Natsamrat Marathi Natak 23.pdf (2026)
import pdfplumber def extract_features(pdf_path): with pdfplumber.open(pdf_path) as pdf: text = "".join([page.extract_text() or "" for page in pdf.pages])
"file_name": "Natsamrat Marathi Natak 23.pdf", "title": "Natsamrat", "language": "Marathi", "author": "V.V. Shirwadkar (Kusumagraj)", "genre": "Tragedy / Drama", "act_scene": "Act 2, Scene 3", "key_dialogues": [ "नाटक संपले की नट संपतो...", "ही माझी मुलगी मला हाकलून देतेय?" ], "characters_present": ["Natsamrat", "Kaveri", "Bhai", "Nama"], "themes": ["Aging artist", "Family neglect", "Pride and fall"] Natsamrat Marathi Natak 23.pdf
It sounds like you want to create or extract a good feature (likely a data feature, preview, metadata summary, or a descriptive highlight) from the file – which is probably a PDF of the famous Marathi play Natsamrat (by V.V. Shirwadkar, popularly known as Kusumagraj). Since you didn’t specify the technical context (e
Since you didn’t specify the technical context (e.g., Python script, ML dataset, search index, or content summary), I’ll provide the : 1. Feature for a Search / Document Retrieval System If you’re building a search index, a good feature for this PDF would be: or content summary)
If you need to programmatically extract a feature (e.g., page count, text length, presence of certain dialogues):
features = "page_count": len(pdf.pages), "total_characters": len(text), "contains_natsamrat_dialogue": "नटसम्राट" in text, "contains_act2": "अंक दुसरा" in text or "Act 2" in text, "approx_lines": len(text.split("\n")), "file_name": pdf_path.split("/")[-1]
return features print(extract_features("Natsamrat Marathi Natak 23.pdf")) 3. Feature for a Machine Learning Dataset (e.g., play classification) If you’re building a dataset of Marathi plays, a good feature row would be:
