forked from 0xWheatyz/SPARC
Compare commits
1 Commits
| Author | SHA1 | Date | |
|---|---|---|---|
| f33447eef8 |
@@ -40,9 +40,3 @@ JWT_SECRET=your-secure-jwt-secret-change-in-production
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# When USE_CACHE=true: check database for cached responses before making API calls
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# When USE_CACHE=true: check database for cached responses before making API calls
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# When USE_CACHE=false: always make fresh API calls (still stores results in database)
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# When USE_CACHE=false: always make fresh API calls (still stores results in database)
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USE_CACHE=true
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USE_CACHE=true
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# ---- Webhooks ----
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# Comma-separated list of webhook URLs for job completion and alert notifications
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# Supports generic HTTP POST and Slack/Discord incoming webhooks
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# WEBHOOK_URLS=https://hooks.slack.com/services/XXX,https://example.com/webhook
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+57
-17
@@ -169,6 +169,9 @@ async def lifespan(app: FastAPI):
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import logging
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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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logging.getLogger(__name__).warning("Marked %d stale jobs as failed on startup", stale)
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_db.close()
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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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yield
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# Cleanup
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# Cleanup
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_analyzer = None
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_analyzer = None
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@@ -369,6 +372,60 @@ async def delete_user(
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return {"message": "User deleted"}
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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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# ============== Analytics Endpoint ==============
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@@ -519,25 +576,8 @@ def _run_batch_job(job_id: str, companies: list[str], max_workers: int):
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progress=100,
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progress=100,
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result_json=_json.dumps(batch_response.model_dump(), default=str),
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result_json=_json.dumps(batch_response.model_dump(), default=str),
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)
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)
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# Fire webhook notification
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from SPARC.webhooks import notify_job_completed
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notify_job_completed(
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job_id=job_id,
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status="completed",
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total_companies=result.total_companies,
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successful=result.successful,
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failed=result.failed,
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)
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except Exception as e:
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except Exception as e:
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db.update_job(job_id, status="failed", error=str(e))
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db.update_job(job_id, status="failed", error=str(e))
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from SPARC.webhooks import notify_job_completed
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notify_job_completed(
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job_id=job_id,
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status="failed",
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total_companies=len(companies),
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successful=0,
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failed=len(companies),
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)
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@app.post("/analyze/batch/async", response_model=JobStatus, tags=["Analysis"])
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@app.post("/analyze/batch/async", response_model=JobStatus, tags=["Analysis"])
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@@ -192,6 +192,35 @@ class DatabaseClient:
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ON jobs(status)
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ON jobs(status)
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""")
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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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self.conn.commit()
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@staticmethod
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@staticmethod
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@@ -803,3 +832,81 @@ class DatabaseClient:
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with conn.cursor() as cursor:
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with conn.cursor() as cursor:
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cursor.execute("SELECT COUNT(*) FROM users")
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cursor.execute("SELECT COUNT(*) FROM users")
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return cursor.fetchone()[0]
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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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@@ -0,0 +1,109 @@
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"""Scheduled patent analysis for tracked companies.
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|
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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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|
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logger = logging.getLogger(__name__)
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|
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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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|
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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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|
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|
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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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|
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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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|
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|
logger.info("Running scheduled analysis for %d tracked companies", len(tracked))
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|
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|
analyzer = CompanyAnalyzer(db_client=db)
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|
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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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|
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|
try:
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|
result = analyzer._analyze_company_safe(name)
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|
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|
if result.success:
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|
new_count = result.patent_count
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|
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|
# Update tracking record
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|
db.update_tracked_company(name, new_count)
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|
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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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|
|
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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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|
|
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|
db.close()
|
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|
logger.info("Scheduled analysis complete")
|
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|
|
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|
|
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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:
|
||||||
|
logger.warning(
|
||||||
|
"apscheduler not installed; scheduled analysis disabled. "
|
||||||
|
"Install with: pip install apscheduler"
|
||||||
|
)
|
||||||
|
return
|
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|
|
||||||
|
scheduler = BackgroundScheduler()
|
||||||
|
scheduler.add_job(
|
||||||
|
run_scheduled_analysis,
|
||||||
|
"interval",
|
||||||
|
hours=SCHEDULE_INTERVAL_HOURS,
|
||||||
|
id="scheduled_patent_analysis",
|
||||||
|
replace_existing=True,
|
||||||
|
)
|
||||||
|
scheduler.start()
|
||||||
|
logger.info(
|
||||||
|
"Scheduled patent analysis started (every %d hours, threshold %d%%)",
|
||||||
|
SCHEDULE_INTERVAL_HOURS,
|
||||||
|
CHANGE_THRESHOLD_PERCENT,
|
||||||
|
)
|
||||||
@@ -1,139 +0,0 @@
|
|||||||
"""Webhook notifications for job completion and alert events.
|
|
||||||
|
|
||||||
Sends JSON payloads to configured webhook URLs with retry logic.
|
|
||||||
Supports generic HTTP POST and Slack-compatible text payloads.
|
|
||||||
"""
|
|
||||||
|
|
||||||
import logging
|
|
||||||
import os
|
|
||||||
import time
|
|
||||||
from datetime import datetime
|
|
||||||
from typing import Any
|
|
||||||
|
|
||||||
import requests
|
|
||||||
|
|
||||||
logger = logging.getLogger(__name__)
|
|
||||||
|
|
||||||
# Comma-separated list of webhook URLs (env var based config)
|
|
||||||
_WEBHOOK_URLS_RAW = os.getenv("WEBHOOK_URLS", "")
|
|
||||||
WEBHOOK_URLS: list[str] = [
|
|
||||||
url.strip() for url in _WEBHOOK_URLS_RAW.split(",") if url.strip()
|
|
||||||
]
|
|
||||||
|
|
||||||
MAX_RETRIES = 3
|
|
||||||
BACKOFF_BASE = 2 # seconds
|
|
||||||
|
|
||||||
|
|
||||||
def _is_slack_url(url: str) -> bool:
|
|
||||||
"""Check if a URL looks like a Slack incoming webhook."""
|
|
||||||
return "hooks.slack.com" in url or "discord.com/api/webhooks" in url
|
|
||||||
|
|
||||||
|
|
||||||
def _build_payload(event_type: str, data: dict[str, Any], slack: bool = False) -> dict:
|
|
||||||
"""Build the webhook payload.
|
|
||||||
|
|
||||||
Args:
|
|
||||||
event_type: Type of event (e.g., "job_completed", "alert")
|
|
||||||
data: Event-specific data
|
|
||||||
slack: If True, wrap in Slack-compatible ``text`` format
|
|
||||||
|
|
||||||
Returns:
|
|
||||||
JSON-serializable payload dict
|
|
||||||
"""
|
|
||||||
payload = {
|
|
||||||
"event": event_type,
|
|
||||||
"timestamp": datetime.utcnow().isoformat() + "Z",
|
|
||||||
**data,
|
|
||||||
}
|
|
||||||
|
|
||||||
if slack:
|
|
||||||
# Build a human-readable summary for Slack/Discord
|
|
||||||
lines = [f"*[SPARC] {event_type}*"]
|
|
||||||
for key, value in data.items():
|
|
||||||
lines.append(f" {key}: {value}")
|
|
||||||
return {"text": "\n".join(lines)}
|
|
||||||
|
|
||||||
return payload
|
|
||||||
|
|
||||||
|
|
||||||
def _send_with_retry(url: str, payload: dict) -> bool:
|
|
||||||
"""Send a POST request with exponential backoff retry.
|
|
||||||
|
|
||||||
Args:
|
|
||||||
url: Webhook URL
|
|
||||||
payload: JSON payload to send
|
|
||||||
|
|
||||||
Returns:
|
|
||||||
True if delivered successfully, False after all retries exhausted
|
|
||||||
"""
|
|
||||||
for attempt in range(1, MAX_RETRIES + 1):
|
|
||||||
try:
|
|
||||||
response = requests.post(url, json=payload, timeout=10)
|
|
||||||
if response.status_code < 300:
|
|
||||||
logger.debug("Webhook delivered to %s (attempt %d)", url, attempt)
|
|
||||||
return True
|
|
||||||
logger.warning(
|
|
||||||
"Webhook %s returned %d (attempt %d/%d)",
|
|
||||||
url, response.status_code, attempt, MAX_RETRIES,
|
|
||||||
)
|
|
||||||
except requests.RequestException as e:
|
|
||||||
logger.warning(
|
|
||||||
"Webhook delivery failed for %s (attempt %d/%d): %s",
|
|
||||||
url, attempt, MAX_RETRIES, e,
|
|
||||||
)
|
|
||||||
|
|
||||||
if attempt < MAX_RETRIES:
|
|
||||||
wait = BACKOFF_BASE ** attempt
|
|
||||||
time.sleep(wait)
|
|
||||||
|
|
||||||
logger.error("Webhook permanently failed for %s after %d attempts", url, MAX_RETRIES)
|
|
||||||
return False
|
|
||||||
|
|
||||||
|
|
||||||
def notify(event_type: str, data: dict[str, Any]) -> None:
|
|
||||||
"""Fire all configured webhooks for an event.
|
|
||||||
|
|
||||||
Safe to call even when no webhooks are configured (returns immediately).
|
|
||||||
|
|
||||||
Args:
|
|
||||||
event_type: Event identifier (e.g., "job_completed", "patent_alert")
|
|
||||||
data: Event data to include in the payload
|
|
||||||
"""
|
|
||||||
if not WEBHOOK_URLS:
|
|
||||||
return
|
|
||||||
|
|
||||||
for url in WEBHOOK_URLS:
|
|
||||||
slack = _is_slack_url(url)
|
|
||||||
payload = _build_payload(event_type, data, slack=slack)
|
|
||||||
_send_with_retry(url, payload)
|
|
||||||
|
|
||||||
|
|
||||||
def notify_job_completed(
|
|
||||||
job_id: str,
|
|
||||||
status: str,
|
|
||||||
total_companies: int,
|
|
||||||
successful: int,
|
|
||||||
failed: int,
|
|
||||||
) -> None:
|
|
||||||
"""Send notification when a batch job completes."""
|
|
||||||
notify("job_completed", {
|
|
||||||
"job_id": job_id,
|
|
||||||
"status": status,
|
|
||||||
"total_companies": total_companies,
|
|
||||||
"successful": successful,
|
|
||||||
"failed": failed,
|
|
||||||
"summary": f"Batch job {job_id}: {successful}/{total_companies} succeeded",
|
|
||||||
})
|
|
||||||
|
|
||||||
|
|
||||||
def notify_alert(
|
|
||||||
company_name: str,
|
|
||||||
alert_type: str,
|
|
||||||
message: str,
|
|
||||||
) -> None:
|
|
||||||
"""Send notification for a tracked company alert."""
|
|
||||||
notify("patent_alert", {
|
|
||||||
"company_name": company_name,
|
|
||||||
"alert_type": alert_type,
|
|
||||||
"message": message,
|
|
||||||
})
|
|
||||||
@@ -15,3 +15,4 @@ pandas
|
|||||||
bcrypt
|
bcrypt
|
||||||
PyJWT
|
PyJWT
|
||||||
slowapi
|
slowapi
|
||||||
|
apscheduler
|
||||||
|
|||||||
Reference in New Issue
Block a user