Update app.py

app.py

@@ -1,150 +1,89 @@
 import gradio as gr
 import pandas as pd
 import matplotlib.pyplot as plt
+from fpdf import FPDF
 import io
-from datetime import datetime
-from reportlab.lib.pagesizes import letter
-from reportlab.pdfgen import canvas
 
-REQUIRED_COLUMNS = ['DeviceID', 'Lab', 'Type', 'Timestamp', 'Status', 'UsageCount']
+df = pd.DataFrame()
 
-# ----------------------------
-# Load Logs Safely
-# ----------------------------
-def load_logs(file_obj):
+def upload_csv(file):
+    global df
     try:
-        if file_obj is not None:
-            df = pd.read_csv(file_obj.name)
-            df.columns = df.columns.str.strip()  # remove whitespace around column names
-            if not all(col in df.columns for col in REQUIRED_COLUMNS):
-                raise ValueError(f"CSV must contain columns: {', '.join(REQUIRED_COLUMNS)}")
-            df['Timestamp'] = pd.to_datetime(df['Timestamp'], errors='coerce')
-            df.dropna(subset=['Timestamp'], inplace=True)
-        else:
-            df = pd.DataFrame({
-                'DeviceID': ['D001', 'D002', 'D003'],
-                'Lab': ['Lab A', 'Lab B', 'Lab A'],
-                'Type': ['UV', 'Weight', 'Cell'],
-                'Timestamp': [pd.Timestamp('2025-06-01 09:00:00'),
-                              pd.Timestamp('2025-06-01 10:00:00'),
-                              pd.Timestamp('2025-06-01 11:00:00')],
-                'Status': ['OK', 'DOWN', 'OK'],
-                'UsageCount': [120, 85, 100]
-            })
-        return df
+        df = pd.read_csv(file.name)
+        required_columns = {'DeviceID', 'Lab', 'Type', 'Timestamp', 'Status', 'UsageCount'}
+        if not required_columns.issubset(df.columns):
+            return None, "CSV must contain columns: " + ", ".join(required_columns)
+        labs = ['All'] + sorted(df['Lab'].dropna().unique().tolist())
+        types = ['All'] + sorted(df['Type'].dropna().unique().tolist())
+        return (labs, types), ""
     except Exception as e:
-        raise ValueError(f"Failed to load CSV: {e}")
+        return None, f"Failed to load CSV: {str(e)}"
 
-# ----------------------------
-# Summarize Log Data
-# ----------------------------
-def summarize_logs(df, selected_lab, selected_type):
+def filter_and_plot(selected_lab, selected_type):
+    global df
+    if df.empty:
+        return None
+    filtered_df = df.copy()
     if selected_lab != "All":
-        df = df[df['Lab'] == selected_lab]
+        filtered_df = filtered_df[filtered_df["Lab"] == selected_lab]
     if selected_type != "All":
-        df = df[df['Type'] == selected_type]
-    summary = df.groupby(['Lab', 'Type'])['Status'].value_counts().unstack().fillna(0)
-    return summary
-
-# ----------------------------
-# Generate Chart
-# ----------------------------
-def generate_chart(df, selected_lab, selected_type):
-    summary = summarize_logs(df, selected_lab, selected_type)
-    fig, ax = plt.subplots(figsize=(8, 4))
-    summary.plot(kind='bar', stacked=True, ax=ax)
-    ax.set_title("Device Uptime/Downtime Summary")
-    ax.set_ylabel("Count")
-    ax.set_xlabel("Lab + Device Type")
-    ax.legend(title="Status")
-    fig.tight_layout()
-    return fig
-
-# ----------------------------
-# Export PDF using ReportLab
-# ----------------------------
-def export_pdf(df, selected_lab, selected_type):
-    summary = summarize_logs(df, selected_lab, selected_type)
-    buffer = io.BytesIO()
-    pdf = canvas.Canvas(buffer, pagesize=letter)
-    width, height = letter
-
-    pdf.setFont("Helvetica-Bold", 14)
-    pdf.drawCentredString(width / 2, height - 40, "LabOps Dashboard Summary Report")
-    pdf.setFont("Helvetica", 10)
-    pdf.drawCentredString(width / 2, height - 60, f"Generated: {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}")
-
-    y = height - 100
-    pdf.setFont("Helvetica-Bold", 10)
-    pdf.drawString(50, y, "Lab")
-    pdf.drawString(150, y, "Device Type")
-    pdf.drawString(300, y, "OK")
-    pdf.drawString(350, y, "DOWN")
-    y -= 20
-    pdf.setFont("Helvetica", 10)
-
-    for (lab, dev_type), row in summary.iterrows():
-        pdf.drawString(50, y, str(lab))
-        pdf.drawString(150, y, str(dev_type))
-        pdf.drawString(300, y, str(int(row.get('OK', 0))))
-        pdf.drawString(350, y, str(int(row.get('DOWN', 0))))
-        y -= 20
-        if y < 50:
-            pdf.showPage()
-            y = height - 50
-
-    pdf.save()
-    buffer.seek(0)
-    return ("LabOps_Summary.pdf", buffer.read())
+        filtered_df = filtered_df[filtered_df["Type"] == selected_type]
+    
+    # Prepare plot
+    plt.figure(figsize=(8, 4))
+    status_counts = filtered_df["Status"].value_counts()
+    status_counts.plot(kind="bar", color=["green", "red"])
+    plt.title("Status Counts")
+    plt.xlabel("Status")
+    plt.ylabel("Count")
+    
+    buf = io.BytesIO()
+    plt.savefig(buf, format="png")
+    buf.seek(0)
+    return buf
+
+def download_pdf(selected_lab, selected_type):
+    global df
+    if df.empty:
+        return None
+    filtered_df = df.copy()
+    if selected_lab != "All":
+        filtered_df = filtered_df[filtered_df["Lab"] == selected_lab]
+    if selected_type != "All":
+        filtered_df = filtered_df[filtered_df["Type"] == selected_type]
 
-# ----------------------------
-# Dashboard Interface Logic
-# ----------------------------
-def update_ui(file_obj):
-    try:
-        df = load_logs(file_obj)
-        labs = ["All"] + sorted(df['Lab'].unique().tolist())
-        types = ["All"] + sorted(df['Type'].unique().tolist())
-        return df, gr.Dropdown.update(choices=labs, value="All"), gr.Dropdown.update(choices=types, value="All"), gr.Textbox.update(visible=False)
-    except Exception as e:
-        return None, gr.Dropdown.update(choices=[], value=None), gr.Dropdown.update(choices=[], value=None), gr.Textbox.update(value=f"❌ Error: {e}", visible=True)
+    pdf = FPDF()
+    pdf.add_page()
+    pdf.set_font("Arial", size=12)
+    pdf.cell(200, 10, txt="LabOps Summary Report", ln=True, align='C')
+    pdf.ln(10)
 
-def dashboard(df, selected_lab, selected_type):
-    try:
-        return generate_chart(df, selected_lab, selected_type)
-    except Exception as e:
-        return gr.update(visible=True), gr.Textbox.update(value=f"❌ Error: {e}", visible=True)
+    for index, row in filtered_df.iterrows():
+        line = f"{row['Timestamp']} | {row['DeviceID']} | {row['Lab']} | {row['Type']} | {row['Status']} | {row['UsageCount']}"
+        pdf.multi_cell(0, 10, txt=line)
 
-def generate_pdf_button(df, selected_lab, selected_type):
-    try:
-        filename, pdf_bytes = export_pdf(df, selected_lab, selected_type)
-        return gr.File.update(value=(filename, pdf_bytes), visible=True), gr.Textbox.update(visible=False)
-    except Exception as e:
-        return gr.File.update(visible=False), gr.Textbox.update(value=f"❌ Error: {e}", visible=True)
+    output = io.BytesIO()
+    pdf.output(output)
+    output.seek(0)
+    return output
 
-# ----------------------------
-# Gradio Interface
-# ----------------------------
 with gr.Blocks() as demo:
-    gr.Markdown("## 🖊️ LabOps Dashboard with Filters")
-    gr.Markdown("Upload lab device logs, filter by Lab and Equipment Type, visualize uptime/downtime & generate PDF reports.")
-
-    df_state = gr.State()
+    gr.Markdown("🧪 **LabOps Dashboard with Filters**\nUpload lab device logs, filter by Lab and Equipment Type, visualize uptime/downtime & generate PDF reports.")
 
     with gr.Row():
-        file_input = gr.File(label="Upload Log CSV", file_types=[".csv"])
+        csv_input = gr.File(label="Upload Log CSV", file_types=[".csv"])
+    
+    with gr.Row():
         lab_dropdown = gr.Dropdown(label="Select Lab", choices=["All"])
         type_dropdown = gr.Dropdown(label="Select Equipment Type", choices=["All"])
 
-    plot_output = gr.Plot()
-    error_output = gr.Textbox(visible=False, label="Errors")
-    download_button = gr.Button("Download PDF Summary")
-    download_file = gr.File(label="Download PDF", visible=False)
+    plot_output = gr.Image(label="Plot")
+    download_btn = gr.Button("Download PDF Summary")
+    error_box = gr.Textbox(visible=False)
 
-    file_input.change(fn=update_ui, inputs=file_input, outputs=[df_state, lab_dropdown, type_dropdown, error_output])
-    lab_dropdown.change(fn=dashboard, inputs=[df_state, lab_dropdown, type_dropdown], outputs=plot_output)
-    type_dropdown.change(fn=dashboard, inputs=[df_state, lab_dropdown, type_dropdown], outputs=plot_output)
-    download_button.click(fn=generate_pdf_button, inputs=[df_state, lab_dropdown, type_dropdown], outputs=[download_file, error_output])
+    csv_input.change(fn=upload_csv, inputs=csv_input, outputs=[(lab_dropdown, type_dropdown), error_box])
+    lab_dropdown.change(fn=filter_and_plot, inputs=[lab_dropdown, type_dropdown], outputs=plot_output)
+    type_dropdown.change(fn=filter_and_plot, inputs=[lab_dropdown, type_dropdown], outputs=plot_output)
+    download_btn.click(fn=download_pdf, inputs=[lab_dropdown, type_dropdown], outputs=gr.File())
 
-if __name__ == '__main__':
-    demo.launch()
+demo.launch()