# pip install bs4
from bs4 import BeautifulSoup # python 爬蟲利器
"""
Beautiful Soup 是一個可以從HTML或XML文件中提取數據的Python庫.
它能夠通過你喜歡的轉換器實現慣用的文檔導航,查找,
修改文檔的方式.Beautiful Soup會幫你節省數小時甚至數天的工作時間.
"""
import requests
blog_url = 'https://blog.51cto.com/13118411/2154806'
data = requests.get(blog_url)
print(data)
print(data.text)
<Response [200]>
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<h1 class="artical-title">天氣預報定製</h1>
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<a href="javascript:;" class="time fr">2018-08-04 22:59:05</a>
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<div class="con artical-content editor-preview-side"><pre><code class="language-python"># api aplication programming interface
# 不通軟件不同系統之間的功能相互調用
# json是其中重要的一種數據交換形式
# 定製天氣預報 https://www.sojson.com/open/api/weather/json.shtml?city=
# http://jsonviewer.stack.hu/
# https://www.sojson.com/open/api/weather/json.shtml
?city=%E5%8C%97%E4%BA%AC</code></pre>
<pre><code class="language-python">import requests # pip install requests 請求 網上api的調用形式
url = 'https://www.sojson.com/open/api/weather/json.shtml?city='
city = '北京'
ret = requests.get(url + city) # 請求的對象
print(ret.json())</code></pre>
<pre><code>{'date': '20180804', 'message': 'Success !', 'status': 200, 'city': '北京', 'count': 9, 'data': {'shidu': '70%', 'pm25': 44.0, 'pm10': 78.0, 'quality': '良', 'wendu': '30', 'ganmao': '極少數敏感人羣應減少戶外活動', 'yesterday': {'date': '03日星期五', 'sunrise': '05:13', 'high': '高溫 36.0℃', 'low': '低溫 26.0℃', 'sunset': '19:27', 'aqi': 107.0, 'fx': '南風', 'fl': '<3級', 'type': '晴', 'notice': '願你擁有比陽光明媚的心情'}, 'forecast': [{'date': '04日星期六', 'sunrise': '05:14', 'high': '高溫 36.0℃', 'low': '低溫 27.0℃', 'sunset': '19:26', 'aqi': 97.0, 'fx': '南風', 'fl': '<3級', 'type': '晴', 'notice': '願你擁有比陽光明媚的心情'}, {'date': '05日星期日', 'sunrise': '05:15', 'high': '高溫 35.0℃', 'low': '低溫 25.0℃', 'sunset': '19:25', 'aqi': 103.0, 'fx': '東南風', 'fl': '<3級', 'type': '雷陣雨', 'notice': '帶好雨具，別在樹下躲雨'}, {'date': '06日星期一', 'sunrise': '05:16', 'high': '高溫 31.0℃', 'low': '低溫 25.0℃', 'sunset': '19:24', 'aqi': 97.0, 'fx': '南風', 'fl': '<3級', 'type': '雷陣雨', 'notice': '帶好雨具，別在樹下躲雨'}, {'date': '07日星期二', 'sunrise': '05:17', 'high': '高溫 31.0℃', 'low': '低溫 25.0℃', 'sunset': '19:22', 'aqi': 113.0, 'fx': '西南風', 'fl': '<3級', 'type': '雷陣雨', 'notice': '帶好雨具，別在樹下躲雨'}, {'date': '08日星期三', 'sunrise': '05:18', 'high': '高溫 30.0℃', 'low': '低溫 24.0℃', 'sunset': '19:21', 'aqi': 68.0, 'fx': '東南風', 'fl': '<3級', 'type': '雷陣雨', 'notice': '帶好雨具，別在樹下躲雨'}]}}</code></pre>
<pre><code class="language-python"># 象字典一樣取值
d = ret.json()
# print(d['status'])
# print(d['city'])
# print(d['data'])
# print(d['data']['yesterday'])
def hot_weather(data):
"""定製化天氣預報"""
try:
weather_list = data['data']['forecast']
# print(weather_list)
for day in weather_list:
print(day['date'], day['high'], day['low'], day['sunset'], day['notice'])
except Exception as e:
print(e)
hot_weather(d)</code></pre>
<pre><code>04日星期六 高溫 36.0℃ 低溫 27.0℃ 19:26 願你擁有比陽光明媚的心情
05日星期日 高溫 35.0℃ 低溫 25.0℃ 19:25 帶好雨具，別在樹下躲雨
06日星期一 高溫 31.0℃ 低溫 25.0℃ 19:24 帶好雨具，別在樹下躲雨
07日星期二 高溫 31.0℃ 低溫 25.0℃ 19:22 帶好雨具，別在樹下躲雨
08日星期三 高溫 30.0℃ 低溫 24.0℃ 19:21 帶好雨具，別在樹下躲雨</code></pre>
<pre><code class="language-python">%cd D:\全棧\json api
d = ret.json()
import json
with open('weather.json', 'w') as f:
json.dump(d, f)</code></pre>
<pre><code>D:\全棧\json api</code></pre></div>
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contents = BeautifulSoup(data.text, 'html.parser') # data.text博客文本，html.parser這個類自帶的功能
# print(contents) 輸出更標準化
all_p = contents.find_all('p') # 尋找p標籤
all_text = ''
for p in all_p:
# print(p.text)
all_text += str(p.text) # 拼接成一個句子
print(all_text)
掃一掃體驗手機閱讀0分享收藏Ctrl+Enter 發佈發佈取消0
# pip install jieba 對中文進行拆解爲獨立的詞語
import jieba
text = jieba.cut(all_text) # jieba.cut()
"""
Signature: jieba.cut(sentence, cut_all=False, HMM=True)
Docstring:
The main function that segments an entire sentence that contains
Chinese characters into seperated words.
"""
text_list= []
for t in text:
print(t)
text_list.append(t)
Building prefix dict from the default dictionary ...
Dumping model to file cache C:\Users\coop\AppData\Local\Temp\jieba.cache
Loading model cost 1.107 seconds.
Prefix dict has been built succesfully.
掃一掃
體驗
手機
閱讀
0
分享
收藏
Ctrl
+
Enter
發佈
發佈
取消
0
import collections # python 內置的api，以上jieba也可叫做api，收集
count = collections.Counter(text_list) # 產生一個對象count
for key, val in count.most_common(30):
# 有序（返回前n個出現次數最多的）
print(key, val)
0 2
發佈 2
掃一掃 1
體驗 1
手機 1
閱讀 1
分享 1
收藏 1
Ctrl 1
+ 1
Enter 1
1
取消 1
# 做接口 可以給被人這個py文件，也可以是個鏈接
import collections
def get_most_common(text_list, max_num = 30):
"""根據max_num取排名靠前的詞和出現次數"""
ret = {'status':0, "statusText":'ok', 'data':{}} # api通用格式
try:
new_list = list(text_list)
count = collections.Counter(new_list)
ret['data'] = count.most_common(max_num)
except Exception as e:
ret['status'] = 1
ret['statusText'] = e
return ret
get_most_common(text_list)
{'status': 0,
'statusText': 'ok',
'data': [('0', 2),
('發佈', 2),
('掃一掃', 1),
('體驗', 1),
('手機', 1),
('閱讀', 1),
('分享', 1),
('收藏', 1),
('Ctrl', 1),
('+', 1),
('Enter', 1),
('\xa0', 1),
('取消', 1)]}
