...

src/main/python/kr/co/swh/lecture/opensource/project/naverblog/naver-blog-nlp-ranking-d3-step3.py

@@ -1,66 +1,66 @@
-from konlpy.tag import Kkma
-import os
-import sys
-import urllib.request
-import json
-import re
-
-def naver_blog_search(client_id, client_secret, text):
-    encText = urllib.parse.quote(text)
-    url = "https://openapi.naver.com/v1/search/blog?query=" + encText # json 결과
-    # url = "https://openapi.naver.com/v1/search/blog.xml?query=" + encText # xml 결과
-    request = urllib.request.Request(url)
-    request.add_header("X-Naver-Client-Id",client_id)
-    request.add_header("X-Naver-Client-Secret",client_secret)
-    response = urllib.request.urlopen(request)
-    rescode = response.getcode()
-    if(rescode==200):
-        response_body = response.read()
-        return response_body.decode('utf-8')
-    else:
-        print("Error Code:" + rescode)
-    
-def striphtml(data):
-    p = re.compile('<.*?>')
-    return p.sub('', data)
-
-def nlp_process():
-    result = []
-    kkma = Kkma()
-    naver_result = naver_blog_search('OJgN42xxZiJXpnZtCH1j', 'crXggqJhhW', '코딩')
-    y = json.loads(naver_result)
-    for b in y['items']:
-        for word, pos in kkma.pos(striphtml(b['description'])):
-            if pos == 'NNG' or pos == 'NNP':
-                result.append(word)
-                
-    words = set(result)
-    loofWords = list(words)
-    countList = []
-    for b in loofWords:
-        if result.count(b) > 1:
-            dic = dict()
-            dic["text"] = b
-            dic["size"] = result.count(b)
-            countList.append(dic)
-    return countList
-
-
-
-from flask import Flask, jsonify, render_template
-import requests
-from bs4 import BeautifulSoup
-
-app = Flask(__name__)
-# app.config['JSON_AS_ASCII'] = False
-countList = ""
-
-@app.route("/")
-def view():
-    return render_template("naver-blog-nlp-ranking-d3.html", values=countList)
-
-if __name__ == "__main__":
-    countResultList = nlp_process()
-    print(countResultList)
-    countList = countResultList;
+from konlpy.tag import Kkma
+import os
+import sys
+import urllib.request
+import json
+import re
+
+def naver_blog_search(client_id, client_secret, text):
+    encText = urllib.parse.quote(text)
+    url = "https://openapi.naver.com/v1/search/blog?query=" + encText # json 결과
+    # url = "https://openapi.naver.com/v1/search/blog.xml?query=" + encText # xml 결과
+    request = urllib.request.Request(url)
+    request.add_header("X-Naver-Client-Id",client_id)
+    request.add_header("X-Naver-Client-Secret",client_secret)
+    response = urllib.request.urlopen(request)
+    rescode = response.getcode()
+    if(rescode==200):
+        response_body = response.read()
+        return response_body.decode('utf-8')
+    else:
+        print("Error Code:" + rescode)
+    
+def striphtml(data):
+    p = re.compile('<.*?>')
+    return p.sub('', data)
+
+def nlp_process(word):
+    result = []
+    naver_result = naver_blog_search('OJgN42xxZiJXpnZtCH1j', 'crXggqJhhW', word)
+    y = json.loads(naver_result)
+    for b in y['items']:
+        for word, pos in kkma.pos(striphtml(b['description'])):
+            if pos == 'NNG' or pos == 'NNP':
+                result.append(word)
+                
+    words = set(result)
+    loofWords = list(words)
+    countList = []
+    for b in loofWords:
+        if result.count(b) > 1:
+            dic = dict()
+            dic["text"] = b
+            dic["size"] = result.count(b)
+            countList.append(dic)
+    return countList
+
+
+
+from flask import Flask, jsonify, render_template
+import requests
+from bs4 import BeautifulSoup
+
+app = Flask(__name__)
+# app.config['JSON_AS_ASCII'] = False
+countList = ""
+kkma = Kkma()
+
+@app.route("/<word>")
+def view(word):
+    countResultList = nlp_process(word)
+    print(countResultList)
+    countList = countResultList;
+    return render_template("naver-blog-nlp-ranking-d3.html", values=countList)
+
+if __name__ == "__main__":
     app.run(host="127.0.0.1", port="8080")