abstract-math 0.0.0.47

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abstract_math

Description

The abstract_math Python module, currently in its Alpha development stage (version 0.0.0.14), is designed for performing complex mathematical operations and token manipulations. This module comprises primarily of two scripts: safe_math and derive_tokens.

Features

• Performing complex mathematical operations.
• Manipulation and derivation of mathematical tokens, referred to as 'lamports'.
• High precision for decimal calculations for better accuracy.
• Functions for deriving quantities like lamports, virtual reserves, sol reserves, sol amounts, token reserves, token amounts, derived token ratio, price, and token decimals.
• Module components for updating Sol and token variables.

Scripts Overview

• derive_tokens.py: This script is involved in the complex manipulation or derivation of mathematical tokens, referred to as 'lamports'. The functions defined in this script handle various aspects of token manipulations and calculations.

Installation

To install the abstract_math module, ensure that your Python version is 3.6 or later. This module currently does not have any external dependencies to be installed.

Usage

This module could potentially be used as a framework for handling complex mathematical operations or token manipulations. Developers interested in working with and enhancing this module can access the source code at the repository (provide repo link here).

Dependencies

Currently, the module does not require any external dependencies.

License

The module is provided under the MIT License.

Author & Contact

This Python module was authored by 'putkoff', who can be reached at [e-mail] for further queries or assistance.

Contributing

Contributions are welcome to help in the development of the abstract_math module, particularly with the 'safe_math' and 'derive_tokens' scripts that form the core of the module.

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No description available

Installation

pip install Unknown Package

Dependencies

None

Modules

src/abstract_math/safe_math.py

Description of script based on prompt: You are analyzing a Python script 'safe_math.py' l (mock response)

src/abstract_math/init.py

Description of script based on prompt: You are analyzing a Python script 'init.py' lo (mock response)

src/abstract_math/derive_tokens.py

Description of script based on prompt: You are analyzing a Python script 'derive_tokens.p (mock response)