""" Utility functions for grouping per-page results into document-level results. This module provides common functionality for: - Extracting page numbers from image filenames - Converting page-level keys to document-level keys - Grouping page-level elements into document-level structure Usage: from doc_grouping import group_pages_to_documents # Group page-level results into document-level doc_results = group_pages_to_documents( page_results, file_ext_mapping={"jpg": "pdf"}, ) """ import re from typing import Dict, List, Optional, Tuple def extract_page_number(image_key: str) -> int: """ Extract page number from image key. Supports formats like: - 'document_page0001.jpg' -> 1 - 'document_page0042.pdf' -> 42 Args: image_key: Image filename with page suffix Returns: Page number (1-based), or 1 if no page number found """ match = re.search(r"_page(\d{4})\.", image_key) if match: return int(match.group(1)) return 1 def to_doc_key(image_key: str) -> str: """ Convert page image key to document key by removing the page suffix. Example: 'mt_2020-06-25T04-07-00Z_s100j0q8_39-43_page0001.jpg' -> 'mt_2020-06-25T04-07-00Z_s100j0q8_39-43.jpg' Args: image_key: Page-level image filename Returns: Document-level filename (without page suffix) """ return re.sub(r"_page\d{4}(?=\.)", "", image_key) def replace_ext(filename: str, file_ext_mapping: Dict[str, str]) -> str: """ Replace file extension according to mapping. Args: filename: Original filename file_ext_mapping: Dict mapping source extensions to destination extensions e.g., {"jpg": "pdf", "jpeg": "pdf"} Returns: Filename with replaced extension """ if not file_ext_mapping: return filename src_ext = filename.split(".")[-1] dst_ext = file_ext_mapping.get(src_ext, src_ext) return filename[: -(len(src_ext))] + dst_ext def parse_ext_mapping(mapping_str: str) -> Dict[str, str]: """ Parse file extension mapping from CLI string format. Supports two formats: - Colon format: "jpg:pdf" (single mapping) - Arrow format: "jpg->pdf,jpeg->pdf" (multiple mappings) Args: mapping_str: String in format "src:dst" or "src1->dst1,src2->dst2" Returns: Dict mapping source extensions to destination extensions Raises: ValueError: If mapping format is invalid """ file_ext_mapping = {} if not mapping_str: return file_ext_mapping # Try colon format first (single mapping) if ":" in mapping_str and "->" not in mapping_str: parts = mapping_str.split(":") if len(parts) == 2: src, dst = parts[0].strip(), parts[1].strip() if src and dst: return {src: dst} # Try arrow format (multiple mappings) for pair in mapping_str.split(","): pair = pair.strip() if "->" in pair: src, dst = pair.split("->", 1) src = src.strip() dst = dst.strip() if src and dst: file_ext_mapping[src] = dst elif ":" in pair: src, dst = pair.split(":", 1) src = src.strip() dst = dst.strip() if src and dst: file_ext_mapping[src] = dst if not file_ext_mapping and mapping_str: raise ValueError( f"Invalid mapping format: '{mapping_str}'. " "Use 'src:dst' or 'src1->dst1,src2->dst2' format." ) return file_ext_mapping def group_pages_to_documents( page_data: Dict[str, Dict], file_ext_mapping: Optional[Dict[str, str]] = None, elements_key: str = "elements", include_merged_tables: bool = True, ) -> Dict[str, Dict]: """ Group page-level results into document-level results. Takes a dictionary of page-level results (keyed by page image filename) and aggregates them into document-level results. Args: page_data: Dict mapping page filenames to their data. Each page data should have an 'elements' list. Example: {"doc_page0001.jpg": {"elements": [...]}, ...} file_ext_mapping: Optional dict mapping source extensions to destination. e.g., {"jpg": "pdf"} to output "doc.pdf" instead of "doc.jpg" elements_key: Key name for the elements list in each page (default: "elements") include_merged_tables: Whether to include empty "merged_tables" list (default: True) Returns: Dict mapping document filenames to aggregated data. Example: {"doc.pdf": {"elements": [...], "merged_tables": []}} """ if file_ext_mapping is None: file_ext_mapping = {} result: Dict[str, Dict] = {} id_counters: Dict[str, int] = {} for page_key, page_content in page_data.items(): # Get document key and page number doc_key_raw = to_doc_key(page_key) doc_key = replace_ext(doc_key_raw, file_ext_mapping) page_number = extract_page_number(page_key) # Initialize document entry if not exists if doc_key not in result: result[doc_key] = {elements_key: []} if include_merged_tables: result[doc_key]["merged_tables"] = [] id_counters[doc_key] = 0 # Get elements from page data elements = page_content.get(elements_key, []) # Add each element with updated id and page number for elem in elements: # Create a copy to avoid modifying original new_elem = elem.copy() if "content" in elem: new_elem["content"] = elem["content"].copy() new_elem["id"] = id_counters[doc_key] new_elem["page"] = page_number result[doc_key][elements_key].append(new_elem) id_counters[doc_key] += 1 return result def is_multi_page_dataset(page_keys: List[str]) -> bool: """ Check if the dataset contains multi-page documents. Looks for page suffixes like '_page0001' in the filenames. Args: page_keys: List of page-level filenames Returns: True if any filename has a page suffix """ page_pattern = re.compile(r"_page\d{4}\.") return any(page_pattern.search(key) for key in page_keys)