Remove all references to pylint

.pre-commit-config.yaml

@@ -8,18 +8,6 @@ repos:
         args: [ --fix ]
       - id: ruff-format
 
-  - repo: https://github.com/asottile/pyupgrade
-    rev: v3.15.0
-    hooks:
-    - id: pyupgrade
-      args: [--py38-plus]
-
-  - repo: https://github.com/PyCQA/pylint
-    rev: v3.0.3
-    hooks:
-      - id: pylint
-        args: ["--disable=import-error"]
-
   - repo: local
     hooks:
       - id: mypy

profiler.py

@@ -2,10 +2,10 @@
 import pstats
 import random
 
-import torchvision  # type: ignore[import-untyped]  # pylint: disable=unused-import  # noqa: F401
-from tqdm import trange  # pylint: disable=unused-import  # noqa: F401
+import torchvision  # type: ignore[import-untyped]  # noqa: F401
+from tqdm import trange  # noqa: F401
 
-from torchinfo import summary  # pylint: disable=unused-import  # noqa: F401
+from torchinfo import summary  # noqa: F401
 
 
 def profile() -> None:

requirements-dev.txt

@@ -1,10 +1,5 @@
-black
 codecov
-flake8
-isort
 mypy
-pycln
-pylint
 pytest
 pytest-cov
 pre-commit

ruff.toml

@@ -1,3 +1,4 @@
+target-version = "py37"
 select = ["ALL"]
 ignore = [
     "ANN101",  # Missing type annotation for `self` in method
@@ -13,20 +14,21 @@ ignore = [
 	"FBT002",  # Boolean default value in function definition
 	"FBT003",  # Boolean positional value in function call
 	"FIX002",  # Line contains TODO
-	"ISC001",  # single-line-implicit-string-concatenation
+	"ISC001",  # Isort
     "PLR0911", # Too many return statements (11 > 6)
 	"PLR2004", # Magic value used in comparison, consider replacing 2 with a constant variable
     "PLR0912", # Too many branches
 	"PLR0913", # Too many arguments to function call
 	"PLR0915", # Too many statements
-	"PTH123",  # `open()` should be replaced by `Path.open()`
 	"S101",    # Use of `assert` detected
 	"S311",    # Standard pseudo-random generators are not suitable for cryptographic purposes
 	"T201",    # print() found
+	"T203",    # pprint() found
 	"TCH001",  # Move application import into a type-checking block
     "TCH003",  # Move standard library import into a type-checking block
 	"TD002",   # Missing author in TODO; try: `# TODO(<author_name>): ...`
 	"TD003",   # Missing issue link on the line following this TODO
+	"TD005",   # Missing issue description after `TODO`
 	"TRY003",  # Avoid specifying long messages outside the exception class
 
 	# torchinfo-specific ignores
@@ -42,7 +44,6 @@ ignore = [
     "TRY004",  # Prefer `TypeError` exception for invalid type
     "TRY301",  # Abstract `raise` to an inner function
 ]
-target-version = "py37"
 exclude = ["tests"]  # TODO: check tests too
 
 [flake8-pytest-style]

setup.cfg

@@ -33,25 +33,7 @@ torchinfo = py.typed
 
 [mypy]
 strict = True
-implicit_reexport = True
+warn_unreachable = True
+disallow_any_unimported = True
+extra_checks = True
 enable_error_code = ignore-without-code
-
-[pylint.MESSAGES CONTROL]
-extension-pkg-whitelist = torch
-enable =
-    useless-suppression,
-    deprecated-pragma,
-    use-symbolic-message-instead,
-disable =
-    missing-module-docstring,
-    missing-function-docstring,
-    too-many-instance-attributes,
-    too-many-arguments,
-    too-many-branches,
-    too-many-locals,
-    invalid-name,
-    line-too-long,  # Covered by flake8
-    no-member,
-    fixme,
-    duplicate-code,
-fail-on = useless-suppression

tests/conftest.py

@@ -6,7 +6,8 @@
 import pytest
 
 from torchinfo import ModelStatistics
-from torchinfo.formatting import HEADER_TITLES, ColumnSettings
+from torchinfo.enums import ColumnSettings
+from torchinfo.formatting import HEADER_TITLES
 from torchinfo.torchinfo import clear_cached_forward_pass
 
 

tests/fixtures/genotype.py

@@ -1,5 +1,4 @@
 # type: ignore
-# pylint: skip-file
 from collections import namedtuple
 
 import torch

tests/fixtures/models.py

@@ -1,4 +1,3 @@
-# pylint: disable=too-few-public-methods
 from __future__ import annotations
 
 import math
@@ -303,7 +302,7 @@ def __init__(self) -> None:
         self.constant = 5
 
     def forward(self, x: dict[int, torch.Tensor], scale_factor: int) -> torch.Tensor:
-        return scale_factor * (x[256] + x[512][0]) * self.constant
+        return cast(torch.Tensor, scale_factor * (x[256] + x[512][0]) * self.constant)
 
 
 class ModuleDictModel(nn.Module):
@@ -359,7 +358,7 @@ def __int__(self) -> IntWithGetitem:
         return self
 
     def __getitem__(self, val: int) -> torch.Tensor:
-        return self.tensor * val
+        return cast(torch.Tensor, self.tensor * val)
 
 
 class EdgecaseInputOutputModel(nn.Module):
@@ -576,7 +575,7 @@ def __init__(self) -> None:
         self.b = nn.Parameter(torch.empty(10), requires_grad=False)
 
     def forward(self, x: torch.Tensor) -> torch.Tensor:
-        return self.w * x + self.b
+        return cast(torch.Tensor, self.w * x + self.b)
 
 
 class MixedTrainable(nn.Module):
@@ -718,7 +717,7 @@ def __init__(
     def forward(self, x: torch.Tensor) -> torch.Tensor:
         h = torch.mm(x, self.a) + self.b
         if self.output_dim is None:
-            return h
+            return cast(torch.Tensor, h)
         return cast(torch.Tensor, self.fc2(h))
 
 

tests/fixtures/tmva_net.py

@@ -1,5 +1,4 @@
 # type: ignore
-# pylint: skip-file
 import torch
 import torch.nn.functional as F
 from torch import nn

tests/torchinfo_test.py

@@ -541,14 +541,14 @@ def test_empty_module_list() -> None:
 
 
 def test_single_parameter_model() -> None:
-    class ParameterA(nn.Module):  # pylint: disable=too-few-public-methods
+    class ParameterA(nn.Module):
         """A model with one parameter."""
 
         def __init__(self) -> None:
             super().__init__()
             self.w = nn.Parameter(torch.zeros(1024))
 
-    class ParameterB(nn.Module):  # pylint: disable=too-few-public-methods
+    class ParameterB(nn.Module):
         """A model with one parameter and one Conv2d layer."""
 
         def __init__(self) -> None:

torchinfo/layer_info.py

@@ -87,7 +87,7 @@ def trainable(self) -> str:
 
     @staticmethod
     def calculate_size(
-        inputs: DETECTED_INPUT_OUTPUT_TYPES, batch_dim: int | None
+        inputs: DETECTED_INPUT_OUTPUT_TYPES | None, batch_dim: int | None
     ) -> tuple[list[int], int]:
         """
         Set input_size or output_size using the model's inputs.

torchinfo/torchinfo.py

@@ -203,7 +203,6 @@ class name as the key. If the forward pass is an expensive operation,
         model_mode = Mode(mode)
 
     if verbose is None:
-        # pylint: disable=no-member
         verbose = 0 if hasattr(sys, "ps1") and sys.ps1 else 1
 
     if cache_forward_pass is None:
@@ -269,7 +268,7 @@ def forward_pass(
     **kwargs: Any,
 ) -> list[LayerInfo]:
     """Perform a forward pass on the model using forward hooks."""
-    global _cached_forward_pass  # pylint: disable=global-variable-not-assigned
+    global _cached_forward_pass
     model_name = model.__class__.__name__
     if cache_forward_pass and model_name in _cached_forward_pass:
         return _cached_forward_pass[model_name]
@@ -485,7 +484,7 @@ def get_device(
             model_parameter = None
 
         if model_parameter is not None and model_parameter.is_cuda:
-            return model_parameter.device
+            return model_parameter.device  # type: ignore[no-any-return]
         return torch.device("cuda" if torch.cuda.is_available() else "cpu")
     return None
 
@@ -664,7 +663,6 @@ def apply_hooks(
         # some unknown reason (infinite recursion)
         stack += [
             (name, mod, curr_depth + 1, global_layer_info[module_id])
-            # pylint: disable=protected-access
             for name, mod in reversed(module._modules.items())
             if mod is not None
         ]
@@ -673,5 +671,5 @@ def apply_hooks(
 
 def clear_cached_forward_pass() -> None:
     """Clear the forward pass cache."""
-    global _cached_forward_pass  # pylint: disable=global-statement
+    global _cached_forward_pass
     _cached_forward_pass = {}