Initial commit

app.py

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+import streamlit as st
+from streamlit_calendar import calendar
+import pandas as pd
+import database
+import datetime
+
+# --- Configuration ---
+st.set_page_config(page_title="Work Tracker", layout="wide")
+
+# --- Database Init ---
+if "db_initialized" not in st.session_state:
+    database.init_db()
+    st.session_state["db_initialized"] = True
+
+# --- UI Layout ---
+st.title("📅 Work Hours Tracker")
+
+col1, col2 = st.columns([2, 1])
+
+# --- Calendar Section ---
+with col1:
+    st.subheader("Select Work Days")
+    
+    # Fetch existing data to populate calendar
+    df = database.get_all_days()
+    
+    # Format events for streamlit-calendar
+    events = []
+    if not df.empty:
+        for date_str in df['date']:
+            events.append({
+                "title": "Worked",
+                "start": date_str,
+                "allDay": True,
+                "color": "#4CAF50" # Green for worked days
+            })
+
+    # Calendar options
+    calendar_options = {
+        "headerToolbar": {
+            "left": "today prev,next",
+            "center": "title",
+            "right": "dayGridMonth,dayGridWeek"
+        },
+        "initialView": "dayGridMonth",
+        "selectable": True,
+    }
+
+    # Render Calendar
+    cal = calendar(events=events, options=calendar_options, key="calendar")
+
+    # Handle Click Events
+    if cal.get("callback") == "dateClick":
+        clicked_date = cal["dateClick"]["dateStr"]
+        database.toggle_day(clicked_date)
+        st.rerun() # Refresh to update calendar and stats
+
+# --- Statistics Section ---
+with col2:
+    st.subheader("Statistics")
+    
+    if not df.empty:
+        # Convert to datetime
+        df['date'] = pd.to_datetime(df['date'])
+        df = df.sort_values('date')
+        
+        # Calculate weekly stats
+        # Resample to weekly frequency (W-MON)
+        weekly_counts = df.resample('W-MON', on='date').size()
+        
+        if not weekly_counts.empty:
+            avg_days_per_week = weekly_counts.mean()
+            st.metric("Avg Days / Week (Total)", f"{avg_days_per_week:.2f}")
+
+            # Plotting
+            st.line_chart(weekly_counts, use_container_width=True)
+            
+            # Monthly breakdown
+            monthly_counts = df.resample('M', on='date').size()
+            st.write("### Monthly Breakdown")
+            st.dataframe(monthly_counts.rename("Days Worked"))
+            
+    else:
+        st.info("No work days logged yet. Click dates on the calendar.")
+
+# --- Debugging (Optional) ---
+# with st.expander("Raw Data"):
+#     st.dataframe(df)