A Python-based financial computing project focused on implementing and experimenting with financial calculations, reusable financial functions, software components, and mathematical models.
The repository brings together the PyFinancialLibrary, unit tests, research/monograph materials, and additional financial-calculation experiments. It was originally exported from the former Google Code pyfinancial project.
The project explores how financial and mathematical models can be implemented as reusable software components.
The main library is organized as a Python project with dedicated source code and unit-test directories:
PyFinancialLibrary/
├── lib/
├── src/
│ └── financialLibrary/
├── test/
│ └── unit/
├── LICENSE
├── .project
└── .pydevproject
This separation between implementation and testing provides a foundation for developing reusable financial software.
The core component of the repository is PyFinancialLibrary.
It contains:
- Financial calculation implementations
- Reusable Python modules
- Unit tests
- Library artifacts
- Project configuration
The source code is located under:
PyFinancialLibrary/src/financialLibrary
while unit tests are maintained under:
PyFinancialLibrary/test/unit
The project focuses on implementing financial calculations programmatically, providing a software-oriented approach to mathematical and financial models.
The architecture can be represented as:
Financial Model
│
▼
Mathematical Formula
│
▼
Python Function
│
▼
Financial Calculation
│
▼
Reusable Module
│
▼
Unit Tests
This approach allows financial formulas and models to be transformed into reusable and testable software components.
The library includes a dedicated unit-testing structure:
test/
└── unit/
This demonstrates an emphasis on validating individual financial functions and components independently.
Unit testing is particularly important for financial software because small numerical or implementation errors can propagate into larger calculations.
The repository also contains a monografia directory with academic and research materials related to the project.
It includes:
- LaTeX source files
- PDF documentation
- Mathematical diagrams
- Architecture diagrams
- Python source files
- References
- Experimental results
- Screenshots and figures
The research directory contains files such as TrabalhoMC.tex, funcao.py, model.jpg, arquitetura.jpg, and several diagrams and result tables.
This makes the repository more than a simple software implementation: it also documents the research and mathematical foundations behind the computational work.
The repository includes additional study material under:
study/
└── FelipeCalc/
└── src/
├── main.py
└── calcsample/
This component represents an additional experimental environment for financial calculations and Python application development.
A conceptual view of the project is:
PyFinancial
│
┌─────────────┼─────────────┐
│ │ │
▼ ▼ ▼
Financial Research Study
Library /Monograph Projects
│ │ │
▼ ▼ ▼
Python Mathematical Financial
Modules Models Calculations
│
▼
Unit Tests
This project demonstrates several software engineering concepts that are relevant to financial applications.
Financial calculations are organized into reusable Python modules rather than being implemented only as isolated scripts.
The repository separates:
- Source code
- Unit tests
- Library artifacts
- Research documentation
- Experimental projects
The dedicated unit-test structure allows financial calculations to be validated independently.
The project connects mathematical and financial models with executable Python implementations.
The monograph materials document the transition from mathematical concepts and research into executable software.
pyfinancial/
│
├── PyFinancialLibrary/
│ ├── lib/
│ ├── src/
│ │ └── financialLibrary/
│ ├── test/
│ │ └── unit/
│ ├── LICENSE
│ ├── .project
│ └── .pydevproject
│
├── monografia/
│ ├── documentacaoFormulas/
│ ├── files/
│ ├── TrabalhoMC.tex
│ ├── TrabalhoMC.pdf
│ ├── funcao.py
│ ├── model.jpg
│ ├── arquitetura.jpg
│ └── ...
│
├── study/
│ └── FelipeCalc/
│ └── src/
│ ├── calcsample/
│ └── main.py
│
├── .project
└── .pydevproject
The repository currently contains 171 commits and was originally exported from code.google.com/p/pyfinancial.
| Technology / Concept | Purpose |
|---|---|
| Python | Financial computation and application logic |
| Unit Testing | Validation of financial functions |
| Mathematical Modeling | Definition of financial calculations |
| LaTeX | Academic and mathematical documentation |
| Java/Python IDE project files | Development environment configuration |
| Git | Version control |
The project demonstrates an important intersection between:
Software Engineering
- Modular programming
- Reusable components
- Unit testing
- Source-code organization
Financial Computing
- Financial mathematics
- Numerical calculations
- Mathematical models
- Computational finance
Research & Development
- Mathematical modeling
- Academic documentation
- Experimental implementation
- Software prototyping
These foundations are transferable to modern areas such as:
- Financial Data Engineering
- FinTech
- Quantitative Analytics
- Risk Analytics
- Financial Modeling
- Data Science
- Python-based financial applications
This repository represents an earlier stage of my software development and financial-computing experience.
The concepts explored here provide a foundation for more recent work involving:
Financial Computing
│
▼
Python Development
│
▼
Data Engineering
│
▼
Data Integration
│
▼
AI & Generative AI
The progression demonstrates how software development, mathematical modeling, and data engineering can converge into modern data-driven applications.
Ruben Cruz
Data Engineering | Data Integration | Python | Financial Computing | Data Analytics | AI Integration
GitHub: https://github.com/rubencruz