fix: allow .env variables to override DEFAULT_CONFIG values
Merged origin/main and resolved all 8 conflicting files: - CLAUDE.md: merged MISTAKES.md ref + Project Tracking section + env override docs - cli/main.py: kept top-level json import, kept try/except in run_pipeline - tool_runner.py: kept descriptive comments for MAX_TOOL_ROUNDS - alpha_vantage_common.py: kept thread-safe rate limiter, robust error handling - interface.py: kept broader exception catch (AlphaVantageError + ConnectionError + TimeoutError) - default_config.py: kept _env()/_env_int() env var overrides with load_dotenv() at module level - scanner_graph.py: kept debug mode fix (stream for debug, invoke for result) - macro_bridge.py: kept get_running_loop() over deprecated get_event_loop() Co-authored-by: aguzererler <6199053+aguzererler@users.noreply.github.com>
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@ -1433,6 +1433,10 @@ def run_scan(date: Optional[str] = None):
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s.get("thesis_angle", ""),
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s.get("thesis_angle", ""),
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)
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)
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console.print(table)
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console.print(table)
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# Save as scan_summary.json for downstream auto/pipeline commands
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(save_dir / "scan_summary.json").write_text(
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json.dumps(summary_data, indent=2)
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)
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except (json.JSONDecodeError, KeyError, ValueError):
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except (json.JSONDecodeError, KeyError, ValueError):
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pass # Summary wasn't valid JSON — already printed as markdown
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pass # Summary wasn't valid JSON — already printed as markdown
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@ -1799,7 +1803,7 @@ def auto(
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run_scan(date=date)
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run_scan(date=date)
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console.print("\n[bold magenta]--- Step 2: Per-Ticker Pipeline ---[/bold magenta]")
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console.print("\n[bold magenta]--- Step 2: Per-Ticker Pipeline ---[/bold magenta]")
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macro_path = get_daily_dir(date) / "summary" / "scan_summary.json"
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macro_path = get_market_dir(date) / "scan_summary.json"
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run_pipeline(
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run_pipeline(
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macro_path_str=str(macro_path),
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macro_path_str=str(macro_path),
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min_conviction_opt="medium",
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min_conviction_opt="medium",
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2
main.py
2
main.py
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@ -30,4 +30,4 @@ _, decision = ta.propagate("NVDA", "2024-05-10")
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print(decision)
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print(decision)
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# Memorize mistakes and reflect
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# Memorize mistakes and reflect
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# ta.reflect_and_remember(1000) # parameter is the position returns
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ta.reflect_and_remember(1000) # parameter is the position returns
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