Metadata-Version: 2.4
Name: math-engine
Version: 0.6.5
Summary: A fast and secure mathematical expression evaluator.
Author-email: Jan Teske <jan.teske.06@gmail.com>
Project-URL: Homepage, https://github.com/JanTeske06/math_engine
Project-URL: Source, https://github.com/JanTeske06/math_engine
Project-URL: Changelog, https://github.com/JanTeske06/math_engine/blob/master/CHANGELOG.md
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.8
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: rich
Requires-Dist: prompt_toolkit
Provides-Extra: test
Requires-Dist: pytest>=7.0.0; extra == "test"
Requires-Dist: pytest-cov; extra == "test"
Dynamic: license-file


# Math Engine v0.6.5 


[![PyPI version](https://badge.fury.io/py/math-engine.svg)](https://badge.fury.io/py/math-engine)
[![Python Versions](https://img.shields.io/pypi/pyversions/math-engine.svg)](https://pypi.org/project/math-engine/)
[![codecov](https://codecov.io/gh/JanTeske06/math_engine/graph/badge.svg)](https://codecov.io/gh/JanTeske06/math_engine)
[![PyPI Downloads](https://static.pepy.tech/personalized-badge/math-engine?period=total&units=NONE&left_color=GREY&right_color=BLACK&left_text=downloads)](https://pepy.tech/projects/math-engine)


A fast, safe, configurable expression parser and calculator for Python.

**math_engine** is a powerful expression evaluation library designed for developers who need a **safe**, **configurable**, and **extendable** alternative to Python’s built-in `eval()` or other ad-hoc parsers.  
It provides a complete pipeline:

* Tokenizer
* AST (Abstract Syntax Tree) parser
* Evaluator (numeric + equation solver)
* Formatter and type-safe output system
* Support for decimal, integer, binary, octal, hexadecimal
* Custom variables
* Scientific functions
* Strict error codes for reliable debugging and automated testing



This library is ideal for:

* Developers building calculators, interpreters, scripting engines
* Students learning compilers, math parsing, and ASTs
* Security-sensitive applications where `eval()` is not acceptable
* Anyone who needs equation solving, custom formats, and strict errors

---

# Features

### Core Features

* Full AST-based expression parsing
* Safe evaluation (no execution of Python code)
* Decimal, Integer, Float, Boolean, Binary, Octal, Hexadecimal
* Custom variables
* Linear equation solving (`x + 3 = 7`)
* Scientific functions: `sin`, `cos`, `tan`, `log`, `sqrt`, `π`, `e^`
* Automatic format correction (`correct_output_format`)
* Strong error handling with unique codes
* Settings system with presets
* Optional strict modes:
  * `only_hex`
  * `only_binary`
  * `only_octal`

### Non-Decimal Support

* Read binary `0b1101`
* Read octal `0o755`
* Read hexadecimal `0xFF`
* Convert results into binary/hex/octal format
* Enforce only-hex/only-binary/only-octal mode
* Prefix parsing (`hex:`, `bin:`, `int:`, `str:` ...)

---

# Installation

```bash
pip install math-engine
````

-----

# Command Line Interface (CLI)

Math Engine works directly from your terminal! After installing via pip, you can use the command `math-engine`, `calc` or `start`.

### 1\. Interactive Mode (REPL)

Start the shell to calculate, manage variables, and change settings dynamically.

```bash
$ math-engine

Math Engine 0.6.3 Interactive Shell
Type 'help' for commands, 'exit' to leave.
----------------------------------------
Examples:
  >>> 3 + 3 * 4 
  15
  
  >>> hex: 255
  0xff
  
  >>> x + 5, x=10    (Inline Variables)
  15
  
  >>> set setting word_size 8
  Setting updated: word_size -> 8
```

### 2\. Direct Calculation

You can also pass expressions directly (great for scripting):

```bash
$ math-engine "3 + 3"
6

$ math-engine "hex: 255"
0xff
```

-----

# Quick Start

## Basic Evaluation

```python
import math_engine

math_engine.evaluate("2 + 2")
# Decimal('4')
```

## Different Output Formats

```python
math_engine.evaluate("hex: 255")
# '0xff'

math_engine.evaluate("binary: 13")
# '0b1101'

math_engine.evaluate("octal: 64")
# '0o100'
```

## Automatic Format Correction

```python
import math_engine

settings = math_engine.load_all_settings()
settings["correct_output_format"] = True
math_engine.load_preset(settings)

math_engine.evaluate("bool: 3+3=6")
# True
```

## Reset all Settings to Default

```python
import math_engine

math_engine.reset_settings()
```

If a requested output type does not match the actual result, `correct_output_format=True` allows math\_engine to fall back to a compatible type instead of raising an error.

-----

# Prefix System (Casting Syntax)

math\_engine supports a powerful prefix-based casting system:

| Prefix   | Meaning     | Example                            |
| -------- | ----------- | ---------------------------------- |
| `dec:`   | Decimal     | `dec: 3/2` → `1.50`                |
| `int:`   | Integer     | `int: 10/3` → error if non-integer |
| `float:` | Float       | `float: 1/3`                       |
| `bool:`  | Boolean     | `bool: 3 = 3`                      |
| `hex:`   | Hexadecimal | `hex: 15`                          |
| `bin:`   | Binary      | `bin: 5`                           |
| `oct:`   | Octal       | `oct: 64`                          |
| `str:`   | String      | `str: 3+3` → `"6"`                 |

Example:

```python
math_engine.evaluate("hex: 3 + 3")
# '0x6'
```

-----

# Variables

```python
vars = {
    "A": 10,
    "B": 5,
}

math_engine.evaluate("A + B", variables=vars)
# Decimal('15')
```

Alternatively, you can pass variables as keyword arguments:

```python
math_engine.evaluate("A + B", A=10, B=5)
# Decimal('15')
```

Variables are mapped internally to a safe internal representation and are designed to be simple and predictable.

-----

# Scientific Functions

```python
math_engine.evaluate("sin(30)")
math_engine.evaluate("cos(90)")
math_engine.evaluate("log(100,10)")
math_engine.evaluate("√(16)")
math_engine.evaluate("pi * 2")
```

All functions are processed by the internal `ScientificEngine`, honoring your settings (for example, `use_degrees`).

-----

# Linear Equation Solver

```python
math_engine.evaluate("x + 3 = 10")
# Decimal('7')
```

Invalid or nonlinear equations produce errors with codes like:

  * 3005 – Non-linear equation
  * 3002 – Multiple variables
  * 3022 – One side empty

-----

# Non-Decimal Numbers (Binary, Octal, Hex)

```python
math_engine.evaluate("0xFF + 3")
# Decimal('258')

math_engine.evaluate("0b1010 * 3")
# Decimal('30')
```

Non-decimal parsing respects the setting `allow_non_decimal`. If it is set to `False`, using `0b`, `0o`, or `0x` will raise a conversion error.

-----

# Bitwise Operations & Developer Mode (v0.5.0)

Math Engine can act as a **programmer's calculator**. It supports standard operator precedence and bitwise logic.

### New Operators

| Operator | Description | Example  | Result |
| :------- | :---------- | :------- | :----- |
| `&`      | Bitwise AND | `3 & 1`  | `1`    |
| `\|`     | Bitwise OR  | `1 \| 2` | `3`    |
| `^`      | Bitwise XOR | `3 ^ 1`  | `2`    |
| `<<`     | Left Shift  | `1 << 2` | `4`    |
| `>>`     | Right Shift | `8 >> 2` | `2`    |
| `**`     | Power       | `2 ** 3` | `8`    |

> Note: Since `^` is used for **XOR**, use `**` for exponentiation (power).

### Word Size & Overflow Simulation

You can simulate hardware constraints (like C++ `int8`, `uint16`, etc.) by setting a `word_size`.

  * **`word_size: 0` (Default):** Python mode (arbitrary precision, no overflow).
  * **`word_size: 8/16/32/64`:** Enforces bit limits. Numbers will wrap around (overflow) accordingly.

### Signed vs. Unsigned Mode

When `word_size > 0`, you can control how values are interpreted via `signed_mode`:

  * **`True` (Default):** Use **Two's Complement** for negative values.
  * **`False`:** Treat all values as unsigned.

**Example: 8-bit Simulation**

```python
import math_engine

settings = math_engine.load_all_settings()
settings["word_size"] = 8
settings["signed_mode"] = True
math_engine.load_preset(settings)

math_engine.evaluate("127 + 1")
# In 8-bit signed arithmetic this overflows to -128
# Decimal('-128')
```

Hex output respects the current word size and signedness:

```python
math_engine.evaluate("hex: -1")
# Hex representation consistent with word_size / signed_mode configuration
```

### Force-only-hex Mode

```python
settings = math_engine.load_all_settings()
settings["only_hex"] = True
math_engine.load_preset(settings)

math_engine.evaluate("FF + 3")
# Decimal('258')
```
Input validation ensures safety and prevents mixing incompatible formats in strict modes.

---
## Bitwise & Low-Level Operations

Math Engine now includes a rich collection of low-level bit manipulation functions commonly used in systems programming, embedded development, cryptography, and hardware-oriented tools.

**Bitwise functions:**
- `bitand(x, y)` — bitwise AND  
- `bitor(x, y)` — bitwise OR  
- `bitxor(x, y)` — bitwise XOR  
- `bitnot(x)` — bitwise NOT  

**Bit manipulation utilities:**
- `setbit(x, n)` — sets bit *n*  
- `clrbit(x, n)` — clears bit *n*  
- `togbit(x, n)` — toggles bit *n*  
- `testbit(x, n)` — returns 1 if bit *n* is set, else 0  

**Shift operations:**
- `shl(x, n)` — logical left shift  
- `shr(x, n)` — logical right shift  

All bitwise functions:
- respect `word_size` and `signed_mode`  
- support overflow/wrap-around behavior  
- fully support binary, hex, decimal, and octal inputs  
- participate in the AST just like standard operators  

This makes Math Engine behave like a full-featured programmer’s calculator with CPU-like precision control.

-----

# Settings System

You can inspect and modify settings programmatically.

### Load Current Settings

```python
import math_engine

settings = math_engine.load_all_settings()
print(settings)
```

### Apply a Full Preset

This is a plain Python `dict` (not JSON):

```python
preset = {
    "decimal_places": 2,
    "use_degrees": False,
    "allow_augmented_assignment": True,
    "fractions": False,
    "allow_non_decimal": True,
    "debug": False,
    "correct_output_format": True,
    "default_output_format": "decimal:",
    "only_hex": False,
    "only_binary": False,
    "only_octal": False,
    # New in 0.3.0
    "word_size": 0,        # 0 = unlimited, or 8, 16, 32, 64
    "signed_mode": True,   # True = Two's Complement, False = Unsigned
    # New in 0.6.0
    "readable_error": True
}

math_engine.load_preset(preset)
```

### Change a Single Setting

```python
math_engine.change_setting("decimal_places", 10)
```

You can also read a single setting:

```python
decimal_places = math_engine.load_one_setting("decimal_places")
```

-----


# Error Handling (v0.6.0: Visual & Precise)

Math Engine 0.6.0 introduces a dual-mode error handling system designed for both interactive use and strict library integration.

## 1\. Visual Feedback (Default Behavior)

By default (`readable_error = True`), the engine catches syntax errors internally and prints a visual diagnostic to the console. This is perfect for CLI tools or quick debugging, as it points exactly to the issue without crashing the program.

```python
import math_engine

# readable_error is True by default
math_engine.evaluate("sin(5") 
```

**Console Output:**

```text
Errormessage: Unbalanced parenthesis.
Code: 3009 
Equation: sin(5
             ^ HERE IS THE PROBLEM (Position: 5)
```

## 2\. Programmatic Handling (Exceptions)

If you are building an application or running unit tests, you likely want to catch exceptions instead of printing to stdout. You can disable `readable_error` to raise standard `MathError` exceptions.

The exception object carries **precise start and end indices**:

  * `e.position_start` (int): Index where the error begins.
  * `e.position_end` (int): Index where the error ends.

<!-- end list -->

```python
import math_engine
from math_engine.utility import error as E

# Disable visual printing to catch exceptions
math_engine.change_setting("readable_error", False)

try:
  math_engine.evaluate("10.5 + 4.2.1")
except E.SyntaxError as e:
  print(f"Error Code: {e.code}")
  print(f"Location: {e.position_start} to {e.position_end}")

  # You can use these indices to highlight the error in your own UI
  bad_part = e.equation[e.position_start: e.position_end + 1]
  print(f"Invalid segment: '{bad_part}'")

```

## Testing and Reliability

To write unit tests with `pytest`, ensure you set `readable_error` to `False` so that exceptions are raised and can be asserted.

```python
import pytest
import math_engine
from math_engine import error as E

def test_division_by_zero():
    # Ensure exceptions are raised
    math_engine.change_setting("readable_error", False)
    
    with pytest.raises(E.CalculationError) as exc:
        math_engine.evaluate("10 / 0")
        
    # Assert the error is Division by Zero (3003)
    assert exc.value.code == "3003"
    # Assert the error points exactly to the zero/operator
    assert exc.value.position_start == 3 
```

## Example Error Codes

| Code | Meaning                     |
| ---- | --------------------------- |
| 3003 | Division by zero            |
| 3034 | Empty input                 |
| 3036 | Multiple = signs            |
| 3032 | Multiple-character variable |
| 8000 | Conversion to int failed    |
| 8006 | Output conversion error     |

For a complete list of all error codes and their meanings, please see the **[Error Codes Reference](https://github.com/JanTeske06/math_engine/blob/master/ERRORS.md)**.
---
# Performance

  * No use of Python `eval()`
  * Predictable performance through AST evaluation
  * Optimized tokenization
  * Fast conversion of non-decimal numbers

Future updates focus on:

  * Expression caching
  * Compiler-like optimizations
  * Faster scientific evaluation

-----

# Use Cases

### Calculator Applications

Build full scientific or programmer calculators, both GUI and command line.

### Education

Great for learning about lexers, parsers, ASTs, and expression evaluation.

### Embedded Scripting

Safe math evaluation inside larger apps.

### Security-Sensitive Input

Rejects arbitrary Python code and ensures controlled evaluation.

### Data Processing

Conversion between hex/bin/decimal is easy and reliable.

-----

# Roadmap (Future Versions)

  * Non-decimal output formatting upgrades
  * Strict type-matching modes
  * Function overloading
  * Memory/register system
  * Speed optimization via caching
  * User-defined functions
  * Expression pre-compilation
  * Better debugging output

-----

# Changelog

See [CHANGELOG.md](https://github.com/JanTeske06/math_engine/blob/master/CHANGELOG.md) for details.

-----

# License

[MIT License](https://github.com/JanTeske06/math_engine/blob/master/LICENSE)

-----
# AI

I want to be transparent about my workflow.
Parts of this project, especially the README text, documentation sections, and a significant portion of the test scaffolding, were created with the help of AI tools.

All architecture decisions, design choices, algorithms, implementations, refactorings, and debugging were done by me personally. AI served purely as a productivity aid: helping me improve clarity, expand test coverage faster, and polish documentation.

---
# Contributing

Contributions are welcome.
Feel free to submit issues or PRs on GitHub:

[https://github.com/JanTeske06/math\_engine](https://github.com/JanTeske06/math_engine)

---

