infra: add print rule to ruff (langchain-ai#16221)

Added noqa for existing prints. Can slowly remove / will prevent more
being intro'd

Author: Erick Friis

.github/scripts/check_diff.py

@@ -47,4 +47,4 @@
         else:
             pass
     json_output = json.dumps(list(dirs_to_run))
-    print(f"dirs-to-run={json_output}")
+    print(f"dirs-to-run={json_output}")  # noqa: T201

.github/scripts/get_min_versions.py

@@ -62,4 +62,6 @@ def get_min_version_from_toml(toml_path: str):
 # Call the function to get the minimum versions
 min_versions = get_min_version_from_toml(toml_file)
 
-print(" ".join([f"{lib}=={version}" for lib, version in min_versions.items()]))
+print(
+    " ".join([f"{lib}=={version}" for lib, version in min_versions.items()])
+)  # noqa: T201

.github/workflows/extract_ignored_words_list.py

@@ -7,4 +7,4 @@
     pyproject_toml.get("tool", {}).get("codespell", {}).get("ignore-words-list")
 )
 
-print(f"::set-output name=ignore_words_list::{ignore_words_list}")
+print(f"::set-output name=ignore_words_list::{ignore_words_list}")  # noqa: T201

docs/api_reference/create_api_rst.py

@@ -1,4 +1,5 @@
 """Script for auto-generating api_reference.rst."""
+
 import importlib
 import inspect
 import os
@@ -186,7 +187,7 @@ def _load_package_modules(
             modules_by_namespace[top_namespace] = _module_members
 
         except ImportError as e:
-            print(f"Error: Unable to import module '{namespace}' with error: {e}")
+            print(f"Error: Unable to import module '{namespace}' with error: {e}")  # noqa: T201
 
     return modules_by_namespace
 

docs/docs/integrations/document_loaders/example_data/source_code/example.py

@@ -3,7 +3,7 @@ def __init__(self, name):
         self.name = name
 
     def greet(self):
-        print(f"Hello, {self.name}!")
+        print(f"Hello, {self.name}!")  # noqa: T201
 
 
 def main():

docs/scripts/generate_api_reference_links.py

@@ -64,7 +64,7 @@ def main():
     global_imports = {}
 
     for file in find_files(args.docs_dir):
-        print(f"Adding links for imports in {file}")
+        print(f"Adding links for imports in {file}")  # noqa: T201
         file_imports = replace_imports(file)
 
         if file_imports:

libs/cli/langchain_cli/integration_template/pyproject.toml

@@ -58,6 +58,7 @@ select = [
   "E",  # pycodestyle
   "F",  # pyflakes
   "I",  # isort
+  "T201", # print
 ]
 
 [tool.mypy]

libs/cli/langchain_cli/integration_template/scripts/check_imports.py

@@ -10,8 +10,8 @@
             SourceFileLoader("x", file).load_module()
         except Exception:
             has_faillure = True
-            print(file)
+            print(file)  # noqa: T201
             traceback.print_exc()
-            print()
+            print()  # noqa: T201
 
     sys.exit(1 if has_failure else 0)

libs/cli/pyproject.toml

@@ -45,6 +45,7 @@ select = [
   "E",  # pycodestyle
   "F",  # pyflakes
   "I",  # isort
+  "T201", # print
 ]
 
 [tool.poe.tasks]

libs/community/langchain_community/callbacks/arize_callback.py

@@ -49,7 +49,7 @@ def __init__(
         if SPACE_KEY == "SPACE_KEY" or API_KEY == "API_KEY":
             raise ValueError("❌ CHANGE SPACE AND API KEYS")
         else:
-            print("✅ Arize client setup done! Now you can start using Arize!")
+            print("✅ Arize client setup done! Now you can start using Arize!")  # noqa: T201
 
     def on_llm_start(
         self, serialized: Dict[str, Any], prompts: List[str], **kwargs: Any
@@ -161,9 +161,9 @@ def on_llm_end(self, response: LLMResult, **kwargs: Any) -> None:
                     environment=Environments.PRODUCTION,
                 )
                 if response_from_arize.status_code == 200:
-                    print("✅ Successfully logged data to Arize!")
+                    print("✅ Successfully logged data to Arize!")  # noqa: T201
                 else:
-                    print(f'❌ Logging failed "{response_from_arize.text}"')
+                    print(f'❌ Logging failed "{response_from_arize.text}"')  # noqa: T201
 
     def on_llm_error(self, error: BaseException, **kwargs: Any) -> None:
         """Do nothing."""

libs/community/langchain_community/callbacks/clearml_callback.py

@@ -509,8 +509,8 @@ def flush_tracker(
                     target_filename=name,
                 )
             except NotImplementedError as e:
-                print("Could not save model.")
-                print(repr(e))
+                print("Could not save model.")  # noqa: T201
+                print(repr(e))  # noqa: T201
                 pass
 
         # Cleanup after adding everything to ClearML

libs/community/langchain_community/callbacks/confident_callback.py

@@ -116,13 +116,13 @@ def on_llm_end(self, response: LLMResult, **kwargs: Any) -> None:
                         output=output,
                         query=query,
                     )
-                    print(f"Answer Relevancy: {result}")
+                    print(f"Answer Relevancy: {result}")  # noqa: T201
                 elif isinstance(metric, UnBiasedMetric):
                     score = metric.measure(output)
-                    print(f"Bias Score: {score}")
+                    print(f"Bias Score: {score}")  # noqa: T201
                 elif isinstance(metric, NonToxicMetric):
                     score = metric.measure(output)
-                    print(f"Toxic Score: {score}")
+                    print(f"Toxic Score: {score}")  # noqa: T201
                 else:
                     raise ValueError(
                         f"""Metric {metric.__name__} is not supported by deepeval 

libs/community/langchain_community/callbacks/infino_callback.py

@@ -86,7 +86,7 @@ def _send_to_infino(
             },
         }
         if self.verbose:
-            print(f"Tracking {key} with Infino: {payload}")
+            print(f"Tracking {key} with Infino: {payload}")  # noqa: T201
 
         # Append to Infino time series only if is_ts is True, otherwise
         # append to Infino log.
@@ -245,7 +245,7 @@ def on_chat_model_start(
                     self._send_to_infino("prompt_tokens", prompt_tokens)
 
         if self.verbose:
-            print(
+            print(  # noqa: T201
                 f"on_chat_model_start: is_chat_openai_model= \
                   {self.is_chat_openai_model}, \
                   chat_openai_model_name={self.chat_openai_model_name}"

libs/community/langchain_community/callbacks/mlflow_callback.py

@@ -646,9 +646,11 @@ def on_retriever_end(
             {
                 "page_content": doc.page_content,
                 "metadata": {
-                    k: str(v)
-                    if not isinstance(v, list)
-                    else ",".join(str(x) for x in v)
+                    k: (
+                        str(v)
+                        if not isinstance(v, list)
+                        else ",".join(str(x) for x in v)
+                    )
                     for k, v in doc.metadata.items()
                 },
             }
@@ -757,15 +759,15 @@ def flush_tracker(self, langchain_asset: Any = None, finish: bool = False) -> No
                         langchain_asset.save_agent(langchain_asset_path)
                         self.mlflg.artifact(langchain_asset_path)
                     except AttributeError:
-                        print("Could not save model.")
+                        print("Could not save model.")  # noqa: T201
                         traceback.print_exc()
                         pass
                     except NotImplementedError:
-                        print("Could not save model.")
+                        print("Could not save model.")  # noqa: T201
                         traceback.print_exc()
                         pass
                 except NotImplementedError:
-                    print("Could not save model.")
+                    print("Could not save model.")  # noqa: T201
                     traceback.print_exc()
                     pass
         if finish:

libs/community/langchain_community/callbacks/wandb_callback.py

@@ -558,8 +558,8 @@ def flush_tracker(
                 model_artifact.add_file(str(langchain_asset_path))
                 model_artifact.metadata = load_json_to_dict(langchain_asset_path)
             except NotImplementedError as e:
-                print("Could not save model.")
-                print(repr(e))
+                print("Could not save model.")  # noqa: T201
+                print(repr(e))  # noqa: T201
                 pass
             self.run.log_artifact(model_artifact)
 
@@ -577,7 +577,9 @@ def flush_tracker(
                 name=name if name else self.name,
                 notes=notes if notes else self.notes,
                 visualize=visualize if visualize else self.visualize,
-                complexity_metrics=complexity_metrics
-                if complexity_metrics
-                else self.complexity_metrics,
+                complexity_metrics=(
+                    complexity_metrics
+                    if complexity_metrics
+                    else self.complexity_metrics
+                ),
             )

libs/community/langchain_community/chat_message_histories/rocksetdb.py

@@ -34,7 +34,7 @@ class RocksetChatMessageHistory(BaseChatMessageHistory):
             history.add_user_message("hi!")
             history.add_ai_message("whats up?")
 
-            print(history.messages)
+            print(history.messages)  # noqa: T201
     """
 
     # You should set these values based on your VI.

libs/community/langchain_community/chat_models/deepinfra.py

@@ -1,4 +1,5 @@
 """deepinfra.com chat models wrapper"""
+
 from __future__ import annotations
 
 import json
@@ -207,7 +208,7 @@ def _completion_with_retry(**kwargs: Any) -> Any:
                 return response
             except Exception as e:
                 # import pdb; pdb.set_trace()
-                print("EX", e)
+                print("EX", e)  # noqa: T201
                 raise
 
         return _completion_with_retry(**kwargs)
@@ -231,7 +232,7 @@ async def _completion_with_retry(**kwargs: Any) -> Any:
                     self._handle_status(response.status, response.text)
                     return await response.json()
             except Exception as e:
-                print("EX", e)
+                print("EX", e)  # noqa: T201
                 raise
 
         return await _completion_with_retry(**kwargs)

libs/community/langchain_community/chat_models/human.py

@@ -1,4 +1,5 @@
 """ChatModel wrapper which returns user input as the response.."""
+
 from io import StringIO
 from typing import Any, Callable, Dict, List, Mapping, Optional
 
@@ -30,9 +31,9 @@ def _display_messages(messages: List[BaseMessage]) -> None:
             width=10000,
             line_break=None,
         )
-        print("\n", "======= start of message =======", "\n\n")
-        print(yaml_string)
-        print("======= end of message =======", "\n\n")
+        print("\n", "======= start of message =======", "\n\n")  # noqa: T201
+        print(yaml_string)  # noqa: T201
+        print("======= end of message =======", "\n\n")  # noqa: T201
 
 
 def _collect_yaml_input(

libs/community/langchain_community/document_loaders/assemblyai.py

@@ -150,7 +150,7 @@ def load(self) -> List[Document]:
                 )
                 transcript_response.raise_for_status()
             except Exception as e:
-                print(f"An error occurred: {e}")
+                print(f"An error occurred: {e}")  # noqa: T201
                 raise
 
             transcript = transcript_response.json()["text"]
@@ -166,7 +166,7 @@ def load(self) -> List[Document]:
                 )
                 paragraphs_response.raise_for_status()
             except Exception as e:
-                print(f"An error occurred: {e}")
+                print(f"An error occurred: {e}")  # noqa: T201
                 raise
 
             paragraphs = paragraphs_response.json()["paragraphs"]
@@ -181,7 +181,7 @@ def load(self) -> List[Document]:
                 )
                 sentences_response.raise_for_status()
             except Exception as e:
-                print(f"An error occurred: {e}")
+                print(f"An error occurred: {e}")  # noqa: T201
                 raise
 
             sentences = sentences_response.json()["sentences"]
@@ -196,7 +196,7 @@ def load(self) -> List[Document]:
                 )
                 srt_response.raise_for_status()
             except Exception as e:
-                print(f"An error occurred: {e}")
+                print(f"An error occurred: {e}")  # noqa: T201
                 raise
 
             srt = srt_response.text
@@ -211,7 +211,7 @@ def load(self) -> List[Document]:
                 )
                 vtt_response.raise_for_status()
             except Exception as e:
-                print(f"An error occurred: {e}")
+                print(f"An error occurred: {e}")  # noqa: T201
                 raise
 
             vtt = vtt_response.text

libs/community/langchain_community/document_loaders/blackboard.py

@@ -109,13 +109,13 @@ def load(self) -> List[Document]:
             documents = []
             for path in relative_paths:
                 url = self.base_url + path
-                print(f"Fetching documents from {url}")
+                print(f"Fetching documents from {url}")  # noqa: T201
                 soup_info = self._scrape(url)
                 with contextlib.suppress(ValueError):
                     documents.extend(self._get_documents(soup_info))
             return documents
         else:
-            print(f"Fetching documents from {self.web_path}")
+            print(f"Fetching documents from {self.web_path}")  # noqa: T201
             soup_info = self.scrape()
             self.folder_path = self._get_folder_path(soup_info)
             return self._get_documents(soup_info)
@@ -295,4 +295,4 @@ def _parse_filename_from_url(self, url: str) -> str:
         load_all_recursively=True,
     )
     documents = loader.load()
-    print(f"Loaded {len(documents)} pages of PDFs from {loader.web_path}")
+    print(f"Loaded {len(documents)} pages of PDFs from {loader.web_path}")  # noqa: T201

libs/community/langchain_community/document_loaders/blob_loaders/file_system.py

@@ -1,4 +1,5 @@
 """Use to load blobs from the local file system."""
+
 from pathlib import Path
 from typing import Callable, Iterable, Iterator, Optional, Sequence, TypeVar, Union
 
@@ -46,7 +47,7 @@ class FileSystemBlobLoader(BlobLoader):
         from langchain_community.document_loaders.blob_loaders import FileSystemBlobLoader
         loader = FileSystemBlobLoader("/path/to/directory")
         for blob in loader.yield_blobs():
-            print(blob)
+            print(blob)  # noqa: T201
     """  # noqa: E501
 
     def __init__(

libs/community/langchain_community/document_loaders/confluence.py

@@ -564,7 +564,7 @@ def process_attachment(
                 texts.append(text)
             except requests.HTTPError as e:
                 if e.response.status_code == 404:
-                    print(f"Attachment not found at {absolute_url}")
+                    print(f"Attachment not found at {absolute_url}")  # noqa: T201
                     continue
                 else:
                     raise

libs/community/langchain_community/document_loaders/dropbox.py

@@ -121,7 +121,7 @@ def _load_file_from_path(self, file_path: str) -> Optional[Document]:
             file_extension = os.path.splitext(file_path)[1].lower()
 
             if file_extension == ".pdf":
-                print(f"File {file_path} type detected as .pdf")
+                print(f"File {file_path} type detected as .pdf")  # noqa: T201
                 from langchain_community.document_loaders import UnstructuredPDFLoader
 
                 # Download it to a temporary file.
@@ -136,10 +136,10 @@ def _load_file_from_path(self, file_path: str) -> Optional[Document]:
                     if docs:
                         return docs[0]
                 except Exception as pdf_ex:
-                    print(f"Error while trying to parse PDF {file_path}: {pdf_ex}")
+                    print(f"Error while trying to parse PDF {file_path}: {pdf_ex}")  # noqa: T201
                     return None
             else:
-                print(
+                print(  # noqa: T201
                     f"File {file_path} could not be decoded as pdf or text. Skipping."
                 )