helper.py

from scipy import sparse
import pickle
import pandas as pd
X = sparse.load_npz("data/yourmatrix.npz")
with open('data/neigh.pkl','rb') as f:
    neigh=pickle.load(f)
df=pd.read_csv('data.csv')
df.fillna('')
def top(start=0,end=20):
	collect=[]
	for i,row in df.iloc[start:end,[0,1,3,5,21,4,19,7]].iterrows():
		collect.append(dict(row))
	return collect		
	
def rem(index=0):
	remm=neigh.kneighbors(X[index:index+1],n_neighbors=100,return_distance=False)
	data=df.iloc[remm[0],[0,1,3,5,21,4,19,7]].dropna()
	# ['title', 'author', 'description', 'coverImg', 'rating', 'likedPercent','isbn']
	'''
	{1: 'title',
 3: 'author',
 4: 'rating',
 5: 'description',
 19: 'likedPercent',
 21: 'coverImg'
	7:'isbn'
	}
	'''
	collect=[]
	for index,row in data.iterrows():
		collect.append(dict(row))
	return collect
def send_index(index):
	print(index)
	remm=neigh.kneighbors(X[index:index+1],n_neighbors=100,return_distance=False)
	return remm