Upload 2 files

query_seller_sale.py

@@ -1,102 +1,148 @@
-# query_seller_sale.py\
-
 queries = {
-    "query": """
+    "query_seller_net_data": """
     WITH seller_net_data AS (
-    SELECT
-        company_id,
-        company_name,
-        ordering_channel,
-        segement_code,
-        sales_channel,
-        settlement_model,
-        settlement_model_code,
-        order_type,
-        order_date,
-        fiscal_year,
-        bag_id,
-        settlement_type,
-        recon_status,
-        return_window_date,
-        payout_window_date,
-        expected_payout_date,
-        sett_no,
-        sett_id,
-        mrp,
-        seller_discounts,
-        store_discount_amount,
-        bca,
-        product_gst_perc,
-        round(vog,2) as vog,
-        tds_on_bca,
-        tcs_on_vog,
-        seller_fees,
-        seller_tender_value,
-        round(seller_net_collection,2) as seller_net_collection,
-        ROUND(mrp - seller_discounts - store_discount_amount,2) AS bca_cc,
-        ROUND(bca - (mrp - seller_discounts - store_discount_amount),2) AS diff_bca_cc,
-        ROUND((mrp - seller_discounts - store_discount_amount) * 100 / (100 + ABS(product_gst_perc)), 2) AS vog_cc,
-        ROUND(vog - ROUND((mrp - seller_discounts - store_discount_amount) * 100 / (100 + ABS(product_gst_perc)), 2),2) AS diff_vog_cc,
+        SELECT
+            company_id,
+            company_name,
+            ordering_channel,
+            segement_code,
+            sales_channel,
+            settlement_model,
+            settlement_model_code,
+            order_type,
+            order_date,
+            fiscal_year,
+            bag_id,
+            settlement_type,
+            recon_status,
+            return_window_date,
+            payout_window_date,
+            expected_payout_date,
+            sett_no,
+            sett_id,
+            mrp,
+            seller_discounts,
+            store_discount_amount,
+            bca,
+            product_gst_perc,
+            round(vog,2) as vog,
+            tds_on_bca,
+            tcs_on_vog,
+            seller_fees,
+            seller_tender_value,
+            round(seller_net_collection,2) as seller_net_collection,
+            ROUND(mrp - seller_discounts - store_discount_amount,2) AS bca_cc,
+            ROUND(bca - (mrp - seller_discounts - store_discount_amount),2) AS diff_bca_cc,
+            ROUND((mrp - seller_discounts - store_discount_amount) * 100 / (100 + ABS(product_gst_perc)), 2) AS vog_cc,
+            ROUND(vog - ROUND((mrp - seller_discounts - store_discount_amount) * 100 / (100 + ABS(product_gst_perc)), 2),2) AS diff_vog_cc,
 
-        -- TDS calculation logic
-        CASE 
-            WHEN segement_code IN ("FY", "UN") AND DATE(order_date) >= '2024-10-01' THEN 
-                ROUND((mrp - seller_discounts - store_discount_amount), 2) * 0.001
-            WHEN segement_code IN ("FY", "UN") AND DATE(order_date) < '2024-10-01' THEN 
-                ROUND((mrp - seller_discounts - store_discount_amount), 2) * 0.01
-            ELSE 0
-        END AS tds_cc,
+            -- TDS calculation logic
+            CASE 
+                WHEN segement_code IN ("FY", "UN") AND DATE(order_date) >= '2024-10-01' THEN 
+                    ROUND((mrp - seller_discounts - store_discount_amount), 2) * 0.001
+                WHEN segement_code IN ("FY", "UN") AND DATE(order_date) < '2024-10-01' THEN 
+                    ROUND((mrp - seller_discounts - store_discount_amount), 2) * 0.01
+                ELSE 0
+            END AS tds_cc,
 
-        -- TCS calculation logic
-        CASE 
-            WHEN segement_code IN ("FY", "UN") AND DATE(order_date) >= '2024-07-10' THEN 
-                ROUND((mrp - seller_discounts - store_discount_amount) * 100 / (100 + ABS(product_gst_perc)), 2) * 0.005
-            WHEN segement_code IN ("FY", "UN") AND DATE(order_date) < '2024-07-10' THEN 
-                ROUND((mrp - seller_discounts - store_discount_amount) * 100 / (100 + ABS(product_gst_perc)), 2) * 0.01
-            ELSE 0
-        END AS tcs_cc
-    FROM 
-        `fynd-db.finance_recon_tool_asia.09_seller_net_collection_daily`
-    WHERE
-        expected_payout_date BETWEEN "{start_date}" AND "{end_date}"
-),
+            -- TCS calculation logic
+            CASE 
+                WHEN segement_code IN ("FY", "UN") AND DATE(order_date) >= '2024-07-10' THEN 
+                    ROUND((mrp - seller_discounts - store_discount_amount) * 100 / (100 + ABS(product_gst_perc)), 2) * 0.005
+                WHEN segement_code IN ("FY", "UN") AND DATE(order_date) < '2024-07-10' THEN 
+                    ROUND((mrp - seller_discounts - store_discount_amount) * 100 / (100 + ABS(product_gst_perc)), 2) * 0.01
+                ELSE 0
+            END AS tcs_cc
+        FROM 
+            `fynd-db.finance_recon_tool_asia.09_seller_net_collection_daily`
+        WHERE
+            expected_payout_date BETWEEN "{start_date}" AND "{end_date}"
+    ),
 
--- Subquery to count occurrences of each bag_id and concatenation of bag_id and settlement_type
-bag_con_count_data AS (
+    -- Subquery to count occurrences of each bag_id and concatenation of bag_id and settlement_type
+    bag_con_count_data AS (
+        SELECT
+            bag_id,
+            settlement_type,
+            COUNT(*) AS bagg_count,
+            CONCAT(bag_id, settlement_type) AS bag_settlement_concat,
+            COUNT(CONCAT(bag_id, settlement_type)) AS bag_settlement_concat_count  -- Count of concatenated values
+        FROM
+            seller_net_data
+        GROUP BY
+            bag_id, settlement_type
+    )
+
+    -- Final query
     SELECT
-        bag_id,
-        settlement_type,
-        COUNT(*) AS bagg_count,
-        CONCAT(bag_id, settlement_type) AS bag_settlement_concat,
-        COUNT(CONCAT(bag_id, settlement_type)) AS bag_settlement_concat_count  -- Count of concatenated values
+        sd.*,
+        ROUND((tds_cc - tds_on_bca), 2) AS diff_tds,
+        ROUND((tcs_cc - tcs_on_vog), 2) AS diff_tcs,
+        ROUND((mrp - seller_discounts - store_discount_amount - seller_tender_value + seller_fees),2) AS seller_sale_cc,
+        ROUND(((mrp - seller_discounts - store_discount_amount - seller_tender_value + seller_fees) - tds_cc - tcs_cc),2) AS seller_net_cc,
+        ROUND(((mrp - seller_discounts - store_discount_amount - seller_tender_value + seller_fees) - tds_cc - tcs_cc - seller_net_collection), 2) AS net_diff_cc,
+        CONCAT(sd.bag_id, ",") AS conccat,  -- Concatenated bag_id
+        CONCAT(sd.bag_id, sd.settlement_type) AS bag_cc,  -- Bag ID with settlement type
+        bcc.bagg_count AS bag_count,  -- Count of each bag_id and settlement type
+        bcc.bag_settlement_concat AS bag_con,  -- Concatenated bag_id and settlement_type
+        bcc.bag_settlement_concat_count AS bag_con_count,  -- Count of concatenated values
+        CASE
+            WHEN order_type = 'COD' THEN CONCAT(company_id, '_', segement_code, '_', settlement_model_code, '_', order_type, '_V')
+            WHEN order_type = 'PPD' THEN CONCAT(company_id, '_', segement_code, '_', settlement_model_code, '_', order_type, '_C')
+        END AS ledger_name
     FROM
-        seller_net_data
-    GROUP BY
-        bag_id, settlement_type
-)
+        seller_net_data sd
+    LEFT JOIN
+        bag_con_count_data bcc
+    ON
+        sd.bag_id = bcc.bag_id AND sd.settlement_type = bcc.settlement_type;
+    """,
 
--- Final query
-SELECT
-    sd.*,
-    ROUND((tds_cc - tds_on_bca), 2) AS diff_tds,
-    ROUND((tcs_cc - tcs_on_vog), 2) AS diff_tcs,
-    ROUND((mrp - seller_discounts - store_discount_amount - seller_tender_value + seller_fees),2) AS seller_sale_cc,
-    ROUND(((mrp - seller_discounts - store_discount_amount - seller_tender_value + seller_fees) - tds_cc - tcs_cc),2) AS seller_net_cc,
-    ROUND(((mrp - seller_discounts - store_discount_amount - seller_tender_value + seller_fees) - tds_cc - tcs_cc - seller_net_collection), 2) AS net_diff_cc,
-    CONCAT(sd.bag_id, ",") AS conccat,  -- Concatenated bag_id
-    CONCAT(sd.bag_id, sd.settlement_type) AS bag_cc,  -- Bag ID with settlement type
-    bcc.bagg_count AS bag_count,  -- Count of each bag_id and settlement type
-    bcc.bag_settlement_concat AS bag_con,  -- Concatenated bag_id and settlement_type
-    bcc.bag_settlement_concat_count AS bag_con_count,  -- Count of concatenated values
-    CASE
-        WHEN order_type = 'COD' THEN CONCAT(company_id, '_', segement_code, '_', settlement_model_code, '_', order_type, '_V')
-        WHEN order_type = 'PPD' THEN CONCAT(company_id, '_', segement_code, '_', settlement_model_code, '_', order_type, '_C')
-    END AS ledger_name
-FROM
-    seller_net_data sd
-LEFT JOIN
-    bag_con_count_data bcc
-ON
-    sd.bag_id = bcc.bag_id AND sd.settlement_type = bcc.settlement_type;
+    "query_brand_accounting_entries": """
+    SELECT
+        DENSE_RANK() OVER (ORDER BY expected_payout_date,company_id,VOUCHERTYPENAME,sales_channel,expected_payout_date,order_type ASC) entry_code,
+        DATE,
+        Mode,
+        VOUCHERTYPENAME,
+        Narration,
+        DebitLedger,
+        AmountDebitLedger,
+        CreditLedger,
+        AmountCreditLedger
+    FROM (
+        WITH
+          Truth_table AS (SELECT * FROM `fynd-db.Brand_Accounting_Entries_Asia.Brand_Seller_Sale_FY25_Table`)
+        SELECT
+          expected_payout_date,
+          format_date('%Y%m%d', expected_payout_date) as DATE,
+          "Journal" as Mode,
+          VOUCHERTYPENAME,
+          CONCAT(Narration," for ", sales_channel, " for the period ",expected_payout_date ) AS Narration,
+          entry_Type,
+          order_type,
+          A.segement_code,
+          company_id,
+          sales_channel,
+          CASE WHEN seller_sales_amount > 0 AND B.ordering_channel IN ("FY", "FP", "FS", "UN", "OE","OM") AND entity = "seller" AND mop = "COD" THEN ledger_name WHEN seller_sales_amount > 0 AND B.ordering_channel IN ("FY", "FP", "FS", "UN", "OE","OM") AND entity = "seller" AND mop = "PPD" THEN ledger_name ELSE Credit_Ledger END AS DebitLedger,
+          CASE WHEN seller_sales_amount > 0 THEN ROUND(seller_sales_amount*-1) ELSE ROUND(seller_sales_amount) END AS AmountDebitLedger,
+          CASE WHEN seller_sales_amount < 0 AND B.ordering_channel IN ("FY", "FP", "FS", "UN", "OE","OM") AND entity = "seller" AND mop = "COD" THEN ledger_name WHEN seller_sales_amount < 0 AND B.ordering_channel IN ("FY", "FP", "FS", "UN", "OE","OM") AND entity = "seller" AND mop = "PPD" THEN ledger_name ELSE Credit_Ledger END AS CreditLedger,
+          CASE WHEN seller_sales_amount < 0 THEN ROUND(seller_sales_amount)*-1 ELSE ROUND(seller_sales_amount) END AS AmountCreditLedger
+        FROM 
+          `fynd-db.Brand_Accounting_Entries_Asia.Seller_sale_Logic` AS A
+        LEFT JOIN
+          Truth_table as B
+        ON
+          A.segement_code = B.ordering_channel 
+          AND A.entry_Type = B.Status
+          AND A.order_type = B.mop
+        WHERE
+          order_type = 'COD'
+          AND expected_payout_date BETWEEN '{start_date}' AND '{end_date}'
+        GROUP BY
+          1,2,3,4,5,6,7,8,9,10,11,12,13,14
+        ORDER BY 
+          expected_payout_date,company_id,VOUCHERTYPENAME,sales_channel,order_type ASC
+    )
+    ORDER BY entry_code ASC
     """
 }

seller.py

@@ -11,8 +11,7 @@ import pandas as pd
 import io
 import time
 
-# Dropdown for channels/members
-# webhook_url = list(Webhook_urls.keys())
+# HTML for button styles and progress bar
 html_subject = """
 <html>
 <head>
@@ -66,53 +65,107 @@ html_subject = """
 """
 
 st.markdown(html_subject, unsafe_allow_html=True)
-# selection = st.multiselect("", webhook_url)
-
 
 def check_duplicates(credentials_file):
     """Check for duplicates using BigQuery with the provided credentials file."""
     results = {}
     credentials = service_account.Credentials.from_service_account_info(json.loads(credentials_file))
+    scopes = ['https://www.googleapis.com/auth/cloud-platform',
+              'https://www.googleapis.com/auth/drive']
     client = bigquery.Client(credentials=credentials, project=credentials.project_id)
-    
-    query = queries["query"].format(start_date = start_date_str, end_date = end_date_str) # Access the query string from the dictionary
 
-    # Show a loading spinner
-    with st.spinner(":red[Performing seller sale validation...]"):
-        # Create a custom progress bar
-        progress_bar = st.empty()
-        progress_bar.markdown(
-            """
-            <div class="progress-bar">
-                <span id="progress"></span>
-            </div>
-            """, unsafe_allow_html=True
-        )
-        
+    # Format and execute all queries
+    for query_name, query_template in queries.items():
+        formatted_query = query_template.format(start_date=start_date_str, end_date=end_date_str)
+
+        # Execute the query
         try:
-            query_job = client.query(query)
-            # Simulate loading progress
-            for percent_complete in range(0, 101, 10):
-                time.sleep(0.1)  # Simulate work being done
-                progress_bar.markdown(
-                    f"""
-                    <div class="progress-bar">
-                        <span style="width: {percent_complete}%;"></span>
-                    </div>
-                    """, unsafe_allow_html=True
-                )
+            query_job = client.query(formatted_query)
             df = query_job.result().to_dataframe()
-            st.write("", df)
+            results[query_name] = df  # Store the DataFrame in the results dictionary
+
+            # Display the DataFrame in the UI
+            subheader_html = f"""
+            <div style="background-image: linear-gradient(to right, #800000, #ff0000); 
+                        -webkit-background-clip: text; 
+                        -webkit-text-fill-color: transparent; 
+                        margin: 10px 0;">
+                <h4 style="margin: 0; font-size: 20px;">Results for {query_name}</h4> <!-- Change h2 to h4 -->
+            </div>
+            """
+
+# Render the subheader
+            st.markdown(subheader_html, unsafe_allow_html=True)
+            st.dataframe(df)  # Display each DataFrame in the Streamlit app
+
         except Exception as e:
-            st.error(f"An error occurred: {e}")
-            return results
+            st.error(f"An error occurred while querying {query_name}: {e}")
+
+    # Check if the expected DataFrames are available for downloading
+    if 'query_seller_net_data' in results and 'query_brand_accounting_entries' in results:
+        df_net_data = results['query_seller_net_data']
+        df_brand_entries = results['query_brand_accounting_entries']
 
-    if not df.empty:
-        results["Query Result"] = df
+        # Save both DataFrames to an Excel file with different sheets
+        excel_buffer = io.BytesIO()
+        with pd.ExcelWriter(excel_buffer, engine='openpyxl') as writer:
+            df_net_data.to_excel(writer, sheet_name='ss_data', index=False)  # Changed to Net Data
+            df_brand_entries.to_excel(writer, sheet_name='ss_entry', index=False)  # Changed to Brand Accounting
 
+        excel_buffer.seek(0)
+
+        # Create a CSV output with both DataFrames
+        csv_buffer = io.StringIO()
+        df_net_data.to_csv(csv_buffer, index=False, header=True)  # Write first DataFrame to CSV
+        csv_buffer.write("\n")  # Add a new line to separate the sections
+        df_net_data.to_csv(csv_buffer, index=False)
+        df_brand_entries.to_csv(csv_buffer, index=False, header=True)  # Write second DataFrame to CSV
+        csv_buffer.seek(0)
+
+        # # Buttons to download the Excel and CSV files
+        col1, col2 = st.columns(2)
+        with col1:
+            button_styles = """
+                <style>
+                div.stButton > button {
+                    color: #ffffff; /* Text color */
+                    font-size: 30px;
+                    background-image: linear-gradient(to right, #800000, #ff0000); /* Maroon to light red gradient */
+                    border: none;
+                    padding: 10px 20px;
+                    cursor: pointer;
+                    border-radius: 15px;
+                    display: inline-block;
+                    box-shadow: 0 4px 6px rgba(0, 0, 0, 0.1), 0 8px 15px rgba(0, 0, 0, 0.1); /* Box shadow */
+                    transition: all 0.3s ease; /* Smooth transition on hover */
+                }
+                div.stButton > button:hover {
+                    background-color: #00ff00; /* Hover background color */
+                    color: #ff0000; /* Hover text color */
+                    box-shadow: 0 6px 10px rgba(0, 0, 0, 0.2), 0 12px 20px rgba(0, 0, 0, 0.2); /* Box shadow on hover */
+                }
+                </style>
+                """
+            # Inject styles into the app
+            st.markdown(button_styles, unsafe_allow_html=True)
+
+            # Display the download button
+            st.download_button(
+                label="Download Excel file",
+                data=excel_buffer,  # Use the base64 data URL for the file
+                file_name="query_results.xlsx",
+                mime="application/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
+                key="download_excel"  # Optionally specify a key for the button
+            )
     return results
 
-# Streamlit UI
+
+
+
+# Streamlit UI for uploading credentials
+st.markdown(html_subject, unsafe_allow_html=True)
+
+# Upload credentials file
 html_subject = """
     <html>
     <head>
@@ -159,22 +212,21 @@ html_subject = """
                 -webkit-text-fill-color: transparent;
                 margin: 0;
                 text-shadow: 0 2px 5px rgba(0, 0, 0, 0.4);
-            ">Upload service a/c credentials</h3>
+            ">Upload the JSON file</h3>
         </div>
     </body>
     </html>
     """
 
-st.markdown(html_subject, unsafe_allow_html=True)
-
 
-
-# Upload credentials file
+st.markdown(html_subject, unsafe_allow_html=True)
 credentials_file = st.file_uploader("", type="json")
 
-
-
-html_subject = """
+st.write("")
+col1, col2 = st.columns([0.118, 0.125])
+# First column for Start Date
+with col1:
+    html_subject_start = """
     <html>
     <head>
     <style>
@@ -220,23 +272,73 @@ html_subject = """
                 -webkit-text-fill-color: transparent;
                 margin: 0;
                 text-shadow: 0 2px 5px rgba(0, 0, 0, 0.4);
-            ">Select the expected payout date</h3>
+            ">Start date</h3>
         </div>
     </body>
     </html>
     """
 
-st.markdown(html_subject, unsafe_allow_html=True)
-
+    st.markdown(html_subject_start, unsafe_allow_html=True)
+    date_input_key_start = "start_date_input" 
+    start_date = st.date_input("", value=None, key=date_input_key_start)
 
-st.write("")
-col1, col2 = st.columns([0.118, 0.125])
-with col1:
-    start_date = st.date_input("Start date", value = None)
+# Second column for End Date
 with col2:
-    end_date = st.date_input("End date", value = None)
-
+    html_subject_end = """
+    <html>
+    <head>
+    <style>
+        .button {
+            display: inline-block;
+            padding: 10px 20px;
+            border-radius: 12px;
+            background: linear-gradient(to bottom, #f8f9fa, #e0e0e0);
+            box-shadow: 
+                0 6px 12px rgba(0, 0, 0, 0.3), 
+                0 8px 16px rgba(0, 0, 0, 0.2), 
+                inset 0 -2px 4px rgba(255, 255, 255, 0.6);
+            text-align: center;
+            position: relative;
+            transform: translateY(4px);
+            transition: transform 0.2s ease-in-out, box-shadow 0.2s ease-in-out;
+            cursor: pointer;
+            user-select: none;
+        }
+        .button:hover {
+            box-shadow: 
+                0 8px 16px rgba(0, 0, 0, 0.3), 
+                0 12px 24px rgba(0, 0, 0, 0.2);
+            transform: translateY(2px);
+        }
+        .button:active {
+            box-shadow: 
+                0 4px 8px rgba(0, 0, 0, 0.3), 
+                0 6px 12px rgba(0, 0, 0, 0.2);
+            transform: translateY(0);
+        }
+    </style>
+    </head>
+    <body>
+        <div class="button">
+            <h3 style="
+                font-size: 20px;
+                color: #ffffff;
+                background-image: linear-gradient(to right, #800000, #ff0000, #ffdab9);
+                background-clip: text;
+                -webkit-background-clip: text;
+                text-fill-color: transparent;
+                -webkit-text-fill-color: transparent;
+                margin: 0;
+                text-shadow: 0 2px 5px rgba(0, 0, 0, 0.4);
+            ">End date</h3>
+        </div>
+    </body>
+    </html>
+    """
 
+    st.markdown(html_subject_end, unsafe_allow_html=True)
+    date_input_key_end = "end_date_input"  # Changed key to be unique
+    end_date = st.date_input("", value=None, key=date_input_key_end)
 if credentials_file is not None:
     if start_date and end_date:  # Ensure dates are selected
         start_date_str = start_date.strftime("%Y-%m-%d")
@@ -248,31 +350,15 @@ if credentials_file is not None:
         # Check for duplicates
         results = check_duplicates(credentials_data)
         
-        if "Query Result" in results:
-            df = results["Query Result"]
-            
-            # Download buttons
-            csv = df.to_csv(index=False)
-            excel = io.BytesIO()
-            with pd.ExcelWriter(excel, engine='openpyxl') as writer:
-                df.to_excel(writer, index=False)
-            excel.seek(0)
-            
-            col1, col2 = st.columns([0.125, 0.5])
-            with col1:
-                st.download_button(
-                    label=":red[Download CSV]",
-                    data=csv,
-                    file_name="seller_sale_recon.csv",
-                    mime="text/csv"
-                )
-
-            with col2:
-                st.download_button(
-                    label=":red[Download Excel]",
-                    data=excel,
-                    file_name="seller_sale_recon.xlsx",
-                    mime="application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
-                )
+        # Prepare to save results in an Excel file
+        if results:
+            excel_buffer = io.BytesIO()
+            with pd.ExcelWriter(excel_buffer, engine='openpyxl') as writer:
+                if 'query_seller_net_data' in results:
+                    results['query_seller_net_data'].to_excel(writer, sheet_name='Net Data', index=False)
+                if 'query_brand_accounting_entries' in results:
+                    results['query_brand_accounting_entries'].to_excel(writer, sheet_name='Brand Accounting', index=False)
+        else:
+            st.error("No results found.")
     else:
         st.warning("Please select both the start and end dates to proceed.")