add ruff

Author: EYH0602

pyproject.toml

@@ -85,3 +85,6 @@ warn_redundant_casts = true
 warn_unreachable = true
 warn_unused_ignores = false
 plugins = ["returns.contrib.mypy.returns_plugin"]
+
+[tool.ruff]
+exclude = ["tests/", "plots/"]

scripts/preprocess_benchmark.py

@@ -2,11 +2,12 @@
 
 import json
 import os
-import markdown_to_json
+
 import fire
-from tfbench.common import md2task, BenchmarkTask
 from funcy import lmap
 
+from tfbench.common import md2task, BenchmarkTask
+
 
 def main(input_raw_benchmark_path: str = "benchmark", output_path: str = "tfb.json"):
 

scripts/result_token_stat.py

@@ -1,11 +1,11 @@
+import json
+
 import tiktoken
 import fire
 from dacite import from_dict
-import json
-from funcy_chain import Chain
 import pandas
 
-from tfbench.common import BenchmarkTask, get_prompt
+from tfbench.common import BenchmarkTask
 
 
 def main(input_file="tfb.json"):
@@ -20,5 +20,6 @@ def main(input_file="tfb.json"):
     print(f"min: {df.token_count.min()}")
     print(f"avg: {df.token_count.mean()}")
 
+
 if __name__ == "__main__":
     fire.Fire(main)

src/tfbench/add_dependency.py

@@ -52,8 +52,8 @@ def _is_input(code: str, call: str) -> bool:
     """check if a function call is an input to the task"""
     inputs: list[list[str]] = (
         Chain(code.splitlines())
-        .filter(lambda l: "=" in l)
-        .map(lambda l: l.split("=")[0])
+        .filter(lambda line: "=" in line)
+        .map(lambda line: line.split("=")[0])
         .map(str.strip)
         .map(str.split)
         .value

src/tfbench/dataset.py

@@ -102,7 +102,7 @@ def main(
 ):
     """script to extract benchmark tasks from Haskell repositories"""
     with open(input_repo_list_path) as fp:
-        repo_id_list = [l.strip() for l in fp.readlines()]
+        repo_id_list = [line.strip() for line in fp.readlines()]
 
     logging.info(f"Loaded {len(repo_id_list)} repos to be processed")
     num_func = 0

src/tfbench/experiment.py

@@ -3,6 +3,7 @@
 """
 
 from typing import Callable
+import logging
 
 from openai import OpenAI
 from anthropic import Anthropic, InternalServerError
@@ -133,7 +134,8 @@ def generate_type_signature(prompt: str) -> str | None:
             thinking, answer = message.content
             text = answer.text  # type: ignore
             return text if isinstance(text, str) else None
-        except:
+        except Exception as e:
+            logging.error(f"Error processing message content: {e}")
             return None
 
     return generate_type_signature