mirror of
https://github.com/zoffline/zwift-offline.git
synced 2026-08-02 08:57:57 -07:00
164 lines
13 KiB
Python
Executable File
164 lines
13 KiB
Python
Executable File
#! /usr/bin/env python
|
||
|
||
# Use this script to populate bot.txt with names from https://www.procyclingstats.com
|
||
# pip install beautifulsoup4 country-converter fuzzywuzzy
|
||
# scripts/get_pro_names.py -h
|
||
|
||
|
||
from bs4 import BeautifulSoup
|
||
import urllib.request
|
||
import json
|
||
import country_converter as coco
|
||
import argparse
|
||
import getpass
|
||
import os
|
||
import sys
|
||
import xml.etree.ElementTree as ET
|
||
from fuzzywuzzy import process
|
||
from fuzzywuzzy import fuzz
|
||
|
||
base_url = "https://www.procyclingstats.com/rankings.php?filter=Filter"
|
||
cc = coco.CountryConverter()
|
||
|
||
teams = {
|
||
'UAE Team Emirates': {'jersey_name': 'UAE', 'jersey_signature': 1751349769, 'bike_name': 'Colnago Colnago V3RS', 'bike_signature': 3628259811, 'front_wheel_name': 'Enve G23', 'front_wheel_signature': 190867464, 'rear_wheel_name': 'Enve SES 7.8', 'rear_wheel_signature': 886534142},
|
||
'Soudal - Quick Step': {'jersey_name': 'Deceuninck-Quick-Step', 'jersey_signature': 2906189156, 'bike_name': 'Specialized Tarmac SL7', 'bike_signature': 935373427, 'front_wheel_name': 'Roval Rapide CLX', 'front_wheel_signature': 2181416413, 'rear_wheel_name': 'Roval Rapide CLX', 'rear_wheel_signature': 3548735686},
|
||
'Jumbo-Visma': {'jersey_name': 'Team Jumbo-Visma Men 2023', 'jersey_signature': 88214615, 'bike_name': 'Cervelo R5', 'bike_signature': 106535518, 'front_wheel_name': 'Reserve Reserve 25 GR', 'front_wheel_signature': 635220876, 'rear_wheel_name': 'Reserve Reserve 25 GR', 'rear_wheel_signature': 1842698274},
|
||
'Alpecin-Deceuninck': {'jersey_name': 'Deceuninck-Quick-Step', 'jersey_signature': 2906189156, 'bike_name': 'Canyon Aeroad 2015', 'bike_signature': 1520594784, 'front_wheel_name': 'Shimano C50', 'front_wheel_signature': 1742598126, 'rear_wheel_name': 'Shimano C50', 'rear_wheel_signature': 3725678091},
|
||
'Trek - Segafredo': {'jersey_name': 'Trek-Segafredo Women', 'jersey_signature': 1154847422, 'bike_name': 'Trek Madone', 'bike_signature': 4129467727, 'front_wheel_name': 'Bontrager Aeolus5', 'front_wheel_signature': 702195190, 'rear_wheel_name': 'Bontrager Aeolus5', 'rear_wheel_signature': 3594144634},
|
||
'Movistar Team': {'jersey_name': 'Movistar Team', 'jersey_signature': 1842355135, 'bike_name': 'Canyon Aeroad 2015', 'bike_signature': 1520594784, 'front_wheel_name': 'Zipp 202', 'front_wheel_signature': 442607221, 'rear_wheel_name': 'Zipp 808', 'rear_wheel_signature': 214800767},
|
||
'Lotto Dstny': {'jersey_name': 'Lotto', 'jersey_signature': 4130579852},
|
||
'EF Education-EasyPost': {'jersey_name': 'EF Education First', 'jersey_signature': 2349035663, 'bike_name': 'Cannondale System Six', 'bike_signature': 2005280203, 'front_wheel_name': 'HED HED Vanquish RC6 Pro', 'front_wheel_signature': 1791179228, 'rear_wheel_name': 'HED HED Vanquish RC6 Pro', 'rear_wheel_signature': 2913819265},
|
||
'INEOS Grenadiers': {'jersey_name': 'INEOS Grenadiers 2022 Pro', 'jersey_signature': 542207259, 'bike_name': 'Pinarello Dogma F', 'bike_signature': 4208139356, 'front_wheel_name': 'Zwift 50mm Carbon', 'front_wheel_signature': 2060527008, 'rear_wheel_name': 'Zwift 50mm Carbon', 'rear_wheel_signature': 1848192392},
|
||
'Groupama - FDJ': {'jersey_name': 'Groupama FDJ 2023', 'jersey_signature': 2814449542, 'bike_name': 'Specialized Amira S-Works', 'bike_signature': 2662728556, 'front_wheel_name': 'Shimano C50', 'front_wheel_signature': 1742598126, 'rear_wheel_name': 'Shimano C50', 'rear_wheel_signature': 3725678091},
|
||
'Bahrain - Victorious': {'jersey_name': 'Bahrain McLaren', 'jersey_signature': 2155858980, 'bike_name': 'Merida Scultura', 'bike_signature': 3033010663, 'front_wheel_name': 'Zwift 50mm Carbon', 'front_wheel_signature': 2060527008, 'rear_wheel_name': 'Zwift 50mm Carbon', 'rear_wheel_signature': 1848192392},
|
||
'Team DSM': {'jersey_name': 'Team ODZ', 'jersey_signature': 2695025247, 'bike_name': 'Scott Foil', 'bike_signature': 1315158373, 'front_wheel_name': 'Shimano C50', 'front_wheel_signature': 1742598126, 'rear_wheel_name': 'Shimano C50', 'rear_wheel_signature': 3725678091},
|
||
'Team Jayco AlUla': {'jersey_name': 'Team 3R', 'jersey_signature': 493134166, 'bike_name': 'Giant Propel Advanced SL Disc', 'bike_signature': 103914490, 'front_wheel_name': 'Cadex CADEX 42', 'front_wheel_signature': 1497226614, 'rear_wheel_name': 'Cadex CADEX 42', 'rear_wheel_signature': 1347687916},
|
||
'Uno-X Pro Cycling Team': {'jersey_name': 'NTT Pro Cycling Team', 'jersey_signature': 3612223524},
|
||
'Cofidis': {'jersey_name': 'Cofidis 2018', 'jersey_signature': 927604154, 'bike_name': 'Cervelo R5', 'bike_signature': 106535518, 'front_wheel_name': 'Shimano C60', 'front_wheel_signature': 272842014, 'rear_wheel_name': 'Shimano C40', 'rear_wheel_signature': 530549195},
|
||
'Intermarché - Circus - Wanty': {'jersey_name': 'Intermarché–Wanty–Gobert Matériaux', 'jersey_signature': 88121645, 'bike_name': 'Cube Cube Litening', 'bike_signature': 1767548815, 'front_wheel_name': 'Enve SES 2.2', 'front_wheel_signature': 1881778071, 'rear_wheel_name': 'Zwift Handcycle', 'rear_wheel_signature': 2602078812},
|
||
'BORA - hansgrohe': {'jersey_name': 'Bora-Hansgrohe', 'jersey_signature': 321508751, 'bike_name': 'Specialized Tarmac SL7', 'bike_signature': 935373427, 'front_wheel_name': 'Roval Rapide CLX', 'front_wheel_signature': 2181416413, 'rear_wheel_name': 'Roval Rapide CLX', 'rear_wheel_signature': 3548735686},
|
||
'Team Medellín - EPM': {'jersey_name': 'Team 3R', 'jersey_signature': 493134166},
|
||
'Team Arkéa Samsic': {'jersey_name': 'Arkea-Samsic', 'jersey_signature': 598687666, 'bike_name': 'Trek Madone', 'bike_signature': 4129467727, 'front_wheel_name': 'Lightweight Lightweight Meilenstein', 'front_wheel_signature': 2282170788, 'rear_wheel_name': 'Lightweight Lightweight Meilenstein', 'rear_wheel_signature': 3659884507},
|
||
'AG2R Citroën Team': {'jersey_name': 'Team 3R', 'jersey_signature': 493134166, 'bike_name': 'BMC BmcTeamMachine2022', 'bike_signature': 3868468027, 'front_wheel_name': 'Campagnolo Bora Ultra 35', 'front_wheel_signature': 1053884173, 'rear_wheel_name': 'Campagnolo Bora Ultra 35', 'rear_wheel_signature': 1614586487},
|
||
'Astana Qazaqstan Team': {'jersey_name': 'ASTANA PRO TEAM', 'jersey_signature': 1969335676, 'bike_name': 'Giant GiantRevolt2022', 'bike_signature': 2360271970, 'front_wheel_name': 'Shimano C60', 'front_wheel_signature': 272842014, 'rear_wheel_name': 'Shimano C40', 'rear_wheel_signature': 530549195},
|
||
'Israel - Premier Tech': {'jersey_name': 'Israel Premier-Tech', 'jersey_signature': 552170906},
|
||
'TotalEnergies': {'jersey_name': 'Stages Kit', 'jersey_signature': 751130480},
|
||
'Team SD Worx': {'jersey_name': 'Team SD Worx', 'jersey_signature': 1494272741},
|
||
'UAE Team ADQ': {'jersey_name': 'UAE', 'jersey_signature': 1751349769},
|
||
'FDJ - SUEZ': {'jersey_name': 'FDJ Suez 2023', 'jersey_signature': 3360845221},
|
||
'Canyon//SRAM Racing': {'jersey_name': 'SRAM', 'jersey_signature': 2500137555},
|
||
'AG Insurance - Soudal Quick-Step': {'jersey_name': 'Lotto-Soudal', 'jersey_signature': 3103938066},
|
||
'Human Powered Health': {'jersey_name': 'Human Powered Health Fan', 'jersey_signature': 854534852},
|
||
'Team Jumbo-Visma': {'jersey_name': 'Team Jumbo-Visma Men 2023', 'jersey_signature': 88214615},
|
||
'Liv Racing TeqFind': {'jersey_name': 'Liv Racing 2019', 'jersey_signature': 3932519699},
|
||
'Israel Premier Tech Roland': {'jersey_name': 'Israel Premier-Tech', 'jersey_signature': 552170906},
|
||
'EF Education-TIBCO-SVB': {'jersey_name': 'Team EF Education-TIBCO-SVB', 'jersey_signature': 2795352821},
|
||
'Fenix-Deceuninck': {'jersey_name': 'Deceuninck-Quick-Step', 'jersey_signature': 2906189156},
|
||
'CERATIZIT-WNT Pro Cycling': {'jersey_name': 'Ceratizit-WNT', 'jersey_signature': 97975537},
|
||
'St Michel - Mavic - Auber93 WE': {'jersey_name': 'South Africa Elite', 'jersey_signature': 3305515323},
|
||
'Lifeplus Wahoo': {'jersey_name': 'Wahoo', 'jersey_signature': 3553917933},
|
||
'Cofidis Women Team': {'jersey_name': 'Cofidis', 'jersey_signature': 4191972189},
|
||
'Arkéa Pro Cycling Team': {'jersey_name': 'NTT Pro Cycling Team', 'jersey_signature': 3612223524},
|
||
'MAT Atom Deweloper Wrocław': {'jersey_name': 'Race Leader - Rosa', 'jersey_signature': 1295920261},
|
||
'Top Girls Fassa Bortolo': {'jersey_name': 'Clash Of Clubs Blue', 'jersey_signature': 520081294}
|
||
}
|
||
|
||
def get_pros(url, male, get_jersey, get_equipment):
|
||
data = []
|
||
|
||
req = urllib.request.Request(url, headers={'User-Agent': 'Mozilla/5.0'})
|
||
site = urllib.request.urlopen(req).read()
|
||
soup = BeautifulSoup(site)
|
||
|
||
for td in soup.find_all('td'):
|
||
if td.span and td.contents[0]:
|
||
tmp = {}
|
||
if "flag" in repr(td.contents[0]):
|
||
code = td.span.get_attribute_list("class")[1]
|
||
tmp['country_code'] = cc.convert(names=code, to='ISOnumeric')
|
||
tmp['is_male'] = male
|
||
if td.a:
|
||
tmp['first_name'] = (td.a.contents[1].strip())
|
||
tmp['last_name'] = (td.a.span.contents[0])
|
||
if td.a and td.contents[0]:
|
||
if "cu600" in repr(td) and td.a.contents:
|
||
if 'first_name' in tmp:
|
||
if get_jersey:
|
||
if td.a.contents[0] in teams:
|
||
tmp['jersey'] = teams[td.a.contents[0]]['jersey_signature']
|
||
else:
|
||
best_match = process.extractOne(td.a.contents[0], jerseys.keys(), scorer=fuzz.token_set_ratio)
|
||
print ("%s %s : %s - %s" % (tmp['first_name'],tmp['last_name'],td.a.contents[0], best_match))
|
||
tmp['jersey'] = jerseys[best_match[0]]
|
||
if get_equipment:
|
||
if td.a.contents[0] in teams:
|
||
team = teams[td.a.contents[0]]
|
||
if 'bike_signature' in team:
|
||
tmp['bike_frame'] = team['bike_signature']
|
||
if 'front_wheel_signature' in team:
|
||
tmp['bike_wheel_front'] = team['front_wheel_signature']
|
||
if 'rear_wheel_signature' in team:
|
||
tmp['bike_wheel_rear'] = team['rear_wheel_signature']
|
||
|
||
data.append(tmp)
|
||
|
||
return data
|
||
|
||
tree = ET.parse('../cdn/gameassets/GameDictionary.xml')
|
||
root = tree.getroot()
|
||
jerseys = {}
|
||
for x in root.findall("./JERSEYS/JERSEY"):
|
||
jerseys[x.get('name')] = int(x.get('signature'))
|
||
|
||
def main(argv):
|
||
global args
|
||
|
||
parser = argparse.ArgumentParser(description='Populate Bot names with professional riders')
|
||
parser.add_argument('-n', '--nation', help='Riders from specified nation only', default=False)
|
||
parser.add_argument('-f', '--female', help='Female riders only', default=False, action='store_true')
|
||
parser.add_argument('-m', '--male', help='Male riders only', default=False, action='store_true')
|
||
parser.add_argument('-a', '--alltime', help='Use all time ranking', default=False, action='store_true')
|
||
parser.add_argument('-p', '--pages', help='Number of pages to process', default=1)
|
||
parser.add_argument('-j', '--jersey', help='Get team jerseys', default=False, action='store_true')
|
||
parser.add_argument('-e', '--equipment', help='Get team bike and wheels', default=False, action='store_true')
|
||
args = parser.parse_args()
|
||
url_additions = ""
|
||
url_list = []
|
||
if args.alltime:
|
||
url_additions += "&s=all-time"
|
||
if args.nation:
|
||
url_additions += "&nation="+args.nation
|
||
if args.female:
|
||
url_list = [ { "url": base_url + url_additions + "&p=we", "is_male": False } ]
|
||
elif args.male:
|
||
url_list = [ { "url": base_url + url_additions + "&p=me", "is_male": True } ]
|
||
else:
|
||
url_list = [ { "url": base_url + url_additions + "&p=me", "is_male": True }, { "url": base_url + url_additions + "&p=we", "is_male": False } ]
|
||
if args.pages:
|
||
new_url_list = url_list.copy()
|
||
for x in range(1,int(args.pages)):
|
||
offset = str(x*100)
|
||
for url in url_list:
|
||
new_url_list += [ { "url": url['url'] + "&offset=" + offset, "is_male": url['is_male'] }]
|
||
url_list = new_url_list.copy()
|
||
|
||
total_data = {}
|
||
total_data['riders'] = []
|
||
for item in url_list:
|
||
total_data['riders'] = total_data['riders'] + get_pros(item['url'], item['is_male'], args.jersey, args.equipment)
|
||
total_data['body_types'] = [16, 48, 80, 272, 304, 336, 528, 560, 592]
|
||
total_data['hair_types'] = [25953412, 175379869, 398510584, 659452569, 838618949, 924073005, 1022111028, 1262230565, 1305767757, 1569595897, 1626212425, 1985754517, 2234835005, 2507058825, 3092564365, 3200039653, 3296520581, 3351295312, 3536770137, 4021222889, 4179410997, 4294226781]
|
||
total_data['facial_hair_types'] = [248681634, 398510584, 867351826, 1947387842, 2173853954, 3169994930, 4131541011, 4216468066]
|
||
|
||
with open('bot.txt', 'w') as outfile:
|
||
json.dump(total_data, outfile, indent=2)
|
||
|
||
if __name__ == '__main__':
|
||
try:
|
||
main(sys.argv)
|
||
except KeyboardInterrupt:
|
||
pass
|
||
except SystemExit as se:
|
||
print("ERROR:", se)
|