jwlin

[
  {
    "_id": "58d5c70c27ea7d070060160e",
    "categories": [
      "55de81ac9d1fa51000f94770",
      "55de81929d1fa51000f94769",
      "55de81879d1fa51000f94766"
    ],
    "coverImage": {
      "_id": "58f318cc4909c907004ac575",

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def crawl():
    # 初始 API: https://api.hahow.in/api/courses?limit=12&status=PUBLISHED
    # 接續 API: https://api.hahow.in/api/courses?latestId=54d5a117065a7e0e00725ac0&latestValue=2015-03-27T15:38:27.187Z&limit=30&status=PUBLISHED
    headers = {'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) '
                             'AppleWebKit/537.36 (KHTML, like Gecko) '
                             'Chrome/59.0.3071.115 Safari/537.36'}
    url = 'https://api.hahow.in/api/courses'
    courses = list()
    resp_courses = requests.get(url + '?limit=30&status=PUBLISHED', headers=headers).json()
    while resp_courses:  # 有回傳資料則繼續下一輪擷取

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{
    "_id": "58744feda8aae907000d06c0",
    "categories": [
      "55de81ac9d1fa51000f94770",
      "55de81929d1fa51000f94769"
    ],
    "coverImage": {
      "_id": "588421e46ecf3a0700b7a31d",
      "url": "https://hahow.in/images/588421e46ecf3a0700b7a31d"
    },

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with open('hahow_courses.json', 'r', encoding='utf-8') as f:
    courses = json.load(f)
	
# 取出程式類課程的募資價/上線價/學生數，並顯示統計資料
pre_order_prices = list()
prices = list()
tickets = list()
lengths = list()
for c in courses:
    if '55de81ac9d1fa51000f94770' in c['categories']:

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jwlin

def getTopic(self, ai, imgtopic, Dict): 
    # JW:　features 是準備要被預測 topic 的變數, 應該要挪到下方 prediction 開始前, 程式比較連貫
    #extrat the features of the element
    features = str(re.sub(' +', ' ', ' '.join(self.extract_features(ai, imgtopic, Dict, 1))))
    #print (features)
    
    # JW:　從這裡開始可以獨立切一個 function, 只呼叫一次, 把 train 好的 model 存起來
    #open training data file
    current_dir = os.path.dirname(_file_)
    corpus_dir = os.path.join(current_dir, 'corpus', 'all-corpus')

jwlin

#!/usr/bin/python
# -*- coding: utf-8 -*-

"""
Extract features from htmls
"""

import sys, os, random, datetime
from bs4 import BeautifulSoup
# preprocess.py 檔案在這裡

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from django.http import HttpResponse
from django.shortcuts import get_object_or_404, render
from .models import Account, Client

def show(request):
    uname = request.POST["uname"]
    if "injection" in request.POST:  
        # Use raw SQL and string concatenation, resulting in SQL injection
        accounts = Account.objects.raw(f'SELECT * FROM atm_account as a, atm_client as c WHERE a.client_id=c.id and c.username="{uname}"')    
    else: