Comply with ruff's PTH rule

nerval/evaluate.py

 import logging
-import os
 from csv import reader
 from pathlib import Path
 from typing import List
@@ -343,14 +342,14 @@ def run(annotation: Path, prediction: Path, threshold: int, verbose: bool) -> di
     return scores
 
 
-def run_multiple(file_csv, folder, threshold, verbose):
+def run_multiple(file_csv: Path, folder: Path, threshold: int, verbose: bool):
     """Run the program for multiple files (correlation indicated in the csv file)"""
     # Read the csv in a list
-    with open(file_csv) as read_obj:
+    with file_csv.open() as read_obj:
         csv_reader = reader(read_obj)
         list_cor = list(csv_reader)
 
-    if os.path.isdir(folder):
+    if folder.is_dir():
         list_bio_file = list(folder.rglob("*.bio"))
 
         count = 0
@@ -362,10 +361,10 @@ def run_multiple(file_csv, folder, threshold, verbose):
             predict = None
 
             for file in list_bio_file:
-                if row[0] == os.path.basename(file):
+                if row[0] == file.name:
                     annot = file
             for file in list_bio_file:
-                if row[1] == os.path.basename(file):
+                if row[1] == file.name:
                     predict = file
 
             if annot and predict:

pyproject.toml

@@ -33,4 +33,6 @@ select = [
     "Q",
     # flake8-unused-arguments
     "ARG",
+    # flake8-use-pathlib
+    "PTH",
 ]

setup.py

@@ -27,7 +27,7 @@ def parse_requirements():
 
 setup(
     name="nerval",
-    version=open("VERSION").read(),
+    version=Path("VERSION").read_text(),
     description="Tool to evaluate NER on noisy text.",
     author="Teklia",
     author_email="contact@teklia.com",