Add linting, coverage, dependabot; clean up dead code and README

- Add ruff linter + pytest-cov to dev deps and CI pipeline
- CI now runs lint check before tests, uploads coverage report
- Add dependabot for pip and github-actions weekly updates
- Remove analyze_sentiment_with_claude alias and rename all callers
- Update README architecture with 8 missing strategy modules, 2 scripts
- Fix test count in README (698 tests across 34 files)
- Fix all ruff lint issues (import sorting, unused vars, whitespace)

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

Author: costajohnt

.github/dependabot.yml

@@ -0,0 +1,17 @@
+version: 2
+updates:
+  - package-ecosystem: "pip"
+    directory: "/"
+    schedule:
+      interval: "weekly"
+    open-pull-requests-limit: 5
+    labels:
+      - "dependencies"
+
+  - package-ecosystem: "github-actions"
+    directory: "/"
+    schedule:
+      interval: "weekly"
+    open-pull-requests-limit: 5
+    labels:
+      - "dependencies"

.github/workflows/ci.yml

@@ -11,8 +11,23 @@ concurrency:
   cancel-in-progress: true
 
 jobs:
+  lint:
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v4
+
+      - name: Install uv
+        uses: astral-sh/setup-uv@v4
+
+      - name: Install Python and dependencies
+        run: uv sync
+
+      - name: Lint with ruff
+        run: uv run ruff check .
+
   test:
     runs-on: ubuntu-latest
+    needs: lint
     steps:
       - uses: actions/checkout@v4
 
@@ -22,5 +37,12 @@ jobs:
       - name: Install Python and dependencies
         run: uv sync
 
-      - name: Run tests
-        run: uv run python -m pytest tests/ -v --tb=short
+      - name: Run tests with coverage
+        run: uv run python -m pytest tests/ -v --tb=short --cov=strategies --cov=scripts --cov-report=term-missing --cov-report=html
+
+      - name: Upload coverage report
+        if: always()
+        uses: actions/upload-artifact@v4
+        with:
+          name: coverage-report
+          path: htmlcov/

README.md

@@ -118,6 +118,14 @@ strategies/
   signal_scorer.py                 Empirical signal scoring (bucket win rates)
   constants.py                     Tunable strategy parameters (agent-modifiable)
   enums.py                         Shared enums (Action, InsiderRecommendation)
+  cooldown.py                      Re-entry cooldown after stop-loss exits
+  equity_tracker.py                Per-position high-water mark tracking
+  regime.py                        Market regime detection (bull/bear/sideways)
+  resilience.py                    API retry decorator with exponential backoff
+  risk_guard.py                    Portfolio-level kill switch (daily loss + drawdown)
+  state_db.py                      SQLite trading state persistence
+  stop_orders.py                   Stop-loss order placement helpers
+  weekly_trend.py                  Weekly SMA trend filter (blocks severe downtrends)
 
 scripts/
   scan_with_sentiment.py           3-layer composite signal + sizing + sector guard
@@ -137,14 +145,16 @@ scripts/
   strategy_agent.py                Autonomous strategy agent (weekly review + event check)
   agent_tools.py                   Agent tool definitions + safety-hardcoded dispatch
   shadow_evaluator.py              Shadow experiment evaluation
+  daily_metrics.py                 Daily performance metrics snapshot
+  walkforward.py                   Walk-forward backtesting validation
   daily_run.sh                     Local pipeline automation
   account_status.py                Quick account connection check
   run_strategy.py                  Single-ticker mean-reversion analysis
   momentum_screener.py             Market-wide momentum screener
 
 data/                              Trading state (signals.csv, trades.csv, metrics.json)
 data/agent/                        Agent state (changelog, experiments, overrides)
-tests/                             654 tests across 30 test files
+tests/                             698 tests across 34 test files
 ```
 
 ## Testing

client.py

@@ -3,10 +3,9 @@
 import os
 from pathlib import Path
 
-from dotenv import load_dotenv
-
-from alpaca.trading.client import TradingClient
 from alpaca.data.historical import StockHistoricalDataClient
+from alpaca.trading.client import TradingClient
+from dotenv import load_dotenv
 
 
 def _load_env():

pyproject.toml

@@ -19,4 +19,21 @@ dependencies = [
 [dependency-groups]
 dev = [
     "pytest>=9.0.2",
+    "pytest-cov>=6.0",
+    "ruff>=0.11.0",
 ]
+
+[tool.ruff]
+target-version = "py314"
+line-length = 120
+
+[tool.ruff.lint]
+select = ["E", "F", "W", "I"]
+ignore = ["E501"]
+
+[tool.ruff.lint.per-file-ignores]
+"tests/*.py" = ["E402"]
+"scripts/*.py" = ["E402"]
+
+[tool.pytest.ini_options]
+addopts = "--tb=short"

scripts/agent_tools.py

@@ -13,7 +13,7 @@
 import subprocess
 import sys
 import tempfile
-from datetime import datetime, date, timedelta
+from datetime import date, datetime, timedelta
 from pathlib import Path
 
 sys.path.insert(0, str(Path(__file__).parent.parent))
@@ -209,7 +209,7 @@ def _files_in_cooling_period() -> set[str]:
                     cooling.add(f)
         except (ValueError, TypeError):
             # Fail safe: treat unparseable as within cooling period
-            print(f"  WARNING: Could not parse timestamp for deployed change — treating as in cooling period")
+            print("  WARNING: Could not parse timestamp for deployed change — treating as in cooling period")
             for f in change.get("files_modified", []):
                 cooling.add(f)
     return cooling
@@ -335,7 +335,7 @@ def read_performance_summary() -> dict:
 
 def read_positions() -> dict:
     """Read current open positions from Alpaca API.
-    
+
     Returns dict with positions list and account summary.
     """
     try:
@@ -372,7 +372,7 @@ def read_positions() -> dict:
 
 def read_code(file_path: str) -> dict:
     """Read a file from the repo.
-    
+
     Returns dict with content or error. Validates path is within project.
     """
     try:
@@ -403,10 +403,10 @@ def read_experiment_results() -> dict:
             experiments.append(json.loads(f.read_text()))
         except Exception as e:
             experiments.append({"file": f.name, "error": str(e)})
-    
+
     active = [e for e in experiments if e.get("status") == "active"]
     completed = [e for e in experiments if e.get("status") in ("promoted", "discarded", "expired")]
-    
+
     return {
         "total": len(experiments),
         "active": len(active),
@@ -685,11 +685,9 @@ def compute_measured_impact(change_id: str) -> dict:
 
     # Find the changelog entry
     entry = None
-    entry_idx = None
     for i, change in enumerate(changelog["changes"]):
         if change.get("id") == change_id:
             entry = change
-            entry_idx = i
             break
 
     if entry is None:
@@ -881,7 +879,7 @@ def _compute_strategy_correlation() -> dict:
 
 def edit_file(file_path: str, old_string: str, new_string: str, rationale: str) -> dict:
     """Edit a file with no-touch enforcement.
-    
+
     Returns success/failure dict. Rejects edits to protected files and files
     in cooling period.
     """
@@ -931,7 +929,7 @@ def edit_file(file_path: str, old_string: str, new_string: str, rationale: str)
 
 def run_backtest(params: dict | None = None) -> dict:
     """Run pipeline_backtest.py and return structured results.
-    
+
     Enforces max invocations per run. params is a dict of CLI arguments.
     """
     global _backtests_this_run
@@ -1031,7 +1029,7 @@ def run_tests() -> dict:
 
 def create_experiment(experiment_id: str, hypothesis: str, variant: dict) -> dict:
     """Create a shadow-mode experiment.
-    
+
     variant should contain: file, parameter, baseline_value, variant_value.
     Enforces max active experiment limit.
     """
@@ -1095,7 +1093,7 @@ def create_experiment(experiment_id: str, hypothesis: str, variant: dict) -> dic
 
 def deploy_change(commit_message: str, evidence: dict) -> dict:
     """Atomic deploy: branch, commit, test, backtest, merge.
-    
+
     Enforces: budget, test pass, backtest Sharpe floor, safety invariants.
     evidence dict should contain: sample_size, change_type, diagnosis.
     """
@@ -1316,19 +1314,19 @@ def _update_pending_status(status: str, commit_sha: str | None = None, snapshot:
 
 def rollback_change(commit_sha: str, reason: str) -> dict:
     """Revert a specific agent-authored commit.
-    
+
     Only reverts commits authored by the agent (checks changelog).
     Runs tests after revert to confirm clean state.
     """
     changelog = _load_changelog()
-    
+
     # Find the change in changelog
     change_entry = None
     for change in changelog["changes"]:
         if change.get("commit_sha") == commit_sha:
             change_entry = change
             break
-    
+
     if change_entry is None:
         return {"success": False, "error": f"Commit {commit_sha} not found in agent changelog — refusing to revert non-agent commits"}
 
@@ -1339,7 +1337,7 @@ def rollback_change(commit_sha: str, reason: str) -> dict:
     dependent_shas = []
     change_files = set(change_entry.get("files_modified", []))
     change_ts = change_entry.get("timestamp", "")
-    
+
     for other in changelog["changes"]:
         if other.get("commit_sha") == commit_sha:
             continue
@@ -1415,7 +1413,7 @@ def rollback_change(commit_sha: str, reason: str) -> dict:
 
 def pause_strategy(strategy_name: str, reason: str) -> dict:
     """Write a pause flag for a strategy. Auto-expires after 3 days.
-    
+
     Valid strategies: screener, momentum, sentiment.
     """
     valid = {"screener", "momentum", "sentiment"}
@@ -1466,12 +1464,12 @@ def is_strategy_paused(strategy_name: str) -> bool:
 
 def log_decision(summary: str, details: dict) -> dict:
     """Log a decision to the changelog. REQUIRED every agent run.
-    
+
     Use for both action decisions and "do nothing" decisions.
     """
     _ensure_agent_dirs()
     changelog = _load_changelog()
-    
+
     entry = {
         "id": f"dec-{datetime.now().strftime('%Y%m%d-%H%M%S')}",
         "timestamp": datetime.now().isoformat(),

scripts/backtest.py

@@ -63,7 +63,7 @@ def main():
     if trades:
         print(f"  Completed trades: {len(trades)}")
         wins = [t for t in trades if t["pnl_pct"] > 0]
-        losses = [t for t in trades if t["pnl_pct"] <= 0]
+        [t for t in trades if t["pnl_pct"] <= 0]
         avg_pnl = sum(t["pnl_pct"] for t in trades) / len(trades)
         total_pnl = sum(t["pnl_pct"] for t in trades)
         print(f"  Win rate:         {len(wins)}/{len(trades)} ({len(wins)/len(trades)*100:.0f}%)")

scripts/daily_metrics.py

@@ -13,7 +13,7 @@
 sys.path.insert(0, str(Path(__file__).parent.parent))
 
 from client import get_trading_client
-from scripts.trade_logger import log_daily_metrics, SIGNAL_LOG, TRADE_LOG
+from scripts.trade_logger import SIGNAL_LOG, log_daily_metrics
 
 
 def _count_today_signals() -> tuple[int, int, int]:
@@ -36,7 +36,7 @@ def _count_today_signals() -> tuple[int, int, int]:
         print(f"  NOTE: Signal log not found ({SIGNAL_LOG}) — signal counts will be zero.")
     except (csv.Error, OSError) as e:
         print(f"  WARNING: Error reading signal log: {e}")
-        print(f"  Signal counts may be incomplete.")
+        print("  Signal counts may be incomplete.")
     return signals, buys, vetoes
 
 

scripts/dashboard.py

@@ -16,9 +16,9 @@
 
 sys.path.insert(0, str(Path(__file__).parent.parent))
 
-from client import get_trading_client, get_data_client
-from strategies.sector import get_sector_exposure, get_sector, SECTOR_MAP
-from strategies.cooldown import load_cooldowns, is_on_cooldown, COOLDOWN_DAYS
+from client import get_trading_client
+from strategies.cooldown import COOLDOWN_DAYS, is_on_cooldown, load_cooldowns
+from strategies.sector import get_sector_exposure
 
 app = Flask(__name__)
 
@@ -92,8 +92,8 @@ def _read_log_tail(n: int = 50) -> list[str]:
 def _get_hold_days(trading_client, symbol: str) -> int | None:
     """Look up when the most recent buy order for *symbol* was filled."""
     try:
-        from alpaca.trading.requests import GetOrdersRequest
         from alpaca.trading.enums import QueryOrderStatus
+        from alpaca.trading.requests import GetOrdersRequest
 
         orders = trading_client.get_orders(GetOrdersRequest(
             status=QueryOrderStatus.CLOSED,
@@ -275,7 +275,7 @@ def _compute_performance_data(positions: list, trading_client) -> dict:
 
     win_rate = (len(wins) / len(trades_with_pl) * 100) if trades_with_pl else 0
     avg_win_pct = (sum(w["pl_pct"] for w in wins) / len(wins)) if wins else 0
-    avg_loss_pct = (sum(l["pl_pct"] for l in losses) / len(losses)) if losses else 0
+    avg_loss_pct = (sum(t["pl_pct"] for t in losses) / len(losses)) if losses else 0
 
     best_trade = max(trades_with_pl, key=lambda x: x["pl_pct"]) if trades_with_pl else None
     worst_trade = min(trades_with_pl, key=lambda x: x["pl_pct"]) if trades_with_pl else None
@@ -287,7 +287,7 @@ def _compute_performance_data(positions: list, trading_client) -> dict:
     vetoed_buy_signals = total_buy_signals - executed_buy_signals
 
     # Of executed buys, how many are currently winning (open or closed)?
-    winning_symbols = set(w["symbol"] for w in wins)
+    set(w["symbol"] for w in wins)
     # Also count open positions that are currently profitable
     winning_open = set(ot["symbol"] for ot in open_trades if ot["pl_pct"] > 0)
     losing_open = set(ot["symbol"] for ot in open_trades if ot["pl_pct"] <= 0)