OC_P7_DA-Python

Projet n°7: DA-Python OpenClassrooms (Develop a user interface for a Python web application).

The program calculates the best combination of stocks based on their profits using two approaches: bruteforce and dynamic programming (knapsack algorithm).

Getting Started

Prerequisites

• Python 3.11 or higher
• Git

Installation

1. Clone the repository:

   git clone https://github.com/Majestic-MJ12/OC_P7_DA-Python.git
   

2. Navigate to the project directory:

   cd OC_P7_DA-Python 
   

3. Set up a virtual environment:

   python -m venv env
   

4. Activate the virtual environment:
   • On Windows:

     env\scripts\activate
     

   • On MacOS and Linux:

     source env/bin/activate
     

5. Install the required packages:

   pip install -r requirements.txt
   

Usage

Bruteforce

To run the bruteforce approach, use the following command:

python bruteforce.py

By default, the investment amount is set to 500€. However, it is possible to enter a custom amount as follows:

python bruteforce.py 400

Note: The bruteforce approach only processes data from the "shares.csv" file, which contains 20 stocks. Datasets 1 and 2 would result in an extremely long execution time (What is solved with the optimized.py).

Dynamic Programming

To run the dynamic programming approach, use the following command:

python optimized.py dataset1

Replace "dataset1" with the name of the file you want to process, without the file path or extension. By default, the investment amount is set to 500€. However, it is possible to enter a custom amount as follows:

python optimized.py dataset2 600

It is also possible to process the test file (20 stocks), with or without a custom amount:

python optimized.py shares

python optimized.py shares 400

Note: During data processing, the program displays a progress bar (thanks to "tqdm").

Slides

Here you'll find the slides that explain the optimised solution (including the bruteforce):

Link to PDF

Built With

• Python
• Git

License

GNU AFFERO GENERAL PUBLIC LICENSE