43dd286a2cd8995d5eaef7fee2066340423b818ed3fd70adf0bad5f1fac53fed"},
+    {file = "importlib_metadata-6.6.0.tar.gz", hash = "sha256:92501cdf9cc66ebd3e612f1b4f0c0765dfa42f0fa38ffb319b6bd84dd675d705"},
+]
+
+[package.dependencies]
+typing-extensions = {version = ">=3.6.4", markers = "python_version < \"3.8\""}
+zipp = ">=0.5"
+
+[package.extras]
+docs = ["furo", "jaraco.packaging (>=9)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"]
+perf = ["ipython"]
+testing = ["flake8 (<5)", "flufl.flake8", "importlib-resources (>=1.3)", "packaging", "pyfakefs", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=1.3)", "pytest-flake8", "pytest-mypy (>=0.9.1)", "pytest-perf (>=0.9.2)"]
+
+[[package]]
+name = "nodeenv"
+version = "1.8.0"
+description = "Node.js virtual environment builder"
+category = "dev"
+optional = false
+python-versions = ">=2.7,!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,!=3.6.*"
+files = [
+    {file = "nodeenv-1.8.0-py2.py3-none-any.whl", hash = "sha256:df865724bb3c3adc86b3876fa209771517b0cfe596beff01a92700e0e8be4cec"},
+    {file = "nodeenv-1.8.0.tar.gz", hash = "sha256:d51e0c37e64fbf47d017feac3145cdbb58836d7eee8c6f6d3b6880c5456227d2"},
+]
+
+[package.dependencies]
+setuptools = "*"
+
 [[package]]
 name = "numpy"
 version = "1.21.1"
@@ -5,6 +132,36 @@ description = "NumPy is the fundamental package for array computing with Python.
 category = "main"
 optional = false
 python-versions = ">=3.7"
+files = [
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+    {file = "numpy-1.21.1-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:1412aa0aec3e00bc23fbb8664d76552b4efde98fb71f60737c83efbac24112f1"},
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+    {file = "numpy-1.21.1-cp37-cp37m-win32.whl", hash = "sha256:73101b2a1fef16602696d133db402a7e7586654682244344b8329cdcbbb82172"},
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+    {file = "numpy-1.21.1-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:f01f28075a92eede918b965e86e8f0ba7b7797a95aa8d35e1cc8821f5fc3ad6a"},
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+    {file = "numpy-1.21.1-cp39-cp39-win_amd64.whl", hash = "sha256:01721eefe70544d548425a07c80be8377096a54118070b8a62476866d5208e33"},
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+    {file = "numpy-1.21.1.zip", hash = "sha256:dff4af63638afcc57a3dfb9e4b26d434a7a602d225b42d746ea7fe2edf1342fd"},
+]
 
 [[package]]
 name = "nvidia-cublas-cu11"
@@ -13,6 +170,30 @@ description = "CUBLAS native runtime libraries"
 category = "main"
 optional = false
 python-versions = ">=3"
+files = [
+    {file = "nvidia_cublas_cu11-11.10.3.66-py3-none-manylinux1_x86_64.whl", hash = "sha256:d32e4d75f94ddfb93ea0a5dda08389bcc65d8916a25cb9f37ac89edaeed3bded"},
+    {file = "nvidia_cublas_cu11-11.10.3.66-py3-none-win_amd64.whl", hash = "sha256:8ac17ba6ade3ed56ab898a036f9ae0756f1e81052a317bf98f8c6d18dc3ae49e"},
+]
+
+[package.dependencies]
+setuptools = "*"
+wheel = "*"
+
+[[package]]
+name = "nvidia-cuda-cupti-cu11"
+version = "11.7.101"
+description = "CUDA profiling tools runtime libs."
+category = "main"
+optional = false
+python-versions = ">=3"
+files = [
+    {file = "nvidia_cuda_cupti_cu11-11.7.101-py3-none-manylinux1_x86_64.whl", hash = "sha256:e0cfd9854e1f2edaa36ca20d21cd0bdd5dcfca4e3b9e130a082e05b33b6c5895"},
+    {file = "nvidia_cuda_cupti_cu11-11.7.101-py3-none-win_amd64.whl", hash = "sha256:7cc5b8f91ae5e1389c3c0ad8866b3b016a175e827ea8f162a672990a402ab2b0"},
+]
+
+[package.dependencies]
+setuptools = "*"
+wheel = "*"
 
 [[package]]
 name = "nvidia-cuda-nvrtc-cu11"
@@ -21,6 +202,15 @@ description = "NVRTC native runtime libraries"
 category = "main"
 optional = false
 python-versions = ">=3"
+files = [
+    {file = "nvidia_cuda_nvrtc_cu11-11.7.99-2-py3-none-manylinux1_x86_64.whl", hash = "sha256:9f1562822ea264b7e34ed5930567e89242d266448e936b85bc97a3370feabb03"},
+    {file = "nvidia_cuda_nvrtc_cu11-11.7.99-py3-none-manylinux1_x86_64.whl", hash = "sha256:f7d9610d9b7c331fa0da2d1b2858a4a8315e6d49765091d28711c8946e7425e7"},
+    {file = "nvidia_cuda_nvrtc_cu11-11.7.99-py3-none-win_amd64.whl", hash = "sha256:f2effeb1309bdd1b3854fc9b17eaf997808f8b25968ce0c7070945c4265d64a3"},
+]
+
+[package.dependencies]
+setuptools = "*"
+wheel = "*"
 
 [[package]]
 name = "nvidia-cuda-runtime-cu11"
@@ -29,6 +219,14 @@ description = "CUDA Runtime native Libraries"
 category = "main"
 optional = false
 python-versions = ">=3"
+files = [
+    {file = "nvidia_cuda_runtime_cu11-11.7.99-py3-none-manylinux1_x86_64.whl", hash = "sha256:cc768314ae58d2641f07eac350f40f99dcb35719c4faff4bc458a7cd2b119e31"},
+    {file = "nvidia_cuda_runtime_cu11-11.7.99-py3-none-win_amd64.whl", hash = "sha256:bc77fa59a7679310df9d5c70ab13c4e34c64ae2124dd1efd7e5474b71be125c7"},
+]
+
+[package.dependencies]
+setuptools = "*"
+wheel = "*"
 
 [[package]]
 name = "nvidia-cudnn-cu11"
@@ -37,6 +235,14 @@ description = "cuDNN runtime libraries"
 category = "main"
 optional = false
 python-versions = ">=3"
+files = [
+    {file = "nvidia_cudnn_cu11-8.5.0.96-2-py3-none-manylinux1_x86_64.whl", hash = "sha256:402f40adfc6f418f9dae9ab402e773cfed9beae52333f6d86ae3107a1b9527e7"},
+    {file = "nvidia_cudnn_cu11-8.5.0.96-py3-none-manylinux1_x86_64.whl", hash = "sha256:71f8111eb830879ff2836db3cccf03bbd735df9b0d17cd93761732ac50a8a108"},
+]
+
+[package.dependencies]
+setuptools = "*"
+wheel = "*"
 
 [[package]]
 name = "nvidia-ml-py3"
@@ -45,6 +251,90 @@ description = "Python Bindings for the NVIDIA Management Library"
 category = "main"
 optional = false
 python-versions = "*"
+files = [
+    {file = "nvidia-ml-py3-7.352.0.tar.gz", hash = "sha256:390f02919ee9d73fe63a98c73101061a6b37fa694a793abf56673320f1f51277"},
+]
+
+[[package]]
+name = "pandas"
+version = "1.1.5"
+description = "Powerful data structures for data analysis, time series, and statistics"
+category = "main"
+optional = false
+python-versions = ">=3.6.1"
+files = [
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+    {file = "pandas-1.1.5-cp36-cp36m-manylinux1_i686.whl", hash = "sha256:5a780260afc88268a9d3ac3511d8f494fdcf637eece62fb9eb656a63d53eb7ca"},
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+    {file = "ruff-0.0.267-py3-none-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:db33deef2a5e1cf528ca51cc59dd764122a48a19a6c776283b223d147041153f"},
+    {file = "ruff-0.0.267-py3-none-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:9adf1307fa9d840d1acaa477eb04f9702032a483214c409fca9dc46f5f157fe3"},
+    {file = "ruff-0.0.267-py3-none-manylinux_2_17_ppc64.manylinux2014_ppc64.whl", hash = "sha256:0afca3633c8e2b6c0a48ad0061180b641b3b404d68d7e6736aab301c8024c424"},
+    {file = "ruff-0.0.267-py3-none-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:2972241065b1c911bce3db808837ed10f4f6f8a8e15520a4242d291083605ab6"},
+    {file = "ruff-0.0.267-py3-none-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:f731d81cb939e757b0335b0090f18ca2e9ff8bcc8e6a1cf909245958949b6e11"},
+    {file = "ruff-0.0.267-py3-none-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:20c594eb56c19063ef5a57f89340e64c6550e169d6a29408a45130a8c3068adc"},
+    {file = "ruff-0.0.267-py3-none-musllinux_1_2_aarch64.whl", hash = "sha256:45d61a2b01bdf61581a2ee039503a08aa603dc74a6bbe6fb5d1ce3052f5370e5"},
+    {file = "ruff-0.0.267-py3-none-musllinux_1_2_armv7l.whl", hash = "sha256:2107cec3699ca4d7bd41543dc1d475c97ae3a21ea9212238b5c2088fa8ee7722"},
+    {file = "ruff-0.0.267-py3-none-musllinux_1_2_i686.whl", hash = "sha256:786de30723c71fc46b80a173c3313fc0dbe73c96bd9da8dd1212cbc2f84cdfb2"},
+    {file = "ruff-0.0.267-py3-none-musllinux_1_2_x86_64.whl", hash = "sha256:5a898953949e37c109dd242cfcf9841e065319995ebb7cdfd213b446094a942f"},
+    {file = "ruff-0.0.267-py3-none-win32.whl", hash = "sha256:d12ab329474c46b96d962e2bdb92e3ad2144981fe41b89c7770f370646c0101f"},
+    {file = "ruff-0.0.267-py3-none-win_amd64.whl", hash = "sha256:d09aecc9f5845586ba90911d815f9772c5a6dcf2e34be58c6017ecb124534ac4"},
+    {file = "ruff-0.0.267-py3-none-win_arm64.whl", hash = "sha256:7df7eb5f8d791566ba97cc0b144981b9c080a5b861abaf4bb35a26c8a77b83e9"},
+    {file = "ruff-0.0.267.tar.gz", hash = "sha256:632cec7bbaf3c06fcf0a72a1dd029b7d8b7f424ba95a574aaa135f5d20a00af7"},
+]
+
+[[package]]
+name = "setuptools"
+version = "67.7.2"
+description = "Easily download, build, install, upgrade, and uninstall Python packages"
+category = "main"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "setuptools-67.7.2-py3-none-any.whl", hash = "sha256:23aaf86b85ca52ceb801d32703f12d77517b2556af839621c641fca11287952b"},
+    {file = "setuptools-67.7.2.tar.gz", hash = "sha256:f104fa03692a2602fa0fec6c6a9e63b6c8a968de13e17c026957dd1f53d80990"},
+]
+
+[package.extras]
+docs = ["furo", "jaraco.packaging (>=9)", "jaraco.tidelift (>=1.4)", "pygments-github-lexers (==0.0.5)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-favicon", "sphinx-hoverxref (<2)", "sphinx-inline-tabs", "sphinx-lint", "sphinx-notfound-page (==0.8.3)", "sphinx-reredirects", "sphinxcontrib-towncrier"]
+testing = ["build[virtualenv]", "filelock (>=3.4.0)", "flake8 (<5)", "flake8-2020", "ini2toml[lite] (>=0.9)", "jaraco.envs (>=2.2)", "jaraco.path (>=3.2.0)", "pip (>=19.1)", "pip-run (>=8.8)", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=1.3)", "pytest-flake8", "pytest-mypy (>=0.9.1)", "pytest-perf", "pytest-timeout", "pytest-xdist", "tomli-w (>=1.0.0)", "virtualenv (>=13.0.0)", "wheel"]
+testing-integration = ["build[virtualenv]", "filelock (>=3.4.0)", "jaraco.envs (>=2.2)", "jaraco.path (>=3.2.0)", "pytest", "pytest-enabler", "pytest-xdist", "tomli", "virtualenv (>=13.0.0)", "wheel"]
+
+[[package]]
+name = "six"
+version = "1.16.0"
+description = "Python 2 and 3 compatibility utilities"
+category = "main"
+optional = false
+python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*"
+files = [
+    {file = "six-1.16.0-py2.py3-none-any.whl", hash = "sha256:8abb2f1d86890a2dfb989f9a77cfcfd3e47c2a354b01111771326f8aa26e0254"},
+    {file = "six-1.16.0.tar.gz", hash = "sha256:1e61c37477a1626458e36f7b1d82aa5c9b094fa4802892072e49de9c60c4c926"},
+]
 
 [[package]]
 name = "toml"
@@ -82,6 +524,10 @@ description = "Python Library for Tom's Obvious, Minimal Language"
 category = "main"
 optional = false
 python-versions = ">=2.6, !=3.0.*, !=3.1.*, !=3.2.*"
+files = [
+    {file = "toml-0.10.2-py2.py3-none-any.whl", hash = "sha256:806143ae5bfb6a3c6e736a764057db0e6a0e05e338b5630894a5f779cabb4f9b"},
+    {file = "toml-0.10.2.tar.gz", hash = "sha256:b3bda1d108d5dd99f4a20d24d9c348e91c4db7ab1b749200bded2f839ccbe68f"},
+]
 
 [[package]]
 name = "torch"
@@ -90,6 +536,29 @@ description = "Tensors and Dynamic neural networks in Python with strong GPU acc
 category = "main"
 optional = false
 python-versions = ">=3.7.0"
+files = [
+    {file = "torch-1.13.1-cp310-cp310-manylinux1_x86_64.whl", hash = "sha256:fd12043868a34a8da7d490bf6db66991108b00ffbeecb034228bfcbbd4197143"},
+    {file = "torch-1.13.1-cp310-cp310-manylinux2014_aarch64.whl", hash = "sha256:d9fe785d375f2e26a5d5eba5de91f89e6a3be5d11efb497e76705fdf93fa3c2e"},
+    {file = "torch-1.13.1-cp310-cp310-win_amd64.whl", hash = "sha256:98124598cdff4c287dbf50f53fb455f0c1e3a88022b39648102957f3445e9b76"},
+    {file = "torch-1.13.1-cp310-none-macosx_10_9_x86_64.whl", hash = "sha256:393a6273c832e047581063fb74335ff50b4c566217019cc6ace318cd79eb0566"},
+    {file = "torch-1.13.1-cp310-none-macosx_11_0_arm64.whl", hash = "sha256:0122806b111b949d21fa1a5f9764d1fd2fcc4a47cb7f8ff914204fd4fc752ed5"},
+    {file = "torch-1.13.1-cp311-cp311-manylinux1_x86_64.whl", hash = "sha256:22128502fd8f5b25ac1cd849ecb64a418382ae81dd4ce2b5cebaa09ab15b0d9b"},
+    {file = "torch-1.13.1-cp37-cp37m-manylinux1_x86_64.whl", hash = "sha256:76024be052b659ac1304ab8475ab03ea0a12124c3e7626282c9c86798ac7bc11"},
+    {file = "torch-1.13.1-cp37-cp37m-manylinux2014_aarch64.whl", hash = "sha256:ea8dda84d796094eb8709df0fcd6b56dc20b58fdd6bc4e8d7109930dafc8e419"},
+    {file = "torch-1.13.1-cp37-cp37m-win_amd64.whl", hash = "sha256:2ee7b81e9c457252bddd7d3da66fb1f619a5d12c24d7074de91c4ddafb832c93"},
+    {file = "torch-1.13.1-cp37-none-macosx_10_9_x86_64.whl", hash = "sha256:0d9b8061048cfb78e675b9d2ea8503bfe30db43d583599ae8626b1263a0c1380"},
+    {file = "torch-1.13.1-cp37-none-macosx_11_0_arm64.whl", hash = "sha256:f402ca80b66e9fbd661ed4287d7553f7f3899d9ab54bf5c67faada1555abde28"},
+    {file = "torch-1.13.1-cp38-cp38-manylinux1_x86_64.whl", hash = "sha256:727dbf00e2cf858052364c0e2a496684b9cb5aa01dc8a8bc8bbb7c54502bdcdd"},
+    {file = "torch-1.13.1-cp38-cp38-manylinux2014_aarch64.whl", hash = "sha256:df8434b0695e9ceb8cc70650afc1310d8ba949e6db2a0525ddd9c3b2b181e5fe"},
+    {file = "torch-1.13.1-cp38-cp38-win_amd64.whl", hash = "sha256:5e1e722a41f52a3f26f0c4fcec227e02c6c42f7c094f32e49d4beef7d1e213ea"},
+    {file = "torch-1.13.1-cp38-none-macosx_10_9_x86_64.whl", hash = "sha256:33e67eea526e0bbb9151263e65417a9ef2d8fa53cbe628e87310060c9dcfa312"},
+    {file = "torch-1.13.1-cp38-none-macosx_11_0_arm64.whl", hash = "sha256:eeeb204d30fd40af6a2d80879b46a7efbe3cf43cdbeb8838dd4f3d126cc90b2b"},
+    {file = "torch-1.13.1-cp39-cp39-manylinux1_x86_64.whl", hash = "sha256:50ff5e76d70074f6653d191fe4f6a42fdbe0cf942fbe2a3af0b75eaa414ac038"},
+    {file = "torch-1.13.1-cp39-cp39-manylinux2014_aarch64.whl", hash = "sha256:2c3581a3fd81eb1f0f22997cddffea569fea53bafa372b2c0471db373b26aafc"},
+    {file = "torch-1.13.1-cp39-cp39-win_amd64.whl", hash = "sha256:0aa46f0ac95050c604bcf9ef71da9f1172e5037fdf2ebe051962d47b123848e7"},
+    {file = "torch-1.13.1-cp39-none-macosx_10_9_x86_64.whl", hash = "sha256:6930791efa8757cb6974af73d4996b6b50c592882a324b8fb0589c6a9ba2ddaf"},
+    {file = "torch-1.13.1-cp39-none-macosx_11_0_arm64.whl", hash = "sha256:e0df902a7c7dd6c795698532ee5970ce898672625635d885eade9976e5a04949"},
+]
 
 [package.dependencies]
 nvidia-cublas-cu11 = {version = "11.10.3.66", markers = "platform_system == \"Linux\""}
@@ -101,6 +570,27 @@ typing-extensions = "*"
 [package.extras]
 opt-einsum = ["opt-einsum (>=3.3)"]
 
+[[package]]
+name = "tqdm"
+version = "4.65.0"
+description = "Fast, Extensible Progress Meter"
+category = "main"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "tqdm-4.65.0-py3-none-any.whl", hash = "sha256:c4f53a17fe37e132815abceec022631be8ffe1b9381c2e6e30aa70edc99e9671"},
+    {file = "tqdm-4.65.0.tar.gz", hash = "sha256:1871fb68a86b8fb3b59ca4cdd3dcccbc7e6d613eeed31f4c332531977b89beb5"},
+]
+
+[package.dependencies]
+colorama = {version = "*", markers = "platform_system == \"Windows\""}
+
+[package.extras]
+dev = ["py-make (>=0.1.0)", "twine", "wheel"]
+notebook = ["ipywidgets (>=6)"]
+slack = ["slack-sdk"]
+telegram = ["requests"]
+
 [[package]]
 name = "typing-extensions"
 version = "4.5.0"
@@ -108,22 +598,65 @@ description = "Backported and Experimental Type Hints for Python 3.7+"
 category = "main"
 optional = false
 python-versions = ">=3.7"
+files = [
+    {file = "typing_extensions-4.5.0-py3-none-any.whl", hash = "sha256:fb33085c39dd998ac16d1431ebc293a8b3eedd00fd4a32de0ff79002c19511b4"},
+    {file = "typing_extensions-4.5.0.tar.gz", hash = "sha256:5cb5f4a79139d699607b3ef622a1dedafa84e115ab0024e0d9c044a9479ca7cb"},
+]
+
+[[package]]
+name = "virtualenv"
+version = "20.23.0"
+description = "Virtual Python Environment builder"
+category = "dev"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "virtualenv-20.23.0-py3-none-any.whl", hash = "sha256:6abec7670e5802a528357fdc75b26b9f57d5d92f29c5462ba0fbe45feacc685e"},
+    {file = "virtualenv-20.23.0.tar.gz", hash = "sha256:a85caa554ced0c0afbd0d638e7e2d7b5f92d23478d05d17a76daeac8f279f924"},
+]
+
+[package.dependencies]
+distlib = ">=0.3.6,<1"
+filelock = ">=3.11,<4"
+importlib-metadata = {version = ">=6.4.1", markers = "python_version < \"3.8\""}
+platformdirs = ">=3.2,<4"
+
+[package.extras]
+docs = ["furo (>=2023.3.27)", "proselint (>=0.13)", "sphinx (>=6.1.3)", "sphinx-argparse (>=0.4)", "sphinxcontrib-towncrier (>=0.2.1a0)", "towncrier (>=22.12)"]
+test = ["covdefaults (>=2.3)", "coverage (>=7.2.3)", "coverage-enable-subprocess (>=1)", "flaky (>=3.7)", "packaging (>=23.1)", "pytest (>=7.3.1)", "pytest-env (>=0.8.1)", "pytest-freezegun (>=0.4.2)", "pytest-mock (>=3.10)", "pytest-randomly (>=3.12)", "pytest-timeout (>=2.1)", "setuptools (>=67.7.1)", "time-machine (>=2.9)"]
+
+[[package]]
+name = "wheel"
+version = "0.40.0"
+description = "A built-package format for Python"
+category = "main"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "wheel-0.40.0-py3-none-any.whl", hash = "sha256:d236b20e7cb522daf2390fa84c55eea81c5c30190f90f29ae2ca1ad8355bf247"},
+    {file = "wheel-0.40.0.tar.gz", hash = "sha256:cd1196f3faee2b31968d626e1731c94f99cbdb67cf5a46e4f5656cbee7738873"},
+]
+
+[package.extras]
+test = ["pytest (>=6.0.0)"]
+
+[[package]]
+name = "zipp"
+version = "3.15.0"
+description = "Backport of pathlib-compatible object wrapper for zip files"
+category = "dev"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "zipp-3.15.0-py3-none-any.whl", hash = "sha256:48904fc76a60e542af151aded95726c1a5c34ed43ab4134b597665c86d7ad556"},
+    {file = "zipp-3.15.0.tar.gz", hash = "sha256:112929ad649da941c23de50f356a2b5570c954b65150642bccdd66bf194d224b"},
+]
+
+[package.extras]
+docs = ["furo", "jaraco.packaging (>=9)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"]
+testing = ["big-O", "flake8 (<5)", "jaraco.functools", "jaraco.itertools", "more-itertools", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=1.3)", "pytest-flake8", "pytest-mypy (>=0.9.1)"]
 
 [metadata]
-lock-version = "1.1"
+lock-version = "2.0"
 python-versions = "^3.7"
-content-hash = "9ef847cc37187c3ac9c9d15c14106fcf4a6e3a8e37f76f01dede2a55f8246db9"
-
-[metadata.files]
-numpy = []
-nvidia-cublas-cu11 = []
-nvidia-cuda-nvrtc-cu11 = []
-nvidia-cuda-runtime-cu11 = []
-nvidia-cudnn-cu11 = []
-nvidia-ml-py3 = []
-protobuf = []
-pyrapl = []
-pyyaml = []
-toml = []
-torch = []
-typing-extensions = []
+content-hash = "36965fd0e199aa0f54dcaa642274c1af727cbb9d2cfda7d171123ea80137e943"
diff --git a/pyproject.toml b/pyproject.toml
index 9ebf294..b2f1837 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -36,6 +36,13 @@ deepview-predict = "*"
 
 [tool.poetry.dev-dependencies]
 
+[tool.poetry.group.dev.dependencies]
+ruff = "^0.0.267"
+pre-commit = "2.21.0"
+
 [build-system]
 requires = ["poetry-core>=1.0.0"]
 build-backend = "poetry.core.masonry.api"
+
+[tool.ruff]
+extend-exclude = ["examples", "deepview_profile/protocol_gen/"]
diff --git a/test/test_database.py b/test/test_database.py
index f1e63ef..d2c81be 100644
--- a/test/test_database.py
+++ b/test/test_database.py
@@ -2,6 +2,7 @@
 import random
 import deepview_profile.db.database as database
 
+
 class MockDatabaseInterface(database.DatabaseInterface):
     def __del__(self):
         if os.path.exists("test.sqlite"):
@@ -10,30 +11,39 @@ def __del__(self):
 
 class TestSkylineDatabase:
     test_database: MockDatabaseInterface = MockDatabaseInterface("test.sqlite")
-    energy_table_interface: database.EnergyTableInterface = database.EnergyTableInterface(test_database.connection)
+    energy_table_interface: database.EnergyTableInterface = (
+        database.EnergyTableInterface(test_database.connection)
+    )
 
     # Test if energy table is created
     def test_energy_table_is_created(self):
-        query_result = self.test_database.connection.execute("SELECT name from sqlite_schema WHERE type='table' and name ='ENERGY';")
+        query_result = self.test_database.connection.execute(
+            "SELECT name from sqlite_schema WHERE type='table' and name ='ENERGY';"
+        )
         query_result_list = query_result.fetchall()
-        assert(len(query_result_list) > 0)
+        assert len(query_result_list) > 0
 
     # try adding invalid entry and test if it is added
     def test_invalid_entry_too_short(self):
-        assert(self.energy_table_interface.is_valid_entry([]) == False)
-    
+        assert self.energy_table_interface.is_valid_entry([]) is False
+
     def test_invalid_entry_too_long(self):
-        assert(self.energy_table_interface.is_valid_entry([1,2,3,4,5]) == False)
+        assert self.energy_table_interface.is_valid_entry([1, 2, 3, 4, 5]) is False
 
     def test_invalid_entry_wrong_types(self):
-        assert(self.energy_table_interface.is_valid_entry([None, None, None, None, None]) == False)
+        assert (
+            self.energy_table_interface.is_valid_entry([None, None, None, None, None])
+            is False
+        )
 
     def test_adding_valid_entry(self):
         params = ["entry_point", random.random(), random.random(), random.randint()]
         self.energy_table_interface.add_entry(params)
-        query_result = self.test_database.connection.execute("SELECT * FROM ENERGY;").fetchone()
+        query_result = self.test_database.connection.execute(
+            "SELECT * FROM ENERGY;"
+        ).fetchone()
         # params is passed in by reference so it have the timestamp in it
-        assert(query_result == tuple(params))
+        assert query_result == tuple(params)
 
     # add 10 valid entries and get top 3
     def test_get_latest_n_entries_of_entry_point(self):
@@ -41,13 +51,22 @@ def test_get_latest_n_entries_of_entry_point(self):
             params = ["entry_point", random.random(), random.random(), random.randint()]
             self.energy_table_interface.add_entry(params)
         for _ in range(20):
-            params = ["other_entry_point", random.random(), random.random(), random.randint()]
+            params = [
+                "other_entry_point",
+                random.random(),
+                random.random(),
+                random.randint(),
+            ]
             self.energy_table_interface.add_entry(params)
         entries = []
         for _ in range(3):
             params = ["entry_point", random.random(), random.random(), random.randint()]
             entries.insert(0, params)
             self.energy_table_interface.add_entry(params)
-        latest_n_entries = self.energy_table_interface.get_latest_n_entries_of_entry_point(3, "entry_point")
+        latest_n_entries = (
+            self.energy_table_interface.get_latest_n_entries_of_entry_point(
+                3, "entry_point"
+            )
+        )
         entries = [tuple(entry) for entry in entries]
-        assert(entries == latest_n_entries)
+        assert entries == latest_n_entries
diff --git a/test/test_driver.py b/test/test_driver.py
index b67fb0d..6d5351b 100644
--- a/test/test_driver.py
+++ b/test/test_driver.py
@@ -1,6 +1,7 @@
 
 import pytest
-from utils import *
+import json
+from utils import SkylineSession, BackendContext
 
 with open("config.json", "r") as fp:
     config = json.load(fp)
@@ -8,7 +9,7 @@
 tests = list()
 for entry_point in config["entry_points"]:
     tests.append((config["skyline_bin"], entry_point))
-    
+
 @pytest.mark.parametrize("skyline_bin,entry_point", tests)
 def test_entry_point(skyline_bin, entry_point):
     print(f"Testing {entry_point}")
@@ -16,14 +17,15 @@ def test_entry_point(skyline_bin, entry_point):
     context.spawn_process()
 
     sess = SkylineSession()
-    while context.state == 0: pass
+    while context.state == 0:
+        pass
     sess.connect("localhost", 60120)
     sess.send_initialize_request()
     sess.send_analysis_request()
-    while len(sess.received_messages) < 4: pass
+    while len(sess.received_messages) < 4:
+        pass
 
     sess.cleanup()
     context.terminate()
 
     assert(len(sess.received_messages) == 4)
-    
diff --git a/test/utils.py b/test/utils.py
index 55ebc69..1991f11 100644
--- a/test/utils.py
+++ b/test/utils.py
@@ -6,12 +6,15 @@
 
 from deepview_profile.protocol_gen import innpv_pb2
 
+
 def stream_monitor(stream, callback=None):
     try:
-        for line in stream: callback(line)
-    except OSError as e:
+        for line in stream:
+            callback(line)
+    except OSError:
         print(f"Closing listener for stream {stream}")
 
+
 def socket_monitor(socket, callback=None):
     try:
         while True:
@@ -19,9 +22,10 @@ def socket_monitor(socket, callback=None):
             msg = socket.recv(msg_len)
             print(f"Received message of length {msg_len}")
             callback(msg)
-    except OSError as e:
+    except OSError:
         print(f"Closing listener for socket {socket}")
 
+
 class BackendContext:
     def __init__(self, skyline_bin, entry_point):
         self.process = None
@@ -45,10 +49,19 @@ def spawn_process(self):
         launch_command = [self.skyline_bin, "interactive", entry_filename]
 
         # Launch backend + listener threads for stdout and stderr
-        self.process = subprocess.Popen(launch_command, stdout=subprocess.PIPE, stderr=subprocess.PIPE, cwd=working_dir)
-        self.stdout_thread = threading.Thread(target=stream_monitor, args=(self.process.stdout, self.on_message_stdout))
+        self.process = subprocess.Popen(
+            launch_command,
+            stdout=subprocess.PIPE,
+            stderr=subprocess.PIPE,
+            cwd=working_dir,
+        )
+        self.stdout_thread = threading.Thread(
+            target=stream_monitor, args=(self.process.stdout, self.on_message_stdout)
+        )
         self.stdout_thread.start()
-        self.stderr_thread = threading.Thread(target=stream_monitor, args=(self.process.stderr, self.on_message_stderr))
+        self.stderr_thread = threading.Thread(
+            target=stream_monitor, args=(self.process.stderr, self.on_message_stderr)
+        )
         self.stderr_thread.start()
 
     def join(self):
@@ -58,8 +71,8 @@ def terminate(self):
         self.process.terminate()
         self.stdout_thread.join()
         self.stderr_thread.join()
-        
-        
+
+
 class SkylineSession:
     def __init__(self):
         self.seq_num = 0
@@ -69,7 +82,9 @@ def connect(self, addr, port):
         self.socket = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
         self.socket.connect((addr, port))
 
-        self.listener_thread = threading.Thread(target=socket_monitor, args=(self.socket, self.handle_message))
+        self.listener_thread = threading.Thread(
+            target=socket_monitor, args=(self.socket, self.handle_message)
+        )
         self.listener_thread.start()
 
     def send_message(self, message):
@@ -97,7 +112,7 @@ def send_analysis_request(self):
         request = innpv_pb2.AnalysisRequest()
         request.mock_response = False
         self.send_message(request)
-    
+
     def handle_message(self, message):
         from_server = innpv_pb2.FromServer()
         from_server.ParseFromString(message)
@@ -111,5 +126,3 @@ def cleanup(self):
         # Closing the socket should cause the listener thread to die
         self.socket.close()
         self.listener_thread.join()
-
-