ci: Simplify Python code with ruff rules SIM (#5833)

* ci: Simplify Python code with ruff rules SIM

* Revert #5828

* ruff --select=I --fix haystack/modeling/infer.py

---------

Co-authored-by: Massimiliano Pippi <[email protected]>

e2e/pipelines/test_standard_pipelines.py

@@ -306,7 +306,7 @@ def test_summarization_pipeline():
  output = pipeline.run(query=query, params={"Retriever": {"top_k": 1}})
  answers = output["answers"]
  assert len(answers) == 1
- assert "The Eiffel Tower is one of the world's tallest structures." == answers[0]["answer"].strip()
+ assert answers[0]["answer"].strip() == "The Eiffel Tower is one of the world's tallest structures."
 
 
 def test_summarization_pipeline_one_summary():

e2e/preview/components/test_gpt35_generator.py

@@ -17,7 +17,7 @@ def test_gpt35_generator_run(generator_class, model_name):
  assert "Paris" in results["replies"][0]
  assert len(results["metadata"]) == 1
  assert model_name in results["metadata"][0]["model"]
- assert "stop" == results["metadata"][0]["finish_reason"]
+ assert results["metadata"][0]["finish_reason"] == "stop"
 
 
 @pytest.mark.skipif(
@@ -54,6 +54,6 @@ def __call__(self, chunk):
 
  assert len(results["metadata"]) == 1
  assert model_name in results["metadata"][0]["model"]
- assert "stop" == results["metadata"][0]["finish_reason"]
+ assert results["metadata"][0]["finish_reason"] == "stop"
 
  assert callback.responses == results["replies"][0]

e2e/preview/components/test_whisper_local.py

@@ -14,14 +14,14 @@ def test_whisper_local_transcriber(preview_samples_path):
  docs = output["documents"]
  assert len(docs) == 3
 
- assert "this is the content of the document." == docs[0].text.strip().lower()
+ assert docs[0].text.strip().lower() == "this is the content of the document."
  assert preview_samples_path / "audio" / "this is the content of the document.wav" == docs[0].metadata["audio_file"]
 
- assert "the context for this answer is here." == docs[1].text.strip().lower()
+ assert docs[1].text.strip().lower() == "the context for this answer is here."
  assert (
  str((preview_samples_path / "audio" / "the context for this answer is here.wav").absolute())
  == docs[1].metadata["audio_file"]
  )
 
- assert "answer." == docs[2].text.strip().lower()
- assert "<<binary stream>>" == docs[2].metadata["audio_file"]
+ assert docs[2].text.strip().lower() == "answer."
+ assert docs[2].metadata["audio_file"] == "<<binary stream>>"

e2e/preview/components/test_whisper_remote.py

@@ -22,14 +22,14 @@ def test_whisper_remote_transcriber(preview_samples_path):
  docs = output["documents"]
  assert len(docs) == 3
 
- assert "this is the content of the document." == docs[0].text.strip().lower()
+ assert docs[0].text.strip().lower() == "this is the content of the document."
  assert preview_samples_path / "audio" / "this is the content of the document.wav" == docs[0].metadata["audio_file"]
 
- assert "the context for this answer is here." == docs[1].text.strip().lower()
+ assert docs[1].text.strip().lower() == "the context for this answer is here."
  assert (
  str((preview_samples_path / "audio" / "the context for this answer is here.wav").absolute())
  == docs[1].metadata["audio_file"]
  )
 
- assert "answer." == docs[2].text.strip().lower()
- assert "<<binary stream>>" == docs[2].metadata["audio_file"]
+ assert docs[2].text.strip().lower() == "answer."
+ assert docs[2].metadata["audio_file"] == "<<binary stream>>"

haystack-linter/haystack_linter/linting.py

@@ -37,16 +37,13 @@ def leave_functiondef(self, node: nodes.FunctionDef) -> None:
  self._function_stack.pop()
 
  def visit_call(self, node: nodes.Call) -> None:
- if isinstance(node.func, nodes.Attribute) and isinstance(node.func.expr, nodes.Name):
- if node.func.expr.name == "logging" and node.func.attrname in [
- "debug",
- "info",
- "warning",
- "error",
- "critical",
- "exception",
- ]:
- self.add_message("no-direct-logging", args=node.func.attrname, node=node)
+ if (
+ isinstance(node.func, nodes.Attribute)
+ and isinstance(node.func.expr, nodes.Name)
+ and node.func.expr.name == "logging"
+ and node.func.attrname in ["debug", "info", "warning", "error", "critical", "exception"]
+ ):
+ self.add_message("no-direct-logging", args=node.func.attrname, node=node)
 
 
 class NoLoggingConfigurationChecker(BaseChecker):
@@ -71,9 +68,13 @@ def leave_functiondef(self, node: nodes.FunctionDef) -> None:
  self._function_stack.pop()
 
  def visit_call(self, node: nodes.Call) -> None:
- if isinstance(node.func, nodes.Attribute) and isinstance(node.func.expr, nodes.Name):
- if node.func.expr.name == "logging" and node.func.attrname in ["basicConfig"]:
- self.add_message("no-logging-basicconfig", node=node)
+ if (
+ isinstance(node.func, nodes.Attribute)
+ and isinstance(node.func.expr, nodes.Name)
+ and node.func.expr.name == "logging"
+ and node.func.attrname in ["basicConfig"]
+ ):
+ self.add_message("no-logging-basicconfig", node=node)
 
 
 def register(linter: "PyLinter") -> None:

haystack/agents/base.py

@@ -346,7 +346,7 @@ def run(
  You can only pass parameters to tools that are pipelines, but not nodes.
  """
  try:
- if not self.hash == self.last_hash:
+ if self.hash != self.last_hash:
  self.last_hash = self.hash
  send_event(event_name="Agent", event_properties={"llm.agent_hash": self.hash})
  except Exception as exc:

haystack/document_stores/elasticsearch/es8.py

@@ -299,9 +299,10 @@ def _init_elastic_client(
  return client
 
  def _index_exists(self, index_name: str, headers: Optional[Dict[str, str]] = None) -> bool:
- if logger.isEnabledFor(logging.DEBUG):
- if self.client.options(headers=headers).indices.exists_alias(name=index_name):
- logger.debug("Index name %s is an alias.", index_name)
+ if logger.isEnabledFor(logging.DEBUG) and self.client.options(headers=headers).indices.exists_alias(
+ name=index_name
+ ):
+ logger.debug("Index name %s is an alias.", index_name)
 
  return self.client.options(headers=headers).indices.exists(index=index_name)
 

haystack/document_stores/es_converter.py

@@ -228,9 +228,8 @@ def elasticsearch_index_to_document_store(
  content = record["_source"].pop(original_content_field, "")
  if content:
  meta = {}
- if original_name_field is not None:
- if original_name_field in record["_source"]:
- meta["name"] = record["_source"].pop(original_name_field)
+ if original_name_field is not None and original_name_field in record["_source"]:
+ meta["name"] = record["_source"].pop(original_name_field)
  # Only add selected metadata fields
  if included_metadata_fields is not None:
  for metadata_field in included_metadata_fields:

haystack/document_stores/faiss.py

@@ -447,9 +447,8 @@ def get_all_documents_generator(
  return_embedding = self.return_embedding
 
  for doc in documents:
- if return_embedding:
- if doc.meta and doc.meta.get("vector_id") is not None:
- doc.embedding = self.faiss_indexes[index].reconstruct(int(doc.meta["vector_id"]))
+ if return_embedding and doc.meta and doc.meta.get("vector_id") is not None:
+ doc.embedding = self.faiss_indexes[index].reconstruct(int(doc.meta["vector_id"]))
  yield doc
 
  def get_documents_by_id(

haystack/document_stores/opensearch.py

@@ -382,10 +382,9 @@ def write_documents(
  self.index_type in ["ivf", "ivf_pq"]
  and not index.startswith(".")
  and not self._ivf_model_exists(index=index)
- ):
- if self.get_embedding_count(index=index, headers=headers) >= self.ivf_train_size:
- train_docs = self.get_all_documents(index=index, return_embedding=True, headers=headers)
- self._train_ivf_index(index=index, documents=train_docs, headers=headers)
+ ) and self.get_embedding_count(index=index, headers=headers) >= self.ivf_train_size:
+ train_docs = self.get_all_documents(index=index, return_embedding=True, headers=headers)
+ self._train_ivf_index(index=index, documents=train_docs, headers=headers)
 
  def _embed_documents(self, documents: List[Document], retriever: DenseRetriever) -> np.ndarray:
  """

haystack/document_stores/pinecone.py

@@ -487,7 +487,7 @@ def write_documents(
  documents=document_objects, index=index, duplicate_documents=duplicate_documents
  )
  if document_objects:
- add_vectors = False if document_objects[0].embedding is None else True
+ add_vectors = document_objects[0].embedding is not None
  # If these are not labels, we need to find the correct value for `doc_type` metadata field
  if not labels:
  type_metadata = DOCUMENT_WITH_EMBEDDING if add_vectors else DOCUMENT_WITHOUT_EMBEDDING

haystack/document_stores/search_engine.py

@@ -1620,9 +1620,8 @@ def delete_index(self, index: str):
  self._index_delete(index)
 
  def _index_exists(self, index_name: str, headers: Optional[Dict[str, str]] = None) -> bool:
- if logger.isEnabledFor(logging.DEBUG):
- if self.client.indices.exists_alias(name=index_name):
- logger.debug("Index name %s is an alias.", index_name)
+ if logger.isEnabledFor(logging.DEBUG) and self.client.indices.exists_alias(name=index_name):
+ logger.debug("Index name %s is an alias.", index_name)
 
  return self.client.indices.exists(index=index_name, headers=headers)
 

haystack/document_stores/utils.py

@@ -40,9 +40,8 @@ def eval_data_from_json(
  logger.warning("No title information found for documents in QA file: %s", filename)
 
  for squad_document in data["data"]:
- if max_docs:
- if len(docs) > max_docs:
- break
+ if max_docs and len(docs) > max_docs:
+ break
  # Extracting paragraphs and their labels from a SQuAD document dict
  cur_docs, cur_labels, cur_problematic_ids = _extract_docs_and_labels_from_dict(
  squad_document, preprocessor, open_domain
@@ -84,9 +83,8 @@ def eval_data_from_jsonl(
 
  with open(filename, "r", encoding="utf-8") as file:
  for document in file:
- if max_docs:
- if len(docs) > max_docs:
- break
+ if max_docs and len(docs) > max_docs:
+ break
  # Extracting paragraphs and their labels from a SQuAD document dict
  squad_document = json.loads(document)
  cur_docs, cur_labels, cur_problematic_ids = _extract_docs_and_labels_from_dict(
@@ -96,19 +94,18 @@ def eval_data_from_jsonl(
  labels.extend(cur_labels)
  problematic_ids.extend(cur_problematic_ids)
 
- if batch_size is not None:
- if len(docs) >= batch_size:
- if len(problematic_ids) > 0:
- logger.warning(
- "Could not convert an answer for %s questions.\n"
- "There were conversion errors for question ids: %s",
- len(problematic_ids),
- problematic_ids,
- )
- yield docs, labels
- docs = []
- labels = []
- problematic_ids = []
+ if batch_size is not None and len(docs) >= batch_size:
+ if len(problematic_ids) > 0:
+ logger.warning(
+ "Could not convert an answer for %s questions.\n"
+ "There were conversion errors for question ids: %s",
+ len(problematic_ids),
+ problematic_ids,
+ )
+ yield docs, labels
+ docs = []
+ labels = []
+ problematic_ids = []
 
  yield docs, labels
 

haystack/document_stores/weaviate.py

@@ -661,10 +661,9 @@ def write_documents(
  if isinstance(v, dict):
  json_fields.append(k)
  v = json.dumps(v)
- elif isinstance(v, list):
- if len(v) > 0 and isinstance(v[0], dict):
- json_fields.append(k)
- v = [json.dumps(item) for item in v]
+ elif isinstance(v, list) and len(v) > 0 and isinstance(v[0], dict):
+ json_fields.append(k)
+ v = [json.dumps(item) for item in v]
  _doc[k] = v
  _doc.pop("meta")
 
@@ -734,9 +733,8 @@ def update_document_meta(
  # Weaviate requires dates to be in RFC3339 format
  date_fields = self._get_date_properties(index)
  for date_field in date_fields:
- if date_field in meta:
- if isinstance(meta[date_field], str):
- meta[date_field] = convert_date_to_rfc3339(str(meta[date_field]))
+ if date_field in meta and isinstance(meta[date_field], str):
+ meta[date_field] = convert_date_to_rfc3339(str(meta[date_field]))
 
  self.weaviate_client.data_object.update(meta, class_name=index, uuid=id)
 
@@ -771,10 +769,8 @@ def get_document_count(
  else:
  result = self.weaviate_client.query.aggregate(index).with_meta_count().do()
 
- if "data" in result:
- if "Aggregate" in result.get("data"):
- if result.get("data").get("Aggregate").get(index):
- doc_count = result.get("data").get("Aggregate").get(index)[0]["meta"]["count"]
+ if "data" in result and "Aggregate" in result.get("data") and result.get("data").get("Aggregate").get(index):
+ doc_count = result.get("data").get("Aggregate").get(index)[0]["meta"]["count"]
 
  return doc_count
 
@@ -1153,9 +1149,13 @@ def query(
  query_output = self.weaviate_client.query.raw(gql_query)
 
  results = []
- if query_output and "data" in query_output and "Get" in query_output.get("data"):
- if query_output.get("data").get("Get").get(index):
- results = query_output.get("data").get("Get").get(index)
+ if (
+ query_output
+ and "data" in query_output
+ and "Get" in query_output.get("data")
+ and query_output.get("data").get("Get").get(index)
+ ):
+ results = query_output.get("data").get("Get").get(index)
 
  # We retrieve the JSON properties from the schema and convert them back to the Python dicts
  json_properties = self._get_json_properties(index=index)
@@ -1421,9 +1421,13 @@ def query_by_embedding(
  )
 
  results = []
- if query_output and "data" in query_output and "Get" in query_output.get("data"):
- if query_output.get("data").get("Get").get(index):
- results = query_output.get("data").get("Get").get(index)
+ if (
+ query_output
+ and "data" in query_output
+ and "Get" in query_output.get("data")
+ and query_output.get("data").get("Get").get(index)
+ ):
+ results = query_output.get("data").get("Get").get(index)
 
  # We retrieve the JSON properties from the schema and convert them back to the Python dicts
  json_properties = self._get_json_properties(index=index)

haystack/modeling/data_handler/data_silo.py

@@ -111,10 +111,12 @@ def _get_dataset(self, filename: Optional[Union[str, Path]], dicts: Optional[Lis
  if dicts is None:
  dicts = list(self.processor.file_to_dicts(filename)) # type: ignore
  # shuffle list of dicts here if we later want to have a random dev set split from train set
- if str(self.processor.train_filename) in str(filename):
- if not self.processor.dev_filename:
- if self.processor.dev_split > 0.0:
- random.shuffle(dicts)
+ if (
+ str(self.processor.train_filename) in str(filename)
+ and not self.processor.dev_filename
+ and self.processor.dev_split > 0.0
+ ):
+ random.shuffle(dicts)
 
  num_dicts = len(dicts)
  datasets = []

haystack/modeling/data_handler/processor.py

@@ -488,9 +488,8 @@ def dataset_from_dicts(
  dataset, tensor_names, baskets = self._create_dataset(baskets)
 
  # Logging
- if indices:
- if 0 in indices:
- self._log_samples(n_samples=1, baskets=baskets)
+ if indices and 0 in indices:
+ self._log_samples(n_samples=1, baskets=baskets)
 
  # During inference we need to keep the information contained in baskets.
  if return_baskets:

haystack/modeling/evaluation/eval.py

@@ -194,12 +194,15 @@ def log_results(
  logger.info("\n _________ %s _________", head["task_name"])
  for metric_name, metric_val in head.items():
  # log with experiment tracking framework (e.g. Mlflow)
- if logging:
- if not metric_name in ["preds", "labels"] and not metric_name.startswith("_"):
- if isinstance(metric_val, numbers.Number):
- tracker.track_metrics(
- metrics={f"{dataset_name}_{metric_name}_{head['task_name']}": metric_val}, step=steps
- )
+ if (
+ logging
+ and not metric_name in ["preds", "labels"]
+ and not metric_name.startswith("_")
+ and isinstance(metric_val, numbers.Number)
+ ):
+ tracker.track_metrics(
+ metrics={f"{dataset_name}_{metric_name}_{head['task_name']}": metric_val}, step=steps
+ )
  # print via standard python logger
  if print:
  if metric_name == "report":