feat(backend,docker,docs): implement Go/Gin/SQLite REST API server, Docker containerization, and architecture specifications

- Implement standalone Go backend API server using Gin and pure-Go SQLite (modernc.org/sqlite) - Add 11-table schema DDL migrations (000001_init.up.sql) based on DATA_TABLE.md - Add seed data ingestion tool (cmd/seed) and static TypeScript content exporter (cmd/export-content) - Add configuration loader (internal/config) supporting environment variables and .env files (HOST, PORT, DB_PATH, GIN_MODE, CORS_ALLOW_ORIGINS, AUTO_MIGRATE) - Add lightweight multi-stage Dockerfile and docker-compose.yml with persistent SQLite volume - Add comprehensive architecture specification (ARCHITECTURE.md) and REST API interface specification (API_INTERFACE.md) - Harmonize frontend publications page to consume isHighlight flag from database-synced content
2026-08-24 17:34:51 +09:00
parent 75bf334fec
commit fb6881070c
53 changed files with 8432 additions and 488 deletions
@@ -0,0 +1,175 @@
+#!/usr/bin/env python3
+"""
+Exports curated data from refer_landing_page/content/*.ts and app/page.tsx into backend/seed/data/*.json.
+Ensures is_highlight is properly tagged on the 5 representative publications.
+"""
+
+import json
+import os
+import re
+import sys
+
+REPO_ROOT = os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
+CONTENT_DIR = os.path.join(REPO_ROOT, "refer_landing_page", "content")
+SEED_DATA_DIR = os.path.join(REPO_ROOT, "backend", "seed", "data")
+PAGE_TSX = os.path.join(REPO_ROOT, "refer_landing_page", "app", "page.tsx")
+
+os.makedirs(SEED_DATA_DIR, exist_ok=True)
+
+HIGHLIGHT_TITLES = {
+    "Globally Integrated Trust Authority (GITA) for Resource-Constrained Edge Devices in IoT and 6G",
+    "Application Level Trust Authority (APPLETA) for Resource-Constrained Edge Devices in IoT and 6G",
+    "mQUIC: Use of QUIC for Handover Support with Connection Migration in Wireless/Mobile Networks",
+    "Use of QUIC for CoAP Transport in IoT Networks",
+    "Use of QUIC for Mobile-Oriented Future Internet (Q-MOFI)",
+}
+
+def clean_json_str(s):
+    # Remove trailing commas before ] or }
+    s = re.sub(r',\s*\]', ']', s)
+    s = re.sub(r',\s*\}', '}', s)
+    return s
+
+def extract_json_array_from_ts(filepath, var_name):
+    with open(filepath, "r", encoding="utf-8") as f:
+        content = f.read()
+    
+    # Match export const <var_name>[: Type] = [ ... ];
+    pattern = rf'export\s+const\s+{var_name}(?:\s*:\s*[^=]+)?\s*=\s*(\[\s*[\s\S]*?\s*\]);'
+    match = re.search(pattern, content)
+    if not match:
+        raise ValueError(f"Could not find array literal for '{var_name}' in {filepath}")
+    
+    array_str = clean_json_str(match.group(1))
+    return json.loads(array_str)
+
+def main():
+    print("=== Extracting TypeScript content to JSON for SQLite seeding ===")
+    
+    # 1. Projects
+    projects_file = os.path.join(CONTENT_DIR, "projects.ts")
+    projects = extract_json_array_from_ts(projects_file, "researchProjects")
+    with open(os.path.join(SEED_DATA_DIR, "research_projects.json"), "w", encoding="utf-8") as f:
+        json.dump(projects, f, indent=2, ensure_ascii=False)
+    print(f"✓ Extracted {len(projects)} research projects")
+
+    # 2. Research Areas (from app/page.tsx)
+    with open(PAGE_TSX, "r", encoding="utf-8") as f:
+        page_src = f.read()
+    areas_match = re.search(r'const\s+RESEARCH_AREAS(?:\s*:\s*[^=]+)?\s*=\s*(\[\s*[\s\S]*?\s*\]);', page_src)
+    if not areas_match:
+        raise ValueError("Could not find RESEARCH_AREAS in app/page.tsx")
+    areas_str = clean_json_str(areas_match.group(1))
+    areas_list = json.loads(areas_str)
+    research_areas = [{"name_en": name, "name_kr": None, "display_order": i + 1} for i, name in enumerate(areas_list)]
+    with open(os.path.join(SEED_DATA_DIR, "research_areas.json"), "w", encoding="utf-8") as f:
+        json.dump(research_areas, f, indent=2, ensure_ascii=False)
+    print(f"✓ Extracted {len(research_areas)} research areas")
+
+    # 3. Members & Alumni
+    members_file = os.path.join(CONTENT_DIR, "members.ts")
+    active_members = extract_json_array_from_ts(members_file, "activeMembers")
+    alumni = extract_json_array_from_ts(members_file, "alumni")
+    
+    # Format active members with is_advisor
+    formatted_members = []
+    for i, m in enumerate(active_members):
+        formatted_members.append({
+            "name_ko": m["ko"],
+            "name_en": m["en"],
+            "degree": m["degree"],
+            "affiliation": m.get("affiliation"),
+            "email": "sjkoh@knu.ac.kr" if m["degree"] == "Professor" else None,
+            "is_advisor": m["degree"] == "Professor",
+            "display_order": i + 1,
+        })
+    with open(os.path.join(SEED_DATA_DIR, "members.json"), "w", encoding="utf-8") as f:
+        json.dump(formatted_members, f, indent=2, ensure_ascii=False)
+    print(f"✓ Extracted {len(formatted_members)} active members")
+
+    formatted_alumni = []
+    for a in alumni:
+        formatted_alumni.append({
+            "name_ko": a["ko"],
+            "name_en": a["en"],
+            "degree": a["degree"],
+            "graduated_at": a["graduatedAt"],
+            "major": a.get("major"),
+            "current_position": a.get("currentPosition"),
+        })
+    with open(os.path.join(SEED_DATA_DIR, "alumni.json"), "w", encoding="utf-8") as f:
+        json.dump(formatted_alumni, f, indent=2, ensure_ascii=False)
+    print(f"✓ Extracted {len(formatted_alumni)} alumni")
+
+    # 4. Publications & Patents
+    pubs_file = os.path.join(CONTENT_DIR, "publications.ts")
+    raw_pubs = extract_json_array_from_ts(pubs_file, "publications")
+    raw_patents = extract_json_array_from_ts(pubs_file, "patents")
+
+    matched_highlights = []
+    formatted_pubs = []
+    for p in raw_pubs:
+        title_clean = p["title"].strip()
+        is_hl = title_clean in HIGHLIGHT_TITLES
+        if is_hl:
+            matched_highlights.append(title_clean)
+        formatted_pubs.append({
+            "category": p["category"],
+            "title": p["title"],
+            "authors": p.get("authors"),
+            "venue": p["venue"],
+            "volume": p.get("volume"),
+            "published_at": p["publishedAt"],
+            "kci": bool(p.get("kci", False)),
+            "doi": p.get("doi"),
+            "is_highlight": is_hl,
+        })
+    
+    if len(matched_highlights) != 5:
+        raise ValueError(f"Highlight matching error: expected exactly 5 matched highlights, found {len(matched_highlights)}: {matched_highlights}")
+
+    with open(os.path.join(SEED_DATA_DIR, "publications.json"), "w", encoding="utf-8") as f:
+        json.dump(formatted_pubs, f, indent=2, ensure_ascii=False)
+    print(f"✓ Extracted {len(formatted_pubs)} publications (exactly {len(matched_highlights)} highlights tagged)")
+
+    formatted_patents = []
+    for pat in raw_patents:
+        formatted_patents.append({
+            "title": pat["title"],
+            "inventors": pat["inventors"],
+            "application_no": pat["applicationNo"],
+            "application_at": pat["applicationAt"],
+            "registration_no": pat.get("registrationNo"),
+            "registration_at": pat.get("registrationAt"),
+            "country": pat["country"],
+            "published_at": pat["publishedAt"],
+        })
+    with open(os.path.join(SEED_DATA_DIR, "patents.json"), "w", encoding="utf-8") as f:
+        json.dump(formatted_patents, f, indent=2, ensure_ascii=False)
+    print(f"✓ Extracted {len(formatted_patents)} patents")
+
+    # 5. Lectures (Semesters & Courses)
+    lectures_file = os.path.join(CONTENT_DIR, "lectures.ts")
+    raw_semesters = extract_json_array_from_ts(lectures_file, "semesters")
+    with open(os.path.join(SEED_DATA_DIR, "lectures.json"), "w", encoding="utf-8") as f:
+        json.dump(raw_semesters, f, indent=2, ensure_ascii=False)
+    
+    total_courses = sum(len(s.get("courses", [])) for s in raw_semesters)
+    print(f"✓ Extracted {len(raw_semesters)} semesters with {total_courses} courses")
+
+    # 6. Standardization
+    standards_file = os.path.join(CONTENT_DIR, "standards.ts")
+    raw_standards = extract_json_array_from_ts(standards_file, "standardsBodies")
+    with open(os.path.join(SEED_DATA_DIR, "standards.json"), "w", encoding="utf-8") as f:
+        json.dump(raw_standards, f, indent=2, ensure_ascii=False)
+    
+    total_docs = sum(
+        sum(len(p.get("documents", [])) for p in b.get("projects", []))
+        for b in raw_standards
+    )
+    print(f"✓ Extracted {len(raw_standards)} standards bodies with {total_docs} documents")
+
+    print("=== Extraction completed successfully ===")
+
+if __name__ == "__main__":
+    main()