# Solution Strategy

## Table of Contents

- [Solution Strategy](#solution-strategy)
  - [Table of Contents](#table-of-contents)
  - [Technology Decisions](#technology-decisions)
    - [Programming Language](#programming-language)
    - [Web Framework](#web-framework)
    - [Database](#database)
    - [Frontend Technologies](#frontend-technologies)
  - [Architectural Patterns](#architectural-patterns)
    - [Layered Architecture](#layered-architecture)
    - [Client-Server Pattern](#client-server-pattern)
    - [Containerization](#containerization)
  - [Quality Goals Achievement](#quality-goals-achievement)
    - [Comprehensive Scenario Analysis](#comprehensive-scenario-analysis)
    - [Data-Driven Decision Making](#data-driven-decision-making)
    - [User-Friendly Interface](#user-friendly-interface)
    - [Security](#security)
    - [Scalability](#scalability)
  - [Organizational Decisions](#organizational-decisions)
    - [Development Process](#development-process)

## Technology Decisions

### Programming Language

Python as the primary programming language for its simplicity, readability, and extensive libraries that support rapid development and data analysis.

### Web Framework

FastAPI as the web framework due to its high performance, ease of use, and support for asynchronous programming, which is essential for handling multiple concurrent requests efficiently.

### Database

PostgreSQL as the database system for its robustness, scalability, and strong support for complex queries, which are necessary for managing the application's data effectively.

### Frontend Technologies

Jinja2 for server-side templating to dynamically generate HTML pages, and Chart.js for data visualization to provide interactive charts and graphs for users.

## Architectural Patterns

### Layered Architecture

The system follows a layered architecture pattern, separating concerns into distinct layers: presentation, business logic, and data access. This separation enhances maintainability, scalability, and testability of the application.

### Client-Server Pattern

The application is designed using the client-server pattern, where the client (frontend) interacts with the server (backend) through RESTful APIs. This separation allows for independent development and scaling of the client and server components.

### Containerization

The application is containerized using Docker or podman to ensure consistency across different deployment environments, facilitate scalability, and simplify the deployment process.

## Quality Goals Achievement

### Comprehensive Scenario Analysis

The system employs efficient data processing algorithms and leverages PostgreSQL's capabilities to handle large datasets, enabling users to create and analyze multiple project scenarios effectively.

### Data-Driven Decision Making

Stakeholders have access to real-time data and analytics to inform their decisions.

### User-Friendly Interface

The platform is designed with an intuitive interface that requires minimal training for new users.

### Security

Sensitive data is protected through robust security measures, including encryption and access controls.

### Scalability

The system is designed to scale horizontally by adding more instances of services as needed. This is facilitated by the use of containerization and orchestration tools like Kubernetes, which manage the deployment and scaling of containerized applications.

## Organizational Decisions

### Development Process

The development team follows an Agile methodology, allowing for iterative development, continuous feedback, and adaptability to changing requirements. This approach enhances collaboration among team members and stakeholders, ensuring that the final product meets user needs effectively.