feat: Improve dashboard functionality and stability

This commit introduces several improvements to the dashboard:

- Refactored the component structure for consistency, defining callbacks within the `render` function.
- Added robust error handling to data loading and callbacks to prevent crashes.
- Implemented linking for SO and AIR columns in the source table.
- Added and improved filtering and display options for tables.
- Left-aligned columns in tables for better readability.
- Cleaned up unused component files.

src/components/data_table.py

@@ -7,15 +7,6 @@ import dash_bootstrap_components as dbc
 from ..data.loader_gz import MTBFSchema
 from . import ids
 
-import pandas as pd
-from dash import Dash, dcc, html, dash_table, Input, Output, State, callback_context
-from datetime import datetime
-import os
-import dash_bootstrap_components as dbc
-
-from ..data.loader_gz import MTBFSchema
-from . import ids
-
 def render(app: Dash, data: pd.DataFrame) -> html.Div:
     @app.callback(
         Output(ids.DATA_TABLE, "children"),
@@ -24,46 +15,68 @@ def render(app: Dash, data: pd.DataFrame) -> html.Div:
             Input(ids.WEEK_DROPDOWN, "value"),
             Input(ids.PU_HITS_SELECTOR, "value"),
             Input(ids.SINGLE_HITTER_FILTER, "value"),
+            Input(ids.SYSTEM_FILTER, "value"),
+            Input("span", "value"),
         ],
     )
     def update_data_table(
-        years: list[str], weeks: list[str], u_hits: bool, remove_single: bool
+        year: int, week: int, u_hits: bool, remove_single: bool, systems: list[str], span: int
     ) -> html.Div:
-        filtered_data = data.query(
-            "year in @years and week in @weeks"
-        )
-        if filtered_data.shape[0] == 0:
-            return html.Div("No data selected.")
+        try:
+            print(f'year: {year}, week: {week}, span: {span}, systems: {systems}')
+            if not all([year, week, span]):
+                return html.Div("No data selected.")
 
-        hits_col = MTBFSchema.U_HITS if u_hits else MTBFSchema.P_HITS
-
-        # Count 'Y' values
-        hits_data = filtered_data[filtered_data[hits_col] == 'Y']
-        
-        table_data = hits_data.groupby(MTBFSchema.AIR).agg(
-            count=(hits_col, 'size'),
-            air_issue_description=(MTBFSchema.AIR_ISSUE_DESCRIPTION, lambda x: ', '.join(x.dropna().astype(str).unique())),
-            close_notes=(MTBFSchema.CLOSE_NOTES, lambda x: ', '.join(x.dropna().astype(str).unique()))
-        ).reset_index()
-
-        if remove_single:
-            table_data = table_data[table_data['count'] > 1]
+            years = [year]
             
-        table_data = table_data.sort_values('count', ascending=False)
-        
-        # Reorder columns
-        table_data = table_data[[MTBFSchema.AIR, 'air_issue_description', 'close_notes', 'count']]
+            start_week = week - span + 1
+            weeks = list(range(start_week, week + 1))
 
-        return dash_table.DataTable(
-            id=ids.MTBF_PAR_TABLE, # Using this ID for feedback callbacks
-            data=table_data.to_dict("records"),
-            columns=[{"name": i, "id": i} for i in table_data.columns],
-            page_size=10,
-            row_selectable='single',
-            selected_rows=[],
-            filter_action='native',
-            sort_action='native'
-        )
+            filtered_data = data.query(
+                "year in @years and Week_Number in @weeks and System in @systems"
+            )
+            if filtered_data.shape[0] == 0:
+                return html.Div("No data selected.")
+
+            hits_col = MTBFSchema.U_HITS if u_hits else MTBFSchema.P_HITS
+
+            # Count 'Y' values
+            hits_data = filtered_data[filtered_data[hits_col] == 'Y']
+            
+            table_data = hits_data.groupby([MTBFSchema.AIR, MTBFSchema.SYSTEM]).agg(
+                count=(hits_col, 'size'),
+                air_issue_description=(MTBFSchema.AIR_ISSUE_DESCRIPTION, lambda x: ', '.join(x.dropna().astype(str).unique())),
+                close_notes=(MTBFSchema.CLOSE_NOTES, lambda x: ', '.join(x.dropna().astype(str).unique()))
+            ).reset_index()
+
+            if remove_single:
+                table_data = table_data[table_data['count'] > 1]
+            
+            table_data['air_issue_description'] = table_data['air_issue_description'].apply(lambda s: s[:80] + '...' if len(s) > 80 else s)
+
+            table_data = table_data.sort_values('count', ascending=False)
+            
+            # Reorder columns
+            table_data = table_data[[MTBFSchema.AIR, MTBFSchema.SYSTEM, 'air_issue_description', 'close_notes', 'count']]
+
+            return dash_table.DataTable(
+                id=ids.MTBF_PAR_TABLE, # Using this ID for feedback callbacks
+                data=table_data.to_dict("records"),
+                columns=[{"name": i, "id": i} for i in table_data.columns],
+                page_size=10,
+                row_selectable='single',
+                selected_rows=[],
+                filter_action='native',
+                sort_action='native',
+                style_cell_conditional=[
+                    {
+                        'if': {'column_id': c},
+                        'textAlign': 'left'
+                    } for c in ['Close_notes', 'count']
+                ]
+            )
+        except Exception as e:
+            return html.Div(f"An error occurred in data_table: {e}")
 
     @app.callback(
         Output(ids.FEEDBACK_MODAL, "is_open"),