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novelmetrix-python/ras/api/views.py

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from sqlite3 import connect
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from rest_framework.decorators import api_view
from rest_framework.response import Response
import pandas as pd
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import ras.settings
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import math
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from pymongo import MongoClient
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from sklearn.linear_model import LinearRegression
from sklearn.metrics import mean_squared_error
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from sqlalchemy import create_engine
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from django.db.models import Q
from django.templatetags.static import static
import json
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def getBooksData():
engine = create_engine('mysql+mysqldb://' + ras.settings.DATABASES['default']['USER'] + ':' + ras.settings.DATABASES['default']['PASSWORD'] + '@' + ras.settings.DATABASES['default']['HOST'] + ':3306/' + ras.settings.DATABASES['default']['NAME'])
df = pd.read_sql('SELECT * FROM api_books ORDER BY readed', engine, parse_dates={'readed': {'format': '%m-%Y'}})
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return df
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def getBookChallenge(year = None):
engine = create_engine('mysql+mysqldb://' + ras.settings.DATABASES['default']['USER'] + ':' + ras.settings.DATABASES['default']['PASSWORD'] + '@' + ras.settings.DATABASES['default']['HOST'] + ':3306/' + ras.settings.DATABASES['default']['NAME'])
if(year):
df = pd.read_sql('SELECT * FROM book_challenge where year = ' + year, engine)
else:
df = pd.read_sql('SELECT * FROM book_challenge', engine)
return df
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def filterData(df, datayear = None):
df['readed'] = pd.to_datetime(df['readed'], format='%Y-%m-%d')
df['readed'] = df['readed'].dt.strftime('%m-%Y')
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# Filter data on year
if datayear and datayear is not None:
df = df.where(df['readed'].str.contains(datayear))
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return df
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@api_view(['GET'])
def getStats(request):
if request.META.get('HTTP_YEAR'):
df = filterData(getBooksData(), request.META.get('HTTP_YEAR'))
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print(df)
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df = df.dropna()
statsTotalBooks = df['name'].count()
statsTotalGenres = df['genre'].nunique()
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return Response({
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'totalbooks': statsTotalBooks,
'totalgenres': statsTotalGenres
})
else:
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return Response("No year header included")