refactor: replace month dropdown with week dropdown and update related components

feat: add feedback functionality and modal for category feedback
style: add feedback button styles in CSS
docs: add explanation tab for dashboard usage instructions

assets/style.css

@@ -59,3 +59,17 @@ hr {
         grid-template-columns: 1fr;
     }
 }
+
+.feedback-button {
+    background-color: #007bff;
+    color: white;
+    border: none;
+    padding: 5px 10px;
+    text-align: center;
+    text-decoration: none;
+    display: inline-block;
+    font-size: 12px;
+    margin: 2px 2px;
+    cursor: pointer;
+    border-radius: 4px;
+}

data/feedback.csv

@@ -0,0 +1,2 @@
+timestamp,category,comment
+2025-09-07 20:02:38,groceries,"ABZT please change this air to P1231313"

main.py

@@ -1,6 +1,6 @@
 # initial commit
 from dash import Dash
-from dash_bootstrap_components.themes import BOOTSTRAP
+import dash_bootstrap_components as dbc
 
 from src.components.layout import create_layout
 from src.data.loader_gz import load_spc_data
@@ -17,10 +17,11 @@ with open(config_file) as config_f:
 
 def main() -> None:
     print(os.getenv("MY_ENV_VAR"))
+    print(config["Startup"])
     # load the data and create the data manager
     data = load_spc_data(config["DATA_PATH"])
 
-    app = Dash(external_stylesheets=[BOOTSTRAP])
+    app = Dash(external_stylesheets=[dbc.themes.LUX])
     app.title = "Reliability Dashboard"
     app.layout = create_layout(app, data)
     app.run()

pyproject.toml

@@ -7,4 +7,5 @@ requires-python = ">=3.11"
 dependencies = [
     "dash>=3.2.0",
     "dash-bootstrap-components>=2.0.4",
+    "dotenv>=0.9.9",
 ]

src/components/bar_chart.py

@@ -12,15 +12,15 @@ def render(app: Dash, data: pd.DataFrame) -> html.Div:
         Output(ids.BAR_CHART, "children"),
         [
             Input(ids.YEAR_DROPDOWN, "value"),
-            Input(ids.MONTH_DROPDOWN, "value"),
+            Input(ids.WEEK_DROPDOWN, "value"),
             Input(ids.CATEGORY_DROPDOWN, "value"),
         ],
     )
     def update_bar_chart(
-        years: list[str], months: list[str], categories: list[str]
+        years: list[str], weeks: list[str], categories: list[str]
     ) -> html.Div:
         filtered_data = data.query(
-            "year in @years and month in @months and category in @categories"
+            "year in @years and week in @weeks and category in @categories"
         )
 
         if filtered_data.shape[0] == 0:

src/components/category_dropdown.py

@@ -14,12 +14,12 @@ def render(app: Dash, data: pd.DataFrame) -> html.Div:
         Output(ids.CATEGORY_DROPDOWN, "value"),
         [
             Input(ids.YEAR_DROPDOWN, "value"),
-            Input(ids.MONTH_DROPDOWN, "value"),
+            Input(ids.WEEK_DROPDOWN, "value"),
             Input(ids.SELECT_ALL_CATEGORIES_BUTTON, "n_clicks"),
         ],
     )
-    def select_all_categories(years: list[str], months: list[str], _: int) -> list[str]:
-        filtered_data = data.query("year in @years and month in @months")
+    def select_all_categories(years: list[str], weeks: list[str], _: int) -> list[str]:
+        filtered_data = data.query("year in @years and week in @weeks")
         return sorted(set(filtered_data[DataSchema.CATEGORY].tolist()))
 
     return html.Div(

src/components/data_table.py

@@ -1,48 +1,123 @@
 import pandas as pd
-import plotly.express as px
-from dash import Dash, dcc, html
-from dash.dependencies import Input, Output
+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 import DataSchema
 from . import ids
 
-
 def render(app: Dash, data: pd.DataFrame) -> html.Div:
     @app.callback(
-        Output(ids.BAR_CHART, "children"),
+        Output(ids.DATA_TABLE, "children"),
         [
             Input(ids.YEAR_DROPDOWN, "value"),
-            Input(ids.MONTH_DROPDOWN, "value"),
+            Input(ids.WEEK_DROPDOWN, "value"),
             Input(ids.CATEGORY_DROPDOWN, "value"),
         ],
     )
-    def update_bar_chart(
-        years: list[str], months: list[str], categories: list[str]
+    def update_data_table(
+        years: list[str], weeks: list[str], categories: list[str]
     ) -> html.Div:
         filtered_data = data.query(
-            "year in @years and month in @months and category in @categories"
+            "year in @years and week in @weeks and category in @categories"
         )
 
         if filtered_data.shape[0] == 0:
-            return html.Div("No data selected.", id=ids.BAR_CHART)
+            return html.Div("No data selected.")
 
-        def create_pivot_table() -> pd.DataFrame:
         pt = filtered_data.pivot_table(
             values=DataSchema.AMOUNT,
             index=[DataSchema.CATEGORY],
             aggfunc="sum",
             fill_value=0,
             dropna=False,
-            )
-            return pt.reset_index().sort_values(DataSchema.AMOUNT, ascending=False)
+        ).reset_index().sort_values(DataSchema.AMOUNT, ascending=False)
 
-        fig = px.bar(
-            create_pivot_table(),
-            x=DataSchema.CATEGORY,
-            y=DataSchema.AMOUNT,
-            color=DataSchema.CATEGORY,
+        columns = [{"name": i.capitalize(), "id": i} for i in pt.columns]
+
+        return dash_table.DataTable(
+            id=ids.CATEGORY_TABLE,
+            data=pt.to_dict("records"),
+            columns=columns,
+            row_selectable='single',
+            selected_rows=[]
         )
 
-        return html.Div(dcc.Graph(figure=fig), id=ids.BAR_CHART)
+    @app.callback(
+        Output(ids.FEEDBACK_MODAL, "is_open"),
+        Output(ids.FEEDBACK_MESSAGE, "children"),
+        Input(ids.CATEGORY_TABLE, "selected_rows"),
+        Input(ids.SAVE_FEEDBACK_BUTTON_POPUP, "n_clicks"),
+        Input(ids.CLOSE_FEEDBACK_BUTTON_POPUP, "n_clicks"),
+        State(ids.FEEDBACK_MODAL, "is_open"),
+        State(ids.CATEGORY_TABLE, "data"),
+        State(ids.FEEDBACK_INPUT, "value"),
+    )
+    def handle_feedback_modal(selected_rows, save_clicks, close_clicks, is_open, data, comment):
+        ctx = callback_context
+        if not ctx.triggered:
+            return False, ""
 
-    return html.Div(id=ids.BAR_CHART)
+        triggered_id = ctx.triggered[0]['prop_id'].split('.')[0]
+        
+        if triggered_id == ids.CATEGORY_TABLE and selected_rows:
+            return True, ""
+
+        if triggered_id == ids.SAVE_FEEDBACK_BUTTON_POPUP and selected_rows:
+            selected_row_data = data[selected_rows[0]]
+            category = selected_row_data[DataSchema.CATEGORY]
+            timestamp = datetime.now().strftime('%Y-%m-%d %H:%M:%S')
+            if not comment:
+                comment = ""
+            feedback_data = f'{timestamp},{category},"{comment}"\n'
+            file_path = "data/feedback.csv"
+            try:
+                is_new_file = not os.path.exists(file_path) or os.path.getsize(file_path) == 0
+                with open(file_path, "a") as f:
+                    if is_new_file:
+                        f.write("timestamp,category,comment\n")
+                    f.write(feedback_data)
+                message = f"Feedback for category '{category}' has been saved successfully at {timestamp}."
+                return False, message
+            except Exception as e:
+                return True, "An error occurred while saving feedback."
+
+        if triggered_id == ids.CLOSE_FEEDBACK_BUTTON_POPUP:
+            return False, ""
+
+        return is_open, ""
+
+    @app.callback(
+        Output("feedback-category-label", "children"),
+        Input(ids.CATEGORY_TABLE, "selected_rows"),
+        State(ids.CATEGORY_TABLE, "data"),
+        prevent_initial_call=True
+    )
+    def update_feedback_category_label(selected_rows, data):
+        if selected_rows:
+            category = data[selected_rows[0]][DataSchema.CATEGORY]
+            return f"Category: {category}"
+        return "Category: "
+
+    modal = dbc.Modal(
+        [
+            dbc.ModalHeader(dbc.ModalTitle("Submit Feedback")),
+            dbc.ModalBody([
+                html.H6("Category: ", id="feedback-category-label"),
+                dcc.Input(id=ids.FEEDBACK_INPUT, type='text', placeholder='Enter feedback...', style={'width': '100%'}),
+            ]),
+            dbc.ModalFooter([
+                dbc.Button("Save", id=ids.SAVE_FEEDBACK_BUTTON_POPUP, className="ms-auto", n_clicks=0),
+                dbc.Button("Close", id=ids.CLOSE_FEEDBACK_BUTTON_POPUP, className="ms-auto", n_clicks=0)
+            ]),
+        ],
+        id=ids.FEEDBACK_MODAL,
+        is_open=False,
+    )
+
+    return html.Div([
+        html.Div(id=ids.DATA_TABLE),
+        html.Div(id=ids.FEEDBACK_MESSAGE),
+        modal
+    ])

src/components/explanation_tab.py

@@ -0,0 +1,22 @@
+from dash import Dash, dcc, html
+
+def render(_: Dash) -> html.Div:
+    return html.Div([
+        dcc.Markdown("""
+            ### How to use this Dashboard
+
+            **Dashboard Tab:**
+            - Use the dropdowns at the top to filter the data by year, week, and category.
+            - The bar chart shows the total amount per category for the selected period.
+            - The data table shows the detailed data.
+
+            **Feedback:**
+            - In the data table on the Dashboard tab, you can select a row to provide feedback.
+            - A popup will appear where you can enter your comments for the selected category.
+            - Click "Save" to store your feedback.
+
+            **Feedback Tab:**
+            - This tab displays all the feedback that has been submitted.
+            - The table on this tab updates automatically every 5 seconds.
+        """)
+    ])

src/components/feedback_tab.py

@@ -0,0 +1,27 @@
+from dash import Dash, dcc, html, dash_table
+from dash.dependencies import Input, Output
+import pandas as pd
+
+def render(app: Dash) -> html.Div:
+    @app.callback(
+        Output("feedback-table-content", "children"),
+        Input("feedback-interval", "n_intervals")
+    )
+    def update_feedback_table(_):
+        try:
+            feedback_df = pd.read_csv("data/feedback.csv")
+            return dash_table.DataTable(
+                data=feedback_df.to_dict("records"),
+                columns=[{"name": i, "id": i} for i in feedback_df.columns],
+                page_size=10,
+            )
+        except FileNotFoundError:
+            return html.P("No feedback submitted yet.")
+        except Exception as e:
+            return html.P(f"An error occurred: {e}")
+
+    return html.Div([
+        html.H4("Submitted Feedback"),
+        html.Div(id="feedback-table-content"),
+        dcc.Interval(id="feedback-interval", interval=5 * 1000, n_intervals=0) # 5 seconds
+    ])

src/components/ids.py

@@ -5,8 +5,16 @@ DATA_TABLE = "data-table"
 SELECT_ALL_CATEGORIES_BUTTON = "select-all-categories-button"
 CATEGORY_DROPDOWN = "category-dropdown"
 
-SELECT_ALL_MONTHS_BUTTON = "select-all-months-button"
-MONTH_DROPDOWN = "month-dropdown"
-
 YEAR_DROPDOWN = "year-dropdown"
 SELECT_ALL_YEARS_BUTTON = "select-all-years-button"
+
+WEEK_DROPDOWN = "week-dropdown"
+SELECT_ALL_WEEKS_BUTTON = "select-all-weeks-button"
+
+CATEGORY_TABLE = "category-table"
+
+FEEDBACK_INPUT = "feedback-input"
+FEEDBACK_MESSAGE = "feedback-message"
+FEEDBACK_MODAL = "feedback-modal"
+SAVE_FEEDBACK_BUTTON_POPUP = "save-feedback-button-popup"
+CLOSE_FEEDBACK_BUTTON_POPUP = "close-feedback-button-popup"

src/components/layout.py

@@ -1,29 +1,48 @@
 import pandas as pd
-from dash import Dash, html
+from dash import Dash, dcc, html
 from src.components import (
     bar_chart,
-    category_dropdown,
-    month_dropdown,
-    pie_chart,
+    data_table,
     year_dropdown,
+    week_dropdown,
+    category_dropdown,
+    feedback_tab,
+    explanation_tab,
 )
 
-
 def create_layout(app: Dash, data: pd.DataFrame) -> html.Div:
+    tab_content_style = {'height': 'calc(100vh - 220px)', 'overflowY': 'auto', 'padding': '15px'}
+
     return html.Div(
         className="app-div",
         children=[
             html.H1(app.title),
             html.Hr(),
+            dcc.Tabs(id="tabs", value='tab-dashboard', children=[
+                dcc.Tab(label='Dashboard', value='tab-dashboard', children=[
+                    html.Div(style=tab_content_style, children=[
                         html.Div(
                             className="dropdown-container",
                             children=[
                                 year_dropdown.render(app, data),
-                    month_dropdown.render(app, data),
+                                week_dropdown.render(app, data),
                                 category_dropdown.render(app, data),
                             ],
                         ),
                         bar_chart.render(app, data),
-            pie_chart.render(app, data),
+                        data_table.render(app, data),
+                    ])
+                ]),
+                dcc.Tab(label='Feedback', value='tab-feedback', children=[
+                    html.Div(style=tab_content_style, children=[
+                        feedback_tab.render(app)
+                    ])
+                ]),
+                dcc.Tab(label='Explanation', value='tab-explanation', children=[
+                    html.Div(style=tab_content_style, children=[
+                        explanation_tab.render(app)
+                    ])
+                ]),
+            ]),
         ],
     )

src/components/month_dropdown.py

@@ -1,40 +0,0 @@
-import pandas as pd
-from dash import Dash, dcc, html
-from dash.dependencies import Input, Output
-
-from ..data.loader import DataSchema
-from . import ids
-
-
-def render(app: Dash, data: pd.DataFrame) -> html.Div:
-    all_months: list[str] = data[DataSchema.MONTH].tolist()
-    unique_months = sorted(set(all_months))
-
-    @app.callback(
-        Output(ids.MONTH_DROPDOWN, "value"),
-        [
-            Input(ids.YEAR_DROPDOWN, "value"),
-            Input(ids.SELECT_ALL_MONTHS_BUTTON, "n_clicks"),
-        ],
-    )
-    def select_all_months(years: list[str], _: int) -> list[str]:
-        filtered_data = data.query("year in @years")
-        return sorted(set(filtered_data[DataSchema.MONTH].tolist()))
-
-    return html.Div(
-        children=[
-            html.H6("Month"),
-            dcc.Dropdown(
-                id=ids.MONTH_DROPDOWN,
-                options=[{"label": month, "value": month} for month in unique_months],
-                value=unique_months,
-                multi=True,
-            ),
-            html.Button(
-                className="dropdown-button",
-                children=["Select All"],
-                id=ids.SELECT_ALL_MONTHS_BUTTON,
-                n_clicks=0,
-            ),
-        ]
-    )

src/components/week_dropdown.py

@@ -0,0 +1,53 @@
+import pandas as pd
+from dash import Dash, dcc, html
+from dash.dependencies import Input, Output
+from datetime import datetime, timedelta
+
+from ..data.loader import DataSchema
+from . import ids
+
+def render(app: Dash, data: pd.DataFrame) -> html.Div:
+    all_weeks: list[str] = data[DataSchema.WEEK].tolist()
+    unique_weeks = sorted(set(all_weeks), reverse=True)
+
+    # determine default weeks (last 13)
+    today = datetime.now()
+    last_13_weeks = []
+    for i in range(13):
+        date = today - timedelta(weeks=i)
+        year, week, _ = date.isocalendar()
+        last_13_weeks.append(f"{year}{week:02d}")
+
+    default_weeks = [week for week in last_13_weeks if week in unique_weeks]
+    if not default_weeks and unique_weeks:
+        default_weeks = unique_weeks[:13]
+
+
+    @app.callback(
+        Output(ids.WEEK_DROPDOWN, "value"),
+        [
+            Input(ids.YEAR_DROPDOWN, "value"),
+            Input(ids.SELECT_ALL_WEEKS_BUTTON, "n_clicks"),
+        ],
+    )
+    def select_all_weeks(years: list[str], _: int) -> list[str]:
+        filtered_data = data.query("year in @years")
+        return sorted(set(filtered_data[DataSchema.WEEK].tolist()))
+
+    return html.Div(
+        children=[
+            html.H6("Week"),
+            dcc.Dropdown(
+                id=ids.WEEK_DROPDOWN,
+                options=[{"label": f"{week[:4]}-{week[4:]}", "value": week} for week in unique_weeks],
+                value=default_weeks,
+                multi=True,
+            ),
+            html.Button(
+                className="dropdown-button",
+                children=["Select All"],
+                id=ids.SELECT_ALL_WEEKS_BUTTON,
+                n_clicks=0,
+            ),
+        ]
+    )

src/data/loader.py

@@ -7,6 +7,7 @@ class DataSchema:
     DATE = "date"
     MONTH = "month"
     YEAR = "year"
+    WEEK = "week"
 
 
 def load_transaction_data(path: str) -> pd.DataFrame:
@@ -22,4 +23,8 @@ def load_transaction_data(path: str) -> pd.DataFrame:
     )
     data[DataSchema.YEAR] = data[DataSchema.DATE].dt.year.astype(str)
     data[DataSchema.MONTH] = data[DataSchema.DATE].dt.month.astype(str)
+    data[DataSchema.WEEK] = (
+        data[DataSchema.DATE].dt.isocalendar().year.astype(str)
+        + data[DataSchema.DATE].dt.isocalendar().week.astype(str).str.zfill(2)
+    )
     return data

src/data/loader_gz.py

@@ -6,6 +6,7 @@ class DataSchema:
     DATE = "date"
     MONTH = "month"
     YEAR = "year"
+    WEEK = "week"
 
 class SPC_Schema:
     FC = "FC"
@@ -30,4 +31,8 @@ def load_spc_data(path: str) -> pd.DataFrame:
     )
     data[DataSchema.YEAR] = data[DataSchema.DATE].dt.year.astype(str)
     data[DataSchema.MONTH] = data[DataSchema.DATE].dt.month.astype(str)
+    data[DataSchema.WEEK] = (
+        data[DataSchema.DATE].dt.isocalendar().year.astype(str)
+        + data[DataSchema.DATE].dt.isocalendar().week.astype(str).str.zfill(2)
+    )
     return data

uv.lock

@@ -9,12 +9,14 @@ source = { virtual = "." }
 dependencies = [
     { name = "dash" },
     { name = "dash-bootstrap-components" },
+    { name = "dotenv" },
 ]
 
 [package.metadata]
 requires-dist = [
     { name = "dash", specifier = ">=3.2.0" },
     { name = "dash-bootstrap-components", specifier = ">=2.0.4" },
+    { name = "dotenv", specifier = ">=0.9.9" },
 ]
 
 [[package]]
@@ -141,6 +143,17 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/d6/38/1efeec8b4d741c09ccd169baf8a00c07a0176b58e418d4cd0c30dffedd22/dash_bootstrap_components-2.0.4-py3-none-any.whl", hash = "sha256:767cf0084586c1b2b614ccf50f79fe4525fdbbf8e3a161ed60016e584a14f5d1", size = 204044 },
 ]
 
+[[package]]
+name = "dotenv"
+version = "0.9.9"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "python-dotenv" },
+]
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/b2/b7/545d2c10c1fc15e48653c91efde329a790f2eecfbbf2bd16003b5db2bab0/dotenv-0.9.9-py2.py3-none-any.whl", hash = "sha256:29cf74a087b31dafdb5a446b6d7e11cbce8ed2741540e2339c69fbef92c94ce9", size = 1892 },
+]
+
 [[package]]
 name = "flask"
 version = "3.1.2"
@@ -288,6 +301,15 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/95/a9/12e2dc726ba1ba775a2c6922d5d5b4488ad60bdab0888c337c194c8e6de8/plotly-6.3.0-py3-none-any.whl", hash = "sha256:7ad806edce9d3cdd882eaebaf97c0c9e252043ed1ed3d382c3e3520ec07806d4", size = 9791257 },
 ]
 
+[[package]]
+name = "python-dotenv"
+version = "1.1.1"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/f6/b0/4bc07ccd3572a2f9df7e6782f52b0c6c90dcbb803ac4a167702d7d0dfe1e/python_dotenv-1.1.1.tar.gz", hash = "sha256:a8a6399716257f45be6a007360200409fce5cda2661e3dec71d23dc15f6189ab", size = 41978 }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/5f/ed/539768cf28c661b5b068d66d96a2f155c4971a5d55684a514c1a0e0dec2f/python_dotenv-1.1.1-py3-none-any.whl", hash = "sha256:31f23644fe2602f88ff55e1f5c79ba497e01224ee7737937930c448e4d0e24dc", size = 20556 },
+]
+
 [[package]]
 name = "requests"
 version = "2.32.5"