forked from 0xWheatyz/SPARC
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1 Commits
| Author | SHA1 | Date | |
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| 0b4d712fc5 |
@@ -169,9 +169,6 @@ async def lifespan(app: FastAPI):
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import logging
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logging.getLogger(__name__).warning("Marked %d stale jobs as failed on startup", stale)
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_db.close()
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# Start scheduled analysis if tracked companies are configured
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from SPARC.scheduler import start_scheduler
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start_scheduler()
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yield
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# Cleanup
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_analyzer = None
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@@ -372,60 +369,6 @@ async def delete_user(
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return {"message": "User deleted"}
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# ============== Tracked Companies Endpoints ==============
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class TrackCompanyRequest(BaseModel):
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"""Request to add a company to tracking."""
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company_name: str = Field(..., min_length=1, max_length=255)
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@app.get("/admin/tracked", tags=["Admin"])
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async def list_tracked_companies(
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_: UserResponse = Depends(get_current_admin),
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):
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"""List all tracked companies (admin only)."""
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db = get_db_client()
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return db.list_tracked_companies()
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@app.post("/admin/tracked", tags=["Admin"])
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async def add_tracked_company(
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request: TrackCompanyRequest,
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_: UserResponse = Depends(get_current_admin),
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):
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"""Add a company to the tracked list (admin only)."""
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db = get_db_client()
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result = db.add_tracked_company(request.company_name)
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if not result:
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raise HTTPException(status_code=409, detail="Company already tracked")
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return result
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@app.delete("/admin/tracked/{company_name}", tags=["Admin"])
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async def remove_tracked_company(
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company_name: str,
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_: UserResponse = Depends(get_current_admin),
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):
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"""Remove a company from the tracked list (admin only)."""
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db = get_db_client()
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removed = db.remove_tracked_company(company_name)
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if not removed:
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raise HTTPException(status_code=404, detail="Company not found in tracking list")
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return {"message": f"Stopped tracking {company_name}"}
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@app.get("/admin/alerts", tags=["Admin"])
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async def list_alerts(
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limit: int = Query(default=50, ge=1, le=200),
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_: UserResponse = Depends(get_current_admin),
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):
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"""List recent alerts from scheduled analysis (admin only)."""
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db = get_db_client()
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return db.list_alerts(limit=limit)
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# ============== Analytics Endpoint ==============
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@@ -192,35 +192,6 @@ class DatabaseClient:
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ON jobs(status)
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""")
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# Create tracked companies table for scheduled analysis
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cursor.execute("""
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CREATE TABLE IF NOT EXISTS tracked_companies (
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id SERIAL PRIMARY KEY,
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company_name VARCHAR(255) UNIQUE NOT NULL,
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last_patent_count INTEGER DEFAULT 0,
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last_analysis_at TIMESTAMP,
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created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP
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)
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""")
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# Create alerts table for significant changes
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cursor.execute("""
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CREATE TABLE IF NOT EXISTS alerts (
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id SERIAL PRIMARY KEY,
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company_name VARCHAR(255) NOT NULL,
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alert_type VARCHAR(50) NOT NULL,
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message TEXT NOT NULL,
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old_value NUMERIC,
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new_value NUMERIC,
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created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP
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)
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""")
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cursor.execute("""
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CREATE INDEX IF NOT EXISTS idx_alerts_company
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ON alerts(company_name)
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""")
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self.conn.commit()
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@staticmethod
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@@ -832,81 +803,3 @@ class DatabaseClient:
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with conn.cursor() as cursor:
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cursor.execute("SELECT COUNT(*) FROM users")
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return cursor.fetchone()[0]
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# Tracked Companies Methods
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def add_tracked_company(self, company_name: str) -> Optional[Dict]:
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"""Add a company to the tracking list."""
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with self.get_conn() as conn:
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with conn.cursor(cursor_factory=RealDictCursor) as cursor:
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try:
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cursor.execute(
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"INSERT INTO tracked_companies (company_name) VALUES (%s) RETURNING *",
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(company_name,),
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)
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row = cursor.fetchone()
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conn.commit()
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return dict(row) if row else None
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except Exception:
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conn.rollback()
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return None
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def remove_tracked_company(self, company_name: str) -> bool:
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"""Remove a company from the tracking list."""
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with self.get_conn() as conn:
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with conn.cursor() as cursor:
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cursor.execute(
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"DELETE FROM tracked_companies WHERE LOWER(company_name) = LOWER(%s)",
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(company_name,),
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)
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conn.commit()
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return cursor.rowcount > 0
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def list_tracked_companies(self) -> List[Dict]:
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"""List all tracked companies."""
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with self.get_conn() as conn:
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with conn.cursor(cursor_factory=RealDictCursor) as cursor:
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cursor.execute("SELECT * FROM tracked_companies ORDER BY company_name")
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return [dict(row) for row in cursor.fetchall()]
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def update_tracked_company(
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self, company_name: str, patent_count: int
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) -> None:
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"""Update the last analysis stats for a tracked company."""
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with self.get_conn() as conn:
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with conn.cursor() as cursor:
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cursor.execute(
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"""UPDATE tracked_companies
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SET last_patent_count = %s, last_analysis_at = CURRENT_TIMESTAMP
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WHERE LOWER(company_name) = LOWER(%s)""",
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(patent_count, company_name),
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)
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conn.commit()
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def store_alert(
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self,
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company_name: str,
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alert_type: str,
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message: str,
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old_value: float | None = None,
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new_value: float | None = None,
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) -> None:
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"""Record an alert for a significant change."""
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with self.get_conn() as conn:
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with conn.cursor() as cursor:
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cursor.execute(
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"""INSERT INTO alerts (company_name, alert_type, message, old_value, new_value)
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VALUES (%s, %s, %s, %s, %s)""",
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(company_name, alert_type, message, old_value, new_value),
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)
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conn.commit()
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def list_alerts(self, limit: int = 50) -> List[Dict]:
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"""List recent alerts."""
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with self.get_conn() as conn:
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with conn.cursor(cursor_factory=RealDictCursor) as cursor:
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cursor.execute(
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"SELECT * FROM alerts ORDER BY created_at DESC LIMIT %s",
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(limit,),
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)
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return [dict(row) for row in cursor.fetchall()]
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@@ -1,109 +0,0 @@
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"""Scheduled patent analysis for tracked companies.
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Uses APScheduler to periodically re-analyze tracked companies and
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detect significant changes in patent counts.
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"""
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import logging
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import os
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from SPARC import config
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from SPARC.analyzer import CompanyAnalyzer
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from SPARC.database import DatabaseClient
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logger = logging.getLogger(__name__)
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# Configurable via environment variable (in hours, default 24)
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SCHEDULE_INTERVAL_HOURS = int(os.getenv("SCHEDULE_INTERVAL_HOURS", "24"))
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# Patent count change threshold (percentage) to trigger an alert
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CHANGE_THRESHOLD_PERCENT = int(os.getenv("CHANGE_THRESHOLD_PERCENT", "20"))
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def run_scheduled_analysis() -> None:
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"""Re-analyze all tracked companies and check for significant changes."""
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db = DatabaseClient(config.database_url)
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db.connect()
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db.initialize_schema()
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tracked = db.list_tracked_companies()
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if not tracked:
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logger.info("No tracked companies configured; skipping scheduled analysis")
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return
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logger.info("Running scheduled analysis for %d tracked companies", len(tracked))
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analyzer = CompanyAnalyzer(db_client=db)
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for company_row in tracked:
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name = company_row["company_name"]
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old_count = company_row.get("last_patent_count", 0) or 0
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try:
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result = analyzer._analyze_company_safe(name)
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if result.success:
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new_count = result.patent_count
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# Update tracking record
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db.update_tracked_company(name, new_count)
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# Check for significant change
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if old_count > 0:
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delta_pct = abs(new_count - old_count) / old_count * 100
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if delta_pct >= CHANGE_THRESHOLD_PERCENT:
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direction = "increased" if new_count > old_count else "decreased"
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message = (
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f"Patent count for {name} {direction} by {delta_pct:.0f}% "
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f"({old_count} -> {new_count})"
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)
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logger.warning("ALERT: %s", message)
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db.store_alert(
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company_name=name,
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alert_type="patent_count_change",
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message=message,
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old_value=old_count,
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new_value=new_count,
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)
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elif new_count > 0:
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# First analysis -- record baseline
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logger.info("Baseline for %s: %d patents", name, new_count)
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else:
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logger.warning("Scheduled analysis failed for %s: %s", name, result.error)
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except Exception as e:
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logger.error("Error analyzing tracked company %s: %s", name, e)
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db.close()
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logger.info("Scheduled analysis complete")
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def start_scheduler() -> None:
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"""Start the APScheduler background scheduler.
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Safe to call at application startup. If apscheduler is not installed,
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the function logs a warning and returns without starting anything.
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"""
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try:
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from apscheduler.schedulers.background import BackgroundScheduler
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except ImportError:
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logger.warning(
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"apscheduler not installed; scheduled analysis disabled. "
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"Install with: pip install apscheduler"
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)
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return
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scheduler = BackgroundScheduler()
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scheduler.add_job(
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run_scheduled_analysis,
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"interval",
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hours=SCHEDULE_INTERVAL_HOURS,
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id="scheduled_patent_analysis",
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replace_existing=True,
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)
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scheduler.start()
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logger.info(
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"Scheduled patent analysis started (every %d hours, threshold %d%%)",
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SCHEDULE_INTERVAL_HOURS,
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CHANGE_THRESHOLD_PERCENT,
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)
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+13
-1
@@ -1,3 +1,4 @@
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import logging
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import os
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import re
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from datetime import datetime, timedelta
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@@ -10,6 +11,8 @@ import serpapi
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from SPARC import config
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from SPARC.types import Patent, Patents
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logger = logging.getLogger(__name__)
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class SERP:
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def query(company: str, days_back: int = None) -> Patents:
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@@ -44,6 +47,7 @@ class SERP:
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"tbs": date_filter,
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"api_key": config.api_key,
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}
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logger.info("Querying Google Patents for '%s' (last %d days)", company, days_back)
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search = serpapi.search(params)
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# Convert results to Patent objects, skipping any without PDF links
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patent_ids = []
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@@ -52,8 +56,10 @@ class SERP:
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pdf_link = patent.get("pdf")
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if pdf_link:
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patent_ids.append(Patent(patent_id=patent["publication_number"], pdf_link=pdf_link, summary=None))
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# Patents without PDF links are skipped (see docstring for details)
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else:
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logger.debug("Skipping patent %s (no PDF link)", patent.get("publication_number", "unknown"))
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logger.info("Found %d patents with PDF links for '%s'", len(patent_ids), company)
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return Patents(patents=patent_ids)
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def save_patents(patent: Patent) -> Patent:
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@@ -70,9 +76,13 @@ class SERP:
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os.makedirs("patents", exist_ok=True)
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if not (os.path.exists(pdf_path) and os.path.getsize(pdf_path) > 0):
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logger.info("Downloading PDF for %s", patent.patent_id)
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response = requests.get(patent.pdf_link)
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with open(pdf_path, "wb") as f:
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f.write(response.content)
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logger.debug("Saved %d bytes to %s", len(response.content), pdf_path)
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else:
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logger.debug("Using cached PDF for %s at %s", patent.patent_id, pdf_path)
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patent.pdf_path = pdf_path
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return patent
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@@ -90,11 +100,13 @@ class SERP:
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Dictionary containing all extracted sections
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"""
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logger.debug("Parsing patent PDF: %s", pdf_path)
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with pdfplumber.open(pdf_path) as pdf:
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# Extract all text
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full_text = ""
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for page in pdf.pages:
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full_text += page.extract_text() + "\n"
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logger.debug("Extracted text from %d pages (%d chars)", len(pdf.pages), len(full_text))
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# Define section patterns (common in patents)
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sections = {
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@@ -15,4 +15,3 @@ pandas
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bcrypt
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PyJWT
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slowapi
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apscheduler
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