It organizes the code

src/cli.py

@@ -1,79 +1,17 @@
 #!/usr/bin/env python3
-"""PDF to Text converter with multi-threading support.
+"""PDF to Text converter CLI.
 
-This module provides functionality to convert PDF files to text using OCR technology
-with support for multi-threading to improve performance.
+This module provides the command-line interface for converting PDF files to text
+using OCR technology.
 """
 
 import argparse
 import glob
 import os
-from concurrent.futures import ThreadPoolExecutor
 
 import argcomplete
-import pytesseract
-from pdf2image import convert_from_path
-from PIL import Image
 
-
-def process_page_chunk(pages: list[Image.Image]) -> str:
-    """Process a chunk of pages and return combined text.
-
-    Args:
-        pages: List of PIL Image objects representing PDF pages.
-
-    Returns:
-        str: Combined text extracted from all pages in the chunk.
-    """
-    chunk_text = ""
-    for page in pages:
-        chunk_text += pytesseract.image_to_string(page)
-    return chunk_text
-
-
-def chunk_list(lst: list, chunk_size: int) -> list[list]:
-    """Split a list into chunks of specified size.
-
-    Args:
-        lst: Input list to be chunked.
-        chunk_size: Size of each chunk.
-
-    Returns:
-        List[list]: List of chunks.
-    """
-    return [lst[i : i + chunk_size] for i in range(0, len(lst), chunk_size)]
-
-
-def pdf_to_text(
-    pdf_file: str, output_file: str, max_threads: int = 4, chunk_size: int = 3
-) -> None:
-    """Convert PDF file to text using OCR with multi-threading.
-
-    Args:
-        pdf_file: Path to the input PDF file.
-        output_file: Path where the output text will be saved.
-        max_threads: Maximum number of threads to use for processing.
-        chunk_size: Number of pages to process per thread.
-    """
-    pages = convert_from_path(pdf_file)
-    page_chunks = chunk_list(pages, chunk_size)
-
-    text_chunks = []
-    with ThreadPoolExecutor(max_workers=max_threads) as executor:
-        future_to_chunk = {
-            executor.submit(process_page_chunk, chunk): i
-            for i, chunk in enumerate(page_chunks)
-        }
-
-        text_chunks = [""] * len(page_chunks)
-        for future in future_to_chunk:
-            chunk_idx = future_to_chunk[future]
-            text_chunks[chunk_idx] = future.result()
-
-    final_text = "".join(text_chunks)
-
-    with open(output_file, "w", encoding="utf-8") as f:
-        f.write(final_text)
+from src.pdf2txt import pdf_to_text
 
 
 def pdf_completer(prefix: str, parsed_args: argparse.Namespace, **kwargs) -> list[str]:

src/pdf2txt.py

@@ -0,0 +1,71 @@
+"""Core functionality for PDF to text conversion with multi-threading support.
+
+This module provides the core functionality to convert PDF files to text using OCR
+technology with support for multi-threading to improve performance.
+"""
+
+import pytesseract
+from pdf2image import convert_from_path
+from PIL import Image
+
+
+def process_page_chunk(pages: list[Image.Image]) -> str:
+    """Process a chunk of pages and return combined text.
+
+    Args:
+        pages: List of PIL Image objects representing PDF pages.
+
+    Returns:
+        str: Combined text extracted from all pages in the chunk.
+    """
+    chunk_text = ""
+    for page in pages:
+        chunk_text += pytesseract.image_to_string(page)
+    return chunk_text
+
+
+def chunk_list(lst: list, chunk_size: int) -> list[list]:
+    """Split a list into chunks of specified size.
+
+    Args:
+        lst: Input list to be chunked.
+        chunk_size: Size of each chunk.
+
+    Returns:
+        List[list]: List of chunks.
+    """
+    return [lst[i : i + chunk_size] for i in range(0, len(lst), chunk_size)]
+
+
+def pdf_to_text(
+    pdf_file: str, output_file: str, max_threads: int = 4, chunk_size: int = 3
+) -> None:
+    """Convert PDF file to text using OCR with multi-threading.
+
+    Args:
+        pdf_file: Path to the input PDF file.
+        output_file: Path where the output text will be saved.
+        max_threads: Maximum number of threads to use for processing.
+        chunk_size: Number of pages to process per thread.
+    """
+    from concurrent.futures import ThreadPoolExecutor
+
+    pages = convert_from_path(pdf_file)
+    page_chunks = chunk_list(pages, chunk_size)
+
+    text_chunks = []
+    with ThreadPoolExecutor(max_workers=max_threads) as executor:
+        future_to_chunk = {
+            executor.submit(process_page_chunk, chunk): i
+            for i, chunk in enumerate(page_chunks)
+        }
+
+        text_chunks = [""] * len(page_chunks)
+        for future in future_to_chunk:
+            chunk_idx = future_to_chunk[future]
+            text_chunks[chunk_idx] = future.result()
+
+    final_text = "".join(text_chunks)
+
+    with open(output_file, "w", encoding="utf-8") as f:
+        f.write(final_text)