Metadata-Version: 2.4
Name: scientific-computing-system-2.0
Version: 5.2.5
Summary: A NumPy/SciPy/Pandas/Matplotlib-powered scientific computing platform: accelerated linear algebra, statistics, optimization, integration, interpolation, signal processing, Monte Carlo, graphs (with PageRank), machine learning, time series, visualization and I/O.
Author-email: Furox-Art <furkanarkn1451@gmail.com>
License-Expression: MIT
Project-URL: Homepage, https://github.com/Furox-Art/scientific-computing-system-2.0
Project-URL: Repository, https://github.com/Furox-Art/scientific-computing-system-2.0
Project-URL: Issues, https://github.com/Furox-Art/scientific-computing-system-2.0/issues
Project-URL: Changelog, https://github.com/Furox-Art/scientific-computing-system-2.0/releases
Keywords: scientific-computing,scientific-python,numpy,scipy,pandas,matplotlib,machine-learning,signal-processing,statistics,optimization,monte-carlo,graph-theory,pagerank,time-series,numerical-methods,data-analysis,bayesian-inference,reinforcement-learning,chaos-theory,information-theory,computational-geometry,pde,sde,visualization
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Developers
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: 3.13
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Mathematics
Classifier: Topic :: Scientific/Engineering :: Physics
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Scientific/Engineering :: Visualization
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Classifier: Typing :: Typed
Requires-Python: >=3.10
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: numpy>=1.26
Requires-Dist: scipy>=1.11
Requires-Dist: pandas>=2.2
Requires-Dist: matplotlib>=3.8
Provides-Extra: dev
Requires-Dist: openpyxl; extra == "dev"
Requires-Dist: pyarrow; extra == "dev"
Requires-Dist: pandas-stubs>=2.0; extra == "dev"
Requires-Dist: numpy<2.5,>=1.26; extra == "dev"
Requires-Dist: pytest>=8.0; extra == "dev"
Requires-Dist: pytest-cov; extra == "dev"
Requires-Dist: ruff>=0.4; extra == "dev"
Requires-Dist: mypy>=1.10; extra == "dev"
Requires-Dist: networkx>=3.0; extra == "dev"
Requires-Dist: hypothesis>=6.0; extra == "dev"
Requires-Dist: scikit-learn>=1.4; extra == "dev"
Provides-Extra: test
Requires-Dist: pytest>=8.0; extra == "test"
Requires-Dist: pytest-cov; extra == "test"
Requires-Dist: hypothesis>=6.0; extra == "test"
Requires-Dist: scikit-learn>=1.4; extra == "test"
Provides-Extra: gpu
Requires-Dist: cupy-cuda12x; extra == "gpu"
Provides-Extra: docs
Requires-Dist: mkdocs>=1.6; extra == "docs"
Requires-Dist: mkdocs-material>=9.5; extra == "docs"
Requires-Dist: mkdocstrings[python]>=0.26; extra == "docs"
Provides-Extra: all
Requires-Dist: openpyxl; extra == "all"
Requires-Dist: pyarrow; extra == "all"
Requires-Dist: pandas-stubs>=2.0; extra == "all"
Requires-Dist: numpy<2.5,>=1.26; extra == "all"
Requires-Dist: pytest>=8.0; extra == "all"
Requires-Dist: pytest-cov; extra == "all"
Requires-Dist: ruff>=0.4; extra == "all"
Requires-Dist: mypy>=1.10; extra == "all"
Requires-Dist: networkx>=3.0; extra == "all"
Requires-Dist: mkdocs>=1.6; extra == "all"
Requires-Dist: mkdocs-material>=9.5; extra == "all"
Requires-Dist: mkdocstrings[python]>=0.26; extra == "all"
Requires-Dist: hypothesis>=6.0; extra == "all"
Requires-Dist: scikit-learn>=1.4; extra == "all"
Requires-Dist: cupy-cuda12x; extra == "all"
Dynamic: license-file

# scientific-computing-system-2.0  
  
<p align="center">  
  <img src="https://raw.githubusercontent.com/Furox-Art/scientific-computing-system-2.0/main/docs/assets/promo_hero.png" alt="scientific-computing-system-2.0 scientific computing platform" width="100%">  
</p>  
  
[![CI](https://github.com/Furox-Art/scientific-computing-system-2.0/actions/workflows/tests.yml/badge.svg)](https://github.com/Furox-Art/scientific-computing-system-2.0/actions/workflows/tests.yml)  
[![PyPI](https://img.shields.io/pypi/v/scientific-computing-system-2.0)](https://pypi.org/project/scientific-computing-system-2.0/)  
[![npm](https://img.shields.io/npm/v/scientific-computing-system-2.0)](https://www.npmjs.com/package/scientific-computing-system-2.0)  
[![Python](https://img.shields.io/pypi/pyversions/scientific-computing-system-2.0)](https://pypi.org/project/scientific-computing-system-2.0/)  
  
The original scientific-computing-system was pure Python-no NumPy, no SciPy, no dependencies. It was beautiful and slow and educational.  
  
This is the pragmatic sequel. It uses NumPy, SciPy, pandas, and matplotlib under the hood, but wraps them in a cleaner, more consistent API. You get the speed of optimized C with the readability of modern Python.  
  
## What changed from v1  
  
- **Performance**: 10-100x faster on real workloads (thanks, NumPy)  
- **Coverage**: More algorithms, more edge cases handled  
- **Testing**: Property-based tests, oracle comparisons against reference implementations  
- **Documentation**: Actually complete, with examples that run  
  
## The philosophy  
  
Scientific code should be boring. Not boring to write-boring to read. You should be able to look at a function and know exactly what it does, what it expects, and what it returns. No magic, no hidden state, no "just trust the library."  
  
Every function here has type hints, docstrings with examples, and tests that verify the math against known results. If the documentation and the code disagree, the code is wrong.  
  
## License  
  
MIT. 
