basket.py

import flask
from flask import request, jsonify

import pandas as pd
from mlxtend.preprocessing import TransactionEncoder
from mlxtend.frequent_patterns import apriori

def my_apriori(product):
  # Veri hazırlama
  df = pd.read_csv('./named.csv',names=['products'],header=None)

  # Burada veriyi iki boyutlu diziye çeviriyoruz
  data = list(df["products"].apply(lambda x:x.split(',')))

  te = TransactionEncoder()
  te_data = te.fit(data).transform(data)
  df = pd.DataFrame(te_data, columns=te.columns_)
  df1 = apriori(df, min_support=0.01, use_colnames=True)
  df1.sort_values(by="support",ascending=False)
  df1['length'] = df1['itemsets'].apply(lambda x:len(x))

  prod_key = 'has_' + product
  df1[prod_key] = df1['itemsets'].apply(lambda x: (product in x))
  # print(df1[(df1['length'] > 1) & (df1['support'] >= 0.01) & df1[prod_key]].sort_values(by="support",ascending=False))

  li = []
  for i in df1[(df1['length'] > 1) & df1[prod_key]].sort_values(by="support",ascending=False)['itemsets']:
    for j in i:
      if(j != product): li.append(j)
  return li


app = flask.Flask(__name__)
app.config["DEBUG"] = True

@app.route('/', methods=['GET'])
def home():
  if 'id' in request.args:
    id = request.args['id']
  else:
    return jsonify({ 'success': False, 'data': [], 'message': "Error: No id field provided. Please specify an id."})
  
  return jsonify({'success': True, 'data': my_apriori(id), 'message': 'Succeed'})

app.run()