# lammps-api-and-scripting

> This skill should be used when users ask about api and scripting in lammps; it prioritizes documentation references and then source inspection only for unresolved details.

- Author: Tao E. Li
- Repository: TEL-Research-Group/lammps
- Version: 20260207223556
- Stars: 0
- Forks: 0
- Last Updated: 2026-02-08
- Source: https://github.com/TEL-Research-Group/lammps
- Web: https://mule.run/skillshub/@@TEL-Research-Group/lammps~lammps-api-and-scripting:20260207223556

---

---
name: lammps-api-and-scripting
description: This skill should be used when users ask about api and scripting in lammps; it prioritizes documentation references and then source inspection only for unresolved details.
---

# lammps: API and Scripting

## High-Signal Playbook
### Route the request
- Use `lammps-build-and-install` for shared-library and Python-install prerequisites.
- Use `lammps-simulation-workflows` for ensemble/restart sequencing once control flow is set.
- Use `lammps-analysis-and-output` for structured outputs or data extraction strategies.

### Triage questions
- Do you need Python to launch LAMMPS, or LAMMPS to call Python functions?
- Is LAMMPS built as a shared library in this environment?
- Are you running serial Python or MPI-parallel Python?
- Is your use case command streaming, data extraction, or both?

### Canonical workflow
- Build/install shared LAMMPS + Python module (`doc/src/Python_overview.rst`, `doc/src/Python_install.rst`).
- Verify Python can import `lammps` and find shared libraries.
- Create a `lammps` instance and issue commands incrementally (`doc/src/Python_run.rst`, `doc/src/Python_execute.rst`).
- Use extraction/scatter APIs when direct data exchange is needed (`doc/src/Python_properties.rst`, `doc/src/Python_atoms.rst`).
- Keep core simulation logic debuggable by first validating equivalent plain input scripts.

### Minimal working example
- Python launch skeleton (`doc/src/Python_overview.rst`, `doc/src/Python_run.rst`):
```python
from lammps import lammps
lmp = lammps()
lmp.command("units lj")
lmp.command("atom_style atomic")
lmp.command("read_data data.system")
lmp.command("pair_style lj/cut 2.5")
lmp.command("pair_coeff * * 1.0 1.0")
lmp.command("fix int all nve")
lmp.command("run 1000")
```

### Pitfalls
- Python module use without shared-library build (`doc/src/Python_overview.rst`).
- Environment path issues for module/shared object discovery.
- Assuming interactive parallel Python works in generic terminal setups (`doc/src/Python_overview.rst`).
- Divergence between Python-generated commands and tested input scripts.

### Validation checklist
- Import test passes and one short script runs successfully.
- Thermodynamic output matches equivalent plain-input execution.
- Data extraction returns expected dimensions/types for selected properties.

## Scope
- Handle questions about language bindings, APIs, and programmatic interfaces.
- Keep responses abstract and architectural for large codebases; avoid exhaustive per-function documentation unless requested.

## Primary documentation references
- `doc/src/Python_overview.rst`
- `doc/src/Python_run.rst`
- `doc/src/Python_launch.rst`
- `doc/src/Python_module.rst`
- `doc/src/Python_execute.rst`
- `doc/src/Python_properties.rst`
- `doc/src/Python_atoms.rst`
- `doc/src/Python_scatter.rst`
- `doc/src/Python_neighbor.rst`
- `doc/src/Python_install.rst`

## Workflow
- Start with the primary references above.
- If details are missing, inspect `references/doc_map.md` for additional topic documents (generated inventory plus curated anchors).
- Use tutorials/examples as executable usage patterns when available.
- Use tests as behavior or regression references when available.
- If ambiguity remains after docs, inspect `references/source_map.md` and start with the ranked source entry points.
- Cite exact documentation file paths in responses.

## Tutorials and examples
- `examples`

## Test references
- None discovered.

## Optional deeper inspection
- `fortran`
- `lib`
- `python`
- `src`

## Source entry points for unresolved issues
- `src/library.h`
- `src/library.cpp`
- `src/lammps.h`
- `src/lammps.cpp`
- `python/lammps/core.py`
- `python/lammps/numpy_wrapper.py`
- `python/lammps/data.py`
- `python/lammps/formats.py`
- `fortran/lammps.f90`
- Prefer targeted source search (for example: `rg -n "<symbol_or_keyword>" fortran lib python src`).