Partially automated comment flagging on Stack Overflow.

comment_flagger.py

import requests
import re
import pandas as pd
import html 
import time
import sys

# https://stackapps.com/q/8364/

client_id = '15705'
client_secret = 'iZvNzsXAaSOic6qT*mJMKQ(('
key = 'BTUX)fAFTdhKKhRuF5IKFA(('

def response_has_error(response):
	return any('error' in k for k in response.keys())

access_token = ###YOUR ACCESS TOKEN###  
df = pd.read_csv('comments.csv')

options_url = ('https://api.stackexchange.com/2.2/comments/{}/flags/options?'
			   'key={}&access_token={}&site=stackoverflow')

flag_url = 'https://api.stackexchange.com/2.2/comments/{}/flags/add'

MAX_FLAGS = int(sys.argv[1]) if len(sys.argv) > 1 else 95
count = 0
flagged = set()
for t, c in zip(df['Text'], df['Comment Link']):
	response = requests.get(options_url.format(c, key, access_token)).json()
	if response_has_error(response):
		flagged.add(c)
		continue

	for item in response['items']:
		if item['title'] == "It's no longer needed.":
			option_id = item['option_id']

	response = requests.post(
		flag_url.format(c), 
		data={
			'key': key, 
			'access_token': access_token, 
			'option_id': option_id, 
			'site': 'stackoverflow'}).json()
	
	if not response_has_error(response):
		count += 1
		flagged.add(c)
		print(f'Successfully flagged #{count:>3}: {t!r} (CL: {c:>8})')
		if count == MAX_FLAGS:
			break

		time.sleep(5)

print(f'Total flagged: {count}')
df[~df['Comment Link'].isin(flagged)].to_csv('comments.csv', index=False)