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We maintain all customers in one database. There are heaps of customers who have user cards. So, I decided to split up the customers based on the country and load them into corresponding country tables.

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Multi Specialty Hospital

I own a multi-specialty hospital chain with locations all across the world. My hospital is famous for vaccinations. Patients who come to my hospital (across the globe) will be given a user card with which they can access any of my hospitals in any location.

The Problem

We maintain all customers in one database. There are heaps of customers who have user cards. So, I decided to split up the customers based on the country and load them into corresponding country tables.

To pull customers by country, my developers should know where all the Customer Data is available. So, the data extracting will be done by our Source System. They will pull all the relevant customer data and will give us a pipe delimited data file.

In design documents, you will have:

File Position Column Name Field Length Data Type Mandatory Key Column
1 Customer Name 255 VARCHAR Y N
2 Customer ID 18 VARCHAR Y Y
3 Customer Open Date DATE Y N
4 Last Consulted Date DATE N N
5 Vaccination Type 5 VARCHAR N N
6 Doctor Consulted 255 VARCHAR N N
7 State 5 VARCHAR N N
8 Country 5 VARCHAR N N
9 Post Code 5 INTEGER N N
10 Date of Birth DATE N N
11 Active Customer 1 CHAR N N

The sample file format will be:

H|Customer_Name|CustomerID|CustomerOpenDate|LastConsultedDate|VaccinationType|Doctor|State|Country|PostCode|DateofBirth|ActiveCustomer D|Yael|1|20101012|20121013|sput5|Piper Sheppard|Lange|Peru|75532|06031987|A D|Xaviera|2|20101112|20210329|sput5|Savannah Keith|Sint|Peru|3604|26011999|A D|Matthew|3|20100323|20160202|sput5|Justin Leblanc|Marlb|Peru|18518|17121996|A D|Alec|4|20210101|20220305|sput5|Colin Hodge|Eindh|Nepal|19167|15031966|A D|Ethan|5|20200505|20210814|sput5|Charlotte Campbell|Keumi|Nepal|Z4730|27061959|A D|Macey|6|20150518|20190808|mvd|Garrison Mosley|Salci|Peru|87049|17081971|A D|Angelica|7|20171214|20171214|covix|TaShya Mendez|Perth|india|61188|11082000|A D|April|8|20190126|20201231|covix|Amal Gray|Burin|India|96896|24071999|A D|Nissim|9|20181130|20181201|mvd|Chelsea Farmer|Masca|Nepal|09666|03101928|A T|9|

Output:

Any script or program which reads the data from files which will load the data into tables, one table per country.

How to use it?

  1. Clone the repository

    git clone https://github.com/ajinzrathod/multi-specialty-hospital.git
    
  2. Go to cloned directory and Install virtual Environment

    python3 -m venv venv
    
  3. Activate Virtual Environment

    For Linux and Mac:

    source venv/bin/activate
    

    For Windows:

    source .\venv\Scripts\activate
    
  4. Install Requirements

  • If you want to use it with jupyter-notebook, use this command:

    pip install -r requirements.txt
    

    OR

  • If you want to use it just using terminal, use this command:

    pip install -r requirements-before-jupyterLab.txt
    

Things to know before you create database

There are 2 folders:

  1. Database-independent
  • Scripts in this folder will create Tables in Any Database. You just have to change the connection string which is also given below:
  1. For-mysql
  • Script is this folder is solely made for MySql as it was asked in question to make "Create table queries". So we have created a procedure named createCountryTable inside create-table-stored-procedure.sql file which can also be found in same directory.

    Connection String:

    engine = create_engine("mysql+mysqlconnector://root:password@localhost/" + db)
    

    Here, root is the username and password is the password. Edit the connection String according to your database configuration.

After updating connection String

  • You need to create a Database named incubyte
  • Now open your Terminal or Command Line
  • Go to database-independent directory or for-mysql directory as per your need.
  • Now run the code using this command: python index.py

Screenshots

Tree

Database after loading tables from txt file


Tree

When country table does NOT exists already


Tree

When country table already exists

Other Details

Python Version: 3.8.10

NOTE: We could remove country column from each country table. But considering a scenario when we want to merge all the data in one table. This would be a easy approach.

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We maintain all customers in one database. There are heaps of customers who have user cards. So, I decided to split up the customers based on the country and load them into corresponding country tables.

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