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graph.py
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graph.py
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import threading
import os
import eel
import pandas as pd
from DATA import Data_Manage
from AI import Analytics
import json
import sys
import sklearn
import joblib
global DATAUPDATE
try:
if os.path.exists('DATA/DATA/PREDICTED_DATA_CSV.csv') == True:
th0 = threading.Thread(target = Data_Manage.Predict)
th0.daemon = True
th0.start()
else:
import main
except :
pass
path1 = 'DATA/DATA/PREDICTED_DATA_CSV.csv'
#path2 = 'Backend/PREDICTED_DATA1.csv' # for testing'
if os.path.exists(path1) != False : # checking the condition for security
'''This will check if there is any preprocessing Left'''
# th1 = threading.Thread(target = Data_Manage.Predict)
# th1.start()
data = pd.read_csv(path1) # **Temp Address**
default_data , status = Analytics.get_range_data(data)
@eel.expose
def UpdateData():
Data_Manage.Update()
End()
os.execl(sys.executable, sys.executable, *sys.argv)
@eel.expose
def last_update():
with open('STATE/last_update.txt','r') as lup:
last = lup.read()
lup.close()
with open('STATE/preprocess.txt','r') as r:
state = str(r.read())
r.close()
with open('STATE/running.txt','r') as r2:
running = str(r2.read())
if(state!="True" and running !="True"):
run = last
else:
run = "True"
return run
@eel.expose
def Check_Update():
with open("STATE/preprocess.txt" ,'r') as r:
val = r.read()
return val
@eel.expose
def class_percent(val = 1):
if val == 1:
# Today
data1 = default_data
elif val == 2:
# This Week
data1 , nan = Analytics.get_range_data(data ,week1=1)
if len(nan) != 0:
pass
elif val == 3 :
data1 , nan = Analytics.get_range_data(data ,Month1=1)
if len(nan) != 0 :
pass
data1 = data1.reset_index(drop=True)
d = Analytics.classes_per( data1 )
return d
@eel.expose
def TIME_GRAPH(val1=1):
th1=threading.Thread(target=time_graph)
#time_graph(val1)
th1.start()
@eel.expose
def time_graph(val=1): # val is added if in future i want to add some date wise data
global data
d = {}
if val == 1:
'''This will show TODAY + Yesterday -> for comparision '''
dic2 , nan = Analytics.get_range_data(data,days=2)
for date in dic2.keys():
val = Analytics.time_spent(dic2[date])
for k in val.keys():
val[k] = int(val[k])
d[date] = val
if len(nan) != 0:
d[str(nan[0])]={0:0}
else:
dic2 , nan = Analytics.get_range_data(data,days=7)
for date in dic2.keys():
val = Analytics.time_spent(dic2[date])
for k in val.keys():
val[k] = int(val[k])
d[date] = val
if len(nan) != 0:
print("DATES NOT PRESENT !!!!",nan)
pass
d2 = json.dumps(d)
return d2
@eel.expose
def date_graph(val=1,gen_date=False):# val is added if in future i want to add some date wise data
global data
if val == 1: # =>1 week data
data2,nan = Analytics.get_range_data(data,week1=1,gen_data=gen_date)
date = Analytics.dates_spent(data2,nan)
elif( val == 2):
data2,nan = Analytics.get_range_data(data,Month1=1,gen_data=gen_date)
date = Analytics.dates_spent(data2,nan)
else:
data2,nan = Analytics.get_range_data(data,week1=12,gen_data=gen_date)
date = Analytics.dates_spent(data2,nan)
date = json.dumps(date)
return date
@eel.expose
def get_sources(val=1):
''''Give opt : 1. to choose time period 2. top 10,20 etc '''
global data
if val == 1:
src = Analytics.get_source_graph(default_data)
elif(val == 2):
# Week
dat,nan = Analytics.get_range_data(data,week1=1)
src = Analytics.get_source_graph(dat)
else:
dat,nan = Analytics.get_range_data(data,Month1=1)
src = Analytics.get_source_graph(dat)
src = json.dumps(src)
return src
@eel.expose
def general_sources(val = 1):
global data
d2={}
if val == 1:
d = Analytics.general_source(default_data)
elif(val == 2):
g_src,nan = Analytics.get_range_data(data,week1=1)
d = Analytics.general_source(g_src)
else:
g_src,nan = Analytics.get_range_data(data,Month1=1)
d = Analytics.general_source(g_src)
for k in d.keys():
d2[k] = str(d[k])
d = json.dumps(d2)
return d
@eel.expose
def indi_class_dist(val=1,Class=["AI","GameD","WebD","AppD","Entertainment","Social Media","Lang"]):
global data
if val ==1:
d = Analytics.class_dist(default_data,Class)
else:
pass
d = json.dumps(d)
return d
@eel.expose
def month_data():
mon_data = Analytics.month_cou(data)
return json.dumps(mon_data)
@eel.expose
def End():
global data,default_data,dic,nan
data = pd.read_csv(path1)
default_data , status = Analytics.get_range_data(data)
dic , nan = Analytics.get_range_data(data,days=2)
eel.init('web')
eel.start('test.html')
try:
eel.start('test.html',port=27000)
except Exception as e:
print(e)
try:
eel.start('test.html',port=15000)
except:
eel.start('test.html')