Create tool

tool

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+import streamlit as st
+import streamlit.components.v1 as components
+import time
+import requests
+import pandas as pd
+import hmac
+import hashlib
+import base64
+from datetime import datetime, timedelta
+import random
+import re
+
+# [지도 라이브러리]
+import folium
+from streamlit_folium import st_folium
+
+# ==========================================
+# 0. API 키 및 설정
+# ==========================================
+
+# [1] 카카오 API (필수)
+KAKAO_REST_KEY = "968344aed4aff4d7aeb37eb199767d5a"
+
+# [2] 네이버 광고 API
+AD_API_KEY = "01000000002855c92d066a6e30d3eaeafbe6adebd688d73c3dd901f151b52c430ddcad5c88"
+AD_SECRET_KEY = "AQAAAAAoVcktBmpuMNPq6vvmrevWXrbXSbEoh/+/3U3vTcTLyA=="
+AD_CUSTOMER_ID = "4173931"
+
+# [3] 기타 설정
+NAVER_SEARCH_ID = "dlOt9fIfGfpSj69uICWc"
+NAVER_SEARCH_SECRET = "_rtIqpqYpd"
+YOUTUBE_API_KEY = "AIzaSyBPgiYOvrPJ4cacWQ42UQb_KZobCcpOIH0"
+
+EXCLUDED_KEYWORDS = ["슈링크", "써마지", "울쎄라", "인모드", "티타늄"] 
+
+# ==========================================
+# 1. 핵심 기능 함수
+# ==========================================
+
+def search_places_kakao(query):
+    """장소 검색"""
+    url = "https://dapi.kakao.com/v2/local/search/keyword.json"
+    headers = {"Authorization": f"KakaoAK {KAKAO_REST_KEY}"}
+    try:
+        res = requests.get(url, params={"query": query, "size": 15}, headers=headers)
+        return res.json()['documents'] if res.status_code == 200 else []
+    except: return []
+
+def get_address_details_kakao(address_str):
+    """주소 -> 좌표 + 법정동 분석"""
+    url = "https://dapi.kakao.com/v2/local/search/address.json"
+    headers = {"Authorization": f"KakaoAK {KAKAO_REST_KEY}"}
+    try:
+        res = requests.get(url, params={"query": address_str}, headers=headers)
+        if res.status_code == 200:
+            docs = res.json()['documents']
+            if docs:
+                data = docs[0]
+                x, y = float(data['x']), float(data['y'])
+                addr = data.get('address', {})
+                
+                region_1 = addr.get('region_1depth_name', '') # 충북
+                region_2 = addr.get('region_2depth_name', '') # 청주시 상당구
+                
+                city_name = ""
+                gu_name = ""
+                if region_2:
+                    parts = region_2.split()
+                    if len(parts) >= 2:
+                        city_name = parts[0] # 청주시
+                        gu_name = parts[1]   # 상당구
+                    else:
+                        gu_name = parts[0]   # 강남구
+                
+                b_dong = addr.get('region_3depth_name', '') # 법정동
+                return x, y, region_1, city_name, gu_name, b_dong
+        return 0.0, 0.0, "", "", "", ""
+    except: return 0.0, 0.0, "", "", "", ""
+
+def get_admin_dong(x, y):
+    """행정동 추출 (중앙동 등)"""
+    if x == 0.0 or y == 0.0: return ""
+    url = "https://dapi.kakao.com/v2/local/geo/coord2regioncode.json"
+    headers = {"Authorization": f"KakaoAK {KAKAO_REST_KEY}"}
+    try:
+        res = requests.get(url, params={"x": x, "y": y}, headers=headers)
+        if res.status_code == 200:
+            docs = res.json()['documents']
+            for doc in docs:
+                if doc['region_type'] == 'H': return doc['region_3depth_name']
+        return ""
+    except: return ""
+
+def get_nearby_stations(x, y):
+    if x == 0.0 or y == 0.0: return []
+    url = "https://dapi.kakao.com/v2/local/search/category.json"
+    headers = {"Authorization": f"KakaoAK {KAKAO_REST_KEY}"}
+    params = {"category_group_code": "SW8", "x": x, "y": y, "radius": 1500, "sort": "distance"}
+    try:
+        res = requests.get(url, params=params, headers=headers)
+        if res.status_code == 200:
+            return [{"name": d['place_name'], "clean_name": d['place_name'].split()[0].replace("역",""), "x": float(d['x']), "y": float(d['y'])} for d in res.json()['documents']][:4]
+        return []
+    except: return []
+
+def get_naver_expanded_rankings(seed_keywords, category_seed, filters, loc_info):
+    """
+    [핵심] 위치 기반 필터링 (화이트리스트 방식)
+    """
+    uri = '/keywordstool'
+    timestamp = str(int(time.time() * 1000))
+    msg = f"{timestamp}.GET.{uri}"
+    signature = base64.b64encode(hmac.new(bytes(AD_SECRET_KEY, 'UTF-8'), bytes(msg, 'UTF-8'), hashlib.sha256).digest())
+    headers = {'X-Timestamp': timestamp, 'X-API-KEY': AD_API_KEY, 'X-Customer': AD_CUSTOMER_ID, 'X-Signature': signature}
+    
+    clean_seeds = []
+    seen = set()
+    for k in seed_keywords:
+        k_nospace = k.replace(" ", "")
+        if k_nospace not in seen:
+            clean_seeds.append(k_nospace)
+            seen.add(k_nospace)
+            
+    # [화이트리스트] 행정구역 및 역 이름 정의
+    valid_local_terms = []
+    if loc_info['si']: valid_local_terms.append(loc_info['si'].replace("시", "")) 
+    if loc_info['gu']: valid_local_terms.append(loc_info['gu']) 
+    if loc_info['b_dong']: valid_local_terms.append(re.sub(r'\d+가?', '', loc_info['b_dong'])) 
+    if loc_info['h_dong']: valid_local_terms.append(loc_info['h_dong']) 
+    for s in loc_info['stations']: valid_local_terms.append(s['clean_name'])
+    valid_local_terms = list(set(valid_local_terms))
+
+    all_results = []
+    seen_kwd = set()
+    
+    for i in range(0, len(clean_seeds), 5):
+        chunk = clean_seeds[i:i+5]
+        try:
+            res = requests.get("https://api.naver.com" + uri, params={'hintKeywords': ','.join(chunk), 'showDetail': '1'}, headers=headers)
+            if res.status_code == 200:
+                data = res.json()
+                for item in data.get('keywordList', []):
+                    kwd = item['relKeyword'].replace(" ", "")
+                    if kwd in seen_kwd: continue
+                    if category_seed not in kwd: continue 
+                    if kwd == category_seed: continue 
+                    if any(bad in kwd for bad in EXCLUDED_KEYWORDS): continue
+                    
+                    is_local_relevant = False
+                    for term in valid_local_terms:
+                        if term in kwd:
+                            is_local_relevant = True
+                            break
+                    if not is_local_relevant: continue 
+
+                    if not filters['station']:
+                        if "역" in kwd: continue
+                        is_station_word = False
+                        for s in loc_info['stations']:
+                            if s['clean_name'] in kwd: is_station_word = True; break
+                        if is_station_word: continue
+
+                    priority = 0
+                    if kwd in clean_seeds: priority = 100
+                    for main_k in loc_info['main_keywords']:
+                        if main_k in kwd: priority += 20
+                    
+                    seen_kwd.add(kwd)
+                    pc = item['monthlyPcQcCnt']
+                    mo = item['monthlyMobileQcCnt']
+                    if isinstance(pc, str): pc = 10
+                    if isinstance(mo, str): mo = 10
+                    all_results.append({'key': item['relKeyword'], 'total': pc + mo, 'priority': priority})
+            time.sleep(0.1)
+        except: pass
+    return sorted(all_results, key=lambda x: (x['priority'], x['total']), reverse=True)
+
+def search_bloggers(keyword, display=30):
+    url = "https://openapi.naver.com/v1/search/blog.json"
+    headers = {"X-Naver-Client-Id": NAVER_SEARCH_ID, "X-Naver-Client-Secret": NAVER_SEARCH_SECRET}
+    params = {"query": keyword, "display": display, "sort": "sim"}
+    try:
+        res = requests.get(url, params=params, headers=headers)
+        if res.status_code == 200: return res.json()['items']
+        return None
+    except: return None
+
+# ==========================================
+# 2. 메인 UI
+# ==========================================
+st.set_page_config(page_title="병원 마케팅 마스터", layout="wide")
+
+st.markdown("""
+    <style>
+        #myBtn { display: flex; justify-content: center; align-items: center; position: fixed; bottom: 30px; right: 30px; z-index: 9999;
+            font-size: 20px; border: none; outline: none; background-color: #E1306C; color: white; cursor: pointer; width: 50px; height: 50px;
+            padding: 0; border-radius: 50%; box-shadow: 0px 4px 6px rgba(0,0,0,0.2); transition: transform 0.2s; }
+        #myBtn:hover { transform: scale(1.1); }
+    </style>
+    <button onclick="window.parent.document.querySelector('.main').scrollTo({top:0, behavior:'smooth'})" id="myBtn">▲</button>
+""", unsafe_allow_html=True)
+
+if 'target_location' not in st.session_state: st.session_state.target_location = None
+if 'analysis_result' not in st.session_state: st.session_state.analysis_result = pd.DataFrame()
+if 'search_results' not in st.session_state: st.session_state.search_results = []
+
+st.title("🏥 병원 마케팅 올인원 툴")
+tab1, tab2, tab3, tab4 = st.tabs(["📊 키워드 분석 (Map)", "📝 블로거 발굴", "📺 유튜버 발굴", "📸 인스타 발굴"])
+
+with tab1:
+    st.header("1. 지도 기반 상권 분석 및 키워드 추출")
+    with st.expander("🔍 병원 검색 및 위치 설정", expanded=True):
+        with st.form("search_form"):
+            col1, col2 = st.columns([3, 1], vertical_alignment="bottom")
+            with col1: h_query = st.text_input("병원명 입력", placeholder="예: 디아트의원 청주")
+            with col2: search_btn = st.form_submit_button("병원 찾기")
+        if search_btn and h_query:
+            places = search_places_kakao(h_query)
+            if places: st.session_state.search_results = places
+            else: st.warning("검색 결과가 없습니다.")
+        if st.session_state.search_results:
+            st.divider()
+            options = {f"{p['place_name']} ({p['address_name']})": i for i, p in enumerate(st.session_state.search_results)}
+            selected_option = st.radio("분석할 병원을 선택하세요", list(options.keys()))
+            if st.button("✅ 선택한 병원으로 설정"):
+                target = st.session_state.search_results[options[selected_option]]
+                x, y, region_1, city, gu, b_dong = get_address_details_kakao(target['address_name'])
+                st.session_state.target_location = {"name": target['place_name'], "x": x, "y": y, "do": region_1, "si": city, "gu": gu, "b_dong": b_dong, "h_dong": get_admin_dong(x, y)}
+                st.session_state.target_location['stations'] = get_nearby_stations(x, y)
+                st.rerun()
+
+    if st.session_state.target_location:
+        loc = st.session_state.target_location
+        col1, col2 = st.columns([1.2, 1])
+        with col2:
+            st.subheader("🗺️ 분석 구역")
+            # [수정] 텍스트 말풍선(DivIcon) 기능이 제거된 깨끗한 지도
+            m = folium.Map(location=[loc['y'], loc['x']], zoom_start=15)
+            folium.Marker([loc['y'], loc['x']], popup=f"<b>{loc['name']}</b>", tooltip=loc['name'], icon=folium.Icon(color="red", icon="star", prefix='fa')).add_to(m)
+            folium.Circle(location=[loc['y'], loc['x']], radius=1500, color='#E1306C', fill=True, fill_color='#E1306C', fill_opacity=0.1).add_to(m)
+            for s in loc['stations']:
+                folium.Marker([s['y'], s['x']], tooltip=f"{s['name']} (역세권)", popup=s['name'], icon=folium.Icon(color="green", icon="train", prefix="fa")).add_to(m)
+            st_folium(m, height=450, width="100%")
+            
+            # [AI 상권 분석 리포트]
+            st_names = [s['name'] for s in loc['stations']]
+            st_text = ", ".join(st_names) if st_names else "도보권 내 지하철역 없음"
+            dong_name = loc['h_dong'] if loc['h_dong'] else loc['b_dong']
+            
+            report_box = f"""
+            <div style="background-color:#f0f2f6; padding:15px; border-radius:10px; border-left: 5px solid #E1306C;">
+                <h4 style="margin:0 0 10px 0;">📢 AI 마케팅 상권 분석</h4>
+                <ul style="margin:0; padding-left:20px;">
+                    <li><b>📍 행정구역:</b> 현재 <b>{loc['si']} {loc['gu']} {dong_name}</b> 지역을 분석 중입니다.</li>
+                    <li><b>🚇 교통/접근성:</b> 이 병원은 <b>{st_text}</b> 인근에 위치해 있습니다.</li>
+                    <li><b>💡 전략:</b> 지역명(<b>{loc['gu']}, {dong_name}</b>)이 포함된 키워드를 최우선으로 선점하세요.</li>
+                </ul>
+            </div>
+            """
+            st.markdown(report_box, unsafe_allow_html=True)
+
+        with col1:
+            disp_addr = f"{loc['si']} {loc['gu']} {loc['b_dong']}"
+            if loc['h_dong'] and loc['h_dong'] != loc['b_dong']: disp_addr += f" ({loc['h_dong']})"
+            st.subheader(f"📍 {disp_addr}")
+            st.write("🎯 **키워드 추출 옵션**")
+            c1, c2 = st.columns(2)
+            use_region = c1.checkbox("🏙️ 지역명 (시/구/동)", True)
+            use_station = c2.checkbox("🚇 역세권", True)
+            target_cat = st.selectbox("업종", ["피부과", "성형외과", "치과", "한의원", "정형외과", "안과", "비뇨기과", "산부인과"])
+            
+            if st.button("🚀 키워드 추출", type="primary", use_container_width=True):
+                with st.spinner("지역 기반 정밀 분석 중..."):
+                    seeds = []
+                    main_keywords = []
+                    clean_si = loc['si'].replace("시", "") if loc['si'] else ""
+                    if use_region:
+                        if clean_si: seeds.extend([f"{clean_si}{target_cat}", f"{clean_si}{target_cat}추천"])
+                        if loc['gu']: seeds.extend([f"{loc['gu']}{target_cat}", f"{clean_si}{loc['gu']}{target_cat}"])
+                        clean_b = re.sub(r'\d+가?', '', loc['b_dong'])
+                        seeds.append(f"{clean_b}{target_cat}")
+                        if loc['h_dong']: seeds.append(f"{loc['h_dong']}{target_cat}")
+                    if use_station:
+                        for s in loc['stations']: seeds.extend([f"{s['clean_name']}역{target_cat}", f"{s['clean_name']}{target_cat}"])
+                    loc['main_keywords'] = [clean_si, loc['gu'], loc['h_dong']]
+                    rankings = get_naver_expanded_rankings(seeds, target_cat, {'station': use_station}, loc)
+                    if rankings: st.session_state.analysis_result = pd.DataFrame(rankings)
+            
+            if not st.session_state.analysis_result.empty:
+                df = st.session_state.analysis_result
+                st.success(f"키워드 {len(df)}개")
+                for _, row in df.head(30).iterrows():
+                    icon = "👑" if row['priority'] >= 100 else ("🎯" if row['priority'] >= 60 else "✅")
+                    st.markdown(f"""<div style="border:1px solid #eee; padding:10px; margin-bottom:5px; border-radius:5px; display:flex; justify-content:space-between; align-items:center; background-color:{'#fff0f6' if row['priority']>=80 else 'white'};">
+                        <div><b>{row['key']}</b> <span style="font-size:0.8em; color:#E1306C;">{icon}</span></div>
+                        <div style="text-align:right;"><span style="font-size:0.8em; color:#666;">조회수</span><br><b>{row['total']:,}</b></div>
+                    </div>""", unsafe_allow_html=True)
+                st.download_button("📥 다운로드", df.to_csv(index=False).encode('utf-8-sig'), "keywords.csv", "text/csv", use_container_width=True)
+
+with tab2:
+    st.header("2. 블로거 발굴")
+    with st.form("blog_form"):
+        col_b1, col_b2 = st.columns([3, 1], vertical_alignment="bottom")
+        with col_b1: region_input = st.text_input("타겟 지역명", placeholder="예: 청주 성안길")
+        with col_b2: submit_blog = st.form_submit_button("🕵️‍♀️ 블로거 찾기")
+    if submit_blog and region_input:
+        with st.spinner("블로거 분석 중..."):
+            items = search_bloggers(f"{region_input} 피부과 후기", 30)
+            if items:
+                for i in items:
+                    st.write(f"- [{i['bloggername']}] {i['title'].replace('<b>','').replace('</b>','')}")
+                    st.caption(f"🔗 {i['link']}")
+
+with tab3:
+    st.header("3. 유튜브")
+    st.info("준비중")
+
+with tab4:
+    st.header("4. 인스타")
+    st.info("준비중")