deepmodeling/dpdata-plugin

dpdata-plugin

dpdata loads plugins in two ways:

1. Built-in plugins in dpdata.plugins.* (imported automatically)
2. External plugins exposed via Python package entry points: dpdata.plugins

This skill focuses on external plugin packages, the recommended way to add new formats without modifying dpdata itself.

What can be extended?

Most commonly: add a new Format (file reader/writer) via:

from dpdata.format import Format


@Format.register("myfmt")
class MyFormat(Format): ...

How dpdata discovers plugins

dpdata imports dpdata.plugins during normal use (e.g. dpdata.system imports it). That module:

• imports every built-in module in dpdata/plugins/*.py
• then loads all entry points in group dpdata.plugins

So an external plugin package only needs to ensure that importing the entry-point target triggers the @Format.register(...) side effects.

Minimal external plugin package (based on plugin_example/)

1) Create a new Python package

Example layout:

dpdata_random/
  pyproject.toml
  dpdata_random/
    __init__.py

2) Implement and register your Format

In dpdata_random/__init__.py (shortened example):

from __future__ import annotations

import numpy as np
from dpdata.format import Format


@Format.register("random")
class RandomFormat(Format):
    def from_system(self, file_name, **kwargs):
        nframes = int(file_name)
        return {
            "atom_numbs": [20],
            "atom_names": ["X"],
            "atom_types": np.zeros(20, dtype=int),
            "cells": np.repeat(np.eye(3)[None, ...], nframes, axis=0) * 100.0,
            "coords": np.random.rand(nframes, 20, 3) * 100.0,
            "orig": np.zeros(3),
            "nopbc": False,
        }

Return dicts must match dpdata’s expected schema (cells/coords/atom_names/atom_types/...). Here file_name is the argument dpdata passes into from_system; this example interprets it as an integer frame count.

3) Expose an entry point

In pyproject.toml:

[project]
name = "dpdata_random"
version = "0.0.0"
dependencies = ["numpy", "dpdata"]

[project.entry-points.'dpdata.plugins']
random = "dpdata_random:RandomFormat"

Any importable target works; this pattern points directly at the class.

4) Install and test

In a clean env (recommended via uv):

uv venv
. .venv/bin/activate
uv pip install -e . dpdata numpy
python - <<'PY'
import dpdata
from dpdata.format import Format

# importing dpdata will load entry points (dpdata.plugins)
print('random' in Format.get_formats())
PY

If it prints True, your plugin was discovered.

Debug checklist

• Did you install the plugin package into the same environment where you run dpdata?
• Does pyproject.toml contain [project.entry-points.'dpdata.plugins']?
• Does importing the entry point module/class execute the @Format.register(...) decorator?
• Before choosing a key like random, check Format.get_formats() to avoid colliding with an existing built-in or previously loaded plugin key.
• If using uv run, remember each command runs in its own environment unless you’re in a uv project (or you rely on uv run --with ...).