last commit

Author: sunshinelancer828

.circleci/config.yml

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+# Use the latest 2.1 version of CircleCI pipeline process engine.
+# See: https://circleci.com/docs/2.0/configuration-reference
+version: 2.1
+
+# Define a job to be invoked later in a workflow.
+# See: https://circleci.com/docs/2.0/configuration-reference/#jobs
+jobs:
+  say-hello:
+    # Specify the execution environment. You can specify an image from Dockerhub or use one of our Convenience Images from CircleCI's Developer Hub.
+    # See: https://circleci.com/docs/2.0/configuration-reference/#docker-machine-macos-windows-executor
+    docker:
+      - image: cimg/base:stable
+    # Add steps to the job
+    # See: https://circleci.com/docs/2.0/configuration-reference/#steps
+    steps:
+      - checkout
+      - run:
+          name: "Say hello"
+          command: "echo Hello, World!"
+
+# Invoke jobs via workflows
+# See: https://circleci.com/docs/2.0/configuration-reference/#workflows
+workflows:
+  say-hello-workflow:
+    jobs:
+      - say-hello

apps/accounts/__init__.py

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+from django.contrib import admin
+
+# Register your models here.

apps/accounts/__pycache__/__init__.cpython-310.pyc

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+from django.apps import AppConfig
+
+
+class AccountConfig(AppConfig):
+    # default_auto_field = 'django.db.models.BigAutoField'
+    name = 'apps.accounts'

apps/accounts/__pycache__/admin.cpython-310.pyc

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+from django.contrib.auth.models import User
+
+User._meta.get_field('email')._unique = True
+User._meta.get_field('email').blank = False
+User._meta.get_field('email').null = False

apps/accounts/__pycache__/apps.cpython-310.pyc

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+
+from django.contrib.auth import authenticate, get_user_model
+from djoser.conf import settings
+from djoser.serializers import TokenCreateSerializer
+
+User = get_user_model()
+
+class CustomTokenCreateSerializer(TokenCreateSerializer):
+
+    def validate(self, attrs):
+        password = attrs.get("password")
+        params = {settings.LOGIN_FIELD: attrs.get(settings.LOGIN_FIELD)}
+        self.user = authenticate(
+            request=self.context.get("request"), **params, password=password
+        )
+        if not self.user:
+            self.user = User.objects.filter(**params).first()
+            if self.user and not self.user.check_password(password):
+                self.fail("invalid_credentials")
+        if self.user: # and self.user.is_active:
+            return attrs
+        self.fail("invalid_credentials")

apps/accounts/__pycache__/models.cpython-310.pyc

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+from django.conf.urls import url, include
+
+accounts_urlpatterns = [
+    url(r'^api/v1/', include('djoser.urls')),
+    url(r'^api/v1/', include('djoser.urls.authtoken')),
+]

apps/accounts/__pycache__/serializers.cpython-310.pyc

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+from django.shortcuts import render
+
+# Create your views here.

apps/accounts/__pycache__/urls.cpython-310.pyc

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+from django.contrib import admin
+
+# Register your models here.

apps/accounts/admin.py

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+from django.apps import AppConfig
+
+
+class AnalyticsConfig(AppConfig):
+    default_auto_field = 'django.db.models.BigAutoField'
+    name = 'apps.analytics'

apps/accounts/apps.py

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+# Generated by Django 3.2.9 on 2021-11-14 03:29
+
+from django.db import migrations, models
+import django.db.models.deletion
+
+
+class Migration(migrations.Migration):
+
+    initial = True
+
+    dependencies = [
+        ('master', '0008_alter_master_options'),
+        ('testing', '0001_initial'),
+    ]
+
+    operations = [
+        migrations.CreateModel(
+            name='Analytics',
+            fields=[
+                ('id', models.BigAutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
+                ('status', models.IntegerField(default=1)),
+                ('master', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='master.master')),
+                ('testing', models.OneToOneField(on_delete=django.db.models.deletion.CASCADE, to='testing.testing')),
+            ],
+        ),
+    ]

apps/accounts/models.py

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+# Generated by Django 3.2.9 on 2021-11-14 03:54
+
+from django.db import migrations, models
+import django.utils.timezone
+
+
+class Migration(migrations.Migration):
+
+    dependencies = [
+        ('analytics', '0001_initial'),
+    ]
+
+    operations = [
+        migrations.AddField(
+            model_name='analytics',
+            name='timestamp',
+            field=models.DateTimeField(auto_now_add=True, default=django.utils.timezone.now),
+            preserve_default=False,
+        ),
+    ]

apps/accounts/serializers.py

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+from django.db import models
+from apps.master.models import Master
+from apps.testing.models import Testing
+
+# Create your models here.
+class Analytics(models.Model):
+    
+    master = models.ForeignKey(Master, on_delete=models.CASCADE)
+    timestamp = models.DateTimeField(auto_now_add = True)
+    testing = models.OneToOneField(Testing, on_delete=models.CASCADE)
+    status = models.IntegerField(default=1)
+

apps/accounts/tests.py

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+from rest_framework import serializers
+from apps.testing.serializers import TestSerializer
+from apps.master.serializers import FileSerializer
+from .models import Analytics
+
+class AnalyticsSerializer(serializers.ModelSerializer):
+    master = FileSerializer()
+    testing = TestSerializer()
+
+    class Meta:
+        model = Analytics
+        fields = ['id', 'timestamp', 'master', 'testing', 'status']

apps/accounts/urls.py

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+from django.test import TestCase
+
+# Create your tests here.

apps/accounts/views.py

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+from django.urls import path
+from .views import analytics, analytics_detail
+
+analytics_urlpatterns = [
+    path('analytics', analytics, name='analytics'),
+    path('analytics/<int:pk>', analytics_detail, name="analytics-detail")
+    
+]

apps/analytics/__init__.py

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+from .models import Analytics
+from rest_framework.decorators import api_view
+from django.conf import settings
+from rest_framework.response import Response
+from rest_framework import status
+from .serializers import AnalyticsSerializer
+
+import pandas as pd
+import numpy as np
+
+@api_view(['GET', 'POST'])
+def analytics(request):
+    if request.method == 'POST':
+      file_serializer = AnalyticsSerializer(data=request.data)
+      if file_serializer.is_valid():
+        file_serializer.save()
+        return Response(file_serializer.data, status=status.HTTP_201_CREATED)
+      else:
+        return Response(file_serializer.errors, status=status.HTTP_400_BAD_REQUEST)
+    
+    elif request.method == "GET":
+        analytics = Analytics.objects.all()
+        serializer = AnalyticsSerializer(analytics, many=True)
+        return Response(serializer.data)
+
+@api_view(['DELETE', 'PUT', 'GET'])
+def analytics_detail(request, pk):
+  try:
+    analytics = Analytics.objects.get(pk=pk)
+  except Analytics.DoesNotExist:
+    return Response(status=status.HTTP_404_NOT_FOUND)
+
+  if request.method == 'PUT':
+    master_path = settings.SERVER_URL+ settings.MEDIA_URL + str(analytics.master.file)
+    testing_path = settings.SERVER_URL+ settings.MEDIA_URL + str(analytics.testing.file)
+    if request.data['format'] == 1:
+      topdata = analyzepagetopdata(master_path, testing_path)
+    elif request.data['format'] == 2:
+      topdata = analyzepagedata(master_path, testing_path)
+    return Response(topdata, status=status.HTTP_200_OK)
+
+
+def calculatetotal(masterdf, codenumber):
+    codedata=masterdf.iloc[:,codenumber+2]
+    featuredata=masterdf.iloc[:,1]
+    i=0
+    count=0
+    while i<masterdf.shape[0]:
+        if featuredata[i] is not np.nan:
+            if codedata[i] is not np.nan:
+                count+=1
+                i+=1
+            else:
+                i+=1
+                while i<masterdf.shape[0] and featuredata[i] is np.nan:
+                    if codedata[i] is not np.nan:
+                        count+=1
+                        i+=1
+                        break
+                    i+=1        
+        else:
+            i+=1
+    return count*100
+def calculatemathcing(masterdf,testdf,masternumber,testnumber):
+    masterdata=masterdf.iloc[:,masternumber+2]
+    testdata=testdf.iloc[:,testnumber+2]
+    featuredata=testdf.iloc[:,1]
+    count=0.0
+    i=1
+    while i<testdf.shape[0]:
+        if testdata[i] is not np.nan and masterdata[i-1] is not np.nan:
+            templist=str(masterdata[i-1]).split(', ', 1)
+            if str(testdata[i]).rstrip() == templist[0]:
+                tcount=int(templist[1])
+                tnum=1
+                i+=1
+                while i<testdf.shape[0] and featuredata[i] is np.nan:
+                    if testdata[i] is not np.nan and masterdata[i-1] is not np.nan:
+                        templist=str(masterdata[i-1]).split(', ', 1)
+                        if testdata[i].rstrip() == templist[0]:
+                            tcount+=int(templist[1])
+                            tnum+=1
+                    i+=1
+                count+=float(tcount/tnum)
+            else:
+                i+=1
+        else: i+=1
+    return count
+
+def analyze(masterdf, testdf):
+    result=[]
+    for i in range(1, testdf.shape[1]-2, 1):
+        templist={}
+        for j in range(1, masterdf.shape[1]-2, 1):
+            temp=float(calculatemathcing(masterdf,testdf,j,i)/calculatetotal(masterdf,j))*100
+            if(temp>=100.0):
+                temp=99.9
+            templist.append(str(temp)[0:4]+'%')
+        result.append(templist)
+    return result
+
+def analyzepagedata(masterpath, testpath):
+    masterdata = pd.read_excel(masterpath)
+    masterdf=pd.DataFrame(masterdata)
+    testdata = pd.read_excel(testpath)
+    testdf=pd.DataFrame(testdata)
+    newcolumns=[]
+    list_dictionary=[]
+    newindex=[]
+    newcolumns.append('Sl No')
+    for i in range(0, testdf.shape[1]-3,1):
+        newindex.append(testdf.columns[3:][i])
+    for i in range(0, masterdf.shape[1]-3,1):
+        newcolumns.append(masterdf.columns[3:][i])
+    for i in range(1, testdf.shape[1]-2, 1):
+        templist=[]
+        templist.append(newindex[i-1])
+        for j in range(1, masterdf.shape[1]-2, 1):
+            temp=float(calculatemathcing(masterdf,testdf,j,i)/calculatetotal(masterdf,j))*100
+            if(temp>=100.0):
+                temp=99.9
+            templist.append(str(temp)[0:4]+'%')
+        templist_dictionary=dict(zip(newcolumns, templist))
+        list_dictionary.append(templist_dictionary)
+    return list_dictionary
+# analyze(masterdf, testdf)
+# analyzepagedata(masterpath, testpath)
+def getanalyzedata(masterpath, testpath):
+    masterdata = pd.read_excel(masterpath)
+    masterdf=pd.DataFrame(masterdata)
+    testdata = pd.read_excel(testpath)
+    testdf=pd.DataFrame(testdata)
+    newindex=[]
+    newcolumns=[]
+    for i in range(0, testdf.shape[1]-3,1):
+        newindex.append(testdf.columns[3:][i])
+    for i in range(0, masterdf.shape[1]-3,1):
+        newcolumns.append(masterdf.columns[3:][i])
+    analyzedata=analyze(masterdf, testdf)
+    excelanalyzedata=pd.DataFrame(analyzedata, columns=newcolumns, index=newindex)
+    excelanalyzedata.to_excel(r'E:\PythonDjango\NewOutput2.xlsx', sheet_name='Sheet1')
+
+#getanalyzedata(masterpath, testpath)                         // this is the second result output
+
+def analyzetop(masterdf, testdf):
+    topresult=[]
+    toprank=[]
+    result=[]
+    finalresult=[]
+    for i in range(1, testdf.shape[1]-2, 1):
+        templist=[]
+        toptemplist=[]
+        tempranklist=[]
+        topranklist=[]
+        finaltemplist=[]
+        for j in range(1, masterdf.shape[1]-2,1):
+            temp=float(calculatemathcing(masterdf,testdf,j,i)/calculatetotal(masterdf,j))*100
+            if(temp>=100.0):
+                temp=99.9
+            templist.append(temp)
+            tempranklist.append(j)
+        result.append(templist)
+        for j in range(0, masterdf.shape[1]-4,1):
+            for k in range(j+1,masterdf.shape[1]-3,1):
+                if templist[j]<templist[k]:
+                    temp=templist[j]
+                    templist[j]=templist[k]
+                    templist[k]=temp
+                    temp=tempranklist[j]
+                    tempranklist[j]=tempranklist[k]
+                    tempranklist[k]=temp
+        for j in range(0,5):
+            toptemplist.append(templist[j])
+            topranklist.append(tempranklist[j])
+            finaltemplist.append('Code '+str(tempranklist[j]))
+            finaltemplist.append(str(templist[j])[0:4]+'%')
+        finaltemplist.extend(testdf.iloc[:,i+2][1:])
+        topresult.append(toptemplist)
+        toprank.append(topranklist)
+        finalresult.append(finaltemplist)
+    return finalresult
+
+def analyzepagetopdata(masterpath, testpath):
+    masterdata = pd.read_excel(masterpath)
+    masterdf=pd.DataFrame(masterdata)
+    testdata = pd.read_excel(testpath)
+    testdf=pd.DataFrame(testdata)
+    list_dictionary=[]
+    newcolumns=[]
+    for i in range(0, testdf.shape[1],1):
+        newcolumns.append(testdf.columns[i])
+    analyzetopdata=analyzetop(masterdf, testdf)
+    newfirst=['','','','','','','','','','']
+    newthird=['','','','','','','','','','']
+    newsecond=['Code match-1', 'Code match-1%', 'Code match-2', 'Code match-2%', 'Code match-3', 'Code match-3%', 'Code match-4', 'Code match-4%', 'Code match-5', 'Code match-5%']
+    newfirst.extend(testdf.iloc[:,0][1:])
+    newsecond.extend(testdf.iloc[:,1][1:])
+    newthird.extend(testdf.iloc[:,2][1:])
+    newtopdata=[newfirst, newsecond, newthird]
+    newtopdata.extend(analyzetopdata)
+    for i in range(0, testdf.shape[0]+9,1):
+        templist=[]
+        for j in range(0, testdf.shape[1], 1):
+            if(newtopdata[j][i] is not np.nan):
+                templist.append(newtopdata[j][i])
+            else:
+                templist.append('')
+        templist_dictionary=dict(zip(newcolumns, templist))
+        list_dictionary.append(templist_dictionary)
+    return list_dictionary