na4va4/due_diligence repository overview

⁠due_diligence: Automatize the due diligence process from open sources for consultation

⁠Table of Contents

1. Abstract⁠
2. Theoretical Framework⁠
3. Methodology⁠
4. Deployment⁠
5. Technical Implementation⁠
6. Installation⁠
7. Usage⁠
8. License⁠

⁠Abstract

due_diligence is a web scraping tool designed to take screenshots of the information sources using selenium webdriver. It exports the screenshots as evidences in a word file following the format given in CELEC EP. The information sources are:

• Servicio de Rentas Internas
  • Consulta de RUC/ Empresas fantasmas del SRI⁠
  • Estado Tributario⁠
  • Deudas firmes e impugnadas⁠
• Aduana del Ecuador
  • Liquidaciones vencidas⁠
• Fiscalía
  • Procesos Fiscales⁠
• Consejo de la Judicatura
  • Procesos Judiciales⁠
• Servicio Nacional de Contratación Pública (SERCOP)
  • Búsqueda de no ser contratista incumplido o adjudicatario fallido con el Estado⁠
• Contraloría General del Estado
  • Informes Aprobados⁠
• More to come ...

⁠Theoretical Framework

• Due Diligence: Due diligence is a pre-transaction investigative process aimed at assessing risks and opportunities by thoroughly examining a company or asset to verify expectations and uncover potential issues.
• Web Scraping: The process of extracting data from websites using automated scripts.
• Word Report: Using python-docx to create Word files with the screenshots of the consulted sites.

⁠Methodology

The due_diligence follows a structured approach:

1. User Input: Users provide a RUC.
2. Word Export: The captured screenshots is exported to Word files, with appropriate format.

⁠Deployment

due_diligence is built using Flask, allowing it to run as a web application. The application processes user requests and returns the extracted data in Word format.

⁠Technical Implementation

due_diligence is developed in Python 3.9, utilizing:

• Flask for the web interface.
• Requests for making HTTP requests to the SRI website.
• Selenium for simulating the user interaction with the websites and capture the screenshots.
• Python-docx for exporting the report to Word files.

⁠Installation

⁠Prerequisites

• Python 3.9: Ensure that Python is installed and configured in your system.

or

• Docker: Ensure to have Docker installed and running in the system.

⁠Installation

⁠Via Github

• Clone the repository

  git clone https://github.com/nava2105/due_diligence.git
  cd due_diligence
  

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• Required Libraries: Install the necessary libraries using pip:

  pip install -r requirements.txt
  

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• Run the application

  python app.py
  

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• Access the application: Open your web browser and navigate to http://localhost:5000⁠

⁠Via Dockerhub

• Clone the docker image

  docker pull na4va4/due_diligence
  

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• Run the image in a container

  docker run -p 5000:5000 na4va4/due_diligence
  

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• Access the application: Open your web browser and navigate to http://localhost:5000⁠

⁠Usage

Once the application is up and running, you can interact with the system by:

⁠Generating the due diligence report:

• Input the RUC.
• Submitting the form to generate and download the corresponding Word file.

⁠License

This project is licensed under the MIT License - see the LICENSE⁠ file for details.