Update src/streamlit_app.py

src/streamlit_app.py

@@ -1,40 +1,131 @@
-import altair as alt
-import numpy as np
-import pandas as pd
 import streamlit as st
+import pandas as pd
+import json
+from datetime import datetime
+import io
+import os
+
+# Funzione di conversione
+def convert_json_to_excel_data(json_file_content: str, sheet_name: str = 'Dati Ordine'):
+    try:
+        json_data = json.loads(json_file_content)
+
+        channel = json_data.get('channel')
+        company_code = json_data.get('companyCode')
+        site_code = json_data.get('siteCode')
+
+        order_info = json_data.get('order', {})
+        order_number = order_info.get('orderNumber')
+        order_date_str = order_info.get('orderDate')
+        partner_code = order_info.get('partnerCode')
+        
+        order_date_formatted = None
+        if order_date_str:
+            try:
+                dt_object = datetime.fromisoformat(order_date_str.replace('Z', '+00:00'))
+                order_date_formatted = dt_object.strftime('%d/%m/%Y')
+            except ValueError:
+                st.warning(f"Attenzione: Impossibile parsare la data '{order_date_str}'. Verrà usata la stringa originale.")
+                order_date_formatted = order_date_str
+
+        details = order_info.get('details', [])
+
+        processed_data = []
+        for item in details:
+            row = {
+                'Site': site_code,
+                'Data': order_date_formatted,
+                'Company': company_code,
+                'Furniture': partner_code,
+                'Stato': 'CREATED',
+                'Posizione': item.get('positionId'),
+                'Stato. Articolo': None, 
+                'Codice Articolo': item.get('itemCode'),
+                'Quantità': item.get('quantity'),
+                'Proprietario': item.get('stockOwner'),
+                'Centro di Costo': item.get('warehouse'),
+                'Disponibilità': item.get('availability'),
+                'RefOrder': item.get('refOrder'),
+                'ReasonCO': item.get('reasonCode'),
+                'CancelPosOdA': False if item.get('cancelPosOdA') is None else bool(item.get('cancelPosOdA'))
+            }
+            processed_data.append(row)
+
+        if not processed_data:
+            st.error("Nessun dato di dettaglio trovato per la conversione. Assicurati che il JSON contenga 'order.details'.")
+            return None
+
+        df = pd.DataFrame(processed_data)
+        return df
+
+    except json.JSONDecodeError:
+        st.error(f"Errore: Il contenuto del file non è un JSON valido.")
+        return None
+    except KeyError as ke:
+        st.error(f"Errore: Chiave JSON mancante o struttura inattesa: {ke}. Assicurati che il JSON abbia la struttura attesa (es. 'order.details').")
+        return None
+    except Exception as e:
+        st.error(f"Si è verificato un errore durante la conversione: {e}")
+        return None
+
+# --- Interfaccia Streamlit ---
+st.title("Convertitore JSON a Excel Ordini")
+st.write("Carica il tuo file JSON degli ordini e scarica il foglio Excel formattato.")
+
+uploaded_file = st.file_uploader("Scegli un file JSON", type=["json"])
+
+if uploaded_file is not None:
+    file_name = uploaded_file.name
+    _, file_extension = os.path.splitext(file_name)
+
+    if file_extension.lower() != '.json':
+        st.error("Per favore, carica un file con estensione .json.")
+    else:
+        json_content_bytes = uploaded_file.read()
+        json_content_string = json_content_bytes.decode('utf-8')
+
+        st.info(f"File '{file_name}' caricato. Tentativo di conversione...")
+
+        df_output = convert_json_to_excel_data(json_content_string)
+
+        if df_output is not None:
+            st.success("Conversione completata!")
+            
+            output = io.BytesIO()
+            writer = pd.ExcelWriter(output, engine='xlsxwriter')
+            df_output.to_excel(writer, sheet_name='Dati Ordine', index=False)
+
+            workbook = writer.book
+            worksheet = writer.sheets['Dati Ordine']
+
+            header_format = workbook.add_format({
+                'bold': True, 'font_color': '#FFFFFF', 'bg_color': '#4F81BD',
+                'align': 'center', 'valign': 'vcenter', 'border': 1
+            })
+            
+            col_widths = {
+                'Site': 10, 'Data': 12, 'Company': 15, 'Furniture': 15, 'Stato': 10,
+                'Posizione': 10, 'Stato. Articolo': 15, 'Codice Articolo': 25,
+                'Quantità': 10, 'Proprietario': 15, 'Centro di Costo': 15,
+                'Disponibilità': 15, 'RefOrder': 15, 'ReasonCO': 10, 'CancelPosOdA': 15
+            }
+
+            for col_num, col_name in enumerate(df_output.columns.values):
+                worksheet.write(0, col_num, col_name, header_format)
+                if col_name in col_widths:
+                    worksheet.set_column(col_num, col_num, col_widths[col_name])
+                else:
+                    worksheet.set_column(col_num, col_num, 15)
+            
+            writer.close()
+            output.seek(0)
+
+            st.download_button(
+                label="Scarica file Excel",
+                data=output.getvalue(),
+                file_name="ordine_convertito.xlsx",
+                mime="application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
+            )
 
-"""
-# Welcome to Streamlit!
-
-Edit `/streamlit_app.py` to customize this app to your heart's desire :heart:.
-If you have any questions, checkout our [documentation](https://docs.streamlit.io) and [community
-forums](https://discuss.streamlit.io).
-
-In the meantime, below is an example of what you can do with just a few lines of code:
-"""
-
-num_points = st.slider("Number of points in spiral", 1, 10000, 1100)
-num_turns = st.slider("Number of turns in spiral", 1, 300, 31)
-
-indices = np.linspace(0, 1, num_points)
-theta = 2 * np.pi * num_turns * indices
-radius = indices
-
-x = radius * np.cos(theta)
-y = radius * np.sin(theta)
-
-df = pd.DataFrame({
-    "x": x,
-    "y": y,
-    "idx": indices,
-    "rand": np.random.randn(num_points),
-})
-
-st.altair_chart(alt.Chart(df, height=700, width=700)
-    .mark_point(filled=True)
-    .encode(
-        x=alt.X("x", axis=None),
-        y=alt.Y("y", axis=None),
-        color=alt.Color("idx", legend=None, scale=alt.Scale()),
-        size=alt.Size("rand", legend=None, scale=alt.Scale(range=[1, 150])),
-    ))
+st.markdown("---")
+st.markdown("Sviluppato con Streamlit e Python.")