import csv import json import os import praw import random import re import sys env = json.load(open('.env', 'r')) #print(env) reddit = praw.Reddit( client_id=env["app_id"], client_secret=env["secret"], user_agent=env["user_agent"] ) def main(post_id): post = reddit.submission(id=post_id) post.comments.replace_more(limit=0) sorted_comments = sorted(post.comments, key=lambda c: c.score, reverse=True) if post.link_flair_text is None: raise Exception("Must be a gender or non-binary fashion flair post") elif "Men's" in post.link_flair_text: gender = "M" elif "Women's" in post.link_flair_text or "Ladies'" in post.link_flair_text: gender = "F" elif "Non Binary" in post.link_flair_text: gender = "X" else: raise Exception("Must be a gender or non-binary fashion flair post") data = { "post_id": post_id, "gender_flair": gender, "title": post.title, "selftext": post.selftext, "images": [], } image_urls = [] if post.is_gallery: metadata = post.media_metadata for item in post.gallery_data['items']: url = metadata[item['media_id']]['s']['u'].replace("&", "&") image_urls.append(url) else: raise Exception("Need multiple images for there to be a multimodal eval question") lead_choices = {} firstChoice = None secondChoice = None for c in sorted_comments: text = c.body.strip().lower().replace('first', '1st').replace('second', '2nd').replace('third', '3rd').replace('fourth', '4th').replace('fifth', '5th') text = text.replace('last', str(len(image_urls))) selections = re.findall(r'\d', text) if len(selections) == 0: print("Skipped comment without digit") continue elif len(set(selections)) > 1: print(text) raise Exception("Encountered a top comment with multiple digits, complex") selection = int(selections[0]) if selection not in lead_choices: print(f"Found comment with {c.score} votes: {text}") lead_choices[selection] = c.score data["images"].append(image_urls[selection - 1]) if firstChoice is None: firstChoice = selection elif secondChoice is None: secondChoice = selection break else: print(f"Found repeat comment with {c.score} votes") lead_choices[selection] += c.score if lead_choices[selection] > 100: print("Overwhelming support") if selection == 1: secondChoice = 2 else: secondChoice = selection - 1 lead_choices[secondChoice] = 1 data["images"].append(image_urls[secondChoice - 1]) break if len(lead_choices.keys()) != 2: raise Exception("Did not find two distinct comments with single outfit suggestions") data["firstChoiceVotes"] = lead_choices[firstChoice] data["secondChoice"] = lead_choices[secondChoice] if len(image_urls) > 2: print("We are assuming that there is one image of each outfit") used_set = set(image_urls) remaining = [img for img in used_set if img not in data["images"]] extra_images = random.sample(remaining, min(len(remaining), 2)) data["images"] += extra_images # print(json.dumps(data, indent=2)) fieldnames = [ "post_id", "gender_flair", "title", "selftext", "images", "firstChoiceVotes", "secondChoice" ] filename = "dataset.csv" file_exists = os.path.isfile(filename) with open(filename, mode="a", newline="", encoding="utf-8") as f: writer = csv.DictWriter(f, fieldnames=fieldnames) if not file_exists: writer.writeheader() row = data.copy() row["images"] = ",".join(data["images"]) writer.writerow(row) if __name__ == "__main__": if len(sys.argv) != 2: print("Usage: python outfit_scraper.py ") sys.exit(1) main(sys.argv[1])