def examsOutputPage(request): import exams_model chem_name = request.POST.get('chemical_name') scenarios =request.POST.get('scenarios') farm =request.POST.get('farm_pond') mw = request.POST.get('molecular_weight') sol = request.POST.get('solubility') koc = request.POST.get('Koc') vp = request.POST.get('vapor_pressure') aem = request.POST.get('aerobic_aquatic_metabolism') anm = request.POST.get('anaerobic_aquatic_metabolism') aqp = request.POST.get('aquatic_direct_photolysis') tmper = request.POST.get('temperature') n_ph = float(request.POST.get('n_ph')) ph_out = [] hl_out = [] for i in range(int(n_ph)): j=i+1 ph_temp = request.POST.get('ph'+str(j)) ph_out.append(float(ph_temp)) hl_temp = float(request.POST.get('hl'+str(j))) hl_out.append(hl_temp) exams_obj = exams_model.exams(chem_name, scenarios, farm, mw, sol, koc, vp, aem, anm, aqp, tmper, n_ph, ph_out, hl_out) return exams_obj
import subprocess import numpy as np from scipy.optimize import leastsq import zipfile from boto.s3.connection import S3Connection from boto.s3.key import Key from boto.s3.bucket import Bucket import string import random import operator import re # from ubertool_src import keys_Picloud_S3 import keys_Picloud_S3 exams_obj = exams_model.exams('chem_name_1', 'CA Almonds MLRA-17', 'Yes', 70, 71, 72, 73, 24, 25, 26, 27, 3, [5.0, 7.0, 11.0], [11.0, 12.0, 10.0]) def exams_pi(exams_obj): # Generate a random ID for file save def id_generator(size=6, chars=string.ascii_uppercase + string.digits): return ''.join(random.choice(chars) for x in range(size)) name_temp = id_generator() ################################################################################## ######Create a folder if it does not existed, where holds calculations' output.##### ################################################################################## cwd = os.getcwd() + '/exams_test' print("cwd=" + cwd)