INSTALLATION.md

Installation Guide

Quick Start

git clone <your-repo-url>
cd SpatialClaw
pip install -e .

python spatialclaw.py env
python spatialclaw.py list
python spatialclaw.py run spatial-preprocessing --demo
sc list

System Requirements

Component	Minimum	Recommended
Python	3.10	3.10 or 3.11
RAM	8 GB	32 GB+
Disk	2 GB	10 GB+ with full optional spatial stack
GPU	Optional	CUDA GPU for deep learning methods

Dependency Tiers

Core install:

pip install -e .

Optional spatial tiers:

pip install -e ".[spatial]"
pip install -e ".[spatial-domain-identification]"
pip install -e ".[full]"

Interactive and development tiers:

pip install -e ".[interactive]"
pip install -e ".[tui]"
pip install -e ".[memory]"
pip install -e ".[research]"
pip install -e ".[dev]"

Using The Tsinghua PyPI Mirror

pip install -e . -i https://pypi.tuna.tsinghua.edu.cn/simple
pip install -e ".[full]" -i https://pypi.tuna.tsinghua.edu.cn/simple

Verification

For a fast installation check, use the same smoke target as CI-oriented local validation:

python spatialclaw.py list
sc list
make test-smoke

To verify demo execution:

python spatialclaw.py run spatial-preprocessing --demo --output /tmp/spatialclaw_demo
python spatialclaw.py run spatial-orchestrator --demo --output /tmp/spatialclaw_orchestrator
spatialclaw-chat --help
sc-chat --help

Run the full pytest suite only when you need broad regression coverage:

python -m pytest -v

On this server, validation should be run inside the configured conda environment:

conda run -n sppy310 python spatialclaw.py list
conda run -n sppy310 make test-smoke

Troubleshooting

If a package is missing, install it into the active environment:

pip install <package> -i https://pypi.tuna.tsinghua.edu.cn/simple

For CUDA mismatches, install the correct PyTorch wheel before optional spatial deep learning tiers.