Convert directory fbcode/torchx to use the Ruff Formatter

Summary:
Converts the directory specified to use the Ruff formatter in pyfmt

ruff_dog

If this diff causes merge conflicts when rebasing, please run
`hg status -n -0 --change . -I '**/*.{py,pyi}' | xargs -0 arc pyfmt`
on your diff, and amend any changes before rebasing onto latest.
That should help reduce or eliminate any merge conflicts.

allow-large-files

Reviewed By: amyreese

Differential Revision: D66248087

docs/source/conf.py

@@ -191,9 +191,7 @@ def setup(app):
 
     # In Sphinx 1.8 it was renamed to `add_css_file`, 1.7 and prior it is
     # `add_stylesheet` (deprecated in 1.8).
-    add_css = getattr(
-        app, "add_css_file", getattr(app, "add_stylesheet", None)
-    )  # noqa B009
+    add_css = getattr(app, "add_css_file", getattr(app, "add_stylesheet", None))  # noqa B009
     for css_file in html_css_files:
         add_css(css_file)
 

scripts/collect_env.py

@@ -33,8 +33,9 @@ def run(
         args=command, stdout=subprocess.PIPE, stderr=subprocess.PIPE, shell=True
     )
     raw_output, raw_err = p.communicate()
-    raw_output, raw_err = raw_output.strip().decode("utf-8"), raw_err.strip().decode(
-        "utf-8"
+    raw_output, raw_err = (
+        raw_output.strip().decode("utf-8"),
+        raw_err.strip().decode("utf-8"),
     )
     rc = p.returncode
     if rc != 0:

scripts/component_integration_tests.py

@@ -10,6 +10,7 @@
 """
 Kubernetes integration tests.
 """
+
 import argparse
 import logging
 import os

tools/linter/adapters/pyre_linter.py

@@ -109,7 +109,9 @@ def main() -> None:
         level=(
             logging.NOTSET
             if args.verbose
-            else logging.DEBUG if len(args.filenames) < 1000 else logging.INFO
+            else logging.DEBUG
+            if len(args.filenames) < 1000
+            else logging.INFO
         ),
         stream=sys.stderr,
     )

tools/linter/adapters/ufmt_linter.py

@@ -119,7 +119,9 @@ def main() -> None:
         level=(
             logging.NOTSET
             if args.verbose
-            else logging.DEBUG if len(args.filenames) < 1000 else logging.INFO
+            else logging.DEBUG
+            if len(args.filenames) < 1000
+            else logging.INFO
         ),
         stream=sys.stderr,
     )

torchx/cli/test/cmd_run_test.py

@@ -51,14 +51,12 @@ def tearDown(self) -> None:
         torchxconfig.called_args = set()
 
     def test_run_with_multiple_scheduler_args(self) -> None:
-
         args = ["--scheduler_args", "first_args", "--scheduler_args", "second_args"]
         with self.assertRaises(SystemExit) as cm:
             self.parser.parse_args(args)
         self.assertEqual(cm.exception.code, 1)
 
     def test_run_with_multiple_schedule_args(self) -> None:
-
         args = [
             "--scheduler",
             "local_cwd",

torchx/components/dist.py

@@ -56,6 +56,7 @@
 Components APIs
 -----------------
 """
+
 import os
 import re
 import shlex

torchx/components/structured_arg.py

@@ -25,6 +25,7 @@
     with an experiment tracker. The ``/`` delimiter is a natural way to group runs within experiments.
 
 """
+
 import warnings
 from dataclasses import dataclass
 from pathlib import Path

torchx/runner/config.py

@@ -157,6 +157,7 @@ def my_component(a: int) -> specs.AppDef:
 you want to keep personal config overrides on top of a project defined default.
 
 """
+
 import configparser as configparser
 import logging
 import os

torchx/schedulers/aws_batch_scheduler.py

@@ -36,6 +36,7 @@
 https://docs.aws.amazon.com/AmazonECR/latest/userguide/getting-started-cli.html#cli-create-repository
 for how to create a image repository.
 """
+
 import getpass
 import re
 import threading
@@ -155,7 +156,7 @@ def resource_requirements_from_resource(resource: Resource) -> List[Dict[str, st
 
 
 def resource_from_resource_requirements(
-    resource_requirements: List[Dict[str, str]]
+    resource_requirements: List[Dict[str, str]],
 ) -> Resource:
     resrc_req = {
         ResourceType.from_str(r["type"]): int(r["value"]) for r in resource_requirements

torchx/schedulers/kubernetes_mcad_scheduler.py

@@ -17,8 +17,8 @@
 
 TorchX Kubernetes_MCAD scheduler depends on AppWrapper + MCAD.
 
-Install MCAD: 
-See deploying Multi-Cluster-Application-Dispatcher guide 
+Install MCAD:
+See deploying Multi-Cluster-Application-Dispatcher guide
 https://github.com/project-codeflare/multi-cluster-app-dispatcher/blob/main/doc/deploy/deployment.md
 
 This implementation requires MCAD v1.34.1 or higher.
@@ -478,8 +478,10 @@ def get_unique_truncated_appid(app: AppDef) -> str:
     unique_id_size = default_size if size > default_size else size
 
     if unique_id_size <= 3:
-        msg = "Name size has too many characters for some Kubernetes objects. Truncating \
+        msg = (
+            "Name size has too many characters for some Kubernetes objects. Truncating \
 application name."
+        )
         warnings.warn(msg)
         end = 63 - uid_chars - pg_chars
         substring = app.name[0:end]

torchx/schedulers/lsf_scheduler.py

@@ -23,6 +23,7 @@
 See the LSF documentation for more details:
 https://www.ibm.com/docs/en/cloud-private/3.2.x?topic=paks-spectrum-lsf-community-edition
 """
+
 import os.path
 import re
 import subprocess

torchx/schedulers/ray/ray_driver.py

@@ -18,6 +18,7 @@
 _step function, this give more flexibility to us if we want to bette handle the
 node failures.
 """
+
 import json
 import logging
 import os
@@ -148,12 +149,12 @@ def __init__(self, replicas: List[RayActor]) -> None:
         else:
             self.min_replicas = replicas[0].min_replicas  # pyre-ignore[8]
 
-        self.placement_groups: List[PlacementGroup] = (
-            []
-        )  # all the placement groups, shall never change
-        self.actor_info_of_id: Dict[str, ActorInfo] = (
-            {}
-        )  # store the info used to recover an actor
+        self.placement_groups: List[
+            PlacementGroup
+        ] = []  # all the placement groups, shall never change
+        self.actor_info_of_id: Dict[
+            str, ActorInfo
+        ] = {}  # store the info used to recover an actor
         self.active_tasks: List["ray.ObjectRef"] = []  # list of active tasks
 
         self.terminating: bool = False  # if the job has finished and being terminated

torchx/schedulers/slurm_scheduler.py

@@ -11,6 +11,7 @@
 This contains the TorchX Slurm scheduler which can be used to run TorchX
 components on a Slurm cluster.
 """
+
 import csv
 import json
 import logging

torchx/schedulers/test/kubernetes_scheduler_test.py

@@ -112,9 +112,7 @@ def test_app_to_resource_resolved_macros(self) -> None:
             resource = app_to_resource(app, "test_queue", service_account=None)
             actual_cmd = (
                 # pyre-ignore [16]
-                resource["spec"]["tasks"][0]["template"]
-                .spec.containers[0]
-                .command
+                resource["spec"]["tasks"][0]["template"].spec.containers[0].command
             )
             expected_cmd = [
                 "main",

torchx/schedulers/test/ray_scheduler_test.py

@@ -584,9 +584,7 @@ def test_ray_driver_elasticity(self) -> None:
             self.assertIsNotNone(driver.rank_0_port)
 
             # 3-2
-            terminal = (
-                driver._step()
-            )  # actor 1 finished, actor 2 has been scheduled yet, usually, the driver stops here
+            terminal = driver._step()  # actor 1 finished, actor 2 has been scheduled yet, usually, the driver stops here
             self.assertEqual(terminal, True)
             self.assertEqual(driver.command_actors_count, 0)
             self.assertEqual(len(driver.active_tasks), 1)  # actor schedule task

torchx/specs/__init__.py

@@ -12,6 +12,7 @@
 used by components to define the apps which can then be launched via a TorchX
 scheduler or pipeline adapter.
 """
+
 import difflib
 from typing import Callable, Dict, Optional
 

torchx/specs/named_resources_generic.py

@@ -37,6 +37,7 @@
     have 8 cpus.
 
 """
+
 from typing import Callable, Mapping
 
 from torchx.specs.api import Resource

torchx/specs/test/api_test.py

@@ -301,7 +301,6 @@ async def update(value: str, time_seconds: int) -> str:
         self.assertEqual("nentry", default.entrypoint)
 
     def test_concurrent_override_role(self) -> None:
-
         def delay(value: Tuple[str, str], time_seconds: int) -> Tuple[str, str]:
             time.sleep(time_seconds)
             return value

torchx/test/fixtures.py

@@ -9,6 +9,7 @@
 """
 Useful test fixtures (classes that you can subclass your python ``unittest.TestCase``)
 """
+
 import os
 import shutil
 import sys

torchx/tracker/api.py

@@ -179,7 +179,7 @@ def _extract_tracker_name_and_config_from_environ() -> Mapping[str, Optional[str
 
 
 def build_trackers(
-    factory_and_config: Mapping[str, Optional[str]]
+    factory_and_config: Mapping[str, Optional[str]],
 ) -> Iterable[TrackerBase]:
     trackers = []
 

torchx/tracker/backend/test/fsspec_test.py

@@ -171,5 +171,7 @@ def test_create(self) -> None:
 
         tracker = create(f"file://{str(configfile)}")
         self.assertEqual(
-            tracker._path_builder.root_dir, tracker_root_path  # pyre-ignore
+            # pyre-fixme[16]: `TrackerBase` has no attribute `_path_builder`.
+            tracker._path_builder.root_dir,
+            tracker_root_path,
         )

torchx/tracker/mlflow.py

@@ -254,7 +254,10 @@ def run_ids(self, **kwargs: str) -> Iterable[str]:
         return [r.info.run_name for r in runs]
 
     def log_params_flat(
-        self, run_name: str, cfg: Any, key: str = ""  # pyre-ignore[2]
+        self,
+        run_name: str,
+        cfg: Any,
+        key: str = "",  # pyre-ignore[2]
     ) -> None:
         """
         Designed to be primarily used with hydra-style config objects (e.g. dataclasses),