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Removing a personalized class inside the view.py - Django

here is my view.py. Despite the code is a little bit long, I'd like to remove the class Ibm() from inside the else element to a new file called Ibm_class.py. I tried to do that but I couldn't find any way!
def index(request):
if 'GET' == request.method:
return render(request, 'auditoria_app/index.html')
else:
class Ibm(object):
def __init__(self, i):
self.numeroIbm = inputsCombo[get_column_letter(i) + str(10)].value
self.nome = inputsCombo[get_column_letter(i) + str(11)].value
self.cidade = inputsCombo[get_column_letter(i) + str(12)].value
self.uf = inputsCombo[get_column_letter(i) + str(13)].value
self.anosProjeto = inputsCombo[get_column_letter(i) + str(16)].value
self.anosAlternativa = inputsDNCombo[get_column_letter(i) + str(14)].value
if self.anosAlternativa is None:
self.anosAlternativa = 0
self.tipoInvestimento = inputsCombo[get_column_letter(i) + str(21)].value
self.tipoProposta = inputsCombo[get_column_letter(i) + str(24)].value
self.inicioVigencia = inputsCombo[get_column_letter(i) + str(34)].value
self.prazoContrato = inputsCombo[get_column_letter(i) + str(38)].value
# gas station variables
self.faixaMargem = inputsCombo[get_column_letter(i) + str(19)].value
self.rebateTotalCI = 0
self.rebateTotalCB = 0
self.unitariaCI = 0
self.volumeMensalCI = inputsCombo[get_column_letter(i) + str(60)].value
self.volumeMensalCB = inputsDNCombo[get_column_letter(i) + str(32)].value
self.margemCurva = inputsCombo[get_column_letter(i) + str(67)].value * 1000
self.margemCI = []
self.margemCB = []
self.volume12m = 0
self.margem12m = 0
self.curvaPostoCI = []
self.curvaPostoCB = []
self.rebateCI = []
self.rebateCB = []
self.faixaReal = ''
self.volumeTotalCI = inputsCombo[get_column_letter(i) + str(151)].value
self.volumeTotalCB = inputsDNCombo[get_column_letter(i) + str(121)].value
# SELECT store variables
self.feeIsencao = inputsCombo[get_column_letter(i) + str(220)].value
self.feeFaturamento = inputsCombo[get_column_letter(i) + str(222)].value
self.feeReal = inputsCombo[get_column_letter(i) + str(224)].value
self.faturamento = inputsCombo[get_column_letter(i) + str(173)].value
self.pvl = inputsCombo[get_column_letter(i) + str(184)].value
self.feeLoja = inputsCombo[get_column_letter(i) + str(174)].value
self.cashback = []
# credit variables
self.prazoMogasCI1 = inputsCombo[get_column_letter(i) + str(159)].value
self.prazoMogasCI2 = inputsCombo[get_column_letter(i) + str(160)].value
self.prazoMogasCI3 = inputsCombo[get_column_letter(i) + str(161)].value
self.prazoMogasCB1 = inputsDNCombo[get_column_letter(i) + str(151)].value
self.prazoMogasCB2 = inputsDNCombo[get_column_letter(i) + str(152)].value
self.prazoMogasCB3 = inputsDNCombo[get_column_letter(i) + str(153)].value
# economics IBM
self.unitariaIBM = arredonda(outputCombo[get_column_letter(i - 1) + str(42)].value)
self.hsIBM = arredonda(outputCombo[get_column_letter(i - 1) + str(36)].value)
self.cmIBM = percentual(outputCombo[get_column_letter(i - 1) + str(39)].value)
self.tirIBM = percentual(outputCombo[get_column_letter(i - 1) + str(54)].value)
self.npvIBM = arredonda(outputCombo[get_column_letter(i - 1) + str(55)].value)
# if self.tipoInvestimento != 'Loja':
for k in range(0, self.anosProjeto):
margemCI = inputsCombo[get_column_letter(i) + str(109 + k)].value
if margemCI is None or margemCI == '':
margemCI = 0
self.margemCI.append(arredonda(margemCI * 1000))
curvaPostoCI = inputsCombo[get_column_letter(i) + str(130 + k)].value
if curvaPostoCI is None or 0:
curvaPostoCI = 1
self.curvaPostoCI.append(arredonda(curvaPostoCI * 100))
rebateCI = inputsCombo[get_column_letter(i) + str(305 + k)].value
if rebateCI is None:
rebateCI = 0
self.rebateCI.append(rebateCI * 1000)
cashback = inputsCombo[get_column_letter(i) + str(485 + k)].value
if cashback is None:
cashback = 0
else:
cashback = cashback / self.faturamento
self.cashback.append(cashback)
for y in range(0, self.anosAlternativa):
margemCB = inputsDNCombo[get_column_letter(i) + str(79 + y)].value
if margemCB is None or margemCB == '':
margemCB = 0
self.margemCB.append(arredonda(margemCB * 1000))
curvaPostoCB = inputsDNCombo[get_column_letter(i) + str(100 + y)].value
if curvaPostoCB is None or 0:
curvaPostoCB = 1
self.curvaPostoCB.append(arredonda(curvaPostoCB * 100))
rebateCB = inputsDNCombo[get_column_letter(i) + str(204 + y)].value
if rebateCB is None:
rebateCB = 0
self.rebateCB.append(rebateCB * 1000)
# Selecionando os dados da Loja Select
# if self.tipoInvestimento == 'Loja':
self.curvaLojaCI = []
self.curvaLojaCB = []
for k in range(0, self.anosProjeto):
curvaLojaCI = inputsCombo[get_column_letter(i) + str(198 + k)].value
if curvaLojaCI is None or 0:
curvaLojaCI = 1
self.curvaLojaCI.append(curvaLojaCI)
for k in range(0, self.anosAlternativa):
curvaLojaCB = inputsDNCombo[get_column_letter(i) + str(123 + k)].value
if curvaLojaCB is None or 0:
curvaLojaCB = 1
self.curvaLojaCB.append(curvaLojaCB)
self.fpCI = inputsCombo[get_column_letter(i) + str(283)].value
if self.fpCI is None:
self.fpCI = 0
self.rviCI = inputsCombo[get_column_letter(i) + str(285)].value
if self.rviCI is None:
self.rviCI = 0
self.fpCB = inputsDNCombo[get_column_letter(i) + str(201)].value
if self.fpCB is None:
self.fpCB = 0
self.rviCB = inputsDNCombo[get_column_letter(i) + str(202)].value
if self.rviCB is None:
self.rviCB = 0
# initializing gas station functions
self.get_volume()
self.rebate_total_CI()
self.rebate_total_CB()
# self.unitaria_CI()
self.check_faixa()
def get_volume(self):
if self.tipoInvestimento != 'Loja':
for j in range(2, sigma.max_row + 1):
if self.numeroIbm == sigma['A' + str(j)].value:
self.margem12m = sigma['D' + str(j)].value
self.volume12m = sigma['E' + str(j)].value
def check_faixa(self):
if self.tipoInvestimento != 'Loja':
if self.faixaMargem[0] == 'R':
pass
else:
for row in range(5, faixas.max_row + 1):
cidade = faixas['C' + str(row)].value
if cidade == unidecode.unidecode(self.cidade.upper() + '/' + self.uf.upper()):
self.faixaReal = faixas['D' + str(row)].value
if self.faixaReal == '':
self.faixaReal = 'n/a'
def rebate_total_CI(self):
if self.tipoInvestimento != 'Loja':
rebateTotalCI = 0
for k in range(0, self.anosProjeto):
rebateTotalCI += self.volumeMensalCI * 12 * self.curvaPostoCI[k] * self.rebateCI[k]
self.rebateTotalCI = arredonda(rebateTotalCI / 1000)
def rebate_total_CB(self):
if self.tipoInvestimento != 'Loja':
rebateTotalCB = 0
for k in range(0, self.anosAlternativa):
rebateTotalCB += self.volumeMensalCB * 12 * self.curvaPostoCB[k] * self.rebateCB[k]
self.rebateTotalCB = arredonda(rebateTotalCB / 1000)
# UNIT might be extracted from 'OutPut COMBO'
# def unitaria_CI(self):
# self.unitariaCI = (self.rebateTotalCI + self.fpCI + self.rviCI)*10/self.volumeTotalCI
def check_volume_mensal(self):
return self.volumeMensalCI - self.volumeMensalCB
def check_volume_total(self):
return self.volumeTotalCI - self.volumeTotalCB
def check_volumeCB_SIC(self):
return self.volumeMensalCB
excel_file = request.FILES["excel_file"]
wb = openpyxl.load_workbook(excel_file, data_only=True)
inputsCombo = wb['Inputs COMBO']
inputsDNCombo = wb['Inputs DN COMBO']
outputCombo = wb['OutPut COMBO']
faixas = wb['Faixas']
wb2 = openpyxl.load_workbook('media/sigma.xlsx', data_only=True)
sigma = wb2['Planilha1']
wb3 = openpyxl.load_workbook('media/performance.xlsx', data_only=True)
sic = wb3['Performance']
wb4 = openpyxl.load_workbook('media/ultimoContrato.xlsm', data_only=True)
ultimoContrato = wb4['Base']
numeroIbms = inputsCombo['F5'].value
ibms = []
for i in range(8, 8 + numeroIbms):
ibm = Ibm(i)
ibms.append(ibm)
return render(request, 'auditoria_app/index.html', {'ibms': ibms})
-> wb: file is loaded from a upload
-> wb2, wb3, wb4: files are stored inside the media folder
I tried to copy/paste this class and then import it to the view.py file but the excel_file variable must be inside the view and is still needed inside the Ibm_class.py. Any suggestion, pls?
Thank you!

Use dependency injection on your class instead of relying on local/global scope variables. Here, instead of directly using inputsCombo, inputsDNCombo, outputCombo, faixas, and sigma variables within your class, just pass them to the Ibm constructor as class attributes.
views.py
...
from my_app.ibm import Ibm # Or wherever you would put that class
...
def index(request):
...
else:
excel_file = request.FILES["excel_file"]
wb = openpyxl.load_workbook(excel_file, data_only=True)
inputsCombo = wb['Inputs COMBO']
inputsDNCombo = wb['Inputs DN COMBO']
outputCombo = wb['OutPut COMBO']
faixas = wb['Faixas']
wb2 = openpyxl.load_workbook('media/sigma.xlsx', data_only=True)
sigma = wb2['Planilha1']
...
for i in range(8, 8 + numeroIbms):
# Pass the dependencies to the constructor of Ibm class
ibm = Ibm(i, inputsCombo, inputsDNCombo, outputCombo, faixas, sigma)
...
...
ibm.py
class Ibm(object):
# Accept the injected parameters to Ibm class
def __init__(self, i, inputsCombo, inputsDNCombo, outputCombo, faixas, sigma):
self.numeroIbm = inputsCombo[get_column_letter(i) + str(10)].value
self.anosAlternativa = inputsDNCombo[get_column_letter(i) + str(14)].value
self.unitariaIBM = arredonda(outputCombo[get_column_letter(i - 1) + str(42)].value)
# For the arguments that will be used by your other functions e.g. check_faixa, define them as class attributes here
self.faixas = faixas
self.sigma = sigma
def get_volume(self):
if self.tipoInvestimento != 'Loja':
for j in range(2, self.sigma.max_row + 1): # Append "self." to the usage of "sigma" to refer to the class attribute that was set in __init__
if self.numeroIbm == self.sigma['A' + str(j)].value:
self.margem12m = self.sigma['D' + str(j)].value
self.volume12m = self.sigma['E' + str(j)].value
def check_faixa(self):
if self.tipoInvestimento != 'Loja':
if self.faixaMargem[0] == 'R':
pass
else:
for row in range(5, self.faixas.max_row + 1): # Append "self." to the usage of "faixas" to refer to the class attribute that was set in __init__
cidade = self.faixas['C' + str(row)].value
if cidade == unidecode.unidecode(self.cidade.upper() + '/' + self.uf.upper()):
self.faixaReal = self.faixas['D' + str(row)].value
if self.faixaReal == '':
self.faixaReal = 'n/a'

Error , Infeasible No value for uninitialized NumericValue object

I'm trying to optmize a problem of clients/facility allocation and I'm using pyomo to do so. I have the following problem that appear and cannot solve it even if I initialize all the values of Model.z to 0; the problems is still infeasible
from __future__ import division
import pyomo.environ as pyo
#from pyomo.environ import *
from pyomo.opt import SolverFactory
import sys
import numpy as np
import sys
import os
from time import perf_counter
from pulp import *
from pyomo.util.infeasible import log_infeasible_constraints
#print(sys.path)
opt = pyo.SolverFactory('glpk')
opt.options['threads'] =4
#import instance
model = pyo.ConcreteModel()
# n is the number of facility related to J
# m is the number of clients related to I
# t is the number of periods relatdd to T
# H is the maximum number of clients that can be served
[m,n,t,H] = np.genfromtxt(fname = r'./Instances/data-100-10-4-3-0.txt', dtype = None, max_rows = 1)
f_values = np.genfromtxt(fname = r'./Instances/data-100-10-4-3-0.txt', dtype = None, max_rows = 4,skip_header=1)
c_values = np.genfromtxt(fname = r'./Instances/data-100-10-4-3-0.txt', dtype = None, skip_footer = 1,skip_header=5)
p_values = np.genfromtxt(fname = r'./Instances/data-100-10-4-3-0.txt', dtype = None, skip_header=405)
model.J = pyo.Set(initialize=[int(i)+1 for i in range(n)])
model.T= pyo.Set(initialize=[int(i)+1 for i in range(t)])
model.T.pprint()
model.I = pyo.Set(initialize=[int(i)+1 for i in range(m)])
model.H = pyo.Set(initialize=[int(i)+1 for i in range(H)])
# Generation of Subsets of all clients
client_list = [int(i)+1 for i in range(100)]
list_H = [int(i)+1 for i in range(H)]
possible_groups_of_clients=[]
for i in list_H:
possible_groups_of_clients += [list(elem) for elem in itertools.combinations(client_list,i)]
possible_groups_of_clients = possible_groups_of_clients[0:5] #Only select the first 5 subsets
model.K = pyo.Set(initialize=[int(i)+1 for i in range(len(possible_groups_of_clients))])
p_val = np.zeros((len(model.K),len(model.J),len(model.T)))
for t in model.T:
t=t-1 #Pyomo starts at 1
for j in model.J:
j=j-1
count = 0
for k in possible_groups_of_clients:
#k=k+1
c_sum=0;
for p in k:
if t==0:
c_sum = c_sum +c_values[p][j]
elif t==1:
c_sum = c_sum +c_values[p+100][j]
elif t==2:
c_sum = c_sum +c_values[p+200][j]
elif t==3:
c_sum = c_sum +c_values[p+300][j]
#print(f_values[t][j])
p_val[count][j][t] = f_values[t][j]+ c_sum
count=count+1
model.p_val = pyo.Param(model.K,model.J,model.T, initialize = lambda model,k,j,t: p_val[k-1][j-1][t-1])
#Matrice Aik
A = [[0 for k in range(len(possible_groups_of_clients))] for i in range(100)]
#model.p_val = pyo.Param(model.T,model.J,model.K, initialize = lambda model,t,j,k: A[t-1][j-1][k-1])
model.A = pyo.Param(model.I, model.K, mutable= True,initialize= lambda model,i,k: A[i-1][k-1])
count=1
for i in possible_groups_of_clients:
for k in range(100):
k=k+1
#print(k)
if k in i:
model.A[k,count]=1
else:
model.A[k,count]=0
count=count+1
model.z = pyo.Var(model.K,model.J,model.T,initialize= 0,within=pyo.NonNegativeReals,bounds=(0,1))
a=range(len(possible_groups_of_clients))
print(p_values)
# Minization of objective functions
# Constraint unique client
model.uniq_client = pyo.Constraint(
model.I,
rule=lambda model, i: sum(model.A[i,k]*model.z[k,j,t] for t in model.T for j in model.J for k in model.K) == 1
)
model.unique_service_groupclients = pyo.Constraint(
model.J, model.T,
rule=lambda model,j,t: sum(model.z[k,j,t] for k in model.K)<=1
)
model.min_factory_perperiod = pyo.Constraint(
model.T,
rule=lambda model, t: sum(model.z[k,j,t] for j in model.J for k in model.K )>=p_values[t-1]
)
model.obj = pyo.Objective(rule= lambda model:sum(model.p_val[k,j,t]*model.z[k,j,t] for t in model.T for j in model.J for k in model.K ), sense= pyo.minimize)
model.pprint()
Constraint Group Client
sol = pyo.SolverFactory('glpk',).solve(model).write()
log_infeasible_constraints(model)
# ==========================================================
# = Solver Results =
# ==========================================================
# ----------------------------------------------------------
# Problem Information
# ----------------------------------------------------------
Problem:
- Name: unknown
Lower bound: -inf
Upper bound: inf
Number of objectives: 1
Number of constraints: 145
Number of variables: 201
Number of nonzeros: 601
Sense: minimize
# ----------------------------------------------------------
# Solver Information
# ----------------------------------------------------------
Solver:
- Status: ok
Termination condition: infeasible
Statistics:
Branch and bound:
Number of bounded subproblems: 0
Number of created subproblems: 0
Error rc: 0
Time: 0.008042335510253906
ERROR: evaluating object as numeric value: z[1,1,1]
(object: <class 'pyomo.core.base.var._GeneralVarData'>)
No value for uninitialized NumericValue object z[1,1,1]
ERROR: evaluating object as numeric value: 1.0 - (A[1,1]*z[1,1,1] +
A[1,2]*z[2,1,1] + A[1,3]*z[3,1,1] + A[1,4]*z[4,1,1] + A[1,5]*z[5,1,1] +
A[1,1]*z[1,2,1] + A[1,2]*z[2,2,1] + A[1,3]*z[3,2,1] + A[1,4]*z[4,2,1] +
A[1,5]*z[5,2,1] + A[1,1]*z[1,3,1] + A[1,2]*z[2,3,1] + A[1,3]*z[3,3,1] +
A[1,4]*z[4,3,1] + A[1,5]*z[5,3,1] + A[1,1]*z[1,4,1] + A[1,2]*z[2,4,1] +
A[1,3]*z[3,4,1] + A[1,4]*z[4,4,1] + A[1,5]*z[5,4,1] + A[1,1]*z[1,5,1] +
A[1,2]*z[2,5,1] + A[1,3]*z[3,5,1] + A[1,4]*z[4,5,1] + A[1,5]*z[5,5,1] +
A[1,1]*z[1,6,1] + A[1,2]*z[2,6,1] + A[1,3]*z[3,6,1] + A[1,4]*z[4,6,1] +
A[1,5]*z[5,6,1] + A[1,1]*z[1,7,1] + A[1,2]*z[2,7,1] + A[1,3]*z[3,7,1] +
A[1,4]*z[4,7,1] + A[1,5]*z[5,7,1] + A[1,1]*z[1,8,1] + A[1,2]*z[2,8,1] +
A[1,3]*z[3,8,1] + A[1,4]*z[4,8,1] + A[1,5]*z[5,8,1] + A[1,1]*z[1,9,1] +
A[1,2]*z[2,9,1] + A[1,3]*z[3,9,1] + A[1,4]*z[4,9,1] + A[1,5]*z[5,9,1] +
A[1,1]*z[1,10,1] + A[1,2]*z[2,10,1] + A[1,3]*z[3,10,1] + A[1,4]*z[4,10,1]
+ A[1,5]*z[5,10,1] + A[1,1]*z[1,1,2] + A[1,2]*z[2,1,2] + A[1,3]*z[3,1,2] +
A[1,4]*z[4,1,2] + A[1,5]*z[5,1,2] + A[1,1]*z[1,2,2] + A[1,2]*z[2,2,2] +
A[1,3]*z[3,2,2] + A[1,4]*z[4,2,2] + A[1,5]*z[5,2,2] + A[1,1]*z[1,3,2] +
A[1,2]*z[2,3,2] + A[1,3]*z[3,3,2] + A[1,4]*z[4,3,2] + A[1,5]*z[5,3,2] +
A[1,1]*z[1,4,2] + A[1,2]*z[2,4,2] + A[1,3]*z[3,4,2] + A[1,4]*z[4,4,2] +
A[1,5]*z[5,4,2] + A[1,1]*z[1,5,2] + A[1,2]*z[2,5,2] + A[1,3]*z[3,5,2] +
A[1,4]*z[4,5,2] + A[1,5]*z[5,5,2] + A[1,1]*z[1,6,2] + A[1,2]*z[2,6,2] +
A[1,3]*z[3,6,2] + A[1,4]*z[4,6,2] + A[1,5]*z[5,6,2] + A[1,1]*z[1,7,2] +
A[1,2]*z[2,7,2] + A[1,3]*z[3,7,2] + A[1,4]*z[4,7,2] + A[1,5]*z[5,7,2] +
A[1,1]*z[1,8,2] + A[1,2]*z[2,8,2] + A[1,3]*z[3,8,2] + A[1,4]*z[4,8,2] +
A[1,5]*z[5,8,2] + A[1,1]*z[1,9,2] + A[1,2]*z[2,9,2] + A[1,3]*z[3,9,2] +
A[1,4]*z[4,9,2] + A[1,5]*z[5,9,2] + A[1,1]*z[1,10,2] + A[1,2]*z[2,10,2] +
A[1,3]*z[3,10,2] + A[1,4]*z[4,10,2] + A[1,5]*z[5,10,2] + A[1,1]*z[1,1,3] +
A[1,2]*z[2,1,3] + A[1,3]*z[3,1,3] + A[1,4]*z[4,1,3] + A[1,5]*z[5,1,3] +
A[1,1]*z[1,2,3] + A[1,2]*z[2,2,3] + A[1,3]*z[3,2,3] + A[1,4]*z[4,2,3] +
A[1,5]*z[5,2,3] + A[1,1]*z[1,3,3] + A[1,2]*z[2,3,3] + A[1,3]*z[3,3,3] +
A[1,4]*z[4,3,3] + A[1,5]*z[5,3,3] + A[1,1]*z[1,4,3] + A[1,2]*z[2,4,3] +
A[1,3]*z[3,4,3] + A[1,4]*z[4,4,3] + A[1,5]*z[5,4,3] + A[1,1]*z[1,5,3] +
A[1,2]*z[2,5,3] + A[1,3]*z[3,5,3] + A[1,4]*z[4,5,3] + A[1,5]*z[5,5,3] +
A[1,1]*z[1,6,3] + A[1,2]*z[2,6,3] + A[1,3]*z[3,6,3] + A[1,4]*z[4,6,3] +
A[1,5]*z[5,6,3] + A[1,1]*z[1,7,3] + A[1,2]*z[2,7,3] + A[1,3]*z[3,7,3] +
A[1,4]*z[4,7,3] + A[1,5]*z[5,7,3] + A[1,1]*z[1,8,3] + A[1,2]*z[2,8,3] +
A[1,3]*z[3,8,3] + A[1,4]*z[4,8,3] + A[1,5]*z[5,8,3] + A[1,1]*z[1,9,3] +
A[1,2]*z[2,9,3] + A[1,3]*z[3,9,3] + A[1,4]*z[4,9,3] + A[1,5]*z[5,9,3] +
A[1,1]*z[1,10,3] + A[1,2]*z[2,10,3] + A[1,3]*z[3,10,3] + A[1,4]*z[4,10,3]
+ A[1,5]*z[5,10,3] + A[1,1]*z[1,1,4] + A[1,2]*z[2,1,4] + A[1,3]*z[3,1,4] +
A[1,4]*z[4,1,4] + A[1,5]*z[5,1,4] + A[1,1]*z[1,2,4] + A[1,2]*z[2,2,4] +
A[1,3]*z[3,2,4] + A[1,4]*z[4,2,4] + A[1,5]*z[5,2,4] + A[1,1]*z[1,3,4] +
A[1,2]*z[2,3,4] + A[1,3]*z[3,3,4] + A[1,4]*z[4,3,4] + A[1,5]*z[5,3,4] +
A[1,1]*z[1,4,4] + A[1,2]*z[2,4,4] + A[1,3]*z[3,4,4] + A[1,4]*z[4,4,4] +
A[1,5]*z[5,4,4] + A[1,1]*z[1,5,4] + A[1,2]*z[2,5,4] + A[1,3]*z[3,5,4] +
A[1,4]*z[4,5,4] + A[1,5]*z[5,5,4] + A[1,1]*z[1,6,4] + A[1,2]*z[2,6,4] +
A[1,3]*z[3,6,4] + A[1,4]*z[4,6,4] + A[1,5]*z[5,6,4] + A[1,1]*z[1,7,4] +
A[1,2]*z[2,7,4] + A[1,3]*z[3,7,4] + A[1,4]*z[4,7,4] + A[1,5]*z[5,7,4] +
A[1,1]*z[1,8,4] + A[1,2]*z[2,8,4] + A[1,3]*z[3,8,4] + A[1,4]*z[4,8,4] +
A[1,5]*z[5,8,4] + A[1,1]*z[1,9,4] + A[1,2]*z[2,9,4] + A[1,3]*z[3,9,4] +
A[1,4]*z[4,9,4] + A[1,5]*z[5,9,4] + A[1,1]*z[1,10,4] + A[1,2]*z[2,10,4] +
A[1,3]*z[3,10,4] + A[1,4]*z[4,10,4] + A[1,5]*z[5,10,4])
(object: <class 'pyomo.core.expr.numeric_expr.SumExpression'>)
No value for uninitialized NumericValue object z[1,1,1]
Traceback (most recent call last):
File "main.py", line 246, in <module>
log_infeasible_constraints(model)
File "/home/john/.local/lib/python3.6/site-packages/pyomo /util/infeasible.py", line 25, in log_infeasible_constraints
if constr.equality and fabs(value(constr.lower - constr.body)) >= tol:
File "/home/john/.local/lib/python3.6/site-packages/pyomo/core/expr/numvalue.py", line 226, in value
tmp = obj(exception=True)
File "/home/john/.local/lib/python3.6/site-packages/pyomo/core/expr/numeric_expr.py", line 222, in __call__
return evaluate_expression(self, exception)
File "/home/john/.local/lib/python3.6/site-packages/pyomo/core/expr/visitor.py", line 973, in evaluate_expression
return visitor.dfs_postorder_stack(exp)
File "/home/john/.local/lib/python3.6/site-packages/pyomo/core/expr/visitor.py", line 518, in dfs_postorder_stack
flag, value = self.visiting_potential_leaf(_sub)
File "/home/john/.local/lib/python3.6/site-packages/pyomo/core/expr/visitor.py", line 893, in visiting_potential_leaf
return True, value(node)
File "/home/john/.local/lib/python3.6/site-packages/pyomo/core/expr/numvalue.py", line 230, in value
% (obj.name,))
ValueError: No value for uninitialized NumericValue object z[1,1,1]
I got this error whatever I try and I don't understand why Z should be initialized as it is the variable I'm trying to minimize

"out of memory" issue with PETsc in Ubuntu

I am running an OpenMDAO code that uses 2 parallel groups. I have installed PETSc4py and mpi4py inside a virtual python environment. I am getting the following error while running my code. The error reads as follows: "Out of memory. Allocated: 0, Used by process: 236814336"
Here is the full error message:
File "PETSc/Scatter.pyx", line 42, in petsc4py.PETSc.Scatter.create
petsc4py.PETSc.Error: error code 55
[1] VecScatterCreate() line 282 in /tmp/pycharm-packaging/petsc/src/vec/vscat/interface/vscreate.c
[1] VecScatterSetUp() line 211 in /tmp/pycharm-packaging/petsc/src/vec/vscat/interface/vscatfce.c
[1] VecScatterSetUp_MPI1() line 2543 in /tmp/pycharm-packaging/petsc/src/vec/vscat/impls/mpi1/vpscat_mpi1.c
[1] VecScatterSetUp_vectype_private() line 865 in /tmp/pycharm-packaging/petsc/src/vec/vscat/impls/vscat.c
[1] VecScatterCreate_PtoP() line 746 in /tmp/pycharm-packaging/petsc/src/vec/vscat/impls/vscat.c
[1] VecScatterCreateLocal_PtoP_MPI1() line 2436 in /tmp/pycharm-packaging/petsc/src/vec/vscat/impls/mpi1/vpscat_mpi1.c
[1] PetscMallocA() line 390 in /tmp/pycharm-packaging/petsc/src/sys/memory/mal.c
[1] VecScatterCreateLocal_PtoP_MPI1() line 2436 in /tmp/pycharm-packaging/petsc/src/vec/vscat/impls/mpi1/vpscat_mpi1.c
[1] Out of memory. Allocated: 0, Used by process: 237649920
[1] Memory requested 18446744062962991104
-------------------------------------------------------
Primary job terminated normally, but 1 process returned
a non-zero exit code.. Per user-direction, the job has been aborted.
-------------------------------------------------------
--------------------------------------------------------------------------
mpirun detected that one or more processes exited with non-zero status, thus causing
the job to be terminated. The first process to do so was:
Process name: [[43240,1],1]
Exit code: 1
--------------------------------------------------------------------------
I call the process with the following code:
mpirun -np 2 python ./parallel_processing.py
Here is the code for IDF optimization:
from __future__ import print_function
import pickle
import numpy as np
import pandas as pd
import matplotlib.pylab as plt
from openmdao.api import Problem, ScipyOptimizeDriver, SqliteRecorder
import time
import random
from openmdao.recorders.case_reader import CaseReader
from ssbj_vanaret_mda import SsbjMda
from ssbj_vanaret_idf2_mda import SsbjIdf2Mda
def idf_run2(nx, ny):
# make a counter for discipline calls
[str_count, aer_count, pro_count] = np.zeros(3)
a = ["str_count.p", "aer_count.p", "pro_count.p"]
for i in a:
with open(i, "wb") as f:
pickle.dump(0, f)
# Initialize an MDA to generate the starting point for IDF
prob_init = Problem() # initialize the optimization problem
prob_init.model = SsbjMda(nx_input=nx) # create the MDA
# Design variables
prob_init.model.add_design_var('z', lower=np.zeros(nx), upper=np.ones(nx))
prob_init.model.add_design_var('x1', lower=np.zeros(nx), upper=np.ones(nx))
prob_init.model.add_design_var('x2', lower=np.zeros(nx), upper=np.ones(nx))
prob_init.model.add_design_var('x3', lower=np.zeros(nx), upper=np.ones(nx))
# Objective function
prob_init.model.add_objective('range')
# Constraints
for i in range(nx):
prob_init.model.add_constraint('con_g1' + str(i + 1), upper=0)
prob_init.model.add_constraint('con_g2' + str(i + 1), upper=0)
prob_init.model.add_constraint('con_g3' + str(i + 1), upper=0)
prob_init.driver = ScipyOptimizeDriver(optimizer='SLSQP')
prob_init.driver.options['maxiter'] = 0
prob_init.setup(mode='fwd')
prob_init.set_solver_print(1)
prob_init.run_driver()
prob_init.cleanup()
y12_initial = prob_init['y12']
y23_initial = prob_init['y23']
y32_initial = prob_init['y32']
y21_initial = prob_init['y21']
y31_initial = prob_init['y31']
# : initialize MDA for IDF
prob = Problem()
prob.model = SsbjIdf2Mda(nx, ny, y12_initial, y23_initial, y32_initial, y21_initial, y31_initial)
# create the MDA
# Design variables
prob.model.add_design_var('z', lower=np.zeros(nx), upper=np.ones(nx)) # shared variables
prob.model.add_design_var('x1', lower=np.zeros(nx), upper=np.ones(nx)) # local variable for structural discipline
prob.model.add_design_var('x2', lower=np.zeros(nx), upper=np.ones(nx)) # local variable for aerodynamic discipline
prob.model.add_design_var('x3', lower=np.zeros(nx), upper=np.ones(nx)) # local variable for propulsion discipline
# # coupling variables
prob.model.add_design_var('y31')
prob.model.add_design_var('y12')
prob.model.add_design_var('y32')
prob.model.add_design_var('y23')
prob.model.add_design_var('y21')
# Objective function
prob.model.add_objective('obj')
# Constraints
for i in range(nx):
prob.model.add_constraint('con_g1' + str(i + 1), upper=0)
prob.model.add_constraint('con_g2' + str(i + 1), upper=0)
prob.model.add_constraint('con_g3' + str(i + 1), upper=0)
epsilon = 1e-9
# Coupling constraints
for i in range(ny):
prob.model.add_constraint('con_y12' + str(i + 1), upper=epsilon)
prob.model.add_constraint('con_y21' + str(i + 1), upper=epsilon)
prob.model.add_constraint('con_y23' + str(i + 1), upper=epsilon)
prob.model.add_constraint('con_y32' + str(i + 1), upper=epsilon)
prob.model.add_constraint('con_y31' + str(i + 1), upper=epsilon)
# Optimizer options
prob.driver = ScipyOptimizeDriver()
prob.set_solver_print(2)
prob.driver.options['optimizer'] = 'SLSQP'
for tol in [1e-3]:
prob.driver.options['maxiter'] = random.randint(40, 50)
prob.driver.options['tol'] = tol
prob.driver.add_recorder(SqliteRecorder("cases_idf.sql"))
# Run optimization
start_time = time.time()
prob.setup(mode='fwd')
# view_model(prob, outfile='n2_mdfgs.html', show_browser=True)
prob.run_driver()
prob.run_model()
# prob.check_partials()
prob.cleanup()
end_time = time.time()
total_time = end_time - start_time
if prob.driver.options['tol'] == 1e-6:
iters = len(CaseReader('cases_idf.sql').get_cases())
cr = CaseReader('cases_idf.sql')
case_ids = cr.get_cases()
obj_list = ['obj']
z = []
[z.append(case.get_objectives(case)[obj_list[0]]) for case in case_ids]
with open("df_idf.p", "rb") as f:
df_idf = pickle.load(f).append(pd.DataFrame({'total iterations[IDF]': [iters],
'total time[IDF]': [total_time],
'final_objective[IDF]': z[-1]}))
with open("df_idf.p", "wb") as f:
pickle.dump(df_idf, f)
elif prob.driver.options['tol'] == 1e-3:
iters = len(CaseReader('cases_idf.sql').get_cases())
cr = CaseReader('cases_idf.sql')
case_ids = cr.get_cases()
obj_list = ['obj']
z = []
a = ["str_count.p", "aer_count.p", "pro_count.p"]
k = []
for i in a:
with open(i, "rb") as f:
k.append(pickle.load(f))
[z.append(case.get_objectives(case)[obj_list[0]]) for case in case_ids]
with open("df_idf_tol.p", "rb") as f:
df_idf = pickle.load(f).append(pd.DataFrame({'10.total iterations[IDF_tol]': [iters],
'11.total time[IDF_tol]': [total_time],
'12.final_objective[IDF_tol]': z[-1],
'13.str_count[IDF_tol]': k[0],
'14.aer_count[IDF_tol]': k[1],
'15.pro_count[IDF_tol]': k[2]
}))
with open("df_idf_tol.p", "wb") as f:
pickle.dump(df_idf, f)
The MDA for IDF optimization goes here:
from openmdao.api import Group
import numpy as np
from openmdao.api import IndepVarComp, ExecComp, ParallelGroup
from ssbj_vanaret_discipline import StructureDisc
from ssbj_vanaret_discipline import AerodynamicsDisc
from ssbj_vanaret_discipline import PropulsionDisc
from ssbj_vanaret_discipline import PerformanceDisc
class SsbjIdf2Mda(Group):
"""
Analysis for IDF formulation where couplings are managed as additional constraints
on input/output variables of related disciplines.
"""
def __init__(self, nx_input, ny_input, y12_initial, y23_initial, y32_initial, y21_initial, y31_initial):
super(SsbjIdf2Mda, self).__init__()
self.nx = nx_input
self.ny = ny_input
self.y12 = y12_initial
self.y23 = y23_initial
self.y32 = y32_initial
self.y31 = y31_initial
self.y21 = y21_initial
def setup(self):
# Design variables
self.add_subsystem('z_ini', IndepVarComp('z', .5 * np.ones(self.nx)), promotes=['*'])
self.add_subsystem('x1_ini', IndepVarComp('x1', .5 * np.ones(self.nx)), promotes=['*'])
self.add_subsystem('x2_ini', IndepVarComp('x2', .5 * np.ones(self.nx)), promotes=['*'])
self.add_subsystem('x3_ini', IndepVarComp('x3', .5 * np.ones(self.nx)), promotes=['*'])
# Couplings
self.add_subsystem('y31_ini', IndepVarComp('y31', self.y31), promotes=['*'])
self.add_subsystem('y12_ini', IndepVarComp('y12', self.y12), promotes=['*'])
self.add_subsystem('y32_ini', IndepVarComp('y32', self.y32), promotes=['*'])
self.add_subsystem('y23_ini', IndepVarComp('y23', self.y23), promotes=['*'])
self.add_subsystem('y21_ini', IndepVarComp('y21', self.y21), promotes=['*'])
# Disciplines
parallel = self.add_subsystem('parallel', ParallelGroup())
parallel.add_subsystem('Structure', StructureDisc())
parallel.add_subsystem('Aerodynamics', AerodynamicsDisc())
self.add_subsystem('Propulsion', PropulsionDisc())
self.add_subsystem('Performance', PerformanceDisc())
# Shared variables z
self.connect('z', 'parallel.Structure.z')
self.connect('z', 'parallel.Aerodynamics.z')
self.connect('z', 'Propulsion.z')
self.connect('z', 'Performance.z')
# Local variables
self.connect('x1', 'parallel.Structure.x1')
self.connect('x2', 'parallel.Aerodynamics.x2')
self.connect('x3', 'Propulsion.x3')
self.connect('x1', 'Performance.x1')
self.connect('x2', 'Performance.x2')
self.connect('x3', 'Performance.x3')
# Coupling variables
self.connect('y21', 'parallel.Structure.y21')
self.connect('y31', 'parallel.Structure.y31')
self.connect('y32', 'parallel.Aerodynamics.y32')
self.connect('y12', 'parallel.Aerodynamics.y12')
self.connect('y23', 'Propulsion.y23')
# Objective function
self.add_subsystem('Obj', ExecComp('obj=range'), promotes=['obj'])
# Connections
self.connect('Performance.range', 'Obj.range')
# self.connect('Propulsion.y34', 'Performance.y34')
# self.connect('Aerodynamics.y24', 'Performance.y24')
# self.connect('Structure.y14', 'Performance.y14')
self.connect('parallel.Aerodynamics.y21', 'Performance.y21')
self.connect('Propulsion.y31', 'Performance.y31')
self.connect('Propulsion.y32', 'Performance.y32')
self.connect('parallel.Structure.y12', 'Performance.y12')
self.connect('parallel.Aerodynamics.y23', 'Performance.y23')
# Coupling constraints
for i in range(self.ny):
self.add_subsystem('con_Y12' + str(i + 1),
ExecComp('con_y12' + str(i + 1) + '=(y12[' + str(i) + '] - y12k[' + str(i) + ']) ** 2',
y12=self.y12,
y12k=self.y12
),
promotes=['con_y12' + str(i + 1)])
self.connect('parallel.Structure.y12', 'con_Y12' + str(i + 1) + '.y12')
self.connect('y12', 'con_Y12' + str(i + 1) + '.y12k')
for i in range(self.ny):
self.add_subsystem('con_Y21' + str(i + 1),
ExecComp('con_y21' + str(i + 1) + '=(y21[' + str(i) + '] - y21k[' + str(i) + ']) ** 2',
y21=self.y21,
y21k=self.y21
),
promotes=['con_y21' + str(i + 1)])
self.connect('parallel.Aerodynamics.y21', 'con_Y21' + str(i + 1) + '.y21')
self.connect('y21', 'con_Y21' + str(i + 1) + '.y21k')
for i in range(self.ny):
self.add_subsystem('con_Y32' + str(i + 1),
ExecComp('con_y32' + str(i + 1) + '=(y32[' + str(i) + '] - y32k[' + str(i) + ']) ** 2',
y32=self.y32,
y32k=self.y32
),
promotes=['con_y32' + str(i + 1)])
self.connect('Propulsion.y32', 'con_Y32' + str(i + 1) + '.y32')
self.connect('y32', 'con_Y32' + str(i + 1) + '.y32k')
for i in range(self.ny):
self.add_subsystem('con_Y23' + str(i + 1),
ExecComp('con_y23' + str(i + 1) + '=(y23[' + str(i) + '] - y23k[' + str(i) + ']) ** 2',
y23=self.y23,
y23k=self.y23
),
promotes=['con_y23' + str(i + 1)])
self.connect('parallel.Aerodynamics.y23', 'con_Y23' + str(i + 1) + '.y23')
self.connect('y23', 'con_Y23' + str(i + 1) + '.y23k')
for i in range(self.ny):
self.add_subsystem('con_Y31' + str(i + 1),
ExecComp('con_y31' + str(i + 1) + '=(y31[' + str(i) + '] - y31k[' + str(i) + ']) ** 2',
y31=self.y31,
y31k=self.y31
),
promotes=['con_y31' + str(i + 1)])
self.connect('Propulsion.y31', 'con_Y31' + str(i + 1) + '.y31')
self.connect('y31', 'con_Y31' + str(i + 1) + '.y31k')
# Local constraints
for i in range(self.nx):
self.add_subsystem('con_G1' + str(i + 1),
ExecComp('con_g1' + str(i + 1) + '=g1[' + str(i) + ']', g1=np.zeros(self.nx)),
promotes=['con_g1' + str(i + 1)])
self.connect('parallel.Structure.g1', 'con_G1' + str(i + 1) + '.g1')
for i in range(self.nx):
self.add_subsystem('con_G2' + str(i + 1),
ExecComp('con_g2' + str(i + 1) + '=g2[' + str(i) + ']', g2=np.zeros(self.nx)),
promotes=['con_g2' + str(i + 1)])
self.connect('parallel.Aerodynamics.g2', 'con_G2' + str(i + 1) + '.g2')
for i in range(self.nx):
self.add_subsystem('con_G3' + str(i + 1),
ExecComp('con_g3' + str(i + 1) + '=g3[' + str(i) + ']', g3=np.zeros(self.nx)),
promotes=['con_g3' + str(i + 1)])
self.connect('Propulsion.g3', 'con_G3' + str(i + 1) + '.g3')

TypeError: argument 1 must be ImagingCore, not ImagingCore

Under the Windows I get this error. How to fix PIL?
This is error: TypeError: argument 1 must be ImagingCore, not ImagingCore
#!/usr/bin/python
## -*- coding: utf-8 -*-
from PIL import Image, ImageFont
import ImageDraw, StringIO, string
from random import *
from math import *
import os
SITE_PATH = os.path.abspath(os.path.join(os.path.dirname(__file__), "..", ".."))
class Captcha3d(object):
_hypot = 4
_xx, _yy = 35, 70
_CIMAGE = None
_CHARS = string.ascii_lowercase + string.ascii_uppercase + string.digits
_TEXT = ''
def __init__(self):
self._CIMAGE = Image.new("RGB", (self._yy * self._hypot, self._xx * self._hypot), (255,255,255))
self.generateCode()
self.render()
def imageColorAllocate(self, r,g,b):
hexchars = "0123456789ABCDEF"
hexcolor = hexchars[r / 16] + hexchars[r % 16] + hexchars[g / 16] + hexchars[g % 16] + hexchars[b / 16] + hexchars[b % 16]
return int(hexcolor, 16)
def generateCode(self):
chars = self._CHARS
self._TEXT = "".join(choice(chars) for x in range(randint(3, 3)))
def getText(self):
return self._TEXT
def getProection(self, x1,y1,z1):
x = x1 * self._hypot
y = z1 * self._hypot
z = -y1 * self._hypot
xx = 0.707106781187
xy = 0
xz = -0.707106781187
yx = 0.408248290464
yy = 0.816496580928
yz = 0.408248290464 # 1/sqrt(6)
cx = xx*x + xy*y + xz*z
cy = yx*x + yy*y + yz*z + 20*self._hypot
return [cx, cy]
def zFunction(self, x,y):
z = 2.6
if self._CIMAGE.getpixel((y/2,x/2)) == (0,0,0):
z = 0
if z != 0:
z += float(randint(0,60))/100
z += 1.4 * sin((x+self.startX)*pi/15) * sin((y+self.startY)*pi/15)
return z
def render(self):
fontSans = ImageFont.truetype(os.path.join(SITE_PATH, "data", "fonts", "FreeSans.ttf"), 14)
draw = ImageDraw.Draw(self._CIMAGE)
whiteColor = 'white'
draw.rectangle([0, 0, self._yy * self._hypot, self._xx * self._hypot], fill=whiteColor)
#textColor = 'black'
#imgtext = Image.open("i8n.png")
#self._CIMAGE.paste(imgtext, (0,0))
imgtext = Image.new("1", (self._yy * self._hypot, self._xx * self._hypot), (1))
drawtext = ImageDraw.Draw(imgtext)
drawtext.text((1,0), self._TEXT, font=fontSans, fill=0)
self._CIMAGE.paste(imgtext, (0,0))
#draw.text((2,0), self.text, font=fontSans, fill=textColor)
self.startX = randint(0,self._xx)
self.startY = randint(0,self._yy)
crd = {}
x = 0
while x < (self._xx+1):
y = 0
while y < (self._yy+1):
crd[str(x) + '&' + str(y)] = self.getProection(x,y,self.zFunction(x,y))
y += 1
x += 1
x = 0
while x < self._xx:
y = 0
while y < self._yy:
coord = []
coord.append((int(crd[str(x) + '&' + str(y)][0]),int(crd[str(x) + '&' + str(y)][1])))
coord.append((int(crd[str(x+1) + '&' + str(y)][0]),int(crd[str(x+1) + '&' + str(y)][1])))
coord.append((int(crd[str(x+1) + '&' + str(y+1)][0]),int(crd[str(x+1) + '&' + str(y+1)][1])))
coord.append((int(crd[str(x) + '&' + str(y+1)][0]),int(crd[str(x) + '&' + str(y+1)][1])))
c = int(self.zFunction(x,y)*32)
linesColor = (c,c,c)
draw.polygon(coord, fill=whiteColor, outline=linesColor)
#draw.polygon(coord, fill=whiteColor)
y += 1
x += 1
draw.rectangle([0, 0, self._xx, self._yy], fill=whiteColor)
#draw.text((2,0), self.text, font=fontSans, fill=textColor)
#imageString($this->image, 1, 3, 0, (microtime(true)-$this->time), $textColor);
del draw
#self._CIMAGE.save("image.png", "PNG")
return [self._CIMAGE, self._TEXT]
def main():
a = Captcha3d()
print a.getText()
if __name__ == '__main__':
main()

Also happens for me on OSX 10.6.8, Python 2.6.5. I think some class is getting dynamically imported twice.
Try changing
from PIL import Image, ImageFont
to
import Image, ImageFont
That worked for me.

In my case it solved the situation to also import ImageDraw from PIL
from PIL import ImageDraw

importing all PIL things directly from PIL should always work.
However, if you mix imports, as such,
from PIL import Image
import ImageDraw
This can lead to conflict between two un-identical PIL libraries.
This can happen if you have installed both PIL and Pillow
We should really always do,
from PIL import Image
from PIL import ImageDraw
etc.
I.e. be specific about which package to use.

Error in python replace. (AttributeError: 'tuple' object has no attribute 'replace')

Environment
I am using Python 3 and my OS is Windows 7.
I understand that some commands have changed from the transition from python 2.7 to 3 (What I have used).
Problem
The variable is temporary but is this:
(((((0, 7), 7), 8), 4), 5)
Here is the code to get rid of the brackets:
randy = randy.replace(")", "")
randy = randy.replace("(", "")
randy = randy.replace(" ", "")
When it tries to execute the replace function, I get thrown an error:
Traceback (most recent call last):
File "<string>", line 248, in run_nodebug
File "Criptic.py", line 134, in <module>
randy = randy.replace(")", "")
AttributeError: 'tuple' object has no attribute 'replace'
Edit:
Here is all of the code:
#Import string
import string
import random
#Input user data
text = input("Enter your text to be converted: ")
#Test Print
print("-------------------------")
print("Your text is: ",text)
#Break up all the data
data = list(text)
#Lowercase
count = text.count("a")
count1 = text.count("b")
count2 = text.count("c")
count3 = text.count("d")
count4 = text.count("e")
count5 = text.count("f")
count6 = text.count("g")
count7 = text.count("h")
count8 = text.count("i")
count9 = text.count("j")
count10 = text.count("k")
count11 = text.count("l")
count12 = text.count("m")
count13 = text.count("n")
count14 = text.count("o")
count15 = text.count("p")
count16 = text.count("q")
count17 = text.count("r")
count18 = text.count("s")
count19 = text.count("t")
count20 = text.count("u")
count21 = text.count("v")
count22 = text.count("w")
count23 = text.count("x")
count24 = text.count("y")
count25 = text.count("z")
count26 = text.count("A")
#Uppercase
count27 = text.count("B")
count28 = text.count("C")
count29 = text.count("D")
count30 = text.count("E")
count31 = text.count("F")
count32 = text.count("G")
count33 = text.count("H")
count34 = text.count("I")
count35 = text.count("J")
count36 = text.count("K")
count37 = text.count("L")
count38 = text.count("M")
count39 = text.count("N")
count40 = text.count("O")
count41 = text.count("P")
count42 = text.count("Q")
count43 = text.count("R")
count44 = text.count("S")
count45 = text.count("T")
count46 = text.count("U")
count47 = text.count("V")
count48 = text.count("W")
count49 = text.count("X")
count50 = text.count("Y")
count51 = text.count("Z")
#Other Characters
count52 = text.count(" ")
count53 = text.count("?")
count54 = text.count("#")
count55 = text.count("(")
count56 = text.count(")")
count57 = text.count(".")
#Numbers
count58 = text.count("1")
count59 = text.count("2")
count60 = text.count("3")
count61 = text.count("4")
count62 = text.count("5")
count63 = text.count("6")
count64 = text.count("7")
count65 = text.count("8")
count66 = text.count("9")
count67 = text.count("0")
#Counting how many characters in the sentence
finalcount = count + count1 + count2 + count3 + count4 + count5 + count6 + count7 + count8 + count9 + count10 + count11 + count12 + count13 + count14 + count15 + count16 + count17 + count18 + count19 + count20 + count21 + count22 + count23 + count24 + count25 + count26 + count27 + count28 + count29 + count31 + count32 + count33 + count34 + count35 + count36 + count37 + count38 + count39 + count40 + count41 + count42 + count43 + count44 + count45 + count46 + count47 + count48 + count49 + count50 + count51 + count52 + count53 + count54 + count55 + count56 + count57 + count58 + count59 + count60 + count61 + count62 + count63 + count64 + count65 + count66 + count67
#Final count of Characters
print(" Chars: ",finalcount)
print("-------------------------")
char = "ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz!##$%^&*()?_+-=1234567890 "
charnum = 74 + 11
list(char)
randy = 0
num = 0
while num < finalcount:
rand = random.randrange(1,9)
randy = randy,rand
finalcount = finalcount - 1
if rand == 1:
print(text[finalcount],char[random.randrange(0,charnum)],char[random.randrange(0,charnum)],char[random.randrange(0,charnum)],char[random.randrange(0,charnum)],char[random.randrange(0,charnum)],char[random.randrange(0,charnum)],char[random.randrange(0,charnum)],char[random.randrange(0,charnum)],",")
if rand == 2:
print(char[random.randrange(0,charnum)],text[finalcount],char[random.randrange(0,charnum)],char[random.randrange(0,charnum)],char[random.randrange(0,charnum)],char[random.randrange(0,charnum)],char[random.randrange(0,charnum)],char[random.randrange(0,charnum)],char[random.randrange(0,charnum)],",")
if rand == 3:
print(char[random.randrange(0,charnum)],char[random.randrange(0,charnum)],text[finalcount],char[random.randrange(0,charnum)],char[random.randrange(0,charnum)],char[random.randrange(0,charnum)],char[random.randrange(0,charnum)],char[random.randrange(0,charnum)],char[random.randrange(0,charnum)],",")
if rand == 4:
print(char[random.randrange(0,charnum)],char[random.randrange(0,charnum)],char[random.randrange(0,charnum)],text[finalcount],char[random.randrange(0,charnum)],char[random.randrange(0,charnum)],char[random.randrange(0,charnum)],char[random.randrange(0,charnum)],char[random.randrange(0,charnum)],",")
if rand == 5:
print(char[random.randrange(0,charnum)],char[random.randrange(0,charnum)],char[random.randrange(0,charnum)],char[random.randrange(0,charnum)],text[finalcount],char[random.randrange(0,charnum)],char[random.randrange(0,charnum)],char[random.randrange(0,charnum)],char[random.randrange(0,charnum)],",")
if rand == 6:
print(char[random.randrange(0,charnum)],char[random.randrange(0,charnum)],char[random.randrange(0,charnum)],char[random.randrange(0,charnum)],char[random.randrange(0,charnum)],text[finalcount],char[random.randrange(0,charnum)],char[random.randrange(0,charnum)],char[random.randrange(0,charnum)],",")
if rand == 7:
print(char[random.randrange(0,charnum)],char[random.randrange(0,charnum)],char[random.randrange(0,charnum)],char[random.randrange(0,charnum)],char[random.randrange(0,charnum)],char[random.randrange(0,charnum)],text[finalcount],char[random.randrange(0,charnum)],char[random.randrange(0,charnum)],",")
if rand == 8:
print(char[random.randrange(0,charnum)],char[random.randrange(0,charnum)],char[random.randrange(0,charnum)],char[random.randrange(0,charnum)],char[random.randrange(0,charnum)],char[random.randrange(0,charnum)],char[random.randrange(0,charnum)],text[finalcount],char[random.randrange(0,charnum)],",")
if rand == 9:
print(char[random.randrange(0,charnum)],char[random.randrange(0,charnum)],char[random.randrange(0,charnum)],char[random.randrange(0,charnum)],char[random.randrange(0,charnum)],char[random.randrange(0,charnum)],char[random.randrange(0,charnum)],char[random.randrange(0,charnum)],text[finalcount],",")
randy = randy.replace(")", "")
randy = randy.replace("(", "")
randy = randy.replace(" ", "")
print("-------------------------")
print("::::::::Completed::::::::")
print("-------------------------")
print(randy)
print("-This is your code unlock key. Without this code it will not decript!!!! ")
print("-------------------------")

You have a tuple (a sort of list) of numbers, and you want to make that a string. You can't replace the brackets, they aren't a part of the variable, they are just a part of its representation.
Instead you should use join() and str()
result = " ".join(str(x) for x in randy)
However, this probably will not give the right result either, as it is a nested list of tuples. You probably mean: randy = randy + (rand,) instead if randy = randy,rand.

randy = randy,rand
This notation creates a tuple of two elements, tuples do not have a method called replace.
If you just want to concatenate the numbers into a list representation separated by commas, you could do this in your loop:
randy = []
num = 0
while num < finalcount:
rand = random.randrange(1,9)
randy.append(rand)
Then you remove the replace lines, and instead do this
randy = ",".join(randy)
to get a string that has the values separated by commas.
You should maybe add the output that you would like to get to your question, because at the moment it's not quite clear what you want to do exactly.

exam_st_date = (11, 12, 2014)
# Sample Output : The examination will start from : 11 / 12 / 2014
newtup = str(exam_st_date).replace(',', ' /')
print(newtup)
look at mine example should give you some results

To delete a list of characters, you could use the string's translate method:
import string
name = "(((((0, 7), 7), 8), 4), 5)"
table = string.maketrans( '', '', )
print name.translate(table,"()")