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migrate readme to markdown

devel
Stefan Holst 22 hours ago
parent
commit
5ac21edbb1
  1. 4
      .readthedocs.yaml
  2. 32
      README.md
  3. 32
      README.rst
  4. 2
      docs/Makefile
  5. 1
      docs/conf.py
  6. 3
      docs/index.rst
  7. 2
      pyproject.toml

4
.readthedocs.yaml

@ -3,10 +3,10 @@ version: 2 @@ -3,10 +3,10 @@ version: 2
build:
os: "ubuntu-20.04"
tools:
python: "3.8"
python: "3.10"
jobs:
post_create_environment:
- python -m pip install sphinx_rtd_theme
- python -m pip install sphinx_rtd_theme myst-parser
sphinx:
fail_on_warning: true

32
README.md

@ -0,0 +1,32 @@ @@ -0,0 +1,32 @@
KyuPy - Pythonic Processing of VLSI Circuits
============================================
KyuPy is a Python package for processing and analysis of non-hierarchical gate-level VLSI designs.
It contains fundamental building blocks for research software in the fields of VLSI test, diagnosis and reliability:
* Efficient data structures for gate-level circuits and related design data.
* Partial [lark](https://github.com/lark-parser/lark) parsers for common design files like
bench, gate-level Verilog, standard delay format (SDF), standard test interface language (STIL), design exchange format (DEF).
* Bit-parallel gate-level 2-, 4-, and 8-valued logic simulation.
* GPU-accelerated high-throughput gate-level timing simulation.
* High-performance through the use of [numpy](https://numpy.org) and [numba](https://numba.pydata.org).
Getting Started
---------------
KyuPy is available in [PyPI](https://pypi.org/project/kyupy).
It requires Python 3.10 or newer, [lark](https://pypi.org/project/lark), and [numpy](https://numpy.org).
Although optional, [numba](https://numba.pydata.org) should be installed for best performance. [numba-cuda](https://nvidia.github.io/numba-cuda/) is required for GPU/CUDA acceleration.
If numba is not available, KyuPy will automatically fall back to slow, pure Python execution.
The Jupyter Notebook [Introduction.ipynb](https://github.com/s-holst/kyupy/blob/main/examples/Introduction.ipynb) contains some useful examples to get familiar with the API.
Development
-----------
To work with the latest pre-release source code, clone the [KyuPy GitHub repository](https://github.com/s-holst/kyupy).
* Using ``pip``: Run ``pip install -e .`` within your local checkout to make the package available in your Python environment. The source code comes with tests that can be run with ``pytest``.
* Using ``uv``: Run ``uv run pytest`` within your local checkout to get started.

32
README.rst

@ -1,32 +0,0 @@ @@ -1,32 +0,0 @@
KyuPy - Pythonic Processing of VLSI Circuits
============================================
KyuPy is a Python package for processing and analysis of non-hierarchical gate-level VLSI designs.
It contains fundamental building blocks for research software in the fields of VLSI test, diagnosis and reliability:
* Efficient data structures for gate-level circuits and related design data.
* Partial `lark <https://github.com/lark-parser/lark>`_ parsers for common design files like
bench, gate-level Verilog, standard delay format (SDF), standard test interface language (STIL), design exchange format (DEF).
* Bit-parallel gate-level 2-, 4-, and 8-valued logic simulation.
* GPU-accelerated high-throughput gate-level timing simulation.
* High-performance through the use of `numpy <https://numpy.org>`_ and `numba <https://numba.pydata.org>`_.
Getting Started
---------------
KyuPy is available in `PyPI <https://pypi.org/project/kyupy>`_.
It requires Python 3.8 or newer, `lark-parser <https://pypi.org/project/lark-parser>`_, and `numpy`_.
Although optional, `numba`_ should be installed for best performance.
GPU/CUDA support in numba may `require some additional setup <https://numba.readthedocs.io/en/stable/cuda/index.html>`_.
If numba is not available, KyuPy will automatically fall back to slow, pure Python execution.
The Jupyter Notebook `Introduction.ipynb <https://github.com/s-holst/kyupy/blob/main/examples/Introduction.ipynb>`_ contains some useful examples to get familiar with the API.
Development
-----------
To work with the latest pre-release source code, clone the `KyuPy GitHub repository <https://github.com/s-holst/kyupy>`_.
Run ``pip install -e .`` within your local checkout to make the package available in your Python environment.
The source code comes with tests that can be run with ``pytest``.

2
docs/Makefile

@ -1,4 +1,4 @@ @@ -1,4 +1,4 @@
# pip install sphinx sphinx-rtd-theme
# pip install sphinx sphinx-rtd-theme myst-parser
#
# Minimal makefile for Sphinx documentation
#

1
docs/conf.py

@ -35,6 +35,7 @@ release = '0.0.6' @@ -35,6 +35,7 @@ release = '0.0.6'
extensions = [
'sphinx.ext.autodoc',
'sphinx_rtd_theme',
'myst_parser',
]
# Add any paths that contain templates here, relative to this directory.

3
docs/index.rst

@ -1,4 +1,5 @@ @@ -1,4 +1,5 @@
.. include:: ../README.rst
.. include:: ../README.md
:parser: myst_parser.sphinx_
API Reference
-------------

2
pyproject.toml

@ -5,7 +5,7 @@ authors = [ @@ -5,7 +5,7 @@ authors = [
{ name="Stefan Holst", email="mail@s-holst.de" },
]
description = 'High-performance processing and analysis of non-hierarchical VLSI designs'
readme = "README.rst"
readme = "README.md"
requires-python = ">=3.10,<3.14"
dependencies = [
"numpy>=1.17.0",

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