ruff
ruff copied to clipboard
Published
20 hours ago •
astral-sh
astral-sh
Ruff 2025 style guide
Summary
- Stabilize
comprehension_leading_expression_comments_same_line - Stabilize
empty_parameters_no_unnecessary_parentheses_around_return_value - Stabilize
docstring_code_block_in_docstring_indent - Stabilize
match_case_parenthese - Stabilize
with_single_item_pre_39 - Stabilize
f_string_implicit_concatenated_string_literal_quotes - Stabilize
implicit_concatenated_string_formatting(includes new assert formatting)
Closes #13371
Tasks
- [ ] Update deviation black document. It should mention f-string formatting, implicit concatenated string formatting, and assert formatting.
Test plan
Main
| project | similarity index | total files | changed files |
|---|---|---|---|
| cpython | 0.76424 | 1959 | 1781 |
| django | 0.99942 | 2791 | 76 |
| home-assistant | 1.00000 | 12993 | 0 |
| poetry | 1.00000 | 444 | 0 |
| transformers | 0.99909 | 3151 | 15 |
| twine | 1.00000 | 32 | 0 |
| typeshed | 0.99139 | 4766 | 133 |
| warehouse | 0.99962 | 767 | 33 |
| zulip | 1.00000 | 1699 | 0 |
2025
| project | similarity index | total files | changed files |
|---|---|---|---|
| cpython | 0.76395 | 1959 | 1786 |
| django | 0.99921 | 2791 | 108 |
| home-assistant | 0.99980 | 12993 | 146 |
| poetry | 0.99957 | 444 | 8 |
| transformers | 0.99860 | 3151 | 213 |
| twine | 0.99871 | 32 | 3 |
| typeshed | 0.99135 | 4766 | 138 |
| warehouse | 0.99916 | 767 | 51 |
| zulip | 0.99969 | 1699 | 29 |
- [ ] Review ecosystem changes
- [ ] Review snapshot changes
- [ ] Test on larger projects
ruff-ecosystem results
Formatter (stable)
ℹ️ ecosystem check detected format changes. (+1707 -1827 lines in 538 files in 27 projects; 28 projects unchanged)
DisnakeDev/disnake (+2 -2 lines across 1 file)
def set_bandwidth(self, req: BAND_CTL) -> None:
if req not in band_ctl:
raise KeyError(
- f'{req!r} is not a valid bandwidth setting. Try one of: {",".join(band_ctl)}'
+ f"{req!r} is not a valid bandwidth setting. Try one of: {','.join(band_ctl)}"
)
k = band_ctl[req]
def set_signal_type(self, req: SIGNAL_CTL) -> None:
if req not in signal_ctl:
raise KeyError(
- f'{req!r} is not a valid bandwidth setting. Try one of: {",".join(signal_ctl)}'
+ f"{req!r} is not a valid bandwidth setting. Try one of: {','.join(signal_ctl)}"
)
k = signal_ctl[req]
RasaHQ/rasa (+56 -70 lines across 29 files)
# Check if a valid setting for `max_history` was given
if isinstance(max_history, int) and max_history < 1:
raise argparse.ArgumentTypeError(
- f"The value of `--max-history {max_history}` " f"is not a positive integer."
+ f"The value of `--max-history {max_history}` is not a positive integer."
)
return validator.verify_story_structure(
attempts -= 1
rasa.shared.utils.cli.print_error_and_exit(
- "Could not fetch runtime config from server at '{}'. " "Exiting.".format(
+ "Could not fetch runtime config from server at '{}'. Exiting.".format(
config_endpoint
)
)
rasa/core/actions/action.py~L322
if message is None:
if not self.silent_fail:
logger.error(
- "Couldn't create message for response '{}'." "".format(
+ "Couldn't create message for response '{}'.".format(
self.utter_action
)
)
rasa/core/actions/action.py~L470
else:
if not self.silent_fail:
logger.error(
- "Couldn't create message for response action '{}'." "".format(
+ "Couldn't create message for response action '{}'.".format(
self.action_name
)
)
rasa/core/channels/console.py~L194
exit_text = INTENT_MESSAGE_PREFIX + "stop"
rasa.shared.utils.cli.print_success(
- "Bot loaded. Type a message and press enter " "(use '{}' to exit): ".format(
+ "Bot loaded. Type a message and press enter (use '{}' to exit): ".format(
exit_text
)
)
rasa/core/channels/telegram.py~L97
reply_markup.add(KeyboardButton(button["title"]))
else:
logger.error(
- "Trying to send text with buttons for unknown " "button type {}".format(
+ "Trying to send text with buttons for unknown button type {}".format(
button_type
)
)
body = nlg_request_format(utter_action, tracker, output_channel, **kwargs)
logger.debug(
- "Requesting NLG for {} from {}." "The request body is {}." "".format(
+ "Requesting NLG for {} from {}.The request body is {}.".format(
utter_action, self.nlg_endpoint.url, json.dumps(body)
)
)
rasa/core/policies/policy.py~L250
max_training_samples = kwargs.get("max_training_samples")
if max_training_samples is not None:
logger.debug(
- "Limit training data to {} training samples." "".format(
+ "Limit training data to {} training samples.".format(
max_training_samples
)
)
rasa/core/policies/ted_policy.py~L837
# take the last prediction in the sequence
similarities = outputs["similarities"][:, -1, :]
else:
- raise TypeError(
- "model output for `similarities` " "should be a numpy array"
- )
+ raise TypeError("model output for `similarities` should be a numpy array")
if isinstance(outputs["scores"], np.ndarray):
confidences = outputs["scores"][:, -1, :]
else:
rasa/core/policies/unexpected_intent_policy.py~L612
if isinstance(output["similarities"], np.ndarray):
sequence_similarities = output["similarities"][:, -1, :]
else:
- raise TypeError(
- "model output for `similarities` " "should be a numpy array"
- )
+ raise TypeError("model output for `similarities` should be a numpy array")
# Check for unlikely intent
last_user_uttered_event = tracker.get_last_event_for(UserUttered)
):
story_dump = YAMLStoryWriter().dumps(partial_tracker.as_story().story_steps)
error_msg = (
- f"Model predicted a wrong action. Failed Story: " f"\n\n{story_dump}"
+ f"Model predicted a wrong action. Failed Story: \n\n{story_dump}"
)
raise WrongPredictionException(error_msg)
elif prev_action_unlikely_intent:
for policy_config in policy_configs:
config_name = os.path.splitext(os.path.basename(policy_config))[0]
logging.info(
- "Starting to train {} round {}/{}" " with {}% exclusion" "".format(
+ "Starting to train {} round {}/{} with {}% exclusion".format(
config_name, current_run, len(exclusion_percentages), percentage
)
)
domain,
policy_config,
stories=story_file,
- output=str(Path(output_path, f"run_{r +1}")),
+ output=str(Path(output_path, f"run_{r + 1}")),
fixed_model_name=config_name + PERCENTAGE_KEY + str(percentage),
additional_arguments={
**additional_arguments,
rasa/core/training/interactive.py~L346
choices = []
for p in sorted_intents:
name_with_confidence = (
- f'{p.get("confidence"):03.2f} {p.get(INTENT_NAME_KEY):40}'
+ f"{p.get('confidence'):03.2f} {p.get(INTENT_NAME_KEY):40}"
)
choice = {
INTENT_NAME_KEY: name_with_confidence,
rasa/core/training/interactive.py~L674
await _print_history(conversation_id, endpoint)
choices = [
- {"name": f'{a["score"]:03.2f} {a["action"]:40}', "value": a["action"]}
+ {"name": f"{a['score']:03.2f} {a['action']:40}", "value": a["action"]}
for a in predictions
]
rasa/core/training/interactive.py~L723
# export training data and quit
questions = questionary.form(
export_stories=questionary.text(
- message="Export stories to (if file exists, this "
- "will append the stories)",
+ message="Export stories to (if file exists, this will append the stories)",
default=PATHS["stories"],
validate=io_utils.file_type_validator(
rasa.shared.data.YAML_FILE_EXTENSIONS,
rasa/core/training/interactive.py~L738
default=PATHS["nlu"],
validate=io_utils.file_type_validator(
list(rasa.shared.data.TRAINING_DATA_EXTENSIONS),
- "Please provide a valid export path for the NLU data, "
- "e.g. 'nlu.yml'.",
+ "Please provide a valid export path for the NLU data, e.g. 'nlu.yml'.",
),
),
export_domain=questionary.text(
- message="Export domain file to (if file exists, this "
- "will be overwritten)",
+ message="Export domain file to (if file exists, this will be overwritten)",
default=PATHS["domain"],
validate=io_utils.file_type_validator(
rasa.shared.data.YAML_FILE_EXTENSIONS,
"""
if use_syslog:
formatter = logging.Formatter(
- "%(asctime)s [%(levelname)-5.5s] [%(process)d]" " %(message)s"
+ "%(asctime)s [%(levelname)-5.5s] [%(process)d] %(message)s"
)
socktype = SOCK_STREAM if syslog_protocol == TCP_PROTOCOL else SOCK_DGRAM
syslog_handler = logging.handlers.SysLogHandler(
"""
if hot_idx >= length:
raise ValueError(
- "Can't create one hot. Index '{}' is out " "of range (length '{}')".format(
+ "Can't create one hot. Index '{}' is out of range (length '{}')".format(
hot_idx, length
)
)
rasa/nlu/featurizers/sparse_featurizer/count_vectors_featurizer.py~L166
)
if self.stop_words is not None:
logger.warning(
- "Analyzer is set to character, "
- "provided stop words will be ignored."
+ "Analyzer is set to character, provided stop words will be ignored."
)
if self.max_ngram == 1:
logger.warning(
raise ErrorResponse(
HTTPStatus.BAD_REQUEST,
"BadRequest",
- "Invalid parameter value for 'include_events'. "
- "Should be one of {}".format(enum_values),
+ "Invalid parameter value for 'include_events'. Should be one of {}".format(
+ enum_values
+ ),
{"parameter": "include_events", "in": "query"},
)
rasa/shared/core/domain.py~L198
domain = cls.from_directory(path)
else:
raise InvalidDomain(
- "Failed to load domain specification from '{}'. "
- "File not found!".format(os.path.abspath(path))
+ "Failed to load domain specification from '{}'. File not found!".format(
+ os.path.abspath(path)
+ )
)
return domain
rasa/shared/core/events.py~L1964
def __str__(self) -> Text:
"""Returns text representation of event."""
- return (
- "ActionExecutionRejected("
- "action: {}, policy: {}, confidence: {})"
- "".format(self.action_name, self.policy, self.confidence)
+ return "ActionExecutionRejected(action: {}, policy: {}, confidence: {})".format(
+ self.action_name, self.policy, self.confidence
)
def __hash__(self) -> int:
rasa/shared/core/generator.py~L401
if num_active_trackers:
logger.debug(
- "Starting {} ... (with {} trackers)" "".format(
+ "Starting {} ... (with {} trackers)".format(
phase_name, num_active_trackers
)
)
rasa/shared/core/generator.py~L517
phase = 0
else:
logger.debug(
- "Found {} unused checkpoints " "in current phase." "".format(
+ "Found {} unused checkpoints in current phase.".format(
len(unused_checkpoints)
)
)
logger.debug(
- "Found {} active trackers " "for these checkpoints." "".format(
+ "Found {} active trackers for these checkpoints.".format(
num_active_trackers
)
)
rasa/shared/core/generator.py~L553
augmented_trackers, self.config.max_number_of_augmented_trackers
)
logger.debug(
- "Subsampled to {} augmented training trackers." "".format(
+ "Subsampled to {} augmented training trackers.".format(
len(augmented_trackers)
)
)
rasa/shared/core/trackers.py~L634
"""
if not isinstance(dialogue, Dialogue):
raise ValueError(
- f"story {dialogue} is not of type Dialogue. "
- f"Have you deserialized it?"
+ f"story {dialogue} is not of type Dialogue. Have you deserialized it?"
)
self._reset()
rasa/shared/core/training_data/story_reader/story_reader.py~L83
)
if parsed_events is None:
raise StoryParseError(
- "Unknown event '{}'. It is Neither an event " "nor an action).".format(
+ "Unknown event '{}'. It is Neither an event nor an action).".format(
event_name
)
)
rasa/shared/core/training_data/story_reader/yaml_story_reader.py~L334
if not self.domain:
logger.debug(
- "Skipped validating if intent is in domain as domain " "is `None`."
+ "Skipped validating if intent is in domain as domain is `None`."
)
return
rasa/shared/nlu/training_data/formats/dialogflow.py~L34
if fformat not in {DIALOGFLOW_INTENT, DIALOGFLOW_ENTITIES}:
raise ValueError(
- "fformat must be either {}, or {}" "".format(
+ "fformat must be either {}, or {}".format(
DIALOGFLOW_INTENT, DIALOGFLOW_ENTITIES
)
)
access_logger.addHandler(file_handler)
if use_syslog:
formatter = logging.Formatter(
- "%(asctime)s [%(levelname)-5.5s] [%(process)d]" " %(message)s"
+ "%(asctime)s [%(levelname)-5.5s] [%(process)d] %(message)s"
)
socktype = SOCK_STREAM if syslog_protocol == TCP_PROTOCOL else SOCK_DGRAM
syslog_handler = logging.handlers.SysLogHandler(
return EndpointConfig.from_dict(content[endpoint_type])
except FileNotFoundError:
logger.error(
- "Failed to read endpoint configuration " "from {}. No such file.".format(
+ "Failed to read endpoint configuration from {}. No such file.".format(
os.path.abspath(filename)
)
)
tests/core/test_tracker_stores.py~L311
assert isinstance(tracker_store, InMemoryTrackerStore)
-async def _tracker_store_and_tracker_with_slot_set() -> (
- Tuple[InMemoryTrackerStore, DialogueStateTracker]
-):
+async def _tracker_store_and_tracker_with_slot_set() -> Tuple[
+ InMemoryTrackerStore, DialogueStateTracker
+]:
# returns an InMemoryTrackerStore containing a tracker with a slot set
slot_key = "cuisine"
tests/engine/recipes/test_default_recipe.py~L98
(
"data/test_config/config_pretrained_embeddings_mitie.yml",
"data/graph_schemas/config_pretrained_embeddings_mitie_train_schema.yml",
- "data/graph_schemas/"
- "config_pretrained_embeddings_mitie_predict_schema.yml",
+ "data/graph_schemas/config_pretrained_embeddings_mitie_predict_schema.yml",
TrainingType.BOTH,
False,
),
tests/graph_components/validators/test_default_recipe_validator.py~L780
if should_warn:
with pytest.warns(
UserWarning,
- match=(f"'{RulePolicy.__name__}' is not " "included in the model's "),
+ match=(f"'{RulePolicy.__name__}' is not included in the model's "),
) as records:
validator.validate(importer)
else:
tests/graph_components/validators/test_default_recipe_validator.py~L883
num_duplicates: bool,
priority: int,
):
- assert (
- len(policy_types) >= priority + num_duplicates
- ), f"This tests needs at least {priority+num_duplicates} many types."
+ assert len(policy_types) >= priority + num_duplicates, (
+ f"This tests needs at least {priority + num_duplicates} many types."
+ )
# start with a schema where node i has priority i
nodes = {
tests/graph_components/validators/test_default_recipe_validator.py~L895
# give nodes p+1, .., p+num_duplicates-1 priority "priority"
for idx in range(num_duplicates):
- nodes[f"{priority+idx+1}"].config["priority"] = priority
+ nodes[f"{priority + idx + 1}"].config["priority"] = priority
validator = DefaultV1RecipeValidator(graph_schema=GraphSchema(nodes))
monkeypatch.setattr(
tests/graph_components/validators/test_default_recipe_validator.py~L992
with pytest.warns(
UserWarning,
match=(
- "Found rule-based training data but no policy "
- "supporting rule-based data."
+ "Found rule-based training data but no policy supporting rule-based data."
),
):
validator.validate(importer)
tests/nlu/featurizers/test_regex_featurizer.py~L44
@pytest.mark.parametrize(
- "sentence, expected_sequence_features, expected_sentence_features,"
- "labeled_tokens",
+ "sentence, expected_sequence_features, expected_sentence_features,labeled_tokens",
[
(
"hey how are you today",
tests/nlu/featurizers/test_regex_featurizer.py~L219
@pytest.mark.parametrize(
- "sentence, expected_sequence_features, expected_sentence_features, "
- "labeled_tokens",
+ "sentence, expected_sequence_features, expected_sentence_features, labeled_tokens",
[
(
"lemonade and mapo tofu",
tests/nlu/featurizers/test_regex_featurizer.py~L383
@pytest.mark.parametrize(
- "sentence, expected_sequence_features, expected_sentence_features,"
- "case_sensitive",
+ "sentence, expected_sequence_features, expected_sentence_features,case_sensitive",
[
("Hey How are you today", [0.0, 0.0, 0.0], [0.0, 0.0, 0.0], True),
("Hey How are you today", [0.0, 1.0, 0.0], [0.0, 1.0, 0.0], False),
tests/nlu/featurizers/test_spacy_featurizer.py~L133
vecs = ftr._features_for_doc(doc)
vecs_capitalized = ftr._features_for_doc(doc_capitalized)
- assert np.allclose(
- vecs, vecs_capitalized, atol=1e-5
- ), "Vectors are unequal for texts '{}' and '{}'".format(
- e.get(TEXT), e.get(TEXT).capitalize()
+ assert np.allclose(vecs, vecs_capitalized, atol=1e-5), (
+ "Vectors are unequal for texts '{}' and '{}'".format(
+ e.get(TEXT), e.get(TEXT).capitalize()
+ )
)
Snowflake-Labs/snowcli (+12 -10 lines across 5 files)
src/snowflake/cli/_plugins/nativeapp/artifacts.py~L250
def __init__(self, *, project_root: Path, deploy_root: Path):
# If a relative path ends up here, it's a bug in the app and can lead to other
# subtle bugs as paths would be resolved relative to the current working directory.
- assert (
- project_root.is_absolute()
- ), f"Project root {project_root} must be an absolute path."
- assert (
- deploy_root.is_absolute()
- ), f"Deploy root {deploy_root} must be an absolute path."
+ assert project_root.is_absolute(), (
+ f"Project root {project_root} must be an absolute path."
+ )
+ assert deploy_root.is_absolute(), (
+ f"Deploy root {deploy_root} must be an absolute path."
+ )
self._project_root: Path = resolve_without_follow(project_root)
self._deploy_root: Path = resolve_without_follow(deploy_root)
src/snowflake/cli/_plugins/nativeapp/codegen/snowpark/python_processor.py~L433
create_query += f"\nEXTERNAL_ACCESS_INTEGRATIONS=({', '.join(ensure_all_string_literals(extension_fn.external_access_integrations))})"
if extension_fn.secrets:
- create_query += f"""\nSECRETS=({', '.join([f"{ensure_string_literal(k)}={v}" for k, v in extension_fn.secrets.items()])})"""
+ create_query += f"""\nSECRETS=({", ".join([f"{ensure_string_literal(k)}={v}" for k, v in extension_fn.secrets.items()])})"""
create_query += f"\nHANDLER={ensure_string_literal(extension_fn.handler)}"
src/snowflake/cli/_plugins/stage/manager.py~L106
def get_standard_stage_path(self) -> str:
path = self.get_full_stage_path(self.path)
- return f"@{path}{'/'if self.is_directory and not path.endswith('/') else ''}"
+ return f"@{path}{'/' if self.is_directory and not path.endswith('/') else ''}"
def get_standard_stage_directory_path(self) -> str:
path = self.get_standard_stage_path()
tests/test_connection.py~L1312
["connection", "generate-jwt", "-c", "jwt"],
)
assert (
- f'{attribute.capitalize().replace("_", " ")} is not set in the connection context'
+ f"{attribute.capitalize().replace('_', ' ')} is not set in the connection context"
in result.output
)
tests_e2e/test_installation.py~L68
assert "Initialized the new project in" in output
for file in files_to_check:
expected_generated_file = project_path / file
- assert expected_generated_file.exists(), f"[{expected_generated_file}] does not exist. It should be generated from templates directory."
+ assert expected_generated_file.exists(), (
+ f"[{expected_generated_file}] does not exist. It should be generated from templates directory."
+ )
@pytest.mark.e2e
aiven/aiven-client (+2 -2 lines across 1 file)
types = spec["type"]
if isinstance(types, str) and types == "null":
print(
- " {title}{description}\n" " => --remove-option {name}".format(
+ " {title}{description}\n => --remove-option {name}".format(
name=name,
title=spec["title"],
description=description,
types = [types]
type_str = " or ".join(t for t in types if t != "null")
print(
- " {title}{description}\n" " => -c {name}=<{type}> {default}".format(
+ " {title}{description}\n => -c {name}=<{type}> {default}".format(
name=name,
type=type_str,
default=default_desc,
aws/aws-sam-cli (+22 -24 lines across 19 files)
samcli/commands/init/interactive_init_flow.py~L544
click.echo(f"\n{question}")
for index, option in enumerate(options_list):
- click.echo(f"\t{index+1} - {option}")
+ click.echo(f"\t{index + 1} - {option}")
click_choices.append(str(index + 1))
choice = click.prompt(msg, type=click.Choice(click_choices), show_choices=False)
return options_list[int(choice) - 1]
samcli/commands/init/interactive_init_flow.py~L557
click.echo("\nSelect your starter template")
click_template_choices = []
for index, template in enumerate(templates):
- click.echo(f"\t{index+1} - {template['displayName']}")
+ click.echo(f"\t{index + 1} - {template['displayName']}")
click_template_choices.append(str(index + 1))
template_choice = click.prompt("Template", type=click.Choice(click_template_choices), show_choices=False)
chosen_template = templates[int(template_choice) - 1]
samcli/lib/deploy/deployer.py~L513
The maximum duration in minutes to wait for the deployment to complete.
"""
sys.stdout.write(
- "\n{} - Waiting for stack create/update " "to complete\n".format(
- datetime.now().strftime("%Y-%m-%d %H:%M:%S")
- )
+ "\n{} - Waiting for stack create/update to complete\n".format(datetime.now().strftime("%Y-%m-%d %H:%M:%S"))
)
sys.stdout.flush()
samcli/lib/intrinsic_resolver/intrinsic_property_resolver.py~L319
verify_intrinsic_type_list(
value_list,
IntrinsicResolver.FN_JOIN,
- message="The list of values in {} after the " "delimiter must be a list".format(IntrinsicResolver.FN_JOIN),
+ message="The list of values in {} after the delimiter must be a list".format(IntrinsicResolver.FN_JOIN),
)
sanitized_value_list = [
samcli/lib/intrinsic_resolver/intrinsic_property_resolver.py~L487
verify_intrinsic_type_dict(
top_level_value,
IntrinsicResolver.FN_FIND_IN_MAP,
- message="The TopLevelKey is missing in the Mappings dictionary in Fn::FindInMap " "for {}".format(
+ message="The TopLevelKey is missing in the Mappings dictionary in Fn::FindInMap for {}".format(
top_level_key
),
)
samcli/lib/intrinsic_resolver/intrinsic_property_resolver.py~L496
verify_non_null(
second_level_value,
IntrinsicResolver.FN_FIND_IN_MAP,
- message="The SecondLevelKey is missing in the Mappings dictionary in Fn::FindInMap " "for {}".format(
+ message="The SecondLevelKey is missing in the Mappings dictionary in Fn::FindInMap for {}".format(
second_level_key
),
)
samcli/lib/schemas/schemas_directory_hierarchy_builder.py~L11
def get_package_hierarchy(schema_name):
path = "schema"
if schema_name.startswith("aws.partner-"):
- path = path + "." "aws.partner"
+ path = path + ".aws.partner"
tail = schema_name[len("aws.partner-") :]
path = path + "." + sanitize_name(tail)
return path.lower()
tests/integration/local/invoke/test_integrations_cli.py~L183
self.assertEqual(
process_stdout.decode("utf-8"),
"",
- msg="The return statement in the LambdaFunction " "should never return leading to an empty string",
+ msg="The return statement in the LambdaFunction should never return leading to an empty string",
)
@pytest.mark.flaky(reruns=3)
tests/integration/testdata/remote_invoke/lambda-fns/main.py~L9
print("value2 = " + event["key2"])
print("value3 = " + event["key3"])
- return {"message": f'{event["key1"]} {event["key3"]}'}
+ return {"message": f"{event['key1']} {event['key3']}"}
def custom_env_var_echo_handler(event, context):
tests/integration/testdata/sync/code/after/function/app.py~L11
"statusCode": 200,
"body": json.dumps(
{
- "message": f"{layer_method()+2}",
+ "message": f"{layer_method() + 2}",
"message_from_layer": f"{layer_method()}",
"extra_message": np.array([1, 2, 3, 4, 5, 6]).tolist(), # checking external library call will succeed
}
tests/integration/testdata/sync/code/before/function/app.py~L11
"statusCode": 200,
"body": json.dumps(
{
- "message": f"{layer_method()+1}",
+ "message": f"{layer_method() + 1}",
"message_from_layer": f"{layer_method()}",
"extra_message": np.array([1, 2, 3, 4, 5, 6]).tolist(), # checking external library call will succeed
}
tests/integration/testdata/sync/infra/after/Python/function/app.py~L11
"statusCode": 200,
"body": json.dumps(
{
- "message": f"{layer_method()+2}",
+ "message": f"{layer_method() + 2}",
"extra_message": np.array([1, 2, 3, 4, 5, 6]).tolist(), # checking external library call will succeed
}
),
tests/integration/testdata/sync/infra/before/Python/function/app.py~L11
"statusCode": 200,
"body": json.dumps(
{
- "message": f"{layer_method()+1}",
+ "message": f"{layer_method() + 1}",
"extra_message": np.array([1, 2, 3, 4, 5, 6]).tolist(), # checking external library call will succeed
}
),
"statusCode": 200,
"body": json.dumps(
{
- "message": f"{layer_method()+2}",
+ "message": f"{layer_method() + 2}",
"extra_message": np.array([1, 2, 3, 4, 5, 6]).tolist(), # checking external library call will succeed
}
),
"statusCode": 200,
"body": json.dumps(
{
- "message": f"{layer_method()+2}",
+ "message": f"{layer_method() + 2}",
"extra_message": np.array([1, 2, 3, 4, 5, 6]).tolist(), # checking external library call will succeed
}
),
"statusCode": 200,
"body": json.dumps(
{
- "message": f"{layer_method()+1}",
+ "message": f"{layer_method() + 1}",
"extra_message": np.array([1, 2, 3, 4, 5, 6]).tolist(), # checking external library call will succeed
}
),
"statusCode": 200,
"body": json.dumps(
{
- "message": f"{layer_method()+1}",
+ "message": f"{layer_method() + 1}",
"extra_message": np.array([1, 2, 3, 4, 5, 6]).tolist(), # checking external library call will succeed
}
),
tests/integration/testdata/sync/nested/after/child_stack/child_functions/child_function.py~L7
return {
"statusCode": 200,
- "body": json.dumps({"message": f"{layer_method()+6}"}),
+ "body": json.dumps({"message": f"{layer_method() + 6}"}),
}
tests/integration/testdata/sync/nested/after/root_function/root_function.py~L17
return {
"statusCode": 200,
- "body": json.dumps({"message": f"{layer_method()+6}", "location": ip.text.replace("\n", "")}),
+ "body": json.dumps({"message": f"{layer_method() + 6}", "location": ip.text.replace("\n", "")}),
}
tests/integration/testdata/sync/nested/before/child_stack/child_functions/child_function.py~L7
return {
"statusCode": 200,
- "body": json.dumps({"message": f"{layer_method()+5}"}),
+ "body": json.dumps({"message": f"{layer_method() + 5}"}),
}
tests/integration/testdata/sync/nested/before/root_function/root_function.py~L17
return {
"statusCode": 200,
- "body": json.dumps({"message": f"{layer_method()+6}", "location": ip.text.replace("\n", "")}),
+ "body": json.dumps({"message": f"{layer_method() + 6}", "location": ip.text.replace("\n", "")}),
}
"statusCode": 200,
"body": json.dumps(
{
- "message": f"{layer_method()+1}",
+ "message": f"{layer_method() + 1}",
"location": ip.text.replace("\n", ""),
# "extra_message": np.array([1, 2, 3, 4, 5, 6]).tolist() # checking external library call will succeed
}
binary-husky/gpt_academic (+62 -60 lines across 33 files)
crazy_functions/Conversation_To_File.py~L251
[
"`" + hide_cwd(f) + f" ({gen_file_preview(f)})" + "`"
for f in glob.glob(
- f'{get_log_folder(get_user(chatbot), plugin_name="chat_history")}/**/{f_prefix}*.html',
+ f"{get_log_folder(get_user(chatbot), plugin_name='chat_history')}/**/{f_prefix}*.html",
recursive=True,
)
]
crazy_functions/Conversation_To_File.py~L294
[
"`" + hide_cwd(f) + "`"
for f in glob.glob(
- f'{get_log_folder(get_user(chatbot), plugin_name="chat_history")}/**/{f_prefix}*.html',
+ f"{get_log_folder(get_user(chatbot), plugin_name='chat_history')}/**/{f_prefix}*.html",
recursive=True,
)
]
)
for f in glob.glob(
- f'{get_log_folder(get_user(chatbot), plugin_name="chat_history")}/**/{f_prefix}*.html',
+ f"{get_log_folder(get_user(chatbot), plugin_name='chat_history')}/**/{f_prefix}*.html",
recursive=True,
):
os.remove(f)
crazy_functions/Markdown_Translate.py~L193
txt = txt.replace("/blob/", "/")
r = requests.get(txt, proxies=proxies)
- download_local = f'{get_log_folder(plugin_name="批量Markdown翻译")}/raw-readme-{gen_time_str()}.md'
- project_folder = f'{get_log_folder(plugin_name="批量Markdown翻译")}'
+ download_local = f"{get_log_folder(plugin_name='批量Markdown翻译')}/raw-readme-{gen_time_str()}.md"
+ project_folder = f"{get_log_folder(plugin_name='批量Markdown翻译')}"
with open(download_local, "wb+") as f:
f.write(r.content)
file_manifest = [download_local]
crazy_functions/Rag_Interface.py~L168
HALF = REMEMBER_PREVIEW // 2
i_say_to_remember = (
txt[:HALF]
- + f" ...\n...(省略{len(txt_origin)-REMEMBER_PREVIEW}字)...\n... "
+ + f" ...\n...(省略{len(txt_origin) - REMEMBER_PREVIEW}字)...\n... "
+ txt[-HALF:]
)
if (flags["original_input_len"] - flags["clipped_input_len"]) > HALF:
txt_clip = (
txt_clip
- + f" ...\n...(省略{len(txt_origin)-len(txt_clip)-HALF}字)...\n... "
+ + f" ...\n...(省略{len(txt_origin) - len(txt_clip) - HALF}字)...\n... "
+ txt[-HALF:]
)
else:
crazy_functions/Social_Helper.py~L182
try:
Explaination = "\n".join(
- [f'{k}: {v["explain_to_llm"]}' for k, v in self.tools_to_select.items()]
+ [f"{k}: {v['explain_to_llm']}" for k, v in self.tools_to_select.items()]
)
class UserSociaIntention(BaseModel):
crazy_functions/SourceCode_Analyse.py~L28
sys_prompt_array = []
report_part_1 = []
- assert (
- len(file_manifest) <= 512
- ), "源文件太多（超过512个）, 请缩减输入文件的数量。或者，您也可以选择删除此行警告，并修改代码拆分file_manifest列表，从而实现分批次处理。"
+ assert len(file_manifest) <= 512, (
+ "源文件太多（超过512个）, 请缩减输入文件的数量。或者，您也可以选择删除此行警告，并修改代码拆分file_manifest列表，从而实现分批次处理。"
+ )
############################## <第一步，逐个文件分析，多线程> ##################################
for index, fp in enumerate(file_manifest):
# 读取文件
crazy_functions/SourceCode_Analyse.py~L43
)
i_say_show_user = (
prefix
- + f"[{index+1}/{len(file_manifest)}] 请对下面的程序文件做一个概述: {fp}"
+ + f"[{index + 1}/{len(file_manifest)}] 请对下面的程序文件做一个概述: {fp}"
)
# 装载请求内容
inputs_array.append(i_say)
crazy_functions/SourceCode_Analyse.py~L92
for index, content in enumerate(this_iteration_gpt_response_collection):
if index % 2 == 0:
this_iteration_gpt_response_collection[index] = (
- f"{file_rel_path[index//2]}" # 只保留文件名节省token
+ f"{file_rel_path[index // 2]}" # 只保留文件名节省token
)
this_iteration_files = [
os.path.relpath(fp, project_folder)
crazy_functions/SourceCode_Comment.py~L37
history_array = []
sys_prompt_array = []
- assert (
- len(file_manifest) <= 512
- ), "源文件太多（超过512个）, 请缩减输入文件的数量。或者，您也可以选择删除此行警告，并修改代码拆分file_manifest列表，从而实现分批次处理。"
+ assert len(file_manifest) <= 512, (
+ "源文件太多（超过512个）, 请缩减输入文件的数量。或者，您也可以选择删除此行警告，并修改代码拆分file_manifest列表，从而实现分批次处理。"
+ )
# 建立文件树
file_tree_struct = FileNode("root", build_manifest=True)
crazy_functions/SourceCode_Comment.py~L59
)
i_say_show_user = (
prefix
- + f"[{index+1}/{len(file_manifest)}] 请用一句话对下面的程序文件做一个整体概述: {fp}"
+ + f"[{index + 1}/{len(file_manifest)}] 请用一句话对下面的程序文件做一个整体概述: {fp}"
)
# 装载请求内容
MAX_TOKEN_SINGLE_FILE = 2560
crazy_functions/VideoResource_GPT.py~L65
tic_time = 8
for i in range(tic_time):
yield from update_ui_lastest_msg(
- lastmsg=f"即将下载音频。等待{tic_time-i}秒后自动继续, 点击“停止”键取消此操作。",
+ lastmsg=f"即将下载音频。等待{tic_time - i}秒后自动继续, 点击“停止”键取消此操作。",
chatbot=chatbot,
history=[],
delay=1,
crazy_functions/VideoResource_GPT.py~L94
tic_time = 16
for i in range(tic_time):
yield from update_ui_lastest_msg(
- lastmsg=f"即将下载视频。等待{tic_time-i}秒后自动继续, 点击“停止”键取消此操作。",
+ lastmsg=f"即将下载视频。等待{tic_time - i}秒后自动继续, 点击“停止”键取消此操作。",
chatbot=chatbot,
history=[],
delay=1,
crazy_functions/VideoResource_GPT.py~L216
# 展示候选资源
candadate_display = "\n".join(
- [f"{i+1}. {it['title']}" for i, it in enumerate(candadate_dictionary)]
+ [f"{i + 1}. {it['title']}" for i, it in enumerate(candadate_dictionary)]
)
chatbot.append((None, f"候选:\n\n{candadate_display}"))
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
crazy_functions/crazy_utils.py~L166
if retry_op > 0:
retry_op -= 1
mutable[0] += (
- f"[Local Message] 重试中，请稍等 {retry_times_at_unknown_error-retry_op}/{retry_times_at_unknown_error}：\n\n"
+ f"[Local Message] 重试中，请稍等 {retry_times_at_unknown_error - retry_op}/{retry_times_at_unknown_error}：\n\n"
)
if ("Rate limit reached" in tb_str) or (
"Too Many Requests" in tb_str
crazy_functions/crazy_utils.py~L366
fail_info = ""
# 也许等待十几秒后，情况会好转
for i in range(wait):
- mutable[index][2] = f"{fail_info}等待重试 {wait-i}"
+ mutable[index][2] = f"{fail_info}等待重试 {wait - i}"
time.sleep(1)
# 开始重试
if detect_timeout():
raise RuntimeError("检测到程序终止。")
mutable[index][2] = (
- f"重试中 {retry_times_at_unknown_error-retry_op}/{retry_times_at_unknown_error}"
+ f"重试中 {retry_times_at_unknown_error - retry_op}/{retry_times_at_unknown_error}"
)
continue # 返回重试
else:
crazy_functions/diagram_fns/file_tree.py~L85
)
p2 = """ --> """
p3 = (
- f"""{code+str(j)}[\"🗎{child.name}\"]"""
+ f"""{code + str(j)}[\"🗎{child.name}\"]"""
if child.is_leaf
- else f"""{code+str(j)}[[\"📁{child.name}\"]]"""
+ else f"""{code + str(j)}[[\"📁{child.name}\"]]"""
)
edge_code = p1 + p2 + p3
if edge_code in self.parenting_ship:
crazy_functions/gen_fns/gen_fns_shared.py~L22
def try_make_module(code, chatbot):
module_file = "gpt_fn_" + gen_time_str().replace("-", "_")
- fn_path = f'{get_log_folder(plugin_name="gen_plugin_verify")}/{module_file}.py'
+ fn_path = f"{get_log_folder(plugin_name='gen_plugin_verify')}/{module_file}.py"
with open(fn_path, "w", encoding="utf8") as f:
f.write(code)
promote_file_to_downloadzone(fn_path, chatbot=chatbot)
crazy_functions/gen_fns/gen_fns_shared.py~L70
return_dict["traceback"] = ""
try:
module_file = "gpt_fn_" + gen_time_str().replace("-", "_")
- fn_path = f'{get_log_folder(plugin_name="gen_plugin_run")}/{module_file}.py'
+ fn_path = f"{get_log_folder(plugin_name='gen_plugin_run')}/{module_file}.py"
with open(fn_path, "w", encoding="utf8") as f:
f.write(code)
class_name = get_class_name(code)
crazy_functions/latex_fns/latex_toolbox.py~L473
main_file = insert_abstract(main_file)
match_opt1 = pattern_opt1.search(main_file)
match_opt2 = pattern_opt2.search(main_file)
- assert (match_opt1 is not None) or (
- match_opt2 is not None
- ), "Cannot find paper abstract section!"
+ assert (match_opt1 is not None) or (match_opt2 is not None), (
+ "Cannot find paper abstract section!"
+ )
return main_file
crazy_functions/pdf_fns/breakdown_txt.py~L82
remain_txt_to_cut, remain_txt_to_cut_storage
)
process = fin_len / total_len
- logger.info(f"正在文本切分 {int(process*100)}%")
+ logger.info(f"正在文本切分 {int(process * 100)}%")
if len(remain_txt_to_cut.strip()) == 0:
break
return res
crazy_functions/pdf_fns/parse_pdf.py~L181
for i, fragment in enumerate(section_frags):
heading = section["heading"]
if len(section_frags) > 1:
- heading += f" Part-{i+1}"
+ heading += f" Part-{i + 1}"
inputs_array.append(f"你需要翻译{heading}章节，内容如下: \n\n{fragment}")
inputs_show_user_array.append(f"# {heading}\n\n{fragment}")
crazy_functions/pdf_fns/parse_pdf_legacy.py~L96
for i, k in enumerate(gpt_response_collection_md):
if i % 2 == 0:
gpt_response_collection_md[i] = (
- f"\n\n---\n\n ## 原文[{i//2}/{len(gpt_response_collection_md)//2}]： \n\n {paper_fragments[i//2].replace('#', '')} \n\n---\n\n ## 翻译[{i//2}/{len(gpt_response_collection_md)//2}]：\n "
+ f"\n\n---\n\n ## 原文[{i // 2}/{len(gpt_response_collection_md) // 2}]： \n\n {paper_fragments[i // 2].replace('#', '')} \n\n---\n\n ## 翻译[{i // 2}/{len(gpt_response_collection_md) // 2}]：\n "
)
else:
gpt_response_collection_md[i] = gpt_response_collection_md[i]
crazy_functions/rag_fns/llama_index_worker.py~L143
buf = "\n".join(
(
[
- f"(No.{i+1} | score {n.score:.3f}): {n.text}"
+ f"(No.{i + 1} | score {n.score:.3f}): {n.text}"
for i, n in enumerate(nodes)
]
)
crazy_functions/vt_fns/vt_call_plugin.py~L187
# ⭐ ⭐ ⭐ 执行插件
fn = plugin["Function"]
fn_name = fn.__name__
- msg = f'{llm_kwargs["llm_model"]}为您选择了插件: `{fn_name}`\n\n插件说明：{plugin["Info"]}\n\n插件参数：{plugin_sel.plugin_arg}\n\n假如偏离了您的要求，按停止键终止。'
+ msg = f"{llm_kwargs['llm_model']}为您选择了插件: `{fn_name}`\n\n插件说明：{plugin['Info']}\n\n插件参数：{plugin_sel.plugin_arg}\n\n假如偏离了您的要求，按停止键终止。"
yield from update_ui_lastest_msg(
lastmsg=msg, chatbot=chatbot, history=history, delay=2
)
"a/crazy_functions/\345\207\275\346\225\260\345\212\250\346\200\201\347\224\237\346\210\220.py"~L269
if not traceback:
traceback = trimmed_format_exc()
yield from update_ui_lastest_msg(
- f"第 {j+1}/{MAX_TRY} 次代码生成尝试, 失败了~ 别担心, 我们5秒后再试一次... \n\n此次我们的错误追踪是\n```\n{traceback}\n```\n",
+ f"第 {j + 1}/{MAX_TRY} 次代码生成尝试, 失败了~ 别担心, 我们5秒后再试一次... \n\n此次我们的错误追踪是\n```\n{traceback}\n```\n",
chatbot,
history,
5,
"a/crazy_functions/\346\200\273\347\273\223word\346\226\207\346\241\243.py"~L57
this_paper_history = []
for i, paper_frag in enumerate(paper_fragments):
i_say = f"请对下面的文章片段用中文做概述，文件名是{os.path.relpath(fp, project_folder)}，文章内容是 ```{paper_frag}```"
- i_say_show_user = f"请对下面的文章片段做概述: {os.path.abspath(fp)}的第{i+1}/{len(paper_fragments)}个片段。"
+ i_say_show_user = f"请对下面的文章片段做概述: {os.path.abspath(fp)}的第{i + 1}/{len(paper_fragments)}个片段。"
gpt_say = yield from request_gpt_model_in_new_thread_with_ui_alive(
inputs=i_say,
inputs_show_user=i_say_show_user,
for i in range(n_fragment):
NUM_OF_WORD = MAX_WORD_TOTAL // n_fragment
i_say = f"Read this section, recapitulate the content of this section with less than {NUM_OF_WORD} Chinese characters: {paper_fragments[i]}"
- i_say_show_user = f"[{i+1}/{n_fragment}] Read this section, recapitulate the content of this section with less than {NUM_OF_WORD} Chinese characters: {paper_fragments[i][:200]}"
+ i_say_show_user = f"[{i + 1}/{n_fragment}] Read this section, recapitulate the content of this section with less than {NUM_OF_WORD} Chinese characters: {paper_fragments[i][:200]}"
gpt_say = yield from request_gpt_model_in_new_thread_with_ui_alive(
i_say,
i_say_show_user, # i_say=真正给chatgpt的提问， i_say_show_user=给用户看的提问
)
i_say_show_user = (
prefix
- + f"[{index+1}/{len(file_manifest)}] 请对下面的文章片段做一个概述: {os.path.abspath(fp)}"
+ + f"[{index + 1}/{len(file_manifest)}] 请对下面的文章片段做一个概述: {os.path.abspath(fp)}"
)
chatbot.append((i_say_show_user, "[Local Message] waiting gpt response."))
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
for i in range(n_fragment):
NUM_OF_WORD = MAX_WORD_TOTAL // n_fragment
i_say = f"Read this section, recapitulate the content of this section with less than {NUM_OF_WORD} words: {paper_fragments[i]}"
- i_say_show_user = f"[{i+1}/{n_fragment}] Read this section, recapitulate the content of this section with less than {NUM_OF_WORD} words: {paper_fragments[i][:200]} ...."
+ i_say_show_user = f"[{i + 1}/{n_fragment}] Read this section, recapitulate the content of this section with less than {NUM_OF_WORD} words: {paper_fragments[i][:200]} ...."
gpt_say = yield from request_gpt_model_in_new_thread_with_ui_alive(
i_say,
i_say_show_user, # i_say=真正给chatgpt的提问， i_say_show_user=给用户看的提问
"a/crazy_functions/\347\224\237\346\210\220\345\207\275\346\225\260\346\263\250\351\207\212.py"~L22
file_content = f.read()
i_say = f"请对下面的程序文件做一个概述，并对文件中的所有函数生成注释，使用markdown表格输出结果，文件名是{os.path.relpath(fp, project_folder)}，文件内容是 ```{file_content}```"
- i_say_show_user = f"[{index+1}/{len(file_manifest)}] 请对下面的程序文件做一个概述，并对文件中的所有函数生成注释: {os.path.abspath(fp)}"
+ i_say_show_user = f"[{index + 1}/{len(file_manifest)}] 请对下面的程序文件做一个概述，并对文件中的所有函数生成注释: {os.path.abspath(fp)}"
chatbot.append((i_say_show_user, "[Local Message] waiting gpt response."))
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
for i in ra...*[Comment body truncated]*
![github-actions[bot] avatar](https://avatars.githubusercontent.com/in/15368?v=4 "Published by a pub.dev verified publisher"){kind=small}