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app.py

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+
+import os
+import gradio as gr
+from backend import cantitati_piesa
+
+with gr.Blocks() as consum:
+    gr.Markdown(
+        "# CPA Logistics")
+
+    with gr.Tabs():
+        with gr.TabItem(label="Nr.piese "):
+            gr.Markdown(
+                "Aici poti sa calulezi nr. total de unitati ce iti trbuie din fiecare produs."
+                "Te rog ai grija ca fisierul de input nume_fisier.xlsx sa:\n"
+                " \n - incepa direct cu denuirea coloanelor  \n - sa aiba un format constant \n - uite mai jos un exmplu:")
+            exemplu_01 = gr.File(label="Exemplu fisier de input:", value="DATA/consumuri.xlsx")
+            with gr.Row():
+                with gr.Column(scale=1, min_width=400):
+
+                    file_material_a = gr.File(label="Introdu aici lista de consumuri:" )
+
+
+            id_componente = gr.Text(label="Nume colaona id:", value="Denumire")
+            cantitate = gr.Text(label="Nume colaona cantitate:", value="Cantitate")
+
+            msc_button = gr.Button("Calculeaza cantitatea totala din fiecare produs:")
+
+            cantitati_totale = gr.Text(label="Cantitati totale:")
+            cantitati_totale_xlsx = gr.File(label="Cntitati xlsx:")
+
+            msc_button.click(cantitati_piesa,
+                             inputs=[file_material_a,id_componente, cantitate],
+                             outputs=[cantitati_totale, cantitati_totale_xlsx])
+
+
+
+consum.launch(share=False)

backend/__init__.py

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+from .cantitati_consum import cantitati_piesa

backend/cantitati_consum.py

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+import pandas as pd
+import random
+import datetime
+
+# # Specify the file path of the XLS document
+# file_path = 'consumuri.xlsx'
+# # Read the XLS file
+# data = pd.read_excel(file_path)
+# data = data.fillna('<nimic>')
+pd.set_option('display.max_rows', None)  # Display all rows
+pd.set_option('display.max_columns', None)  # Display all columns
+pd.set_option('display.width', 1000)  # Set the display width for showing more information
+pd.set_option('display.colheader_justify', 'center')  # Center justify column headers
+pd.set_option('display.precision', 3)  # Set precision for decimal values
+
+
+def format_items(dictionary):
+    "pretty string"
+    formatted_string = "Item Details:\n"
+    for key, value in dictionary.items():
+        formatted_string += f"{key}: {value}\n"
+    return formatted_string
+
+def cantitati_piesa(file, denumire_id, cantitate):
+    """
+    Calculeaza cate piese trebuie sa fie facute de fiecare data cand intlaneste id d epiese ii aduaga cantitatea..
+    :param file:
+    :type file:
+    :param denumire_id:
+    :type denumire_id:
+    :param cantitate:
+    :type cantitate:
+    :return:
+    :rtype:
+    """
+
+    data=pd.read_excel(file)
+    products = {}
+    for index, row in data.iterrows():
+        denumire = row[denumire_id]
+        if denumire not in ['Consumuri', '<nimic>']:
+
+            if denumire not in products:
+                products[denumire] = row[cantitate]
+            else:
+                products[denumire] += row[cantitate]
+    p={"produs":[], "cantitate":[]}
+    for k in products.keys():
+        p["produs"].append(k)
+        p["cantitate"].append(products[k])
+
+
+    df=pd.DataFrame.from_dict(p)
+
+    # Generate a random number and get the current date
+    random_number = random.randint(1000, 9999)
+    current_date = datetime.datetime.now().strftime("%Y%m%d")
+    filename = f"{file.name}_cantitate_{current_date}_{random_number}.xlsx"
+    df.to_excel(filename, index=False)
+    # Generate a summary string for display
+    summary_string = "Canitati produse:\n" + "\n".join(f"{prod}: {qty}" for prod, qty in products.items())
+
+    # Return the summary string and the path to the Excel file
+    return summary_string, filename
+
+    return df

requirements.txt

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+gradio==4.26.0
+pandas ==2.2
+Requests==2.31.0
+scipy==1.13.0
+torch==2.1.1
+openpyxl