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PyPI version Architecture Processor x86_64 Architecture Processor ARM64 Architecture Processor ARM64 Apple Silicon License: BUSL-1.1

Overview

Purem is an advanced high-performance computational library optimized for vectorized mathematical operations. This project focuses on efficient execution of element-wise transformations, including softmax, exp, and other mathematical functions, leveraging highly optimized assembly code for modern architectures.

Key Features

Purem is a blazing-fast AI math engine that turns your Python formulas into native-speed vectorized execution. Achieve up to 429× faster performance on CPU/GPU/TPU – no rewrites, no dependencies, just speed. Designed for ML researchers, scientific computing, and production-grade workloads that can’t afford to wait.

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🔧 Installation

Install the Python wrapper via pip:

pip install purem

📦 Note: Installation is quick, but purem must be initialized with a license before use. Setup takes less than a minute – we’re ready when you are: https://worktif.com/#start

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🚀 Quickstart

  1. Import and Initialize:

    from purem import purem
    
    purem.configure(license_key='your-license-key')  # Auto-downloads and configures backend

—

🔐 License-Based Activation

The system will download the licensed native Purem engine:

  1. Call purem.configure(license_key='<your-license-key>')

  2. The system will download the native Purem engine

  3. All functions will become available instantly after initialization

Without a valid license key:

  • No native Purem engine will be downloaded

—

🧠 Available Functions

After initialization, you can call:

from purem import purem

# Transforms a list of numbers into a probability distribution.
# Each output value is between 0 and 1, and all outputs sum to 1.
# Commonly used in classification tasks to interpret scores as probabilities.
purem.softmax([...])
...

Full function list: https://worktif.com/docs/basic-usage

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📦 Packaging Notes

This package does not bundle the native Purem engine. You are required to:

  • Use a license key to download it dynamically

—

🧪 Benchmark Tutorial

Visit the Benchmark Tutorial: https://worktif.com/#benchmarks

  • How Purem compares to NumPy, PyTorch and Numba

  • How it reaches low-level performance via native execution

  • Why it’s faster than traditional Python-based computation

—

📧 Distribution and Licensing

The native Purem engine is distributed exclusively through license-based activation. All users must:

  • Use their license key to install

For access, contact us or visit: https://worktif.com/documents/terms-of-service

—

📚 Full Example

# Import required modules
import numpy as np
from purem import purem

# Automatic setup using license key
try:
    purem.configure(license_key='<your-license-key>')
except Exception as e:
    print(f"Setup failed: {e}")

data = np.array([1.0, 2.0, 3.0], dtype=float)
output = purem.softmax(data)

print(output)

—

🧠 Why Purem?

  • 🔥 High level performance with zero Python overhead

  • 🧪 Built-in benchmarking and scientific accuracy

  • 🧩 Easy plug-and-play design

  • 🔐 Secure and license-aware system

—

🛠 Advanced Usage & API Docs

Coming soon…

Release files for purem 3.0.6

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for purem 3.0.6
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purem-3.0.6.tar.gz 14.3 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for purem 3.0.6
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purem-3.0.6-py3-none-any.whl Python 3 none any Details

Total release size: 28.5 kB

Release files / purem-3.0.6.tar.gz

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Release files / purem-3.0.6-py3-none-any.whl

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