Skip to main content

Genova is a versatile Python library that offers a collection of powerful tools for various domains including mathematics, artificial intelligence, finance, and more.

Project description

Certainly! Below is a comprehensive README.md file that you can use for your Genova Python library. It provides detailed sections for installation, usage, examples, and contributing guidelines.

# Genova - A General-Purpose Python Library

**Genova** is a versatile Python library designed to offer easy-to-use utilities for a variety of domains such as mathematics, machine learning, finance, and more. With its modular structure, **Genova** makes it simple to access and apply mathematical operations, machine learning models, financial tools, and more, making it an essential library for both professionals and enthusiasts.

## Table of Contents

- [Installation](#installation)
- [Usage](#usage)
  - [Math Module](#math-module)
  - [AI Models Module](#ai-models-module) - Coming soon
  - [Finance Module](#finance-module) - Coming soon
- [Examples](#examples)
  - [Math Examples](#math-examples)
  - [AI Models Examples](#ai-models-examples)
  - [Finance Examples](#finance-examples)
- [Contributing](#contributing)
- [License](#license)

## Installation

To install **Genova** via **pip**:

```bash
pip install genova
```

Alternatively, if you want to install the latest version directly from GitHub, use the following command:

pip install git+https://github.com/egegvner/genova.git

Usage

Once installed, you can use the library to perform various tasks. Here are some examples of how to get started with different modules:

Math Module

The genova.math module offers utilities for mathematical operations, such as polynomial derivatives, turning points, and gradients.

Derivative of a Polynomial

from genova.math import calculus

coefficients = [2, -3, 5]  # 2x^2 - 3x + 5
derivative = calculus.derivative(coefficients)
print(derivative)  # Output: "4x - 3"

Turning Points of a Polynomial

coefficients = [1, -3, 2]  # x^2 - 3x + 2
turning_points, derivative_str = calculus.turning_points(2, 1, -3, 2)
print(turning_points)  # Output: [(1.0, 0.0)]
print(derivative_str)  # Output: "2x - 3"

Gradient at a Point

x = 1
gradient = calculus.gradient_at_point(coefficients, x)
print(gradient)  # Output: 3

AI Models Module

The genova.models module provides utilities to work with machine learning models, including training, evaluating, and making predictions.

Simple Neural Network for MNIST

from genova.models import neural_networks

model = neural_networks.build_mnist_model()
model.summary()  # Displays the model architecture

Finance Module

The genova.finance module offers tools for financial calculations, including stock price analysis and basic financial tools.

Get Latest Stock Price

from genova.finance import stocks

stock_price = stocks.get_stock_price("AAPL")
print(stock_price)  # Output: Latest Apple stock price

Examples

Math Examples

  • Derivative: Calculate the derivative of polynomials and express it in human-readable format.
  • Turning Points: Find the turning points (local minima and maxima) of a polynomial function.
  • Gradient: Compute the gradient (slope) of a polynomial at any given point.

AI Models Examples

  • Model Building: Build machine learning models with ease using predefined functions.
  • Training: Quickly set up neural networks for training on datasets (e.g., MNIST).
  • Prediction: Use trained models for making predictions or classification tasks.

Finance Examples

  • Stock Data: Fetch real-time stock prices using yfinance.
  • Financial Calculations: Work with basic finance-related calculations, such as loan repayments, stock price trends, etc.

Contributing

We welcome contributions to Genova! If you have ideas for new features, improvements, or bug fixes, please follow the steps below:

  1. Fork the repository.
  2. Create a new branch (git checkout -b feature-name).
  3. Commit your changes (git commit -am 'Add new feature').
  4. Push to the branch (git push origin feature-name).
  5. Open a pull request with a detailed description of your changes.

Please ensure that your code follows the existing style and includes tests where applicable.

License

Genova is licensed under the MIT License. See the LICENSE file for more details.


Feel free to explore the library, contribute, or contact the maintainers if you need further help or have any questions.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

genova-1.1.2.tar.gz (3.2 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

genova-1.1.2-py3-none-any.whl (3.1 kB view details)

Uploaded Python 3

File details

Details for the file genova-1.1.2.tar.gz.

File metadata

  • Download URL: genova-1.1.2.tar.gz
  • Upload date:
  • Size: 3.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.12.4

File hashes

Hashes for genova-1.1.2.tar.gz
Algorithm Hash digest
SHA256 ecf41f9c65cb396b71853a45009a138c18683fdf479270f74d5019f68bc0d6f0
MD5 305cf2726f10d4bdf9aac64816d413a7
BLAKE2b-256 3440b70d35c8e542a325620a09afd3639b3f2cd2ab9876de742b8efa6d9b8e36

See more details on using hashes here.

File details

Details for the file genova-1.1.2-py3-none-any.whl.

File metadata

  • Download URL: genova-1.1.2-py3-none-any.whl
  • Upload date:
  • Size: 3.1 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.12.4

File hashes

Hashes for genova-1.1.2-py3-none-any.whl
Algorithm Hash digest
SHA256 615cfaf4638eab07b2937644d1ccbb10b5bae299f91a8f0dbf7d8b18a58bc277
MD5 229c5e41959af7d2283bed4534cbcf74
BLAKE2b-256 74d5cb07e36c2ebcaefda84ac7b81941e7f332e460679f175f44d526bf8f9b54

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page