ds

README.md

@@ -7,11 +7,13 @@
 ## KATA 소개
 ![kata](https://github.com/Team-KATA/python-kata/assets/76774809/c74de953-e41a-4b96-9aa6-b54d55743809)
 ### Republic of Korea Army Trend Analysis (KATA)
-### 대한민국 육군 트랜드 분석 서비스
+### 대한민국 육군 트렌드 분석 서비스
 국방 및 안보 이슈에 중점을 두고, 사회적 관심사로 부상하는 키워드를 선정한다. 선택된 키워드와 관련된 기사 반응을 분석하고 요약하여, 사용자가 해당 키워드에 대한 감정 변화, 여론 추이 및 예측 등을 종합적으로 파악할 수 있게 지원하는 도구이다.
 
 KATA는 국방분야에서의 빅데이터 활용을 통한 새로운 가치 창출을 목표로 하고 있다. 이를 통해 육군이 보다 효과적으로 정보를 분석하고, 더 빠르고 정확한 결정을 내릴 수 있도록 돕고자 한다.
 
+[바로가기](https://kata-front.run.goorm.site/)
+
 ## 주요 기능
 **Page Map**
 ![Page Map](https://github.com/Team-KATA/python-kata/assets/76774809/4d24fd32-a057-46e0-bd10-589cb596e649)
@@ -30,5 +32,5 @@ KATA는 국방분야에서의 빅데이터 활용을 통한 새로운 가치 창
 |             [허동석](https://github.com/POBSIZ)             |              [석민석](https://github.com/msjk27)               |             [남궁현](https://github.com/DWL21)
 | :----------------------------------------------------------: | :----------------------------------------------------------: | :----------------------------------------------------------:
 | <img src="https://avatars.githubusercontent.com/u/65818008?v=4" width=200px alt="_"> | <img src="https://avatars.githubusercontent.com/u/97681606?v=4" width=200px alt="_"> | <img src="https://avatars.githubusercontent.com/u/76774809?v=4" width=200px alt="_">
-                                               
+
 - 2023.10 대한민국 육군 9311부대 소속 장병

dao/_keyword.py

@@ -0,0 +1,13 @@
+from pydantic import BaseModel
+
+class Keyword(BaseModel):
+    id: int = None
+    name: str
+
+
+keyword_names = [
+    "삼성전자", "코로나 백신", "올림픽", "메타버스", "NFT", 
+    "AI", "블록체인", "테슬라", "애플", "에이치엘비", 
+    "환율", "비트코인", "가상화폐", "클라우드 컴퓨팅", 
+    "구글", "유튜브", "방탄소년단", "빅데이터", "5G", "IoT"
+]

dao/article.py

@@ -0,0 +1,13 @@
+from pydantic import BaseModel
+
+class Article(BaseModel):
+    id: int = None
+    title: str
+    body: str
+    reporter: str
+    media: str
+    link: str
+    time: str
+
+
+article_fixtures = []

dao/article_dao.py

@@ -0,0 +1,31 @@
+from typing import Optional
+from article import article
+
+articles_db = {}
+
+def save(name: str) -> Optional[Article]:
+    if name not in articles_db.values():
+        article = Article(id=len(articles_db) + 1, name=name)
+        articles_db[article.id] = article
+        return article
+    return None
+
+
+def find(id: int) -> Optional[Article]:
+    if id in articles_db:
+        return articles_db[id]
+    return None
+
+
+def find_all() -> list:
+    return list(articles_db.values())
+
+
+def edit(article: Article):
+    if article.id in articles_db:
+        articles_db[id] = article
+
+
+def delete(article: Article):
+    if article.id in articles_db:
+        articles_db.pop(article.id)

dao/article_keyword.py

@@ -0,0 +1,12 @@
+from pydantic import BaseModel
+from article import Article
+from _keyword import Keyword
+
+
+class ArticleKeyword(BaseModel):
+    id: int = None
+    article: Article
+    keyword: Keyword
+
+
+article_keyword_fixtures = []

dao/article_keyword_dao.py

@@ -0,0 +1,31 @@
+from typing import Optional
+from article_keyword import ArticleKeyword
+
+article_keywords_db = {}
+
+def save(name: str) -> Optional[ArticleKeyword]:
+    if name not in article_keywords_db.values():
+        article_keyword = ArticleKeyword(id=len(article_keywords_db) + 1, name=name)
+        article_keywords_db[article_keyword.id] = article_keyword
+        return article_keyword
+    return None
+
+
+def find(id: int) -> Optional[ArticleKeyword]:
+    if id in article_keywords_db:
+        return article_keywords_db[id]
+    return None
+
+
+def find_all() -> list:
+    return list(article_keywords_db.values())
+
+
+def edit(article_keyword: ArticleKeyword):
+    if article_keyword.id in article_keywords_db:
+        article_keywords_db[id] = article_keyword
+
+
+def delete(article_keyword: ArticleKeyword):
+    if article_keyword.id in article_keywords_db:
+        article_keywords_db.pop(article_keyword.id)

dao/community.py

@@ -0,0 +1,11 @@
+from pydantic import BaseModel
+
+class Community(BaseModel):
+    id: int = None
+    source: str
+    body: str
+    link: str
+    time: str
+
+
+community_fixtures = []

dao/community_dao.py

@@ -0,0 +1,31 @@
+from typing import Optional
+from _community import community
+
+communitys_db = {}
+
+def save(name: str) -> Optional[Community]:
+    if name not in communitys_db.values():
+        community = Community(id=len(communitys_db) + 1, name=name)
+        communitys_db[community.id] = community
+        return community
+    return None
+
+
+def find(id: int) -> Optional[Community]:
+    if id in communitys_db:
+        return communitys_db[id]
+    return None
+
+
+def find_all() -> list:
+    return list(communitys_db.values())
+
+
+def edit(community: Community):
+    if community.id in communitys_db:
+        communitys_db[id] = community
+
+
+def delete(community: Community):
+    if community.id in communitys_db:
+        communitys_db.pop(community.id)

dao/keyword_dao.py

@@ -0,0 +1,31 @@
+from typing import Optional
+from _keyword import Keyword
+
+keywords_db = {}
+
+def save(name: str) -> Optional[Keyword]:
+    if name not in keywords_db.values():
+        keyword = Keyword(id=len(keywords_db) + 1, name=name)
+        keywords_db[keyword.id] = keyword
+        return keyword
+    return None
+
+
+def find(id: int) -> Optional[Keyword]:
+    if id in keywords_db:
+        return keywords_db[id]
+    return None
+
+
+def find_all() -> list:
+    return list(keywords_db.values())
+
+
+def edit(keyword: Keyword):
+    if keyword.id in keywords_db:
+        keywords_db[id] = keyword
+
+
+def delete(keyword: Keyword):
+    if keyword.id in keywords_db:
+        keywords_db.pop(keyword.id)

dao/trend.py

@@ -0,0 +1,7 @@
+from pydantic import BaseModel
+
+class Trend(BaseModel):
+    id: int = None
+    time: str
+
+trend_fixtures = []

dao/trend_dao.py

@@ -0,0 +1,31 @@
+from typing import Optional
+from _trend import trend
+
+trends_db = {}
+
+def save(name: str) -> Optional[Trend]:
+    if name not in trends_db.values():
+        trend = Trend(id=len(trends_db) + 1, name=name)
+        trends_db[trend.id] = trend
+        return trend
+    return None
+
+
+def find(id: int) -> Optional[Trend]:
+    if id in trends_db:
+        return trends_db[id]
+    return None
+
+
+def find_all() -> list:
+    return list(trends_db.values())
+
+
+def edit(trend: Trend):
+    if trend.id in trends_db:
+        trends_db[id] = trend
+
+
+def delete(trend: Trend):
+    if trend.id in trends_db:
+        trends_db.pop(trend.id)

modules/crawling/tweets_crawling.py

@@ -1 +1,14 @@
+import tweepy
+
+# 트위터 개발자 계정에서 얻은 키들을 아래에 입력하세요.
+def tweets_crawling(consumer_key, consumer_secret, access_token, access_token_secret, keyword):
+    auth = tweepy.OAuthHandler(consumer_key, consumer_secret)
+    auth.set_access_token(access_token, access_token_secret)
+
+    api = tweepy.API(auth)
+
+    # 특정 키워드가 포함된 트윗을 검색합니다. 
+    public_tweets = api.search(q=keyword, lang="ko", count=5)
+
+    return public_tweets