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Update app.py
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app.py
CHANGED
@@ -136,13 +136,13 @@ inventory_date = datetime.today().strftime('%Y-%m-%d')
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apis = [
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# fetch warehouse ID
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{
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"url": "http://193.203.162.39:
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"params": {"query": warehouse_name, "userId": 164}
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},
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# Stock summary based on warehouse id
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{
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"url": "http://193.203.162.39:
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"params": {"branchId": 343, "onDate": inventory_date, "warehouseId": warehouse_id}
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}
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]
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@@ -1178,6 +1178,7 @@ def handle_large_dataset(df, create_document,isDataFrame):
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# List of required columns
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required_columns = ['BROKER', 'ACCOUNT NUMBER', 'EMPLOYEE NAME', 'ACCOUNT NAME', 'ACCOUNT ID']
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# Filter the DataFrame to include only the required columns
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limited_data = df[required_columns]
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limited_data = limited_data.head(3)
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limited_data_without_first_column = limited_data.iloc[:, 1:]
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apis = [
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# fetch warehouse ID
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{
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"url": "http://193.203.162.39:81/nxt-wms/userWarehouse/fetchWarehouseForUserId?",
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"params": {"query": warehouse_name, "userId": 164}
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},
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# Stock summary based on warehouse id
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{
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"url": "http://193.203.162.39:81/nxt-wms/transactionHistory/stockSummary?",
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"params": {"branchId": 343, "onDate": inventory_date, "warehouseId": warehouse_id}
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}
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]
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# List of required columns
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required_columns = ['BROKER', 'ACCOUNT NUMBER', 'EMPLOYEE NAME', 'ACCOUNT NAME', 'ACCOUNT ID']
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# Filter the DataFrame to include only the required columns
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print(df[required_columns])
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limited_data = df[required_columns]
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limited_data = limited_data.head(3)
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limited_data_without_first_column = limited_data.iloc[:, 1:]
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