bigpyx

bigpyx — Arbitrary-Precision Decimal Numbers for Python

bigpyx is a tiny wrapper around Python’s built-in decimal.Decimal type.

It gives you:

• Easy, consistent handling of big numbers (money, crypto, prices, etc.)
• Configurable precision (DP) and rounding mode (RM)

Perfect when float is too imprecise and you want something safer but still easy to use.

Features

• ✅ Arbitrary-precision decimal arithmetic
• ✅ Global defaults for decimal places (DP) and rounding mode (RM)
• ✅ Minimal, focused API
• ✅ Works with str, int, float, Decimal, and Big values

Installation

If you’ve published this as a package:

pip install bigpyx

Quick Start

from bigpyx import Big

# Basic construction
a = Big("0.1")
b = Big("0.2")

# Addition
c = a + b
print(c)           # -> 0.3

# Or using methods, if you added them:
# c = a.add(b)

# Multiplication
d = Big("1.23") * Big("4")
print(d)           # -> 4.92

Because Big uses Decimal under the hood, you don’t get the usual floating-point surprises:

from bigpyx import Big

print(0.1 + 0.2)        # 0.30000000000000004 (float)
print(Big("0.1") + Big("0.2"))  # 0.3 (Big)

Configuration

Big exposes two important global settings:

from bigpyx import Big

# Maximum decimal places for division, sqrt, etc.
Big.DP = 20    # default: 20

# Rounding mode (like big.js)
# 0: ROUND_DOWN
# 1: ROUND_HALF_UP      (default)
# 2: ROUND_HALF_EVEN
# 3: ROUND_UP
Big.RM = 1

Internally, these map to decimal’s rounding modes via _ROUND_MAP.

You can also use decimal.localcontext() for temporary precision overrides inside your own code, but for most use cases, setting Big.DP and Big.RM is enough.

Creating Big Numbers

from bigpyx import Big
from decimal import Decimal

Big("1.2345")         # from string
Big(12345)            # from int
Big(1.2345)           # from float (not recommended for exact finance values)
Big(Decimal("1.2345"))# from Decimal
Big(Big("1.2345"))    # from another Big

Under the hood, the constructor converts the value to a Decimal and stores it as self._d.

Arithmetic

The exact API here depends on how you implemented Big.

Below is a typical pattern using operator overloading.

Addition

x = Big("1.1")
y = Big("2.2")
print(x + y)      # -> 3.3

Subtraction

x = Big("5")
y = Big("2.5")
print(x - y)      # -> 2.5

Multiplication

x = Big("1.5")
y = Big("3")
print(x * y)      # -> 4.5

Division

Division respects Big.DP and Big.RM:

from bigpyx import Big

Big.DP = 10
Big.RM = 1  # ROUND_HALF_UP

x = Big("1")
y = Big("3")

print(x / y)  # -> 0.3333333333  (10 decimal places)

License

MIT License

Copyright (c) 2025 Matt Henry