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How to use raw_data method in lisa

Best Python code snippet using lisa_python

views.py

Source:views.py

1import datetime2from django.core.exceptions import ValidationError3from django.http import Http404, HttpResponse, HttpResponseRedirect4from django.shortcuts import render, redirect, get_object_or_4045from django.http import HttpResponseForbidden6from django.views.generic.base import TemplateView7from django.views.generic.edit import FormView8from django.views.static import serve9from django.urls import reverse10import hashlib11import os, csv, numpy12import pprint131415from honeypeartea.forms import cmaInput, ngaInput, louvreInput,rijksInput, randomInput1617PROJECT_ROOT = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))1819# Create your views here.20def index(request):21    return render(request, 'index.html')2223def cma(request):24    return render(request, 'cma.html')2526def nga(request):27    return render(request, 'nga.html')2829def louvre(request):30    return render(request, 'louvre.html')3132def rijksmuseum(request):33    return render(request, 'rijksmuseum.html')3435def random(request):36    return render(request, 'random.html')3738394041class cma_form(TemplateView):42    templatename = 'cma.html'4344    def csv2list(self, csvpath):45        with open(csvpath, newline='') as f:46            reader = csv.reader(f)47            header = next(reader)48            data = list(reader)49            return data5051    def get(self, request):52        form = cmaInput()53        return render(request, self. templatename, {'form': form})5455    def post(self, request):56        form = cmaInput(request.POST)57        if form.is_valid():58            dict = {}59            raw_data = []60            art_name = form.cleaned_data['art_name']61            artists = form.cleaned_data['artists']62            all = self.csv2list(os.path.join(PROJECT_ROOT, 'static/resource/cleveland_with_rec.csv'))63            if artists != 'none':64                data = self.csv2list(os.path.join(PROJECT_ROOT, 'static/artist/cleveland_artists.csv'))65                for row in data:66                    if row[0] == artists:67                        raw_data = row68                        break69            elif art_name != "":70                raw_data = []71                for row in all:72                    if row[1] == art_name:73                        raw_data = row[9:]74                        break7576            if raw_data != []:77                dict = {78                    'a': {'name': 'Art name: ' + all[int(raw_data[1])][1], 'year': 'Year: ' + all[int(raw_data[1])][2],79                          'text': "Description: " + (80                              all[int(raw_data[1])][8] if all[int(raw_data[1])][8] != "" else all[int(raw_data[1])][5]),81                          'link': all[int(raw_data[1])][6]},82                    'b': {'name': 'Art name: ' + all[int(raw_data[2])][1], 'year': 'Year: ' + all[int(raw_data[2])][2],83                          'text': "Description: " + (84                              all[int(raw_data[2])][8] if all[int(raw_data[2])][8] != "" else all[int(raw_data[2])][5]),85                          'link': all[int(raw_data[2])][6]},86                    'c': {'name': 'Art name: ' + all[int(raw_data[3])][1], 'year': 'Year: ' + all[int(raw_data[3])][2],87                          'text': "Description: " + (88                              all[int(raw_data[3])][8] if all[int(raw_data[3])][8] != "" else all[int(raw_data[3])][5]),89                          'link': all[int(raw_data[3])][6]},90                    'd': {'name': 'Art name: ' + all[int(raw_data[4])][1], 'year': 'Year: ' + all[int(raw_data[4])][2],91                          'text': "Description: " + (92                              all[int(raw_data[4])][8] if all[int(raw_data[4])][8] != "" else all[int(raw_data[4])][5]),93                          'link': all[int(raw_data[4])][6]},94                    'e': {'name': 'Art name: ' + all[int(raw_data[5])][1], 'year': 'Year: ' + all[int(raw_data[5])][2],95                          'text': "Description: " + (96                              all[int(raw_data[5])][8] if all[int(raw_data[5])][8] != "" else all[int(raw_data[5])][5]),97                          'link': all[int(raw_data[5])][6]},98                    'f': {'name': 'Art name: ' + all[int(raw_data[6])][1], 'year': 'Year: ' + all[int(raw_data[6])][2],99                          'text': "Description: " + (100                              all[int(raw_data[6])][8] if all[int(raw_data[6])][8] != "" else all[int(raw_data[6])][5]),101                          'link': all[int(raw_data[6])][6]},102                    'g': {'name': 'Art name: ' + all[int(raw_data[7])][1], 'year': 'Year: ' + all[int(raw_data[7])][2],103                          'text': "Description: " + (104                              all[int(raw_data[7])][8] if all[int(raw_data[7])][8] != "" else all[int(raw_data[7])][5]),105                          'link': all[int(raw_data[7])][6]},106                    'h': {'name': 'Art name: ' + all[int(raw_data[8])][1], 'year': 'Year: ' + all[int(raw_data[8])][2],107                          'text': "Description: " + (108                              all[int(raw_data[8])][8] if all[int(raw_data[8])][8] != "" else all[int(raw_data[8])][5]),109                          'link': all[int(raw_data[8])][6]},110                    'i': {'name': 'Art name: ' + all[int(raw_data[9])][1], 'year': 'Year: ' + all[int(raw_data[9])][2],111                          'text': "Description: " + (112                              all[int(raw_data[9])][8] if all[int(raw_data[9])][8] != "" else all[int(raw_data[9])][5]),113                          'link': all[int(raw_data[9])][6]},114                    'j': {'name': 'Art name: ' + all[int(raw_data[10])][1],115                          'year': 'Year: ' + all[int(raw_data[10])][2],116                          'text': "Description: " + (117                              all[int(raw_data[10])][8] if all[int(raw_data[10])][8] != "" else all[int(raw_data[10])][118                                  5]), 'link': all[int(raw_data[10])][6]},119                }120121            if dict =={}:122                result = "Please enter valid artwork name or select artist"123            else:124                result = dict125126        args = {'form': form, 'result': result}127        return render(request, self.templatename, args)128129130class nga_form(TemplateView):131    templatename = 'nga.html'132133    def csv2list(self, csvpath):134        with open(csvpath, newline='') as f:135            reader = csv.reader(f)136            header = next(reader)137            data = list(reader)138            return data139140    def get(self, request):141        form = ngaInput()142        return render(request, self. templatename, {'form': form})143144    def post(self, request):145        form = ngaInput(request.POST)146        if form.is_valid():147            dict = {}148            raw_data = []149            art_name = form.cleaned_data['art_name']150            artists = form.cleaned_data['artists']151            all = self.csv2list(os.path.join(PROJECT_ROOT, 'static/resource/nga_with_rec.csv'))152            if artists != 'none':153                data = self.csv2list(os.path.join(PROJECT_ROOT, 'static/artist/nga_artists.csv'))154                for row in data:155                    if row[0] == artists:156                        raw_data = row157                        break158            elif art_name != "":159                raw_data = []160                for row in all:161                    if row[1] == art_name:162                        raw_data = row[10:]163                        break164165            if raw_data != []:166                dict = {167                    'a': {'name': 'Art name: ' + all[int(raw_data[1])][1], 'year': 'Year: ' + all[int(raw_data[1])][2],168                          'text': "Description: " + (169                              all[int(raw_data[1])][10] if all[int(raw_data[1])][10] != "" else all[int(raw_data[1])][8]),170                          'link': all[int(raw_data[1])][9]},171                    'b': {'name': 'Art name: ' + all[int(raw_data[2])][1], 'year': 'Year: ' + all[int(raw_data[2])][2],172                          'text': "Description: " + (173                              all[int(raw_data[2])][10] if all[int(raw_data[2])][10] != "" else all[int(raw_data[2])][8]),174                          'link': all[int(raw_data[2])][9]},175                    'c': {'name': 'Art name: ' + all[int(raw_data[3])][1], 'year': 'Year: ' + all[int(raw_data[3])][2],176                          'text': "Description: " + (177                              all[int(raw_data[3])][10] if all[int(raw_data[3])][10] != "" else all[int(raw_data[3])][8]),178                          'link': all[int(raw_data[3])][9]},179                    'd': {'name': 'Art name: ' + all[int(raw_data[4])][1], 'year': 'Year: ' + all[int(raw_data[4])][2],180                          'text': "Description: " + (181                              all[int(raw_data[4])][10] if all[int(raw_data[4])][10] != "" else all[int(raw_data[4])][8]),182                          'link': all[int(raw_data[4])][9]},183                    'e': {'name': 'Art name: ' + all[int(raw_data[5])][1], 'year': 'Year: ' + all[int(raw_data[5])][2],184                          'text': "Description: " + (185                              all[int(raw_data[5])][10] if all[int(raw_data[5])][10] != "" else all[int(raw_data[5])][8]),186                          'link': all[int(raw_data[5])][9]},187                    'f': {'name': 'Art name: ' + all[int(raw_data[6])][1], 'year': 'Year: ' + all[int(raw_data[6])][2],188                          'text': "Description: " + (189                              all[int(raw_data[6])][10] if all[int(raw_data[6])][10] != "" else all[int(raw_data[6])][8]),190                          'link': all[int(raw_data[6])][9]},191                    'g': {'name': 'Art name: ' + all[int(raw_data[7])][1], 'year': 'Year: ' + all[int(raw_data[7])][2],192                          'text': "Description: " + (193                              all[int(raw_data[7])][10] if all[int(raw_data[7])][10] != "" else all[int(raw_data[7])][8]),194                          'link': all[int(raw_data[7])][9]},195                    'h': {'name': 'Art name: ' + all[int(raw_data[8])][1], 'year': 'Year: ' + all[int(raw_data[8])][2],196                          'text': "Description: " + (197                              all[int(raw_data[8])][10] if all[int(raw_data[8])][10] != "" else all[int(raw_data[8])][8]),198                          'link': all[int(raw_data[8])][9]},199                    'i': {'name': 'Art name: ' + all[int(raw_data[9])][1], 'year': 'Year: ' + all[int(raw_data[9])][2],200                          'text': "Description: " + (201                              all[int(raw_data[9])][10] if all[int(raw_data[9])][10] != "" else all[int(raw_data[9])][8]),202                          'link': all[int(raw_data[9])][9]},203                    'j': {'name': 'Art name: ' + all[int(raw_data[10])][1],204                          'year': 'Year: ' + all[int(raw_data[10])][2],205                          'text': "Description: " + (206                              all[int(raw_data[10])][10] if all[int(raw_data[10])][10] != "" else all[int(raw_data[10])][207                                  8]), 'link': all[int(raw_data[10])][9]},208                }209210            if dict =={}:211                result = "Please enter valid artwork name or select artist"212            else:213                result = dict214215        args = {'form': form, 'result': result}216        return render(request, self.templatename, args)217218219class louvre_form(TemplateView):220    templatename = 'louvre.html'221222    def csv2list(self, csvpath):223        with open(csvpath, newline='') as f:224            reader = csv.reader(f)225            header = next(reader)226            data = list(reader)227            return data228229    def get(self, request):230        form = louvreInput()231        return render(request, self. templatename, {'form': form})232233    def post(self, request):234        form = louvreInput(request.POST)235        if form.is_valid():236            dict = {}237            raw_data = []238            art_name = form.cleaned_data['art_name']239            artists = form.cleaned_data['artists']240            all = self.csv2list(os.path.join(PROJECT_ROOT, 'static/resource/louvre_with_rec.csv'))241            if artists != 'none':242                data = self.csv2list(os.path.join(PROJECT_ROOT, 'static/artist/louvre_artists.csv'))243                for row in data:244                    if row[0] == artists:245                        raw_data = row246                        break247            elif art_name != "":248                raw_data = []249                for row in all:250                    if row[1] == art_name:251                        raw_data = row[11:]252                        break253254            if raw_data != []:255                dict = {256                    'a': {'name': 'Art name: ' + all[int(raw_data[1])][1], 'year': 'Year: ' + all[int(raw_data[1])][3],257                          'text': "Description: " + (258                              all[int(raw_data[1])][11] if all[int(raw_data[1])][11] != "" else all[int(raw_data[1])][6]),259                          'link': all[int(raw_data[1])][5]},260                    'b': {'name': 'Art name: ' + all[int(raw_data[2])][1], 'year': 'Year: ' + all[int(raw_data[2])][3],261                          'text': "Description: " + (262                              all[int(raw_data[2])][11] if all[int(raw_data[2])][11] != "" else all[int(raw_data[2])][6]),263                          'link': all[int(raw_data[2])][5]},264                    'c': {'name': 'Art name: ' + all[int(raw_data[3])][1], 'year': 'Year: ' + all[int(raw_data[3])][3],265                          'text': "Description: " + (266                              all[int(raw_data[3])][11] if all[int(raw_data[3])][11] != "" else all[int(raw_data[3])][6]),267                          'link': all[int(raw_data[3])][5]},268                    'd': {'name': 'Art name: ' + all[int(raw_data[4])][1], 'year': 'Year: ' + all[int(raw_data[4])][3],269                          'text': "Description: " + (270                              all[int(raw_data[4])][11] if all[int(raw_data[4])][11] != "" else all[int(raw_data[4])][6]),271                          'link': all[int(raw_data[4])][5]},272                    'e': {'name': 'Art name: ' + all[int(raw_data[5])][1], 'year': 'Year: ' + all[int(raw_data[5])][3],273                          'text': "Description: " + (274                              all[int(raw_data[5])][11] if all[int(raw_data[5])][11] != "" else all[int(raw_data[5])][6]),275                          'link': all[int(raw_data[5])][5]},276                    'f': {'name': 'Art name: ' + all[int(raw_data[6])][1], 'year': 'Year: ' + all[int(raw_data[6])][3],277                          'text': "Description: " + (278                              all[int(raw_data[6])][11] if all[int(raw_data[6])][11] != "" else all[int(raw_data[6])][6]),279                          'link': all[int(raw_data[6])][5]},280                    'g': {'name': 'Art name: ' + all[int(raw_data[7])][1], 'year': 'Year: ' + all[int(raw_data[7])][3],281                          'text': "Description: " + (282                              all[int(raw_data[7])][11] if all[int(raw_data[7])][11] != "" else all[int(raw_data[7])][6]),283                          'link': all[int(raw_data[7])][5]},284                    'h': {'name': 'Art name: ' + all[int(raw_data[8])][1], 'year': 'Year: ' + all[int(raw_data[8])][3],285                          'text': "Description: " + (286                              all[int(raw_data[8])][11] if all[int(raw_data[8])][11] != "" else all[int(raw_data[8])][6]),287                          'link': all[int(raw_data[8])][5]},288                    'i': {'name': 'Art name: ' + all[int(raw_data[9])][1], 'year': 'Year: ' + all[int(raw_data[9])][3],289                          'text': "Description: " + (290                              all[int(raw_data[9])][11] if all[int(raw_data[9])][11] != "" else all[int(raw_data[9])][6]),291                          'link': all[int(raw_data[9])][5]},292                    'j': {'name': 'Art name: ' + all[int(raw_data[10])][1],293                          'year': 'Year: ' + all[int(raw_data[10])][3],294                          'text': "Description: " + (295                              all[int(raw_data[10])][11] if all[int(raw_data[10])][11] != "" else all[int(raw_data[10])][296                                  6]), 'link': all[int(raw_data[10])][5]},297                }298299            if dict =={}:300                result = "Please enter valid artwork name or select artist"301            else:302                result = dict303304        args = {'form': form, 'result': result}305        return render(request, self.templatename, args)306307308class rijks_form(TemplateView):309    templatename = 'rijksmuseum.html'310311    def csv2list(self, csvpath):312        with open(csvpath, newline='') as f:313            reader = csv.reader(f)314            header = next(reader)315            data = list(reader)316            return data317318    def get(self, request):319        form = rijksInput()320        return render(request, self. templatename, {'form': form})321322    def post(self, request):323        form = rijksInput(request.POST)324        if form.is_valid():325            dict = {}326            raw_data = []327            art_name = form.cleaned_data['art_name']328            artists = form.cleaned_data['artists']329            all = self.csv2list(os.path.join(PROJECT_ROOT, 'static/resource/rijks_with_rec.csv'))330            if artists != 'none':331                data = self.csv2list(os.path.join(PROJECT_ROOT, 'static/artist/rijks_artists.csv'))332                for row in data:333                    if row[0] == artists:334                        raw_data = row335                        break336            elif art_name != "":337                raw_data = []338                for row in all:339                    if row[1] == art_name:340                        raw_data = row[10:21]341                        break342343            if raw_data != []:344345                dict = {346                    'a': {'name': 'Art name: ' + all[int(raw_data[1])][1], 'year': 'Year: ' + all[int(raw_data[1])][3],347                          'text': "Description: " + (348                              all[int(raw_data[1])][9] if all[int(raw_data[1])][9] != "" else all[int(raw_data[1])][5]),349                          'link': all[int(raw_data[1])][-1]},350                    'b': {'name': 'Art name: ' + all[int(raw_data[2])][1], 'year': 'Year: ' + all[int(raw_data[2])][3],351                          'text': "Description: " + (352                              all[int(raw_data[2])][9] if all[int(raw_data[2])][9] != "" else all[int(raw_data[2])][5]),353                          'link': all[int(raw_data[2])][-1]},354                    'c': {'name': 'Art name: ' + all[int(raw_data[3])][1], 'year': 'Year: ' + all[int(raw_data[3])][3],355                          'text': "Description: " + (356                              all[int(raw_data[3])][9] if all[int(raw_data[3])][9] != "" else all[int(raw_data[3])][5]),357                          'link': all[int(raw_data[3])][-1]},358                    'd': {'name': 'Art name: ' + all[int(raw_data[4])][1], 'year': 'Year: ' + all[int(raw_data[4])][3],359                          'text': "Description: " + (360                              all[int(raw_data[4])][9] if all[int(raw_data[4])][9] != "" else all[int(raw_data[4])][5]),361                          'link': all[int(raw_data[4])][-1]},362                    'e': {'name': 'Art name: ' + all[int(raw_data[5])][1], 'year': 'Year: ' + all[int(raw_data[5])][3],363                          'text': "Description: " + (364                              all[int(raw_data[5])][9] if all[int(raw_data[5])][9] != "" else all[int(raw_data[5])][5]),365                          'link': all[int(raw_data[5])][-1]},366                    'f': {'name': 'Art name: ' + all[int(raw_data[6])][1], 'year': 'Year: ' + all[int(raw_data[6])][3],367                          'text': "Description: " + (368                              all[int(raw_data[6])][9] if all[int(raw_data[6])][9] != "" else all[int(raw_data[6])][5]),369                          'link': all[int(raw_data[6])][-1]},370                    'g': {'name': 'Art name: ' + all[int(raw_data[7])][1], 'year': 'Year: ' + all[int(raw_data[7])][3],371                          'text': "Description: " + (372                              all[int(raw_data[7])][9] if all[int(raw_data[7])][9] != "" else all[int(raw_data[7])][5]),373                          'link': all[int(raw_data[7])][-1]},374                    'h': {'name': 'Art name: ' + all[int(raw_data[8])][1], 'year': 'Year: ' + all[int(raw_data[8])][3],375                          'text': "Description: " + (376                              all[int(raw_data[8])][9] if all[int(raw_data[8])][9] != "" else all[int(raw_data[8])][5]),377                          'link': all[int(raw_data[8])][-1]},378                    'i': {'name': 'Art name: ' + all[int(raw_data[9])][1], 'year': 'Year: ' + all[int(raw_data[9])][3],379                          'text': "Description: " + (380                              all[int(raw_data[9])][9] if all[int(raw_data[9])][9] != "" else all[int(raw_data[9])][5]),381                          'link': all[int(raw_data[9])][-1]},382                    'j': {'name': 'Art name: ' + all[int(raw_data[10])][1],383                          'year': 'Year: ' + all[int(raw_data[10])][3],384                          'text': "Description: " + (385                              all[int(raw_data[10])][9] if all[int(raw_data[10])][9] != "" else all[int(raw_data[10])][386                                  5]), 'link': all[int(raw_data[10])][-1]},387                }388389            if dict =={}:390                result = "Please enter valid artwork name or select artist"391            else:392                result = dict393394        args = {'form': form, 'result': result}395        return render(request, self.templatename, args)396397class random_form(TemplateView):398    templatename = 'random.html'399400    def csv2list(self, csvpath):401        with open(csvpath, newline='') as f:402            reader = csv.reader(f)403            header = next(reader)404            data = list(reader)405            return data406407    def get(self, request):408        form = randomInput()409        return render(request, self. templatename, {'form': form})410411    def post(self, request):412        form = randomInput(request.POST)413        if form.is_valid():414            dict = {}415            raw_data = []416            text = form.cleaned_data['text']417            color = form.cleaned_data['color']418            cma = self.csv2list(os.path.join(PROJECT_ROOT, 'static/resource/cleveland_with_rec.csv'))419            nga =  self.csv2list(os.path.join(PROJECT_ROOT, 'static/resource/nga_with_rec.csv'))420            louvre = self.csv2list(os.path.join(PROJECT_ROOT, 'static/resource/louvre_with_rec.csv'))421            rijks = self.csv2list(os.path.join(PROJECT_ROOT, 'static/resource/rijks_with_rec.csv'))422423            if text != "":424                raw_data = numpy.random.randint(low = 0, high = len(cma), size = 11)425                raw_data = [int(i) for i in raw_data]426                if raw_data != []:427                    dict = {428                        'a': {'name': 'Art name: ' + cma[int(raw_data[1])][1],429                              'year': 'Year: ' + cma[int(raw_data[1])][2],430                              'text': "Description: " + (431                                  cma[int(raw_data[1])][8] if cma[int(raw_data[1])][8] != "" else cma[int(raw_data[1])][432                                      5]),433                              'link': cma[int(raw_data[1])][6]},434                        'b': {'name': 'Art name: ' + cma[int(raw_data[2])][1],435                              'year': 'Year: ' + cma[int(raw_data[2])][2],436                              'text': "Description: " + (437                                  cma[int(raw_data[2])][8] if cma[int(raw_data[2])][8] != "" else cma[int(raw_data[2])][438                                      5]),439                              'link': cma[int(raw_data[2])][6]},440                        'c': {'name': 'Art name: ' + nga[int(raw_data[3])][1],441                              'year': 'Year: ' + nga[int(raw_data[3])][2],442                              'text': "Description: " + (443                                  nga[int(raw_data[3])][10] if nga[int(raw_data[3])][10] != "" else444                                  nga[int(raw_data[3])][8]),445                              'link': nga[int(raw_data[3])][9]},446                        'd': {'name': 'Art name: ' + nga[int(raw_data[4])][1],447                              'year': 'Year: ' + nga[int(raw_data[4])][2],448                              'text': "Description: " + (449                                  nga[int(raw_data[4])][10] if nga[int(raw_data[4])][10] != "" else450                                  nga[int(raw_data[4])][8]),451                              'link': nga[int(raw_data[4])][9]},452                        'e': {'name': 'Art name: ' + louvre[int(raw_data[5])][1],453                              'year': 'Year: ' + louvre[int(raw_data[5])][3],454                              'text': "Description: " + (455                                  louvre[int(raw_data[5])][11] if louvre[int(raw_data[5])][11] != "" else456                                  louvre[int(raw_data[5])][457                                      6]),458                              'link': louvre[int(raw_data[5])][5]},459                        'f': {'name': 'Art name: ' + louvre[int(raw_data[6])][1],460                              'year': 'Year: ' + louvre[int(raw_data[6])][3],461                              'text': "Description: " + (462                                  louvre[int(raw_data[6])][11] if louvre[int(raw_data[6])][11] != "" else463                                  louvre[int(raw_data[6])][464                                      6]),465                              'link': louvre[int(raw_data[6])][5]},466                        'g': {'name': 'Art name: ' + louvre[int(raw_data[7])][1],467                              'year': 'Year: ' + louvre[int(raw_data[7])][3],468                              'text': "Description: " + (469                                  louvre[int(raw_data[7])][11] if louvre[int(raw_data[7])][11] != "" else470                                  louvre[int(raw_data[7])][471                                      6]),472                              'link': louvre[int(raw_data[7])][5]},473                        'h': {'name': 'Art name: ' + louvre[int(raw_data[8])][1],474                              'year': 'Year: ' + louvre[int(raw_data[8])][3],475                              'text': "Description: " + (476                                  louvre[int(raw_data[8])][11] if louvre[int(raw_data[8])][11] != "" else477                                  louvre[int(raw_data[8])][478                                      6]),479                              'link': louvre[int(raw_data[8])][5]},480                        'i': {'name': 'Art name: ' + rijks[int(raw_data[9])][1],481                              'year': 'Year: ' + rijks[int(raw_data[9])][3],482                              'text': "Description: " + (483                                  rijks[int(raw_data[9])][9] if rijks[int(raw_data[9])][9] != "" else484                                  rijks[int(raw_data[9])][5]),485                              'link': rijks[int(raw_data[9])][-1]},486                        'j': {'name': 'Art name: ' + rijks[int(raw_data[10])][1],487                              'year': 'Year: ' + rijks[int(raw_data[10])][3],488                              'text': "Description: " + (489                                  rijks[int(raw_data[10])][9] if rijks[int(raw_data[10])][9] != "" else490                                  rijks[int(raw_data[10])][491                                      5]), 'link': rijks[int(raw_data[10])][-1]},492                    }493            elif color != 'none':494                color_nga = self.csv2list(os.path.join(PROJECT_ROOT, 'static/resource/color_nga.csv'))495                if color == 'red':496                    raw_data = color_nga[0]497                elif color == 'blue':498                    raw_data = color_nga[1]499                elif color == 'green':500                    raw_data = color_nga[2]501                if raw_data != []:502                    all = nga503                    dict = {504                        'a': {'name': 'Art name: ' + all[int(raw_data[1])][1],505                              'year': 'Year: ' + all[int(raw_data[1])][2],506                              'text': "Description: " + (507                                  all[int(raw_data[1])][10] if all[int(raw_data[1])][10] != "" else508                                  all[int(raw_data[1])][8]),509                              'link': all[int(raw_data[1])][9]},510                        'b': {'name': 'Art name: ' + all[int(raw_data[2])][1],511                              'year': 'Year: ' + all[int(raw_data[2])][2],512                              'text': "Description: " + (513                                  all[int(raw_data[2])][10] if all[int(raw_data[2])][10] != "" else514                                  all[int(raw_data[2])][8]),515                              'link': all[int(raw_data[2])][9]},516                        'c': {'name': 'Art name: ' + all[int(raw_data[3])][1],517                              'year': 'Year: ' + all[int(raw_data[3])][2],518                              'text': "Description: " + (519                                  all[int(raw_data[3])][10] if all[int(raw_data[3])][10] != "" else520                                  all[int(raw_data[3])][8]),521                              'link': all[int(raw_data[3])][9]},522                        'd': {'name': 'Art name: ' + all[int(raw_data[4])][1],523                              'year': 'Year: ' + all[int(raw_data[4])][2],524                              'text': "Description: " + (525                                  all[int(raw_data[4])][10] if all[int(raw_data[4])][10] != "" else526                                  all[int(raw_data[4])][8]),527                              'link': all[int(raw_data[4])][9]},528                        'e': {'name': 'Art name: ' + all[int(raw_data[5])][1],529                              'year': 'Year: ' + all[int(raw_data[5])][2],530                              'text': "Description: " + (531                                  all[int(raw_data[5])][10] if all[int(raw_data[5])][10] != "" else532                                  all[int(raw_data[5])][8]),533                              'link': all[int(raw_data[5])][9]},534                        'f': {'name': 'Art name: ' + all[int(raw_data[6])][1],535                              'year': 'Year: ' + all[int(raw_data[6])][2],536                              'text': "Description: " + (537                                  all[int(raw_data[6])][10] if all[int(raw_data[6])][10] != "" else538                                  all[int(raw_data[6])][8]),539                              'link': all[int(raw_data[6])][9]},540                        'g': {'name': 'Art name: ' + all[int(raw_data[7])][1],541                              'year': 'Year: ' + all[int(raw_data[7])][2],542                              'text': "Description: " + (543                                  all[int(raw_data[7])][10] if all[int(raw_data[7])][10] != "" else544                                  all[int(raw_data[7])][8]),545                              'link': all[int(raw_data[7])][9]},546                        'h': {'name': 'Art name: ' + all[int(raw_data[8])][1],547                              'year': 'Year: ' + all[int(raw_data[8])][2],548                              'text': "Description: " + (549                                  all[int(raw_data[8])][10] if all[int(raw_data[8])][10] != "" else550                                  all[int(raw_data[8])][8]),551                              'link': all[int(raw_data[8])][9]},552                        'i': {'name': 'Art name: ' + all[int(raw_data[9])][1],553                              'year': 'Year: ' + all[int(raw_data[9])][2],554                              'text': "Description: " + (555                                  all[int(raw_data[9])][10] if all[int(raw_data[9])][10] != "" else556                                  all[int(raw_data[9])][8]),557                              'link': all[int(raw_data[9])][9]},558                        'j': {'name': 'Art name: ' + all[int(raw_data[10])][1],559                              'year': 'Year: ' + all[int(raw_data[10])][2],560                              'text': "Description: " + (561                                  all[int(raw_data[10])][10] if all[int(raw_data[10])][10] != "" else562                                  all[int(raw_data[10])][563                                      8]), 'link': all[int(raw_data[10])][9]},564                    }565566567568569570            if dict =={}:571                result = "Please enter valid text or select color"572            else:573                result = dict574575        args = {'form': form, 'result': result}
...

capping.py

Source:capping.py

1# Takes in the total market cap as a float and a dictionary of dictionaries2# with at least the attributes mentioned below, if more attributes are passed3# in, they are ignored and returned as is, if there were calculations based on4# any of the attributes mentioned below prior to passing them in, they will5# need to be updated.6#7# There should be an entry with the following structure for each market in the8# index (regardless of the need for capping):9#10# sample = {index/symbol1: {'market_cap':         float,11#                           'price':              float,12#                           'circulating_supply': int   }, (repeat x times)}13INITIAL_INVESTMENT = 100000014class RussellCapping:15    def __init__(self, total_mc=None, raw_data=None, capping_percent=None):16        self.initial_total_mc = 702863579317        self.raw_data = {'1': {'symbol': 'btc', 'name': 'bitcoin', 'market_cap': 6487950808, 'price': 431.45, 'circulating supply': 15037467, '24hr volume': '28221886', 'percent_mc': 0.9230739789450348, 'weighted_dollar_mc': 923073.9789450348, 'num_coins': 2139.4691828602035}, '2': {'symbol': 'xrp', 'name': 'ripple', 'market_cap': 202989110, 'price': 0.006053, 'circulating supply': 33537439933, '24hr volume': '273625', 'percent_mc': 0.028880299958373445, 'weighted_dollar_mc': 28880.299958373445, 'num_coins': 4771237.396063678}, '3': {'symbol': 'ltc', 'name': 'litecoin', 'market_cap': 153184845, 'price': 3.49, 'circulating supply': 43878995, '24hr volume': '1948999', 'percent_mc': 0.021794392185260296, 'weighted_dollar_mc': 21794.392185260294, 'num_coins': 6244.81151440123}, '4': {'symbol': 'eth', 'name': 'ethereum', 'market_cap': 72409494, 'price': 0.953277, 'circulating supply': 75958536, '24hr volume': '241462', 'percent_mc': 0.010302069438868135, 'weighted_dollar_mc': 10302.069438868135, 'num_coins': 10807.005140025549}, '5': {'symbol': 'dash', 'name': 'dash', 'market_cap': 19820453, 'price': 3.25, 'circulating supply': 6107434, '24hr volume': '55320', 'percent_mc': 0.002819957326532654, 'weighted_dollar_mc': 2819.957326532654, 'num_coins': 867.6791773946627}, '6': {'symbol': 'doge', 'name': 'dogecoin', 'market_cap': 15091783, 'price': 0.000147, 'circulating supply': 102497368315, '24hr volume': '105352', 'percent_mc': 0.0021471852354379064, 'weighted_dollar_mc': 2147.1852354379066, 'num_coins': 14606702.28189052}, '7': {'symbol': 'ppc', 'name': 'peercoin', 'market_cap': 9788940, 'price': 0.427738, 'circulating supply': 22885358, '24hr volume': '28242', 'percent_mc': 0.001392722611939725, 'weighted_dollar_mc': 1392.7226119397249, 'num_coins': 3256.01796412693}, '8': {'symbol': 'bts', 'name': 'bitshares', 'market_cap': 8687533, 'price': 0.003424, 'circulating supply': 2537052805, '24hr volume': '9096', 'percent_mc': 0.0012360197989846249, 'weighted_dollar_mc': 1236.019798984625, 'num_coins': 360987.09082494886}, '9': {'symbol': 'xlm', 'name': 'stellar', 'market_cap': 8386835, 'price': 0.001734, 'circulating supply': 4837356606, '24hr volume': '42572', 'percent_mc': 0.0011932379549887428, 'weighted_dollar_mc': 1193.2379549887428, 'num_coins': 688141.8425540616}, '10': {'symbol': 'nxt', 'name': 'nxt', 'market_cap': 7329199, 'price': 0.007329, 'circulating supply': 999997096, '24hr volume': '11515', 'percent_mc': 0.0010427626663056491, 'weighted_dollar_mc': 1042.7626663056492, 'num_coins': 142278.98298617126}, '11': {'symbol': 'maid', 'name': 'maidsafecoin', 'market_cap': 6560545, 'price': 0.014497, 'circulating supply': 452552412, '24hr volume': '2090', 'percent_mc': 0.0009334023263139935, 'weighted_dollar_mc': 933.4023263139935, 'num_coins': 64385.895448299205}, '12': {'symbol': 'fct', 'name': 'factom', 'market_cap': 5666723, 'price': 0.647339, 'circulating supply': 8753873, '24hr volume': '410320', 'percent_mc': 0.0008062336941179447, 'weighted_dollar_mc': 806.2336941179448, 'num_coins': 1245.4582438535988}, '13': {'symbol': 'nmc', 'name': 'namecoin', 'market_cap': 5581503, 'price': 0.420126, 'circulating supply': 13285307, '24hr volume': '44570', 'percent_mc': 0.0007941090084022796, 'weighted_dollar_mc': 794.1090084022796, 'num_coins': 1890.1686836860363}, '14': {'symbol': 'bcn', 'name': 'bytecoin', 'market_cap': 5532261, 'price': 3.1e-05, 'circulating supply': 178306134649, '24hr volume': '8936', 'percent_mc': 0.0007871030969494424, 'weighted_dollar_mc': 787.1030969494425, 'num_coins': 25390422.48224008}, '15': {'symbol': 'xmr', 'name': 'monero', 'market_cap': 5516579, 'price': 0.521568, 'circulating supply': 10576902, '24hr volume': '57544', 'percent_mc': 0.0007848719385195778, 'weighted_dollar_mc': 784.8719385195778, 'num_coins': 1504.831466883662}, '16': {'symbol': 'grc', 'name': 'gridcoin', 'market_cap': 3261647, 'price': 0.008778, 'circulating supply': 371581656, '24hr volume': '755', 'percent_mc': 0.0004640512179117829, 'weighted_dollar_mc': 464.0512179117829, 'num_coins': 52865.25608473262}, '17': {'symbol': 'nsr', 'name': 'nushares', 'market_cap': 3144968, 'price': 0.003773, 'circulating supply': 833502552, '24hr volume': 'Low Vol', 'percent_mc': 0.0004474506992000005, 'weighted_dollar_mc': 447.4506992000005, 'num_coins': 118592.81717466221}, '18': {'symbol': 'emc', 'name': 'emercoin', 'market_cap': 2886544, 'price': 0.078433, 'circulating supply': 36802553, '24hr volume': '4231', 'percent_mc': 0.0004106833936216732, 'weighted_dollar_mc': 410.6833936216732, 'num_coins': 5236.104619505479}, '19': {'symbol': 'rby', 'name': 'rubycoin', 'market_cap': 2830918, 'price': 0.125475, 'circulating supply': 22561620, '24hr volume': '3158', 'percent_mc': 0.0004027691978035602, 'weighted_dollar_mc': 402.7691978035602, 'num_coins': 3209.9557505762914}, '20': {'symbol': 'blk', 'name': 'blackcoin', 'market_cap': 2015105, 'price': 0.026803, 'circulating supply': 75182257, '24hr volume': '4367', 'percent_mc': 0.000286699305433765, 'weighted_dollar_mc': 286.699305433765, 'num_coins': 10696.537903733351}}18        self.temp_total_mc = 702863579319        # self.temp_raw_data = raw_data20        self.total_weighted_mc = 021        self.capping_percent = 1022        for crypto in self.raw_data:23            self.raw_data[crypto]['percent_mc'] = self.raw_data[crypto]['market_cap'] / self.temp_total_mc24            self.raw_data[crypto]['capped'] = False25    def russell_capping(self):26        to_cap = self.determine_constituents_to_cap()27        if to_cap is None:28            return self.raw_data.copy(), self.temp_total_mc29        uncapped_percent, uncapped_mc_sum = self.uncapped_info()30        # print('here', to_cap)31        for crypto in to_cap:32            capping_factor = self.calculate_capping_factor(crypto, uncapped_percent, uncapped_mc_sum)33            self.temp_total_mc -= self.raw_data[crypto]['market_cap']34            self.raw_data[crypto]['market_cap'] *= capping_factor35            self.temp_total_mc += self.raw_data[crypto]['market_cap']36            self.raw_data[crypto]['percent_mc'] = self.raw_data[crypto]['market_cap'] / self.temp_total_mc37            self.raw_data[crypto]['weighted_dollar_mc'] = self.raw_data[crypto]['percent_mc'] * INITIAL_INVESTMENT38            self.raw_data[crypto]['num_coins'] = self.raw_data[crypto]['weighted_dollar_mc'] / self.raw_data[crypto]['price']39            self.raw_data[crypto]['capped'] = True40        while True:41            uncapped_percent, uncapped_mc_sum, to_cap = self.recalculate_caps()42            if not to_cap:43                break44                # return self.raw_data.copy(), self.temp_total_mc45            # print('here2', to_cap)46            for crypto in to_cap:47                capping_factor = self.calculate_capping_factor(crypto, uncapped_percent, uncapped_mc_sum)48                self.temp_total_mc -= self.raw_data[crypto]['market_cap']49                self.raw_data[crypto]['market_cap'] *= capping_factor50                self.temp_total_mc += self.raw_data[crypto]['market_cap']51                self.raw_data[crypto]['percent_mc'] = self.raw_data[crypto]['market_cap'] / self.temp_total_mc52                self.raw_data[crypto]['weighted_dollar_mc'] = self.raw_data[crypto]['percent_mc'] * INITIAL_INVESTMENT53                self.raw_data[crypto]['num_coins'] = self.raw_data[crypto]['weighted_dollar_mc'] / self.raw_data[crypto]['price']54                self.raw_data[crypto]['capped'] = True55        for crypto in self.raw_data:56            self.raw_data[crypto]['weighted_dollar_mc'] = self.raw_data[crypto]['percent_mc'] * INITIAL_INVESTMENT57            self.raw_data[crypto]['num_coins'] = self.raw_data[crypto]['weighted_dollar_mc'] / self.raw_data[crypto]['price']58            self.total_weighted_mc += self.raw_data[crypto]['weighted_dollar_mc']59        return self.raw_data, self.temp_total_mc, self.total_weighted_mc60    def recalculate_caps(self):61        uncapped_percent = 062        uncapped_crypto_mc_sum = 063        to_cap = set()64        for crypto in self.raw_data:65            self.raw_data[crypto]['percent_mc'] = self.raw_data[crypto]['market_cap'] / self.temp_total_mc66            if self.raw_data[crypto]['percent_mc'] > 0.1:67                uncapped_percent += self.raw_data[crypto]['percent_mc']68                uncapped_crypto_mc_sum += self.raw_data[crypto]['market_cap']69                to_cap.add(crypto)70        if len(to_cap) == 0:71            return False, False, False72        return (uncapped_percent * 100), uncapped_crypto_mc_sum, to_cap73    def check_uncapped(self):74        pass75    def calculate_capping_factor(self, index, uncapped_percent, uncapped_mc_sum):76        capping_factor = ((self.capping_percent /77                          (self.raw_data[index]['market_cap'] * uncapped_percent))78                          * uncapped_mc_sum)79        # print(index, capping_factor)80        return capping_factor81    def determine_constituents_to_cap(self):82        to_cap = set()83        for crypto in self.raw_data:84            if self.raw_data[crypto]['percent_mc'] > 0.10:85                to_cap.add(crypto)86        if len(to_cap) == 0:87            return None88        return to_cap.copy()89    def uncapped_info(self):90        # Returns the percent and market cap sum of all the uncapped cryptos91        uncapped_percent = 092        uncapped_crypto_mc_sum = 093        for x in self.raw_data:94            if not self.raw_data[x]['capped']:95                uncapped_percent += self.raw_data[x]['percent_mc']96                uncapped_crypto_mc_sum += self.raw_data[x]['market_cap']97        return (uncapped_percent * 100), uncapped_crypto_mc_sum98    def reset_capped_attribute(self):99        for crypto in self.raw_data:...

model.py

Source:model.py

1import os2from pathlib import Path3import pandas as pd4import numpy as np5from sklearn.linear_model import LinearRegression6from sklearn.model_selection import train_test_split7from sklearn.preprocessing import StandardScaler8from sklearn.metrics import mean_absolute_error, r2_score9import joblib10class Model():11    """12    A class that manage the model. 13    """14    def __init__(self) -> None:15        """16        A function that initialize the class.17        """18        self.df = pd.read_csv("data/raw_data.csv")19        self.model_name:str = "model.pkl"20        self.model_column_name:str = "model_columns.pkl"21        self.poly_feature_name:str = "poly_features.pkl"22        self.model_path:str = Path("./model/").joinpath(self.model_name)23        self.poly_features_model_path:str = Path("./model/").joinpath(self.poly_feature_name)24        self.model_column_path:str = Path("./model/").joinpath(self.model_column_name)25        26    def check_model_not_exist(self):27        """28        A Function that check the model file is exist or not. If not exist, create a new model file.29        """30        if not (os.path.exists(self.model_path)):31            self.train_model()32        else:33            print("Model already exist.")34    35    def manipulate_dataset(self):36        """37        A Function that manipulate the dataset.38        """39        40        raw_data: pd.DataFrame = self.df41        # Remove Unexpected rows42        raw_data.drop(raw_data[raw_data['Price'] == 'None' ].index, inplace=True)43        raw_data.drop(raw_data[raw_data['Type of property'] == 'new-real-estate-project-apartments'].index,inplace=True)44        raw_data.drop(raw_data[raw_data['Type of property'] == 'new-real-estate-project-houses'].index,inplace=True)45        raw_data.drop(['Locality'], axis=1, inplace=True)46        # Delete dublicates47        raw_data = raw_data.drop_duplicates()48        # Price 49        raw_data['Price'] = raw_data['Price'].str.replace(',','')50        raw_data['Price'] = raw_data['Price'].astype(np.int64)51        #Bedrooms52        raw_data[raw_data['Type of property'] =='flat-studio']['Bedrooms'].all = 053        raw_data.drop(raw_data[raw_data["Bedrooms"] == "None"].index, inplace=True)54        raw_data["Bedrooms"] = raw_data['Bedrooms'].astype(int)55        # Living Area 56        raw_data.drop(raw_data[raw_data["Living area"] == "None"].index, inplace=True)57        raw_data["Living area"] = raw_data["Living area"].astype(int)58        # Building Condition59        raw_data['Building condition'].replace({60            'As new': 1,61            'Good': 2,62            'Just renovated': 3,63            'To renovate': 4,64            'To be done up': 5,65            'To restore': 6,66            'None': 2,67        }, inplace=True)68        raw_data['Building condition'] = raw_data['Building condition'].astype(int)69        # Kitchen type70        raw_data["Kitchen type"].replace({71            "Installed":2,72            "Hyper equipped":1,73            "None":0,74            "Semi equipped":3,75            "USA hyper equipped":1,76            "Not installed":0,77            "USA installed":2,78            "USA semi equipped":3,79            "USA uninstalled":0,80            }, inplace=True)81        raw_data['Kitchen type'] = raw_data['Kitchen type'].astype(int)82        # Furnished83        raw_data['Furnished'] = raw_data['Furnished'].replace('None', 0).astype(int)84        # Number of Frontage85        apt_median_value = raw_data[raw_data['Number of frontages'] != 'None']['Number of frontages'].median()86        raw_data['Number of frontages'] = raw_data['Number of frontages'].replace('None',2).astype(int)87        # Swimming Pool88        raw_data['Swimming pool'] = raw_data['Swimming pool'].replace('None', 0).astype(int)89        #Type of property90        #print(raw_data['Type of property'].unique())91        raw_data["Type of property"].replace({92            "apartment":0,93            "house":1,94            "duplex":2,95            "villa":3,96            "mixed-use-building":4,97            "exceptional-property": 5,98            "ground-floor": 6,99            "penthouse": 7,100            "loft": 8,101            "apartment-block": 9,102            "town-house": 10,103            "mansion": 11,104            "service-flat": 12,105            "castle": 13,106            "bungalow": 14,107            "triplex": 15,108            "flat-studio": 16,109            "farmhouse": 17,110            "other-property": 18,111            "kot": 19,112            "manor-house": 20,113            "chalet": 21,114            "country-cottage": 22115            }, inplace=True)116        raw_data['Type of property'] = raw_data['Type of property'].astype(int)117        # Terrace surface118        raw_data['Terrace surface'] = raw_data['Terrace surface'].replace('None', 0).astype(int)119        #Garden surface120        raw_data['Garden surface'] = raw_data['Garden surface'].replace('None', 0).astype(int)121        # surface of the plot 122        raw_data['Surface of the plot'] = raw_data['Surface of the plot'].replace('None', None)123        raw_data['Surface of the plot'] = raw_data['Surface of the plot'].fillna(raw_data['Living area'])124        raw_data['Surface of the plot'] = raw_data['Surface of the plot'].astype(int)125        # rename the column126        raw_data = raw_data.rename(columns={"Price": "price", "Bedrooms": "bedrooms",127                                "Living area": "living_area", "Kitchen type": "kitchen_type",128                                "Furnished": "furnished", "Terrace surface": "terrace_surface",129                                "Garden surface": "garden_surface", "Surface of the plot": "plot_surface",130                                "Number of frontages": "frontage", "Swimming pool": "swimming_pool",131                                "Building condition": "condition", "Type of property": "property_type",132        })133        # Save the dataset to a csv file.134        raw_data.to_csv("./data/dataset.csv", index=False)135    def train_model(self):136        """137        A Function that train the model.138        """139        df = pd.read_csv('./data/dataset.csv')140        141        y = df["price"]142        X = df.drop(["price"], axis=1)143        X_train, X_test, y_train, y_test = train_test_split(X, y , test_size=0.2, random_state=0)144        scaler = StandardScaler()145        scaler.fit(X_train)146        features_scal = scaler.transform(X_train)147        regressor = LinearRegression()148        regressor.fit(X_train, y_train)149        print(regressor.score(X_train, y_train))150        predict = regressor.predict(X_train)151        print(regressor.score(X_test, y_test))152        joblib.dump(regressor, "model/model.pkl")153        model_columns = list(X.columns)154        joblib.dump(model_columns, "model/model_columns.pkl")155        print(X.columns)156    def create_model_file(self):157        """158        A Function that create a model file.159        """160        pass161    def check_performance(self):162        """163        A Function that check the performance of the model.164        """165        pass166model = Model()...

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