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ScrapingTools.py
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ScrapingTools.py
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import pandas as pd
import numpy as np
import csv
import math
import random
import socket
import socks
from stem import Signal
from stem.control import Controller
# def writeCsv(data_collection,team1,team2):
# csv_file =team1+"__"+team2+".csv"
# csv_titles.append(csv_file)
# csv_columns = ['title','odd_id','odds_name','odds_value','team1_goal','team2_goal','team_time']
# try:
# with open("1teams/"+csv_file, 'w',encoding='utf-8',newline='') as csvfile:
# writer = csv.DictWriter(csvfile, fieldnames=csv_columns)
# writer.writeheader()
# i=0
# for data in data_collection:
# # print(data_collection[data])
# writer.writerow(data_collection[data])
# data_collection.clear()
# except IOError as ex:
# print("I/O error"+str(ex))
def writeCsv2UniqueSet(data_collection,csv_file,col):
# csv_file = team1+"__"+team2+".csv"
if col is not None:
csv_columns=col
else:
csv_columns = ['title','odd_id','odds_name','odds_value','team1_goal','team2_goal','team_time']
try:
with open(csv_file, 'w',encoding='utf-8',newline='') as csvfile:
writer = csv.DictWriter(csvfile, fieldnames=csv_columns)
writer.writeheader()
i=0
for data in data_collection:
# print(data_collection[data])
writer.writerow(data)
# data_collection.clear()
except IOError as ex:
print("I/O error"+str(ex))
def csvToDict(filename):
df={}
# , header=None, index_col=0, squeeze=True
df=pd.read_csv(filename)#.to_dict()
return df
def eliminateDuplicate(data_collection):
# data_collection.sort_values("title", inplace = True)
data_collection.drop_duplicates(subset ="odd_id", keep = False, inplace = True)
data_collection.to_csv('Updated_Czech Republic U21__Iceland U21.csv')
# print(data_collection)
return data_collection
def sortCsv(filename):
df={}
df=pd.read_csv('1teams/'+filename)
df.sort_index(axis=0, inplace = True,ascending=False)
df.to_csv('2sortResult/'+filename)
return df
def csvToDictListDesc(csv_path,sort):
if sort:
sortCsv(csv_path)
mylist = []
mydict = {}
# read the csv and write to a dictionary
with open('2sortResult/'+csv_path, 'r') as csv_file:
reader = csv.reader(csv_file)
for column in reader:
title=column[1]
str_id=column[2]
odds_name=column[3]
odds_value_=column[4]
team1_score=column[5]
team2_score=column[6]
team_time=column[7]
mydict = {"title":title,"odd_id":str_id,"odds_name":odds_name,"odds_value":odds_value_,"team1_goal":team1_score,"team2_goal":team2_score,"team_time":team_time}
mylist.append(mydict)
return mylist
def csvToDictListLowOdds(csv_path):
mylist = []
mydict = {}
# read the csv and write to a dictionary
try:
with open('4LowOdds/'+csv_path, 'r') as csv_file:
reader = csv.reader(csv_file)
for column in reader:
title=column[0]
str_id=column[1]
odds_name=column[2]
odds_value_=column[3]
team1_score=column[4]
team2_score=column[5]
team_time=column[6]
mydict = {"title":title,"odd_id":str_id,"odds_name":odds_name,"odds_value":odds_value_,"team1_goal":team1_score,"team2_goal":team2_score,"team_time":team_time}
mylist.append(mydict)
except:
pass
return mylist
def finalDataToDictList(csv_path):
mylist = []
mydict = {}
# read the csv and write to a dictionary
with open(csv_path, 'r') as csv_file:
reader = csv.reader(csv_file)
for column in reader:
title=column[0]
odds_name=column[1]
team_time=column[2]
apperance=column[3]
mydict = {"title":title,"odds_name":odds_name,"team_time":team_time,"apperance":apperance}
mylist.append(mydict)
return mylist
def csvToDictList(csv_path):
mylist = []
mydict = {}
# read the csv and write to a dictionary
with open(csv_path, 'r') as csv_file:
reader = csv.reader(csv_file)
for column in reader:
title=column[0]
str_id=column[1]
odds_name=column[2]
odds_value_=column[3]
team1_score=column[4]
team2_score=column[5]
team_time=column[6]
mydict = {"title":title,"odd_id":str_id,"odds_name":odds_name,"odds_value":odds_value_,"team1_goal":team1_score,"team2_goal":team2_score,"team_time":team_time}
mylist.append(mydict)
return mylist
def csvToDictListResult(from_path,csv_path):
mylist = []
mydict = {}
match_odds_count=0
team1=csv_path.split("__")[0].lower()
team2=csv_path.split("__")[1].lower().split(".")[0]
# read the csv and write to a dictionary
with open(from_path+csv_path, 'r') as csv_file:
reader = csv.reader(csv_file)
for column in reader:
if column[0].strip()=="title":
continue
title=column[0]
str_id=column[1]
odds_name=column[2].strip()
odds_value_=column[3]
team1_score=column[4]
team2_score=column[5]
team_time=column[6]
result="undefined"
str_title=title.strip()
score1=int(team1_score)
score2=int(team2_score)
if str_title=="Both teams to score" or str_title=="Home team to score":
if odds_name.strip()=="No goal" and (int(team1_score)==0 and int(team2_score)==0):
result="win"
elif odds_name.strip()=="Goal" and (int(team1_score)>0 and int(team2_score)>0):
result="win"
else:
result="loss"
elif str_title=="Match Odds":
if int(team1_score)>int(team2_score) and odds_name.strip().lower()==team1:
result="win"
elif int(team1_score)==int(team2_score) and odds_name.strip().lower()=="draw":
result="win"
elif int(team2_score)>int(team1_score) and odds_name.strip().lower()==team2:
match_odds_count=0
result="win"
else:
result="loss"
match_odds_count=match_odds_count+1
elif str_title=="Number of goals" or str_title=="Away team number of goals" or str_title=="Home team number of goals":
odd_goal=odds_name.split("or")[0]
less_or_more=""
try:
less_or_more=odds_name.split("or")[1].strip()
except:
less_or_more=""
if int(team1_score)+int(team2_score)==int(odd_goal) and less_or_more=="":
result="win"
elif int(team1_score)+int(team2_score)>=int(odd_goal) and less_or_more=="more":
result="win"
elif int(team1_score)+int(team2_score)<=int(odd_goal) and less_or_more=="less":
result="win"
else:
result="loss"
elif str_title=="Over/Under" or str_title=="Over/Under home team" or str_title=="Over/Under away team":
over_under=odds_name.strip().split(" ")[0].strip().lower()
over_under_point=odds_name.strip().split(" ")[-1].strip()
# print(odds_name.strip()+"again")
# try:
# one=int(over_under_point.split(".")[0])
# except:
# print(odds_name.strip().split(" "))
one=int(over_under_point.split(".")[0])
two=int(over_under_point.split(".")[-1])
if over_under=="over":
if score1+score2>=one+1 and two==5:
result="win"
elif score1+score2>one+1 and two==75:
result="win"
elif score1+score2==one+1 and two==75:
result="half"
else:
result="loss"
elif over_under=="under":
if score1+score2<=one:
result="win"
else:
result="loss"
elif str_title=="Correct Score":
if score1==int(odds_name.strip().split("-")[0]) and score2==int(odds_name.strip().split("-")[1]):
result="win"
else:
result="loss"
elif str_title=="Double Chance":
if odds_name=="X2" and ((score1==score2) or score2>score1):
result="win"
elif odds_name=="1X" and ((score1==score2) or score1>score2):
result="win"
elif odds_name=="12" and ((score1>score2) or score2>score1):
result="win"
else:
result="loss"
elif str_title=="Odd/Even":
if odds_name=="Even" and (score1+score2)==0:
result="win"
elif odds_name=="Even":
if(score1+score2)%2==0:
result="win"
elif odds_name=="Odd" and (score1+score2)%2>0:
result="win"
else:
result="loss"
mydict = {"title":title,"odd_id":str_id,"odds_name":odds_name,"odds_value":odds_value_,"team1_goal":team1_score,"team2_goal":team2_score,"team_time":team_time,"result":result}
mylist.append(mydict)
return mylist
def getUniqueRowsByOdds(mylist,csv_title):
new_data=[]
new_dict={}
i=0
# new_data.append(mylist[1])
for data in mylist:
count=0
rty=False
exist=False
exist_c=0
for n_d in new_data:
if n_d['odd_id'] == data['odd_id']:
exist=True
break
for n_d in new_data:
if data['odd_id']== n_d['odd_id'] and (data['odds_value'] !=n_d['odds_value']):
count=count+1
break
# rty=True
if not exist or(count>0):
new_data.append(data)
# print(rty)
writeCsv2UniqueSet(new_data,'UniqueSetByOdds/'+csv_title)
# getUniqueByTime(new_data,csv_title)
# print(new_data)
def teams_result(mylist,folder,csv_title):
new_data=[]
new_dict={}
i=0
col=['title','odd_id','odds_name','odds_value','team1_goal','team2_goal','team_time','result']
# new_data.append(mylist[1])
for data in mylist:
count=0
rty=False
exist=False
exist_c=0
for n_d in new_data:
if n_d['odd_id'] == data['odd_id']:
exist=True
break
for n_d in new_data:
if data['odd_id']== n_d['odd_id'] and (data['odds_name'] !=n_d['odds_name']):
count=count+1
break
# rty=True
if not exist or(count>0):
new_data.append(data)
writeCsv2UniqueSet(new_data,'1teams_result/'+folder+'/'+csv_title,col)
def get2UniqueRows(mylist,csv_title):
new_data=[]
new_dict={}
i=0
# new_data.append(mylist[1])
for data in mylist:
count=0
rty=False
exist=False
exist_c=0
for n_d in new_data:
if n_d['odd_id'] == data['odd_id']:
exist=True
exist_c=exist_c+1
for n_d in new_data:
if data['odd_id']== n_d['odd_id'] and (data['odds_value'] !=n_d['odds_value'] or data['team1_goal'] !=n_d['team1_goal'] or data['team2_goal'] !=n_d['team2_goal']):
count=count+1
# rty=True
if not exist or(count>0 and exist_c==1):
new_data.append(data)
# print(rty)
getUniqueByTime(new_data,csv_title)
def getUniqueByTime(mylist,csv_title):
new_data=[]
new_dict={}
i=0
# new_data.append(mylist[1])
for data in mylist:
count=0
rty=False
exist=False
exist_c=0
for n_d in new_data:
if n_d['odd_id'] == data['odd_id']:
exist=True
exist_c=exist_c+1
for n_d in new_data:
if data['odd_id']== n_d['odd_id'] and (data['team_time'] !=n_d['team_time']):
count=count+1
# rty=True
if not exist:
new_data.append(data)
writeCsv2UniqueSet(new_data,'3UniqueDataByTime/'+csv_title)
lowOdds(new_data,csv_title)
def lowOdds(mylist,csv_title):
new_data=[]
new_dict={}
i=0
# new_data.append(mylist[1])
for data in mylist:
count=0
rty=False
low_odd=False
try:
if float(data['odds_value'])<2.0:
new_data.append(data)
except:
continue
writeCsv2UniqueSet(new_data,'4LowOdds/'+csv_title)
# np.array_equal(np.array([1, 2]), np.array([1, 2]))
def getSimilarData(csv_titles):
new_data=[]
new_dict={}
title_arr=[]
time_arr=[]
odd_id_arr=[]
row_data=[]
for i in range(99):
for csv_title in csv_titles:
mylist=csvToDictListLowOdds(csv_title)
i=0
for data in mylist:
count=0
rty=False
exist=False
exist_c=0
title=data['title']
team_time=data['team_time']
str_id=data['odd_id']
odds_value_=data['odds_value']
mydict = [title,str_id,odds_value_,team_time]
if mydict in new_data:
break
new_data.append(mydict)
print(new_data)
if np.array_equal(new_data):
row_data.append(new_data[0])
writeCsv2UniqueSet(row_data,'SimilarData/'+'csv_title.csv')
def getSimilarData2(csv_titles):
myDict={}
new_data=[]
arr_len=[]
array_n=0
csv_files=[]
mylist=[]
for csv_title in csv_titles:
try:
# myDict=csvToDictListLowOdds(csv_title)#pd.read_csv('4LowOdds/'+csv_title,usecols=["title","team_time"])
myDict=pd.read_csv('4LowOdds/'+csv_title,usecols=["title","odds_name","team_time"])
new_data.append(np.array(myDict))
arr_len.append(len(myDict))
csv_files.append(csv_title)
except:
continue
new_data.clear()
print(arr_len)
print(csv_titles)
highest_len_csv=list(np.array(arr_len)).index(np.array(arr_len).max())
# try:
myDict=np.array(pd.read_csv('4LowOdds/'+csv_files[highest_len_csv],usecols=["title","odds_name","team_time"]))
for csv_dic in myDict:
count=0
for csv_title in csv_files:
newDict=np.array(pd.read_csv('4LowOdds/'+csv_title,usecols=["title","odds_name","team_time"]))
if csv_dic in newDict:
count=count+1
if count>0:
resultDict = {"title":csv_dic[0],"odds_name":csv_dic[1],"team_time":csv_dic[2],"apperance":count}
mylist.append(resultDict)
# except:
# pass
csv_columns = ['title','odds_name','team_time','apperance']
try:
with open('SimilarData/final_data.csv', 'w',encoding='utf-8',newline='') as csvfile:
writer = csv.DictWriter(csvfile, fieldnames=csv_columns)
writer.writeheader()
i=0
for data in mylist:
print(data)
writer.writerow(data)
# data_collection.clear()
except IOError as ex:
print("I/O error"+str(ex))
def changeIp(controller):
controller.signal(Signal.NEWNYM)
socks.set_default_proxy(socks.SOCKS5,"localhost",9150)
socks.socket=socks.socksocket