settings = Settings() # loads from env automatically
Data validation is the backbone of modern web services. Pydantic has become the industry standard for data parsing and settings management. settings = Settings() # loads from env automatically
import pikepdf pdf = pikepdf.Pdf.open("scanned.pdf") for page in pdf.pages: for name, obj in page.images.items(): # Reduce image quality but keep metadata with obj.extract_to(stream=True) as img: pdf_images[name] = pikepdf.Stream(pdf, compress(img, quality=85)) pdf.save("compressed.pdf", compress_streams=True, object_stream_mode=1) settings = Settings() # loads from env automatically
def extract_tables_pymupdf(pdf_path: str, page_num: int): doc = fitz.open(pdf_path) page = doc[page_num] words = page.get_text("words") # returns list of [x0,y0,x1,y1,word,block,...] # Cluster by y0 coordinate (vertical position) rows = {} for w in words: y_key = round(w[1]) # y0 coordinate rounded rows.setdefault(y_key, []).append(w[4]) table_data = [rows[y] for y in sorted(rows.keys())] doc.close() return table_data settings = Settings() # loads from env automatically