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Just another (cool) no-deps math library

Project description

Metrima Logo

A small, comprehensive math library with fixed-point arithmetic precision and useful utilities.

PyPI version Python License: MIT

Version 0.3.2 UnfinishedAlert: The WeightUnit is unfinished and is currently inaccurate.

Overview

Metrima is a Python math library that provides precise decimal arithmetic through the Fx (Fixed-point) class, eliminating floating-point precision issues. Beyond arithmetic, it includes time unit handling, functional utilities, decorators, and mathematical constants.

Features

Fixed-Point Arithmetic (Fx)

  • Precise Decimal Operations: Avoid floating-point precision errors
  • Full Operator Support: All standard math operations (+, -, *, /, //, %, **)
  • Immutable Design: Thread-safe and predictable behavior
  • Type Conversions: Seamless conversion between Fx, int, float, and str
  • Comparison Operations: Complete set of comparison operators
  • Unary Operations: Negation, absolute value, and rounding

Time Units

  • Time Arithmetic: Hour, Minute, Second, Millisecond classes
  • Automatic Conversions: Seamless operations between different time units
  • Precision Handling: Maintains millisecond precision with automatic overflow

Utility Functions (lib)

  • String manipulation: trim, chop, locate
  • Collection operations: length, invert, combinelst, push_back, attach
  • Type checking: is_whole, is_whitespace, exists
  • Iteration utilities: span, indexed
  • Deep copying: duplicate
  • Validation: has, verify

Decorators

  • @timed: Measure execution time
  • @memo: Memoization with configurable cache
  • @repeat: Execute functions multiple times
  • @legacy: Mark deprecated functions
  • @mimic: Copy function metadata
  • @attribute: Custom property-like descriptor

Mathematical Constants

  • Common constants: PI, E, GOLDEN_RATIO
  • Physical constants: GRAVITY, SPEED_OF_LIGHT, PLANCK_CONSTANT
  • Chemical constants: BOLTZMANN_CONSTANT, AVOGADRO_NUMBER, GAS_CONSTANT
  • Special values: INFINITE, NAN

Installation

pip install metrima

Quick Start

Fixed-Point Arithmetic

from metrima import Fx, fx

# Create fixed-point numbers
a = Fx("1.432")
b = fx(5.1234)  # Convenience function

# Perform arithmetic
result = a + b
print(result)  # 6.5554

# Mix with regular numbers
c = Fx(10.0) - 2.45
print(c)  # 7.55

# Complex expressions
d = (Fx(2.5) + Fx(3.5)) * Fx(4) - Fx(10) / Fx(2)
print(d)  # 19.0

Time Units

from metrima import Hour, Minute, Second, hour, minute, second

# Create time values
duration = Hour(2) + Minute(30)
print(duration)  # 2h 30m (displayed as seconds internally)

# Arithmetic with different units
result = hour(1) - minute(15)
print(second(result))  # 2700 seconds

# Comparisons
print(Minute(60) > Hour(1))  # False

Decorators

from metrima import timed, memo, repeat

@timed
def slow_computation(n):
    return sum(range(n))

result, duration = slow_computation(1000000)
print(f"Computed in {duration:.3f}s")

@memo
def fibonacci(n):
    if n <= 1:
        return n
    return fibonacci(n - 1) + fibonacci(n - 2)

@repeat(increment_counter)(count=5)
def task():
    print("Running task...")

Utility Functions

from metrima import span, chop, trim, duplicate

# Iteration
for i in span(5):
    print(i)  # 0, 1, 2, 3, 4

# String operations
words = chop("hello,world,python", ",")
print(words)  # ['hello', 'world', 'python']

clean = trim("   hello world   ")
print(clean)  # "hello world"

# Deep copy
original = [1, [2, 3]]
copy = duplicate(original)

Why Metrima?

Standard Python floating-point arithmetic can produce unexpected results:

# Python's float arithmetic
0.1 + 0.2  # 0.30000000000000004 😱

# Metrima's Fx arithmetic
Fx(0.1) + Fx(0.2)  # 0.3 ✨

Testing

Metrima includes comprehensive test suites covering all functionality.

Run Interactive Tests

metrimatest

This launches an interactive menu with options:

  1. Competition Demo - Compare Metrima vs Python vs Decimal
  2. Fx Class Testing - Unit tests for fixed-point arithmetic
  3. Decorators Testing - Test all decorator functionality
  4. Library Functions Testing - Test utility functions
  5. TimeUnits Testing - Test time arithmetic

Test from Code

from metrima import test_main, test_fx, test_decorators, test_lib, test_timeunits

test_main()       # Run competition tests
test_fx()         # Test Fx class
test_decorators() # Test decorators
test_lib()        # Test library functions
test_timeunits()  # Test time units

API Reference

Core Functions

from metrima import add, subtract, mul, div, sigma

add(a, b)       # Addition
subtract(a, b)  # Subtraction
mul(a, b)       # Multiplication
div(a, b)       # Division
sigma(lst)      # Sum of list elements

Fx Class Methods

Arithmetic: __add__, __sub__, __mul__, __truediv__, __floordiv__, __mod__, __pow__

Unary: __neg__, __pos__, __abs__, __round__

Comparisons: __eq__, __ne__, __lt__, __le__, __gt__, __ge__

Conversions: __int__, __float__, __str__, __repr__, __bool__

Utility: is_zero(), is_positive(), is_negative(), is_integer(), copy()

Time Unit Classes

Classes: Hour, Minute, Second, Millisecond

Converters: hour(), minute(), second(), ms()

All time units support arithmetic operations, comparisons, and automatic conversions.

Requirements

  • Python >= 3.14
  • tinycolors >= 0.5.1.3 (for colorized output)

Version

Current version: 0.3.0

License

MIT License - see LICENSE file for details.

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

Repository

GitHub: https://github.com/tyydev1/metrima

Authors

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