feat: implement scheduled/recurring analysis with change alerting

Add APScheduler-based background task that periodically re-analyzes
tracked companies and alerts on significant patent count changes.

- Add tracked_companies and alerts tables to database schema
- Add SPARC/scheduler.py with configurable interval and threshold
- Add admin endpoints: GET/POST/DELETE /admin/tracked, GET /admin/alerts
- Scheduler starts at app startup; interval via SCHEDULE_INTERVAL_HOURS
- Change threshold configurable via CHANGE_THRESHOLD_PERCENT env var
- apscheduler is optional; graceful fallback if not installed

Closes leeworks-agents/SPARC#22

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

.gitea/workflows/build.yaml

@@ -9,7 +9,43 @@ on:
   workflow_dispatch:
 
 jobs:
+  test:
+    runs-on: ubuntu-latest
+    steps:
+      - name: Install system dependencies
+        shell: sh
+        run: |
+          apk add --no-cache git python3 py3-pip gcc musl-dev libpq-dev python3-dev
+
+      - name: Checkout code
+        shell: sh
+        run: |
+          git clone http://gitea.gitea.svc.cluster.local/${{ gitea.repository }}.git .
+          git checkout ${{ gitea.sha }}
+
+      - name: Install Python dependencies
+        shell: sh
+        run: |
+          pip3 install --break-system-packages -r requirements.txt ruff
+
+      - name: Run ruff linter
+        shell: sh
+        run: |
+          ruff check SPARC/ tests/
+
+      - name: Run pytest
+        shell: sh
+        env:
+          DATABASE_URL: "sqlite://"
+          API_KEY: "test-key"
+          OPENROUTER_API_KEY: "test-key"
+          JWT_SECRET: "test-secret-for-ci"
+          APP_ENV: "development"
+        run: |
+          python3 -m pytest tests/ -v --tb=short -x
+
   build-api:
+    needs: test
     runs-on: ubuntu-latest
     steps:
       - name: Install dependencies
@@ -81,6 +117,7 @@ jobs:
           echo "API image available at ${{ steps.tags.outputs.IMAGE_TAG }}"
 
   build-frontend:
+    needs: test
     runs-on: ubuntu-latest
     steps:
       - name: Install dependencies

.gitea/workflows/test.yaml

@@ -0,0 +1,46 @@
+name: Test and Lint
+
+on:
+  push:
+    branches:
+      - main
+  pull_request:
+    branches:
+      - main
+  workflow_dispatch:
+
+jobs:
+  test:
+    runs-on: ubuntu-latest
+    steps:
+      - name: Install system dependencies
+        shell: sh
+        run: |
+          apk add --no-cache git python3 py3-pip gcc musl-dev libpq-dev python3-dev
+
+      - name: Checkout code
+        shell: sh
+        run: |
+          git clone http://gitea.gitea.svc.cluster.local/${{ gitea.repository }}.git .
+          git checkout ${{ gitea.sha }}
+
+      - name: Install Python dependencies
+        shell: sh
+        run: |
+          pip3 install --break-system-packages -r requirements.txt ruff
+
+      - name: Run ruff linter
+        shell: sh
+        run: |
+          ruff check SPARC/ tests/
+
+      - name: Run pytest
+        shell: sh
+        env:
+          DATABASE_URL: "sqlite://"
+          API_KEY: "test-key"
+          OPENROUTER_API_KEY: "test-key"
+          JWT_SECRET: "test-secret-for-ci"
+          APP_ENV: "development"
+        run: |
+          python3 -m pytest tests/ -v --tb=short -x

SPARC/__init__.py

@@ -1,3 +1,4 @@
-from .types import Patents, Patent
+from .types import Patent as Patent
+from .types import Patents as Patents
 
-all = ["Patents", "Patent"]
+__all__ = ["Patents", "Patent"]

SPARC/analyzer.py

@@ -5,14 +5,17 @@ to provide company performance estimation based on patent portfolios.
 """
 
 import hashlib
+import logging
 from concurrent.futures import ThreadPoolExecutor, as_completed
 from typing import Callable
 
 from SPARC import config
+
+logger = logging.getLogger(__name__)
 from SPARC.database import DatabaseClient
-from SPARC.serp_api import SERP
 from SPARC.llm import LLMAnalyzer
-from SPARC.types import Patent, Patents, CompanyAnalysisResult, BatchAnalysisResult
+from SPARC.serp_api import SERP
+from SPARC.types import BatchAnalysisResult, CompanyAnalysisResult, Patent, Patents
 
 
 class CompanyAnalyzer:
@@ -52,13 +55,13 @@ class CompanyAnalyzer:
             query_hash = hashlib.sha256(company_name.lower().encode()).hexdigest()
             cached_ids = self.db.get_cached_serp_query(query_hash)
             if cached_ids is not None:
-                print(f"Using cached SERP results for {company_name} ({len(cached_ids)} patents)")
+                logger.info("Using cached SERP results for %s (%d patents)", company_name, len(cached_ids))
                 patents = Patents(patents=[
                     Patent(patent_id=pid, pdf_link="")
                     for pid in cached_ids
                 ])
             else:
-                print(f"Retrieving patents for {company_name}...")
+                logger.info("Retrieving patents for %s...", company_name)
                 patents = SERP.query(company_name)
                 # Cache the SERP results
                 if patents.patents:
@@ -66,12 +69,13 @@ class CompanyAnalyzer:
                         company_name=company_name,
                         query_hash=query_hash,
                         patent_ids=[p.patent_id for p in patents.patents],
+                        ttl_hours=config.serp_cache_ttl_hours,
                     )
 
         if not patents.patents:
             return f"No patents found for {company_name}"
 
-        print(f"Found {len(patents.patents)} patents. Processing...")
+        logger.info("Found %d patents. Processing...", len(patents.patents))
 
         # Download, parse, and minimize patents in parallel
         processed_patents = []
@@ -87,12 +91,12 @@ class CompanyAnalyzer:
                     if result:
                         processed_patents.append(result)
                 except Exception as e:
-                    print(f"Warning: Failed to process {patent.patent_id}: {e}")
+                    logger.warning("Failed to process %s: %s", patent.patent_id, e)
 
         if not processed_patents:
             return f"Failed to process any patents for {company_name}"
 
-        print(f"Analyzing portfolio with LLM...")
+        logger.info("Analyzing portfolio with LLM...")
 
         # Analyze the full portfolio with LLM
         analysis = self.llm_analyzer.analyze_patent_portfolio(
@@ -122,6 +126,7 @@ class CompanyAnalyzer:
           FileNotFoundError: If the patent PDF is not found at the expected path.
         """
         import os
+        logger.info("Analyzing patent %s for %s...", patent_id, company_name)
 
         patent_path = f"patents/{patent_id}.pdf"
 
@@ -183,7 +188,7 @@ class CompanyAnalyzer:
 
             return {"patent_id": patent.patent_id, "content": minimized_content}
         except Exception as e:
-            print(f"Warning: Failed to process {patent.patent_id}: {e}")
+            logger.warning("Failed to process %s: %s", patent.patent_id, e)
             return None
 
     def _analyze_company_safe(self, company_name: str) -> CompanyAnalysisResult:
@@ -254,7 +259,7 @@ class CompanyAnalyzer:
         results: list[CompanyAnalysisResult] = []
         total = len(companies)
 
-        print(f"Starting batch analysis of {total} companies...")
+        logger.info("Starting batch analysis of %d companies...", total)
 
         with ThreadPoolExecutor(max_workers=max_workers) as executor:
             future_to_company = {
@@ -271,8 +276,8 @@ class CompanyAnalyzer:
                     result = future.result()
                     results.append(result)
 
-                    status = "✓" if result.success else "✗"
-                    print(f"[{completed}/{total}] {status} {company}")
+                    status = "OK" if result.success else "FAIL"
+                    logger.info("[%d/%d] %s %s", completed, total, status, company)
 
                     if progress_callback:
                         progress_callback(company, completed, total)
@@ -287,12 +292,12 @@ class CompanyAnalyzer:
                             error=str(e),
                         )
                     )
-                    print(f"[{completed}/{total}] ✗ {company}: {e}")
+                    logger.error("[%d/%d] FAIL %s: %s", completed, total, company, e)
 
         successful = sum(1 for r in results if r.success)
         failed = total - successful
 
-        print(f"\nBatch complete: {successful} succeeded, {failed} failed")
+        logger.info("Batch complete: %d succeeded, %d failed", successful, failed)
 
         return BatchAnalysisResult(
             results=results,
@@ -318,20 +323,20 @@ class CompanyAnalyzer:
         results: list[CompanyAnalysisResult] = []
         total = len(companies)
 
-        print(f"Starting sequential analysis of {total} companies...")
+        logger.info("Starting sequential analysis of %d companies...", total)
 
         for idx, company in enumerate(companies, 1):
-            print(f"\n[{idx}/{total}] Analyzing {company}...")
+            logger.info("[%d/%d] Analyzing %s...", idx, total, company)
             result = self._analyze_company_safe(company)
             results.append(result)
 
-            status = "✓" if result.success else "✗"
-            print(f"[{idx}/{total}] {status} {company}")
+            status = "OK" if result.success else "FAIL"
+            logger.info("[%d/%d] %s %s", idx, total, status, company)
 
         successful = sum(1 for r in results if r.success)
         failed = total - successful
 
-        print(f"\nBatch complete: {successful} succeeded, {failed} failed")
+        logger.info("Batch complete: %d succeeded, %d failed", successful, failed)
 
         return BatchAnalysisResult(
             results=results,

SPARC/api.py

@@ -169,6 +169,9 @@ async def lifespan(app: FastAPI):
         import logging
         logging.getLogger(__name__).warning("Marked %d stale jobs as failed on startup", stale)
     _db.close()
+    # Start scheduled analysis if tracked companies are configured
+    from SPARC.scheduler import start_scheduler
+    start_scheduler()
     yield
     # Cleanup
     _analyzer = None
@@ -369,6 +372,60 @@ async def delete_user(
     return {"message": "User deleted"}
 
 
+# ============== Tracked Companies Endpoints ==============
+
+
+class TrackCompanyRequest(BaseModel):
+    """Request to add a company to tracking."""
+
+    company_name: str = Field(..., min_length=1, max_length=255)
+
+
+@app.get("/admin/tracked", tags=["Admin"])
+async def list_tracked_companies(
+    _: UserResponse = Depends(get_current_admin),
+):
+    """List all tracked companies (admin only)."""
+    db = get_db_client()
+    return db.list_tracked_companies()
+
+
+@app.post("/admin/tracked", tags=["Admin"])
+async def add_tracked_company(
+    request: TrackCompanyRequest,
+    _: UserResponse = Depends(get_current_admin),
+):
+    """Add a company to the tracked list (admin only)."""
+    db = get_db_client()
+    result = db.add_tracked_company(request.company_name)
+    if not result:
+        raise HTTPException(status_code=409, detail="Company already tracked")
+    return result
+
+
+@app.delete("/admin/tracked/{company_name}", tags=["Admin"])
+async def remove_tracked_company(
+    company_name: str,
+    _: UserResponse = Depends(get_current_admin),
+):
+    """Remove a company from the tracked list (admin only)."""
+    db = get_db_client()
+    removed = db.remove_tracked_company(company_name)
+    if not removed:
+        raise HTTPException(status_code=404, detail="Company not found in tracking list")
+    return {"message": f"Stopped tracking {company_name}"}
+
+
+@app.get("/admin/alerts", tags=["Admin"])
+async def list_alerts(
+    limit: int = Query(default=50, ge=1, le=200),
+    _: UserResponse = Depends(get_current_admin),
+):
+    """List recent alerts from scheduled analysis (admin only)."""
+    db = get_db_client()
+    return db.list_alerts(limit=limit)
+
+
 # ============== Analytics Endpoint ==============
 
 

SPARC/config.py

@@ -2,11 +2,20 @@
 
 Loads environment variables from .env file for API keys and other secrets.
 """
-from dotenv import load_dotenv
+import logging
 import os
 
+from dotenv import load_dotenv
+
 load_dotenv()
 
+# Logging configuration
+log_level = os.getenv("LOG_LEVEL", "INFO").upper()
+logging.basicConfig(
+    level=getattr(logging, log_level, logging.INFO),
+    format="%(asctime)s %(levelname)s %(name)s %(message)s",
+)
+
 # SerpAPI key for patent search
 api_key = os.getenv("API_KEY")
 
@@ -30,6 +39,12 @@ use_database = os.getenv("USE_DATABASE", "false").lower() in ("true", "1", "yes"
 patent_search_days = int(os.getenv("PATENT_SEARCH_DAYS", "90"))
 patent_thread_workers = int(os.getenv("PATENT_THREAD_WORKERS", "5"))
 
+# LLM model to use via OpenRouter (e.g. "anthropic/claude-3.5-sonnet", "openai/gpt-4o")
+model = os.getenv("MODEL", "anthropic/claude-3.5-sonnet")
+
+# SERP cache TTL in hours (how long cached search results are considered fresh)
+serp_cache_ttl_hours = int(os.getenv("SERP_CACHE_TTL_HOURS", "24"))
+
 # Root path for running behind a reverse proxy (e.g., "/api" when served at /api/)
 # This ensures OpenAPI docs work correctly when accessed via the proxy
 root_path = os.getenv("ROOT_PATH", "")

SPARC/database.py

@@ -1,14 +1,15 @@
 """Database client for storing and retrieving LLM messages and user authentication."""
 
 import contextlib
-import psycopg2
-from psycopg2.pool import ThreadedConnectionPool
-from psycopg2.extras import RealDictCursor
-from typing import Dict, List, Optional
-from datetime import datetime, timedelta
-import json
 import hashlib
+import json
+from datetime import datetime, timedelta
+from typing import Dict, List, Optional
+
 import bcrypt
+import psycopg2
+from psycopg2.extras import RealDictCursor
+from psycopg2.pool import ThreadedConnectionPool
 
 
 class DatabaseClient:
@@ -191,6 +192,35 @@ class DatabaseClient:
                 ON jobs(status)
             """)
 
+            # Create tracked companies table for scheduled analysis
+            cursor.execute("""
+                CREATE TABLE IF NOT EXISTS tracked_companies (
+                    id SERIAL PRIMARY KEY,
+                    company_name VARCHAR(255) UNIQUE NOT NULL,
+                    last_patent_count INTEGER DEFAULT 0,
+                    last_analysis_at TIMESTAMP,
+                    created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP
+                )
+            """)
+
+            # Create alerts table for significant changes
+            cursor.execute("""
+                CREATE TABLE IF NOT EXISTS alerts (
+                    id SERIAL PRIMARY KEY,
+                    company_name VARCHAR(255) NOT NULL,
+                    alert_type VARCHAR(50) NOT NULL,
+                    message TEXT NOT NULL,
+                    old_value NUMERIC,
+                    new_value NUMERIC,
+                    created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP
+                )
+            """)
+
+            cursor.execute("""
+                CREATE INDEX IF NOT EXISTS idx_alerts_company
+                ON alerts(company_name)
+            """)
+
             self.conn.commit()
 
     @staticmethod
@@ -802,3 +832,81 @@ class DatabaseClient:
             with conn.cursor() as cursor:
                 cursor.execute("SELECT COUNT(*) FROM users")
                 return cursor.fetchone()[0]
+
+    # Tracked Companies Methods
+
+    def add_tracked_company(self, company_name: str) -> Optional[Dict]:
+        """Add a company to the tracking list."""
+        with self.get_conn() as conn:
+            with conn.cursor(cursor_factory=RealDictCursor) as cursor:
+                try:
+                    cursor.execute(
+                        "INSERT INTO tracked_companies (company_name) VALUES (%s) RETURNING *",
+                        (company_name,),
+                    )
+                    row = cursor.fetchone()
+                    conn.commit()
+                    return dict(row) if row else None
+                except Exception:
+                    conn.rollback()
+                    return None
+
+    def remove_tracked_company(self, company_name: str) -> bool:
+        """Remove a company from the tracking list."""
+        with self.get_conn() as conn:
+            with conn.cursor() as cursor:
+                cursor.execute(
+                    "DELETE FROM tracked_companies WHERE LOWER(company_name) = LOWER(%s)",
+                    (company_name,),
+                )
+                conn.commit()
+                return cursor.rowcount > 0
+
+    def list_tracked_companies(self) -> List[Dict]:
+        """List all tracked companies."""
+        with self.get_conn() as conn:
+            with conn.cursor(cursor_factory=RealDictCursor) as cursor:
+                cursor.execute("SELECT * FROM tracked_companies ORDER BY company_name")
+                return [dict(row) for row in cursor.fetchall()]
+
+    def update_tracked_company(
+        self, company_name: str, patent_count: int
+    ) -> None:
+        """Update the last analysis stats for a tracked company."""
+        with self.get_conn() as conn:
+            with conn.cursor() as cursor:
+                cursor.execute(
+                    """UPDATE tracked_companies
+                       SET last_patent_count = %s, last_analysis_at = CURRENT_TIMESTAMP
+                       WHERE LOWER(company_name) = LOWER(%s)""",
+                    (patent_count, company_name),
+                )
+                conn.commit()
+
+    def store_alert(
+        self,
+        company_name: str,
+        alert_type: str,
+        message: str,
+        old_value: float | None = None,
+        new_value: float | None = None,
+    ) -> None:
+        """Record an alert for a significant change."""
+        with self.get_conn() as conn:
+            with conn.cursor() as cursor:
+                cursor.execute(
+                    """INSERT INTO alerts (company_name, alert_type, message, old_value, new_value)
+                       VALUES (%s, %s, %s, %s, %s)""",
+                    (company_name, alert_type, message, old_value, new_value),
+                )
+                conn.commit()
+
+    def list_alerts(self, limit: int = 50) -> List[Dict]:
+        """List recent alerts."""
+        with self.get_conn() as conn:
+            with conn.cursor(cursor_factory=RealDictCursor) as cursor:
+                cursor.execute(
+                    "SELECT * FROM alerts ORDER BY created_at DESC LIMIT %s",
+                    (limit,),
+                )
+                return [dict(row) for row in cursor.fetchall()]

SPARC/llm.py

@@ -1,9 +1,14 @@
 """LLM integration for patent analysis using OpenRouter."""
 
+import logging
+from typing import Dict
+
 from openai import OpenAI
+
 from SPARC import config
 from SPARC.database import DatabaseClient
-from typing import Dict
+
+logger = logging.getLogger(__name__)
 
 
 class LLMAnalyzer:
@@ -20,7 +25,7 @@ class LLMAnalyzer:
         """
         self.test_mode = test_mode
         self.use_cache = use_cache if use_cache is not None else config.use_cache
-        self.model = "anthropic/claude-3.5-sonnet"
+        self.model = config.model
 
         # Always initialize database client for storage and caching
         self.db_client = DatabaseClient(config.database_url)
@@ -59,11 +64,7 @@ Patent Content:
 Provide a concise analysis (2-3 paragraphs) focusing on what this patent reveals about the company's technical direction and competitive advantage."""
 
         if self.test_mode:
-            print("=" * 80)
-            print("TEST MODE - Prompt that would be sent to LLM:")
-            print("=" * 80)
-            print(prompt)
-            print("=" * 80)
+            logger.debug("TEST MODE - Prompt that would be sent to LLM:\n%s", prompt)
             return "[TEST MODE - No API call made]"
 
         # Check cache first
@@ -165,7 +166,7 @@ Patent Portfolio:
 Provide a comprehensive analysis (4-5 paragraphs) with a final verdict on the company's innovation strength and performance outlook."""
 
         if self.test_mode:
-            print(prompt)
+            logger.debug("TEST MODE - Portfolio prompt:\n%s", prompt)
             return "[TEST MODE]"
 
         metadata = {

SPARC/scheduler.py

@@ -0,0 +1,109 @@
+"""Scheduled patent analysis for tracked companies.
+
+Uses APScheduler to periodically re-analyze tracked companies and
+detect significant changes in patent counts.
+"""
+
+import logging
+import os
+
+from SPARC import config
+from SPARC.analyzer import CompanyAnalyzer
+from SPARC.database import DatabaseClient
+
+logger = logging.getLogger(__name__)
+
+# Configurable via environment variable (in hours, default 24)
+SCHEDULE_INTERVAL_HOURS = int(os.getenv("SCHEDULE_INTERVAL_HOURS", "24"))
+
+# Patent count change threshold (percentage) to trigger an alert
+CHANGE_THRESHOLD_PERCENT = int(os.getenv("CHANGE_THRESHOLD_PERCENT", "20"))
+
+
+def run_scheduled_analysis() -> None:
+    """Re-analyze all tracked companies and check for significant changes."""
+    db = DatabaseClient(config.database_url)
+    db.connect()
+    db.initialize_schema()
+
+    tracked = db.list_tracked_companies()
+    if not tracked:
+        logger.info("No tracked companies configured; skipping scheduled analysis")
+        return
+
+    logger.info("Running scheduled analysis for %d tracked companies", len(tracked))
+
+    analyzer = CompanyAnalyzer(db_client=db)
+
+    for company_row in tracked:
+        name = company_row["company_name"]
+        old_count = company_row.get("last_patent_count", 0) or 0
+
+        try:
+            result = analyzer._analyze_company_safe(name)
+
+            if result.success:
+                new_count = result.patent_count
+
+                # Update tracking record
+                db.update_tracked_company(name, new_count)
+
+                # Check for significant change
+                if old_count > 0:
+                    delta_pct = abs(new_count - old_count) / old_count * 100
+                    if delta_pct >= CHANGE_THRESHOLD_PERCENT:
+                        direction = "increased" if new_count > old_count else "decreased"
+                        message = (
+                            f"Patent count for {name} {direction} by {delta_pct:.0f}% "
+                            f"({old_count} -> {new_count})"
+                        )
+                        logger.warning("ALERT: %s", message)
+                        db.store_alert(
+                            company_name=name,
+                            alert_type="patent_count_change",
+                            message=message,
+                            old_value=old_count,
+                            new_value=new_count,
+                        )
+                elif new_count > 0:
+                    # First analysis -- record baseline
+                    logger.info("Baseline for %s: %d patents", name, new_count)
+            else:
+                logger.warning("Scheduled analysis failed for %s: %s", name, result.error)
+
+        except Exception as e:
+            logger.error("Error analyzing tracked company %s: %s", name, e)
+
+    db.close()
+    logger.info("Scheduled analysis complete")
+
+
+def start_scheduler() -> None:
+    """Start the APScheduler background scheduler.
+
+    Safe to call at application startup. If apscheduler is not installed,
+    the function logs a warning and returns without starting anything.
+    """
+    try:
+        from apscheduler.schedulers.background import BackgroundScheduler
+    except ImportError:
+        logger.warning(
+            "apscheduler not installed; scheduled analysis disabled. "
+            "Install with: pip install apscheduler"
+        )
+        return
+
+    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,
+    )

SPARC/serp_api.py

@@ -1,12 +1,15 @@
 import os
-import serpapi
-from SPARC import config
 import re
-import pdfplumber  # pip install pdfplumber
-import requests
 from datetime import datetime, timedelta
 from typing import Dict
-from SPARC.types import Patents, Patent
+
+import pdfplumber  # pip install pdfplumber
+import requests
+import serpapi
+
+from SPARC import config
+from SPARC.types import Patent, Patents
+
 
 class SERP:
   def query(company: str, days_back: int = None) -> Patents:

SPARC/types.py

@@ -4,7 +4,7 @@ from datetime import datetime
 
 @dataclass
 class Patent:
-    patent_id: int
+    patent_id: str
     pdf_link: str
     pdf_path: str | None = None
     summary: dict | None = None

requirements.txt

@@ -15,3 +15,4 @@ pandas
 bcrypt
 PyJWT
 slowapi
+apscheduler

ruff.toml

@@ -0,0 +1,8 @@
+[lint]
+select = ["E", "F", "I"]
+ignore = [
+    "E501",  # line too long (handled by formatter)
+]
+
+[lint.per-file-ignores]
+"tests/*" = ["E402", "F841"]  # allow import not at top of file, unused vars (mocks) in tests

tests/test_analyzer.py

@@ -1,9 +1,11 @@
 """Tests for the high-level company analyzer orchestration."""
 
+from unittest.mock import MagicMock, Mock
+
 import pytest
-from unittest.mock import Mock, patch, call, MagicMock
+
 from SPARC.analyzer import CompanyAnalyzer
-from SPARC.types import Patent, Patents, CompanyAnalysisResult, BatchAnalysisResult
+from SPARC.types import BatchAnalysisResult, Patent, Patents
 
 
 @pytest.fixture(autouse=True)
@@ -24,7 +26,7 @@ class TestCompanyAnalyzer:
         """Test analyzer initialization with API key."""
         mock_llm = mocker.patch("SPARC.analyzer.LLMAnalyzer")
 
-        analyzer = CompanyAnalyzer(openrouter_api_key="test-key")
+        _analyzer = CompanyAnalyzer(openrouter_api_key="test-key")  # noqa: F841
 
         mock_llm.assert_called_once_with(api_key="test-key")
 

tests/test_api.py

@@ -1,12 +1,13 @@
 """Tests for FastAPI web service endpoints."""
 
-import pytest
 from datetime import datetime
-from unittest.mock import Mock, patch
+from unittest.mock import Mock
+
+import pytest
 from fastapi.testclient import TestClient
 
 from SPARC.api import app
-from SPARC.types import CompanyAnalysisResult, BatchAnalysisResult
+from SPARC.types import BatchAnalysisResult, CompanyAnalysisResult
 
 
 @pytest.fixture

tests/test_llm.py

@@ -1,7 +1,9 @@
 """Tests for LLM analysis functionality."""
 
+from unittest.mock import Mock
+
 import pytest
-from unittest.mock import Mock, MagicMock, patch
+
 from SPARC.llm import LLMAnalyzer
 
 

tests/test_serp_api.py

@@ -1,9 +1,8 @@
 """Tests for SERP API patent retrieval and parsing functionality."""
 
-import os
-import pytest
-from unittest.mock import patch, Mock
 from datetime import datetime, timedelta
+from unittest.mock import Mock
+
 from SPARC.serp_api import SERP
 from SPARC.types import Patent