Create data_collector.py

data_collector.py

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+import mysql.connector
+from decimal import Decimal
+import pandas as pd
+# Define the connection parameters
+host = "159.138.104.192"
+user = "storemate_ml"
+password = "bTgZd77VpD^o4Ai6Dw9xs9"
+database = "lite_version"
+
+
+def get_data(b_id,product_name):
+  # Create a connection to the MySQL server
+  try:
+      # Create a connection to the MySQL server
+      connection = mysql.connector.connect(
+          host=host,
+          user=user,
+          password=password,
+          database=database
+      )
+
+      if connection.is_connected():
+          print("Connected to MySQL database")
+
+          # Create a cursor object for executing SQL queries
+          cursor = connection.cursor()
+
+          # Define the SQL SELECT query
+          sql_query = f"""
+  SELECT
+    `b`.`id` AS `business_id`,
+    `b`.`name` AS `business_name`,
+    `p`.`name` AS `product_name`,
+    `p`.`type` AS `product_type`,
+    `c1`.`name` AS `category_name`,
+    `pv`.`name` AS `product_variation`,
+    `v`.`name` AS `variation_name`,
+    `v`.`sub_sku`,
+    `c`.`name` AS `customer`,
+    `c`.`contact_id`,
+    `t`.`id` AS `transaction_id`,
+    `t`.`invoice_no`,
+    `t`.`transaction_date` AS `transaction_date`,
+    (transaction_sell_lines.quantity - transaction_sell_lines.quantity_returned) AS sell_qty,
+    `u`.`short_name` AS `unit`,
+    transaction_sell_lines.unit_price_inc_tax,
+    transaction_sell_lines.unit_price_before_discount
+  FROM `transaction_sell_lines`
+    INNER JOIN `transactions` AS `t`
+      ON `transaction_sell_lines`.`transaction_id` = `t`.`id`
+    INNER JOIN `variations` AS `v`
+      ON `transaction_sell_lines`.`variation_id` = `v`.`id`
+    LEFT JOIN `transaction_sell_lines_purchase_lines` AS `tspl`
+      ON `transaction_sell_lines`.`id` = `tspl`.`sell_line_id`
+    LEFT JOIN `purchase_lines` AS `pl`
+      ON `tspl`.`purchase_line_id` = `pl`.`id`
+    INNER JOIN `product_variations` AS `pv`
+      ON `v`.`product_variation_id` = `pv`.`id`
+    INNER JOIN `contacts` AS `c`
+      ON `t`.`contact_id` = `c`.`id`
+    INNER JOIN `products` AS `p`
+      ON `pv`.`product_id` = `p`.`id`
+    LEFT JOIN `business` AS `b`
+      ON `p`.`business_id` = `b`.`id`
+    LEFT JOIN `categories` AS `c1`
+      ON `p`.`category_id` = `c1`.`id`
+    LEFT JOIN `tax_rates`
+      ON `transaction_sell_lines`.`tax_id` = `tax_rates`.`id`
+    LEFT JOIN `units` AS `u`
+      ON `p`.`unit_id` = `u`.`id`
+    LEFT JOIN `transaction_payments` AS `tp`
+      ON `tp`.`transaction_id` = `t`.`id`
+    LEFT JOIN `transaction_sell_lines` AS `tsl`
+      ON `transaction_sell_lines`.`parent_sell_line_id` = `tsl`.`id`
+  WHERE `t`.`type` = 'sell'
+  AND `t`.`status` = 'final'
+  AND `t`.`business_id` = {b_id}
+  AND `p`.`name` = '{product_name}'
+  GROUP BY `b`.`id`,
+          `transaction_sell_lines`.`id`;
+  """
+
+          # Execute the SQL query
+          cursor.execute(sql_query)
+
+          # Fetch all the rows as a list of tuples
+          results = cursor.fetchall()
+          results = [tuple(
+              float(val) if isinstance(val, Decimal) else val for val in row
+          ) for row in results]
+
+          #print(results)
+
+          # Display the results
+          #for row in results:
+              #print(row)  # You can process the results as needed
+
+          # Close the cursor and connection
+          cursor.close()
+          connection.close()
+
+          # Create a DataFrame
+          columns = ["business_id","business_name","product_name","product_type","category_name","product_variation","variation_name","sub_sku","customer","contact_id","transaction_id","invoice_no","transaction_date","sell_qty","unit","cost_price","selling_price"]
+          df = pd.DataFrame(results, columns=columns)
+          return df,"done"
+
+  except mysql.connector.Error as e:
+      return e,"error"