bump pre-commit hooks, tweak ruff config, delete debug print statements

.pre-commit-config.yaml

@@ -4,7 +4,7 @@ default_install_hook_types: [pre-commit, commit-msg]
 
 repos:
   - repo: https://github.com/astral-sh/ruff-pre-commit
-    rev: v0.1.8
+    rev: v0.1.14
     hooks:
       - id: ruff
         args: [--fix]
@@ -46,7 +46,7 @@ repos:
           - svelte
 
   - repo: https://github.com/pre-commit/mirrors-eslint
-    rev: v8.56.0
+    rev: v9.0.0-alpha.1
     hooks:
       - id: eslint
         types: [file]

README.md

@@ -4,10 +4,10 @@
 
 [![Tests](https://github.com/CederGroupHub/chgnet/actions/workflows/test.yml/badge.svg)](https://github.com/CederGroupHub/chgnet/actions/workflows/test.yml)
 [![Codacy Badge](https://app.codacy.com/project/badge/Coverage/e3bdcea0382a495d96408e4f84408e85)](https://app.codacy.com/gh/CederGroupHub/chgnet/dashboard?utm_source=gh&utm_medium=referral&utm_content=&utm_campaign=Badge_coverage)
-[![arXiv](https://img.shields.io/badge/arXiv-2302.14231-blue)](https://arxiv.org/abs/2302.14231)
-![GitHub repo size](https://img.shields.io/github/repo-size/CederGroupHub/chgnet)
+[![arXiv](https://img.shields.io/badge/arXiv-2302.14231-blue?logo=arxiv&logoColor=white)](https://arxiv.org/abs/2302.14231)
+![GitHub repo size](https://img.shields.io/github/repo-size/CederGroupHub/chgnet?logo=github&logoColor=white&label=Repo%20Size)
 [![PyPI](https://img.shields.io/pypi/v/chgnet?logo=pypi&logoColor=white)](https://pypi.org/project/chgnet?logo=pypi&logoColor=white)
-[![Docs](https://img.shields.io/badge/API-Docs-blue)](https://chgnet.lbl.gov)
+[![Docs](https://img.shields.io/badge/API-Docs-blue?logo=readthedocs&logoColor=white)](https://chgnet.lbl.gov)
 [![Requires Python 3.9+](https://img.shields.io/badge/Python-3.9+-blue.svg?logo=python&logoColor=white)](https://python.org/downloads)
 
 </h4>

examples/fine_tuning.ipynb

@@ -19,7 +19,7 @@
     "    import chgnet\n",
     "except ImportError:\n",
     "    # install CHGNet (only needed on Google Colab or if you didn't install CHGNet yet)\n",
-    "    !pip install chgnet\n"
+    "    !pip install chgnet"
    ]
   },
   {
@@ -45,7 +45,7 @@
     "# If the above line fails in Google Colab due to numpy version issue,\n",
     "# please restart the runtime, and the problem will be solved\n",
     "\n",
-    "chgnet = CHGNet.load()\n"
+    "chgnet = CHGNet.load()"
    ]
   },
   {
@@ -82,7 +82,7 @@
     "\n",
     "# ./my_vasp_calc_dir contains vasprun.xml OSZICAR etc.\n",
     "dataset_dict = parse_vasp_dir(file_root=\"./my_vasp_calc_dir\")\n",
-    "print(list(dataset_dict))\n"
+    "print(list(dataset_dict))"
    ]
   },
   {
@@ -135,7 +135,7 @@
     "converter = CrystalGraphConverter()\n",
     "for idx, struct in enumerate(dataset_dict[\"structure\"]):\n",
     "    graph = converter(struct)\n",
-    "    graph.save(fname=f\"{idx}.pt\")\n"
+    "    graph.save(fname=f\"{idx}.pt\")"
    ]
   },
   {
@@ -205,7 +205,7 @@
     "    stresses.append(\n",
     "        pred[\"s\"] * -10 + np.random.uniform(-0.05, 0.05, size=pred[\"s\"].shape)\n",
     "    )\n",
-    "    magmoms.append(pred[\"m\"] + np.random.uniform(-0.03, 0.03, size=pred[\"m\"].shape))\n"
+    "    magmoms.append(pred[\"m\"] + np.random.uniform(-0.03, 0.03, size=pred[\"m\"].shape))"
    ]
   },
   {
@@ -233,7 +233,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from chgnet.data.dataset import StructureData, get_train_val_test_loader\n"
+    "from chgnet.data.dataset import StructureData, get_train_val_test_loader"
    ]
   },
   {
@@ -260,7 +260,7 @@
     ")\n",
     "train_loader, val_loader, test_loader = get_train_val_test_loader(\n",
     "    dataset, batch_size=8, train_ratio=0.9, val_ratio=0.05\n",
-    ")\n"
+    ")"
    ]
   },
   {
@@ -301,7 +301,7 @@
     "from chgnet.trainer import Trainer\n",
     "\n",
     "# Load pretrained CHGNet\n",
-    "chgnet = CHGNet.load()\n"
+    "chgnet = CHGNet.load()"
    ]
   },
   {
@@ -331,7 +331,7 @@
     "    chgnet.angle_layers,\n",
     "]:\n",
     "    for param in layer.parameters():\n",
-    "        param.requires_grad = False\n"
+    "        param.requires_grad = False"
    ]
   },
   {
@@ -352,7 +352,7 @@
     "    learning_rate=1e-2,\n",
     "    use_device=\"cpu\",\n",
     "    print_freq=6,\n",
-    ")\n"
+    ")"
    ]
   },
   {
@@ -401,7 +401,7 @@
     }
    ],
    "source": [
-    "trainer.train(train_loader, val_loader, test_loader)\n"
+    "trainer.train(train_loader, val_loader, test_loader)"
    ]
   },
   {
@@ -420,7 +420,7 @@
    "outputs": [],
    "source": [
     "model = trainer.model\n",
-    "best_model = trainer.best_model  # best model based on validation energy MAE\n"
+    "best_model = trainer.best_model  # best model based on validation energy MAE"
    ]
   },
   {
@@ -465,7 +465,7 @@
     "# Imagine this is the VASP raw energy\n",
     "vasp_raw_energy = -58.97\n",
     "\n",
-    "print(f\"The raw total energy from VASP of LMO is: {vasp_raw_energy} eV\")\n"
+    "print(f\"The raw total energy from VASP of LMO is: {vasp_raw_energy} eV\")"
    ]
   },
   {
@@ -511,7 +511,7 @@
     "corrected_energy = (\n",
     "    vasp_raw_energy + num_Mn * Mn_correction_in_TMO + num_O * oxide_correction\n",
     ")\n",
-    "print(f\"The corrected total energy after MP2020 = {corrected_energy:.4} eV\")\n"
+    "print(f\"The corrected total energy after MP2020 = {corrected_energy:.4} eV\")"
    ]
   },
   {
@@ -547,7 +547,7 @@
     "MaterialsProject2020Compatibility(check_potcar=False).process_entries(cse)\n",
     "print(\n",
     "    f\"The total energy of LMO after MP2020Compatibility correction = {cse.energy:.4} eV\"\n",
-    ")\n"
+    ")"
    ]
   },
   {
@@ -626,7 +626,7 @@
     }
    ],
    "source": [
-    "trainer.train(train_loader, val_loader, test_loader, train_composition_model=True)\n"
+    "trainer.train(train_loader, val_loader, test_loader, train_composition_model=True)"
    ]
   },
   {
@@ -669,7 +669,7 @@
    "source": [
     "print(\"The pretrained Atom_Ref (per atom reference energy):\")\n",
     "for param in chgnet.composition_model.parameters():\n",
-    "    print(param)\n"
+    "    print(param)"
    ]
   },
   {
@@ -700,7 +700,7 @@
     "]\n",
     "\n",
     "# A list of energy_per_atom values (random values here)\n",
-    "energies_per_atom = [5.5, 6, 4.8, 5.6]\n"
+    "energies_per_atom = [5.5, 6, 4.8, 5.6]"
    ]
   },
   {
@@ -725,7 +725,7 @@
     "new_atom_ref = AtomRef(is_intensive=True)\n",
     "new_atom_ref.initialize_from_MPtrj()\n",
     "for param in new_atom_ref.parameters():\n",
-    "    print(param[:, :3])\n"
+    "    print(param[:, :3])"
    ]
   },
   {
@@ -769,7 +769,7 @@
     "new_atom_ref.fit(structures, energies_per_atom)\n",
     "print(\"After refitting, the AtomRef looks like:\")\n",
     "for param in new_atom_ref.parameters():\n",
-    "    print(param)\n"
+    "    print(param)"
    ]
   }
  ],
@@ -789,7 +789,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.6"
+   "version": "3.11.7"
   }
  },
  "nbformat": 4,

examples/make_graphs.py

@@ -59,12 +59,12 @@ def make_graphs(
 
 def make_one_graph(mp_id: str, graph_id: str, data, graph_dir) -> dict | bool:
     """Convert a structure to a CrystalGraph and save it."""
-    dic = data.data[mp_id].pop(graph_id)
-    struct = Structure.from_dict(dic.pop("structure"))
+    dct = data.data[mp_id].pop(graph_id)
+    struct = Structure.from_dict(dct.pop("structure"))
     try:
         graph = data.graph_converter(struct, graph_id=graph_id, mp_id=mp_id)
         torch.save(graph, os.path.join(graph_dir, f"{graph_id}.pt"))
-        return dic
+        return dct
     except Exception:
         return False
 

pyproject.toml

@@ -74,6 +74,7 @@ select = [
     "RUF",  # Ruff-specific rules
     "SIM",  # flake8-simplify
     "SLOT", # flakes8-slot
+    "T201",
     "TCH",  # flake8-type-checking
     "TID",  # tidy imports
     "TID",  # flake8-tidy-imports
@@ -82,25 +83,34 @@ select = [
     "YTT",  # flake8-2020
 ]
 ignore = [
+    "ANN001",  # TODO add missing type annotations
+    "ANN101",  # Missing type annotation for self in method
     "B019",    # Use of functools.lru_cache on methods can lead to memory leaks
     "C408",    # unnecessary-collection-call
+    "COM812",  # trailing comma missing
     "D100",    # Missing docstring in public module
     "D104",    # Missing docstring in public package
     "D205",    # 1 blank line required between summary line and description
+    "FBT001",  # Boolean positional argument in function
+    "FBT002",  # Boolean keyword argument in function
+    "NPY002",  # TODO replace legacy np.random.seed
     "PLR",     # pylint refactor
     "PLW2901", # Outer for loop variable overwritten by inner assignment target
     "PT006",   # pytest-parametrize-names-wrong-type
     "PT011",   # pytest-raises-too-broad
     "PT013",   # pytest-incorrect-pytest-import
     "PT019",   # pytest-fixture-param-without-value
+    "PTH",     # prefer Path to os.path
 ]
 pydocstyle.convention = "google"
 isort.required-imports = ["from __future__ import annotations"]
 isort.split-on-trailing-comma = false
 
 [tool.ruff.per-file-ignores]
-"tests/*" = ["D103"]
-"examples/*" = ["E402", "I002"] # E402 Module level import not at top of file
+"tests/*" = ["ANN201", "D103", "INP001", "S101"]
+# E402 Module level import not at top of file
+"examples/*" = ["E402", "I002", "T201"]
+"chgnet/**/*" = ["T201"]
 "__init__.py" = ["F401"]
 
 

site/tsconfig.json

@@ -11,6 +11,6 @@
     "sourceMap": true,
 
     "forceConsistentCasingInFileNames": true,
-    "resolveJsonModule": true
-  }
+    "resolveJsonModule": true,
+  },
 }

tests/test_converter.py

@@ -1,5 +1,7 @@
 from __future__ import annotations
 
+from typing import Literal
+
 import pytest
 from pymatgen.core import Lattice, Structure
 from pytest import CaptureFixture
@@ -14,7 +16,7 @@
 
 
 @pytest.fixture()
-def _set_make_graph():
+def _set_make_graph() -> None:
     # fixture to force make_graph to be None and then restore it after test
     from chgnet.graph import converter
 
@@ -27,7 +29,9 @@ def _set_make_graph():
 @pytest.mark.parametrize(
     "atom_graph_cutoff, bond_graph_cutoff", [(5, 3), (5, None), (4, 2)]
 )
-def test_crystal_graph_converter_cutoff(atom_graph_cutoff, bond_graph_cutoff):
+def test_crystal_graph_converter_cutoff(
+    atom_graph_cutoff: float | None, bond_graph_cutoff: float | None
+):
     converter = CrystalGraphConverter(
         atom_graph_cutoff=atom_graph_cutoff, bond_graph_cutoff=bond_graph_cutoff
     )
@@ -36,14 +40,14 @@ def test_crystal_graph_converter_cutoff(atom_graph_cutoff, bond_graph_cutoff):
 
 
 @pytest.mark.parametrize("algorithm", ["legacy", "fast"])
-def test_crystal_graph_converter_algorithm(algorithm):
+def test_crystal_graph_converter_algorithm(algorithm: Literal["legacy", "fast"]):
     converter = CrystalGraphConverter(
         atom_graph_cutoff=5, bond_graph_cutoff=3, algorithm=algorithm
     )
     assert converter.algorithm == algorithm
 
 
-def test_crystal_graph_converter_warns(_set_make_graph):
+def test_crystal_graph_converter_warns(_set_make_graph: None):
     with pytest.warns(UserWarning, match="Unknown algorithm='foobar', using `legacy`"):
         CrystalGraphConverter(
             atom_graph_cutoff=5, bond_graph_cutoff=3, algorithm="foobar"