Some pylint and pyupgrade cleanups (#29)

* Fix line endings of empty files

* Use `not in` for membership test

* Remove unused imports

* Fix implicit string concatenation

* Remove python 2 coding statement

* Change python2's Text into str

* Remove useless linebreaks

* Remove useless parentheses

* Use new-style dictionary and set constructors

* There is no more IOError (alias to OSError now)

* Use .format instead of % string interpolation

* Use super() without redundant arguments

* Remove redundant read flag from open

* Avoid building lists unnecessarily

* Use f-strings with python 3.6

* Black reformat

Co-authored-by: Michael Osthege <[email protected]>

Author: Armavica

doc/conf.py

@@ -1,5 +1,3 @@
-# -*- coding: utf-8 -*-
-#
 # pytensor documentation build configuration file, created by
 # sphinx-quickstart on Tue Oct  7 16:34:06 2008.
 #

doc/extending/extending_pytensor_solution_1.py

@@ -73,7 +73,6 @@ def grad(self, inputs, output_grads):
 import numpy as np
 
 from tests import unittest_tools as utt
-from pytensor import function, printing
 from pytensor import tensor as at
 from pytensor.graph.basic import Apply
 from pytensor.graph.op import Op

doc/generate_dtype_tensor_table.py

@@ -1,5 +1,3 @@
-
-
 letters = [
     ('b', 'int8'),
     ('w', 'int16'),

doc/scripts/docgen.py

@@ -1,8 +1,6 @@
-
 import sys
 import os
 import shutil
-import inspect
 import getopt
 from collections import defaultdict
 
@@ -16,7 +14,7 @@
         sys.argv[1:],
         'o:f:',
         ['rst', 'help', 'nopdf', 'cache', 'check', 'test'])
-    options.update(dict([x, y or True] for x, y in opts))
+    options.update({x: y or True for x, y in opts})
     if options['--help']:
         print(f'Usage: {sys.argv[0]} [OPTIONS] [files...]')
         print('  -o <dir>: output the html files in the specified dir')
@@ -100,8 +98,6 @@ def call_sphinx(builder, workdir):
                 shutil.rmtree(workdir)
             except OSError as e:
                 print('OSError:', e)
-            except IOError as e:
-                print('IOError:', e)
 
     if options['--test']:
         mkdir("doc")

pytensor/_version.py

@@ -105,7 +105,7 @@ def run_command(commands, args, cwd=None, verbose=False, hide_stderr=False, env=
             return None, None
     else:
         if verbose:
-            print("unable to find command, tried %s" % (commands,))
+            print(f"unable to find command, tried {commands}")
         return None, None
     stdout = process.communicate()[0].strip().decode()
     if process.returncode != 0:
@@ -155,7 +155,7 @@ def git_get_keywords(versionfile_abs):
     # _version.py.
     keywords = {}
     try:
-        with open(versionfile_abs, "r") as fobj:
+        with open(versionfile_abs) as fobj:
             for line in fobj:
                 if line.strip().startswith("git_refnames ="):
                     mo = re.search(r'=\s*"(.*)"', line)
@@ -351,7 +351,7 @@ def git_pieces_from_vcs(tag_prefix, root, verbose, runner=run_command):
             if verbose:
                 fmt = "tag '%s' doesn't start with prefix '%s'"
                 print(fmt % (full_tag, tag_prefix))
-            pieces["error"] = "tag '%s' doesn't start with prefix '%s'" % (
+            pieces["error"] = "tag '{}' doesn't start with prefix '{}'".format(
                 full_tag,
                 tag_prefix,
             )

pytensor/compile/debugmode.py

@@ -1604,7 +1604,7 @@ def f():
                     # storage will be None
                     if thunk_py:
                         _logger.debug(
-                            f"{i} - running thunk_py with None as " "output storage"
+                            f"{i} - running thunk_py with None as output storage"
                         )
                         try:
                             thunk_py()
@@ -2063,15 +2063,15 @@ def __init__(
                     infolog = StringIO()
                     print("Optimization process is unstable...", file=infolog)
                     print(
-                        "  (HINT: Ops that the nodes point to must compare " "equal)",
+                        "  (HINT: Ops that the nodes point to must compare equal)",
                         file=infolog,
                     )
                     print(
-                        "(event index)  (one event trace)  (other event " "trace)",
+                        "(event index)  (one event trace)  (other event trace)",
                         file=infolog,
                     )
                     print(
-                        "-------------------------------------------------" "----",
+                        "-----------------------------------------------------",
                         file=infolog,
                     )
                     for j in range(max(len(li), len(l0))):
@@ -2292,7 +2292,7 @@ def __init__(
 
         if not isinstance(linker, _DummyLinker):
             raise Exception(
-                "DebugMode can only use its own linker! You " "should not provide one.",
+                "DebugMode can only use its own linker! You should not provide one.",
                 linker,
             )
 
@@ -2318,7 +2318,7 @@ def __init__(
             self.require_matching_strides = require_matching_strides
 
         if not (self.check_c_code or self.check_py_code):
-            raise ValueError("DebugMode has to check at least one of c and py " "code")
+            raise ValueError("DebugMode has to check at least one of c and py code")
 
     def __str__(self):
         return "DebugMode(linker={}, optimizer={})".format(

pytensor/compile/function/__init__.py

@@ -300,9 +300,7 @@ def opt_log1p(node):
     if uses_tuple:
         # we must use old semantics in this case.
         if profile:
-            raise NotImplementedError(
-                "profiling not supported in old-style " "function"
-            )
+            raise NotImplementedError("profiling not supported in old-style function")
         if uses_updates or uses_givens:
             raise NotImplementedError(
                 "In() instances and tuple inputs trigger the old "

pytensor/compile/function/pfunc.py

@@ -181,7 +181,7 @@ def clone_inputs(i):
             raise TypeError("update target must be a SharedVariable", store_into)
         if store_into in update_d:
             raise ValueError(
-                "this shared variable already has an update " "expression",
+                "this shared variable already has an update expression",
                 (store_into, update_d[store_into]),
             )
 

pytensor/compile/nanguardmode.py

@@ -225,7 +225,7 @@ def do_check_on(value, nd, var=None):
                     print(pytensor.printing.debugprint(nd, file="str"), file=sio)
                 else:
                     print(
-                        "NanGuardMode found an error in an input of the " "graph.",
+                        "NanGuardMode found an error in an input of the graph.",
                         file=sio,
                     )
                 # Add the stack trace

pytensor/compile/profiling.py

@@ -1308,7 +1308,7 @@ def compute_max_stats(running_memory, stats):
 
         if len(fct_memory) > 1:
             print(
-                "Memory Profile (the max between all functions in " "that profile)",
+                "Memory Profile (the max between all functions in that profile)",
                 file=file,
             )
         else:

pytensor/compile/sharedvalue.py

@@ -72,7 +72,7 @@ def __init__(
             self.container = container
             if (value is not None) or (strict is not None):
                 raise TypeError(
-                    "value and strict are ignored if you pass " "a container here"
+                    "value and strict are ignored if you pass a container here"
                 )
         else:
             self.container = Container(

pytensor/configdefaults.py

@@ -585,7 +585,7 @@ def add_compile_configvars():
 
     config.add(
         "cmodule__age_thresh_use",
-        "In seconds. The time after which " "PyTensor won't reuse a compile c module.",
+        "In seconds. The time after which PyTensor won't reuse a compile c module.",
         # 24 days
         IntParam(60 * 60 * 24 * 24, mutable=False),
         in_c_key=False,
@@ -1004,7 +1004,7 @@ def add_testvalue_and_checking_configvars():
 
     config.add(
         "on_shape_error",
-        "warn: print a warning and use the default" " value. raise: raise an error",
+        "warn: print a warning and use the default value. raise: raise an error",
         EnumStr("warn", ["raise"]),
         in_c_key=False,
     )
@@ -1149,14 +1149,14 @@ def add_metaopt_configvars():
 
     config.add(
         "metaopt__optimizer_excluding",
-        ("exclude optimizers with these tags. " "Separate tags with ':'."),
+        ("exclude optimizers with these tags. Separate tags with ':'."),
         StrParam(""),
         in_c_key=False,
     )
 
     config.add(
         "metaopt__optimizer_including",
-        ("include optimizers with these tags. " "Separate tags with ':'."),
+        ("include optimizers with these tags. Separate tags with ':'."),
         StrParam(""),
         in_c_key=False,
     )

pytensor/configparser.py

@@ -125,10 +125,7 @@ def get_config_hash(self):
         )
         return hash_from_code(
             "\n".join(
-                [
-                    "{} = {}".format(cv.name, cv.__get__(self, self.__class__))
-                    for cv in all_opts
-                ]
+                [f"{cv.name} = {cv.__get__(self, self.__class__)}" for cv in all_opts]
             )
         )
 

pytensor/gradient.py

@@ -91,10 +91,8 @@ def grad_not_implemented(op, x_pos, x, comment=""):
 
     return (
         NullType(
-            (
-                "This variable is Null because the grad method for "
-                f"input {x_pos} ({x}) of the {op} op is not implemented. {comment}"
-            )
+            "This variable is Null because the grad method for "
+            f"input {x_pos} ({x}) of the {op} op is not implemented. {comment}"
         )
     )()
 
@@ -114,10 +112,8 @@ def grad_undefined(op, x_pos, x, comment=""):
 
     return (
         NullType(
-            (
-                "This variable is Null because the grad method for "
-                f"input {x_pos} ({x}) of the {op} op is not implemented. {comment}"
-            )
+            "This variable is Null because the grad method for "
+            f"input {x_pos} ({x}) of the {op} op is not implemented. {comment}"
         )
     )()
 
@@ -1275,14 +1271,12 @@ def try_to_copy_if_needed(var):
                     # We therefore don't allow it because its usage has become
                     # so muddied.
                     raise TypeError(
-                        (
-                            f"{node.op}.grad returned None for a gradient term, "
-                            "this is prohibited. Instead of None,"
-                            "return zeros_like(input), disconnected_type(),"
-                            " or a NullType variable such as those made with "
-                            "the grad_undefined or grad_unimplemented helper "
-                            "functions."
-                        )
+                        f"{node.op}.grad returned None for a gradient term, "
+                        "this is prohibited. Instead of None,"
+                        "return zeros_like(input), disconnected_type(),"
+                        " or a NullType variable such as those made with "
+                        "the grad_undefined or grad_unimplemented helper "
+                        "functions."
                     )
 
                 # Check that the gradient term for this input
@@ -1402,10 +1396,8 @@ def access_grad_cache(var):
 
                         if hasattr(var, "ndim") and term.ndim != var.ndim:
                             raise ValueError(
-                                (
-                                    f"{node.op}.grad returned a term with"
-                                    f" {int(term.ndim)} dimensions, but {int(var.ndim)} are required."
-                                )
+                                f"{node.op}.grad returned a term with"
+                                f" {int(term.ndim)} dimensions, but {int(var.ndim)} are required."
                             )
 
                         terms.append(term)
@@ -1767,10 +1759,8 @@ def verify_grad(
     for i, p in enumerate(pt):
         if p.dtype not in ("float16", "float32", "float64"):
             raise TypeError(
-                (
-                    "verify_grad can work only with floating point "
-                    f'inputs, but input {i} has dtype "{p.dtype}".'
-                )
+                "verify_grad can work only with floating point "
+                f'inputs, but input {i} has dtype "{p.dtype}".'
             )
 
     _type_tol = dict(  # relative error tolerances for different types

pytensor/graph/basic.py

@@ -1184,11 +1184,9 @@ def clone_replace(
         items = []
     else:
         raise ValueError(
-            (
-                "replace is neither a dictionary, list, "
-                f"tuple or None ! The value provided is {replace},"
-                f"of type {type(replace)}"
-            )
+            "replace is neither a dictionary, list, "
+            f"tuple or None ! The value provided is {replace},"
+            f"of type {type(replace)}"
         )
     tmp_replace = [(x, x.type()) for x, y in items]
     new_replace = [(x, y) for ((_, x), (_, y)) in zip(tmp_replace, items)]

pytensor/graph/features.py

@@ -679,7 +679,7 @@ def on_detach(self, fgraph):
         """
         if self.fgraph is not fgraph:
             raise Exception(
-                "This NodeFinder instance was not attached to the" " provided fgraph."
+                "This NodeFinder instance was not attached to the provided fgraph."
             )
         self.fgraph = None
         del fgraph.get_nodes

pytensor/graph/op.py

@@ -10,7 +10,6 @@
     List,
     Optional,
     Sequence,
-    Text,
     Tuple,
     TypeVar,
     Union,
@@ -496,7 +495,7 @@ def prepare_node(
         node: Apply,
         storage_map: Optional[StorageMapType],
         compute_map: Optional[ComputeMapType],
-        impl: Optional[Text],
+        impl: Optional[str],
     ) -> None:
         """Make any special modifications that the `Op` needs before doing :meth:`Op.make_thunk`.
 
@@ -573,7 +572,7 @@ def make_thunk(
         storage_map: StorageMapType,
         compute_map: ComputeMapType,
         no_recycling: List[Variable],
-        impl: Optional[Text] = None,
+        impl: Optional[str] = None,
     ) -> ThunkType:
         r"""Create a thunk.
 
@@ -676,7 +675,7 @@ def get_test_value(v: Any) -> Any:
     return v.get_test_value()
 
 
-def missing_test_message(msg: Text) -> None:
+def missing_test_message(msg: str) -> None:
     """Display a message saying that some test_value is missing.
 
     This uses the appropriate form based on ``config.compute_test_value``:

pytensor/graph/rewriting/utils.py

@@ -114,7 +114,7 @@ def is_same_graph_with_merge(var1, var2, givens=None):
     # We also need to make sure we replace a Variable if it is present in
     # `givens`.
     vars_replaced = [givens.get(v, v) for v in fgraph.outputs]
-    o1, o2 = [v.owner for v in vars_replaced]
+    o1, o2 = (v.owner for v in vars_replaced)
     if o1 is None and o2 is None:
         # Comparing two single-Variable graphs: they are equal if they are
         # the same Variable.

pytensor/graph/type.py

@@ -1,5 +1,5 @@
 from abc import abstractmethod
-from typing import Any, Generic, Optional, Text, Tuple, TypeVar, Union
+from typing import Any, Generic, Optional, Tuple, TypeVar, Union
 
 from typing_extensions import TypeAlias
 
@@ -188,7 +188,7 @@ def is_valid_value(self, data: D, strict: bool = True) -> bool:
         except (TypeError, ValueError):
             return False
 
-    def make_variable(self, name: Optional[Text] = None) -> variable_type:
+    def make_variable(self, name: Optional[str] = None) -> variable_type:
         """Return a new `Variable` instance of this `Type`.
 
         Parameters
@@ -199,7 +199,7 @@ def make_variable(self, name: Optional[Text] = None) -> variable_type:
         """
         return self.variable_type(self, None, name=name)
 
-    def make_constant(self, value: D, name: Optional[Text] = None) -> constant_type:
+    def make_constant(self, value: D, name: Optional[str] = None) -> constant_type:
         """Return a new `Constant` instance of this `Type`.
 
         Parameters
@@ -216,7 +216,7 @@ def clone(self, *args, **kwargs) -> "Type":
         """Clone a copy of this type with the given arguments/keyword values, if any."""
         return type(self)(*args, **kwargs)
 
-    def __call__(self, name: Optional[Text] = None) -> variable_type:
+    def __call__(self, name: Optional[str] = None) -> variable_type:
         """Return a new `Variable` instance of Type `self`.
 
         Parameters

pytensor/graph/utils.py

@@ -245,9 +245,7 @@ def __str__(self):
                     def __str__(self):
                         return "{}{{{}}}".format(
                             self.__class__.__name__,
-                            ", ".join(
-                                "{}={!r}".format(p, getattr(self, p)) for p in props
-                            ),
+                            ", ".join(f"{p}={getattr(self, p)!r}" for p in props),
                         )
 
                 dct["__str__"] = __str__