uiuapy 0.2.0

Use the Uiua array programming language from Python

UiuaPy

A bridge between Uiua and NumPy - enabling you to do tacit array processing in Python.

Installation

pip install uiuapy

If building the source distribution, rather than installing a precompiled wheel, you will need to have rustup installed on your machine.

Usage

import uiua

print(uiua.compile('/+')([1, 2, 3]))
# 6.0

print(uiua.compile('⌕')('ab', 'abracabra')) 
# [1 0 0 0 0 1 0 0 0]

Flags

You can allow thread spawning either specific to a program, or specific to an invocation. Invocation flags take precedence over program flags.

import numpy as np
import uiua

xs = np.linspace(0, 1, 10_000)

print(uiua.compile('/+', allow_threads=True)(xs))
# 50000.0

print(uiua.compile('/+')(xs, allow_threads=True))
# 50000.0

NumPy integration

UiuaPy uses the NumPy C-API for taking in Python inputs and returning Python results.

Uiua supports 5 data-types for arrays/scalars:

Uiua type	NumPy equivalent dtype
Num	float64
Byte	uint8
Complex	complex128
Char	Unicode (32-bit characters)
Box	object

If you pass in a NumPy array that does not have one of the above dtypes, it will be automatically converted according to the table below:

NumPy dtype	Converted NumPy dtype	Uiua type
float32	float64	Num
uint64	float64	Num
uint32	float64	Num
uint16	float64	Num
int64	float64	Num
int32	float64	Num
int16	float64	Num
bool	uint8	Byte

Interfacing overhead

Passing a numpy array to uiua requires copying its memory (using memcpy/ std::ptr::copy_nonoverlapping in Rust). The same is true for the values returned from the Uiua computation.

If using anything other than float64, uint8, complex128 or unicode data - there are also type conversion costs to take into account.

Development

Dependencies

• rustup
• uv

# Format code
uv run ruff format
cargo fmt

# Fix/report lints
uv run ruff check --fix
cargo clippy

# Run tests
uv run pytest

# Build wheels
uv build