💼 Mini Real-World Systems & Algorithms Pack

🌟 Real-world software simulators: See how banking loans, Uber cab fares, and Amazon dynamic pricing actually work under the hood!

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💡 What is this Project in 30 Seconds? (In Plain English)

Have you ever wondered how software makes financial and business decisions in seconds?

• How does a bank immediately approve or reject a customer's loan application?
• How does an online shopping app decide festival discounts and VIP member perks?
• How does a ride-hailing app (like Uber or Ola) calculate taxi fares and surge pricing during rain or traffic?

This project is a collection of real-world business engines written in Python:

1. 🏦 Bank Loan Decider: Evaluates income, credit score, and debt to automatically approve loans and calculate monthly EMIs.
2. 🛒 Shopping Discount Calculator: Dynamically adjusts product prices for festival sales, night hours, and loyal customers.
3. 🚖 Cab Fare & Surge Engine: Calculates taxi ride costs based on trip distance, driver proximity, and peak traffic hours.

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📑 Table of Contents

• What is this Project?
• Architecture & Module Overview
• Module Catalog
  • 1. Banking & Loan Underwriting System
  • 2. Dynamic E-Commerce Pricing Engine
  • 3. Ride-Hailing Cab Fare & Surge Calculator
  • 4. Classical Algorithms & Logic Suite
• Repository Structure
• How to Run
• Author & Connect
• License

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📐 Architecture & Module Overview

flowchart TD
    subgraph CorePack["💼 Mini-RealWorld-Systems-Pack"]
        direction TB
        
        subgraph Finance["🏦 Financial Domain"]
            A[Bank Loan Underwriting Engine]
            A --> A1[Age & Income Eligibility Checks]
            A --> A2[Credit Score Validation: 700-900]
            A --> A3[Debt-to-Income DTI Ratios]
            A --> A4[Automated 12-Month EMI Calculator]
        end

        subgraph Retail["🛒 E-Commerce & Retail Domain"]
            B[Dynamic Pricing & Discount Engine]
            B --> B1[Customer Tier Discounts: Premium / New]
            B --> B2[Temporal Demand Adjustment: Night Surge]
            B --> B3[Seasonal Festival Pricing Surges]
            B --> B4[Customer Loyalty Rating Rebates]
        end

        subgraph Mobility["🚖 Mobility & Logistics Domain"]
            C[Cab Fare & Distance Engine]
            C --> C1[Base Fare + Distance Multiplier]
            C --> C2[Peak Hour Dynamic Surge Modeling]
            C --> C3[Driver Proximity Vector Optimization]
        end

        subgraph DSA["🧩 Algorithmic Logic Suite"]
            D[Placement & Technical Algorithms]
            D --> D1[Greedy Coin Change Optimization]
            D --> D2[Two Sum Hash / Pair Search]
            D --> D3[Euclidean Distance Geospatial Matching]
        end
    end

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🚀 Module Catalog

1. 🏦 Banking & Loan Underwriting System

📁 Directory: BankLoanSystem/ | Script: BankLoanEligible.py

• Real-World Problem: Automates credit risk assessment and monthly loan installment computation for retail banking applicants.
• Decision Pipeline:
  • Validates applicant age eligibility ($21 < \text{age} < 60$).
  • Enforces minimum monthly income threshold ($\ge \text{₹}25,000$).
  • Audits credit score against risk parameters ($700 \le \text{Score} \le 900$).
  • Enforces Debt-to-Income (DTI) bounds: Existing obligations must not exceed $50%$ of monthly income.
  • Computes monthly Equated Monthly Installment (EMI) with $10%$ simple interest over a 12-month tenure: $$\text{EMI} = \frac{\text{Principal} + (\text{Principal} \times 0.10)}{12}$$

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2. 🛒 Dynamic E-Commerce Pricing Engine

📁 Directory: ECommercePricingSystem/ | Script: EComDynPricSys.py

• Real-World Problem: Simulates dynamic revenue management algorithms used by platforms like Amazon or Flipkart to optimize cart conversions and margins.
• Decision Pipeline:
  • Tier Rebates: Applies $15%$ discount for Premium members, $5%$ for New customers.
  • Time-of-Purchase Surge: Adds $10%$ during peak night shopping traffic.
  • Festival Season Surge: Incorporates $20%$ demand adjustments during holiday seasons.
  • High-Rating Reward: Delivers an extra $5%$ loyalty discount for customer satisfaction ratings $\ge 4.7/5.0$.

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3. 🚖 Ride-Hailing Cab Fare & Surge Calculator

📁 Directory: TravelFareSystem/ | Script: CabFareFeeCal.py

• Real-World Problem: Models the fare dispatch algorithms implemented by ride-sharing services like Uber and Ola.
• Decision Pipeline:
  • Base Tariff: Calculates fundamental trip cost: $$\text{Fare}_{\text{base}} = \text{₹}50 + (\text{₹}10 \times \text{Distance in km})$$
  • Peak Hour Surge: Automatically applies a $25%$ surge markup during high-traffic commute intervals.
  • Customer Rating Discount: Applies a $10%$ incentive deduction for riders with ratings exceeding $4.5/5.0$.

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4. 🧩 Classical Algorithms & Logic Suite

📁 Directory: Algorithms/

• Focus: Foundational computational algorithms and data structure implementations commonly assessed in technical interviews:

Script	Algorithm / Topic	Complexity	Description
CoinChangeProblem.py	Greedy Optimization	$O(N \log N)$	Finds minimum coin denominations required to construct a target amount.
TwoSum.py	Search / Pair Matching	$O(N^2)$	Identifies pairs of indices within an array whose elements sum to a target value.
DisOfCusDriv.py	Euclidean Distance	$O(D)$	Calculates 2D spatial distance $\sqrt{(x_2-x_1)^2 + (y_2-y_1)^2}$ to dispatch nearest driver.
AttPerCal.py	Threshold Auditing	$O(1)$	Computes academic attendance compliance against the statutory $75%$ requirement.
DelCharCal.py	String Manipulation	$O(N)$	Character deletion and ASCII parsing logic.

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📁 Repository Structure

Mini-RealWorld-Systems-Pack/
├── BankLoanSystem/
│   ├── BankLoanEligible.py         # Underwriting & EMI calculation script
│   └── README.md                   # Banking system documentation
├── ECommercePricingSystem/
│   ├── EComDynPricSys.py           # Dynamic e-commerce pricing engine
│   └── README.md                   # Pricing model documentation
├── TravelFareSystem/
│   ├── CabFareFeeCal.py            # Ride-hailing fare calculation script
│   └── README.md                   # Mobility system documentation
├── Algorithms/
│   ├── CoinChangeProblem.py        # Greedy coin change optimization
│   ├── TwoSum.py                   # Pair sum identification
│   ├── DisOfCusDriv.py             # Spatial closest-driver dispatch
│   ├── AttPerCal.py                # Attendance audit script
│   ├── DelCharCal.py               # String processing logic
│   └── README.md                   # Algorithms suite documentation
├── LICENSE                         # MIT open source license
└── README.md                       # Master portfolio pack documentation

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🚀 How to Run

Clone the repository and run any module directly using Python 3:

git clone https://github.com/ranjithbrs/Mini-RealWorld-Systems-Pack.git
cd Mini-RealWorld-Systems-Pack

# 1. Run Bank Loan Underwriting
python BankLoanSystem/BankLoanEligible.py

# 2. Run Dynamic E-Commerce Pricing
python ECommercePricingSystem/EComDynPricSys.py

# 3. Run Cab Fare Calculator
python TravelFareSystem/CabFareFeeCal.py

# 4. Run Greedy Coin Change Algorithm
python Algorithms/CoinChangeProblem.py

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👨‍💻 Author

Ranjith B
🎓 B.Tech Computer Science & Business Systems (CSBS)
🏛️ Nehru Institute of Engineering and Technology, Coimbatore

• 💼 LinkedIn: linkedin.com/in/ranjith-b-csbs
• 🐙 GitHub: github.com/ranjithbrs
• 🌐 Portfolio: ranjithbrs.github.io/portfolio
• 📧 Email: ranjithb2k06@gmail.com

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📄 License

This project is licensed under the MIT License.