Installation

Choose an install path that matches how you intend to use the stack: a quick check from PyPI, a source checkout for development, or a server-style batch environment.

PyPI (recommended for most users) — install the published package to confirm behaviour and run small experiments:

pip install porosdata-processor

Source checkout — use when you need to read or change implementation details, or to test unpublished fixes:

git clone https://github.com/KiventYip/porosdata-processor.git
cd porosdata-processor
pip install -e .

If the repository documents an optional “full” or development extra, install it in the same environment when you run tests or CI locally.

Environment — use Python 3.8 or newer, preferably inside a virtual environment with enough disk space for raw, intermediate, and structured outputs. For sustained batch work, Linux on SSD or NVMe is usually more predictable than a laptop disk under heavy I/O.

Sanity checks — after install, confirm the package imports and, if you rely on the CLI, that the module entry responds:

import porosdata_processor
print(porosdata_processor.__version__)

python -m porosdata_processor --help

Before the first real run — line up (1) source documents or Parser output under Raw Database, (2) a writable output root for Processed Database / Designed Database, and (3) a small sample you can reprocess until results look stable.

Next: Quick Start · End-to-end workflow · Examples · Home