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-e\n\n# Install required Python packages\npython3 -m pip install --upgrade pip\npip install \\\n numpy \\\n pandas \\\n jupyterlab \\\n ipywidgets \\\n statsmodels \\\n openpyxl \\\n matplotlib \\\n streamlit \\\n fastapi \\\n uvicorn \\\n hypothesis\n\necho \"✅ Python environment ready\"","mode","on","preset_allowlist","allowlist_domains","pypi.org, github.com, files.pythonhosted.org, deb.debian.org, security.ubuntu.com, raw.githubusercontent.com","allowlist_rules","denylist_domains","safe_methods_only","number",3929,"https://github.com/stranske/Trend_Model_Project/pull/3929","state","closed","merged","mergeable","draft","title","chore(codex): bootstrap PR for issue #3915","body","\n\n\n\n## Automated Status Summary\n#### Scope\n- [ ] `trend_portfolio_app.app._PipelineProxy` scans `gc.get_objects()` to prefer patched pipeline modules, which aids testing but adds overhead and magic. Production deployments could benefit from an opt-in simple mode that imports the pipeline directly.\n\n#### Tasks\n- [x] Add an environment flag (e.g., `TREND_PIPELINE_PROXY_SIMPLE`) that, when set, skips GC scanning and directly imports `trend_analysis.pipeline`.\n- [x] Ensure default behaviour remains unchanged (GC scanning enabled) to preserve test friendliness.\n- [x] Add tests covering both modes to assert correct pipeline resolution and instrumentation behaviour.\n\n#### Acceptance criteria\n- [x] - Setting the new env flag yields a direct-import proxy path; default continues to honour GC-scanned modules.\n- [x] - Tests cover simple and default modes and pass without changing existing app behaviour for users who do not set the flag.\n\n**Head SHA:** 18c5f913c8998e0ce6e59c6aa2c997e0e75bd088\n**Latest Runs:** ✅ success — Gate\n**Required:** gate: ✅ success\n\n| Workflow / Job | Result | Logs |\n|----------------|--------|------|\n| Agents PR meta manager | ❔ in progress | [View run](https://github.com/stranske/Trend_Model_Project/actions/runs/19849663830) |\n| CI Autofix Loop | ✅ success | [View run](https://github.com/stranske/Trend_Model_Project/actions/runs/19849591163) |\n| Gate | ✅ success | [View run](https://github.com/stranske/Trend_Model_Project/actions/runs/19849591194) |\n| Health 40 Sweep | ✅ success | [View run](https://github.com/stranske/Trend_Model_Project/actions/runs/19849591165) |\n| Health 44 Gate Branch Protection | ✅ success | [View run](https://github.com/stranske/Trend_Model_Project/actions/runs/19849591173) |\n| Health 45 Agents Guard | ✅ success | [View run](https://github.com/stranske/Trend_Model_Project/actions/runs/19849591182) |\n| Health 50 Security Scan | ✅ success | [View run](https://github.com/stranske/Trend_Model_Project/actions/runs/19849591162) |\n| Maint 52 Validate Workflows | ✅ success | [View run](https://github.com/stranske/Trend_Model_Project/actions/runs/19849591190) |\n| PR 11 - Minimal invariant CI | ✅ success | [View run](https://github.com/stranske/Trend_Model_Project/actions/runs/19849591169) |\n","base","head","base_sha","116715d9a4d28e6aa29a669788640ec8a5722dbd","head_sha","18c5f913c8998e0ce6e59c6aa2c997e0e75bd088","head_repo_id","head_repo_full_name","merge_commit_sha","76414f32f1065289320abbf6edca81d0d426f8fd","comments","diff","user",{"_266":267,"_160":267,"_317":-5,"_270":271,"_53":268},"commits",24,"changed_files",5,"additions",275,"deletions",11,"email","events",[],[],"messages",[],{"_104":1092,"_1093":1094,"_1095":1096,"_1097":1098,"_1099":-5},{"_104":1071,"_108":105,"_342":1072},{"_104":326,"_327":328},"partial_repo_snapshot","files",[329,330],{"_331":574,"_333":-5,"_334":575,"_336":-5},{"_331":332,"_333":-5,"_334":335,"_336":-5},"path","tests/app/test_portfolio_app_additional.py","contents","line_range_contents",[337],"missing_reason",{"_338":339,"_340":341,"_342":343,"_344":70},"line_range_start",1,"line_range_end",403,"content",[345,178,346,347,348,178,349,350,178,351,178,178,352,353,354,355,356,357,178,358,359,360,178,361,362,363,178,178,364,353,365,356,357,366,367,178,361,368,178,178,369,353,370,371,372,357,373,374,375,367,178,361,376,178,178,377,353,354,355,378,178,379,380,178,381,178,361,382,178,178,383,370,384,178,385,178,386,387,388,178,389,390,391,178,392,393,394,395,396,178,361,178,397,398,399,400,178,178,401,402,403,404,405,178,406,178,385,178,407,390,408,409,178,386,387,388,178,410,394,411,396,178,361,178,397,412,399,413,400,414,178,178,415,370,416,178,417,178,418,419,391,178,420,392,393,396,178,421,422,178,423,424,400,178,178,425,426,427,428,178,429,430,431,178,432,433,434,178,178,435,436,437,438,178,439,440,441,442,443,444,445,446,447,178,448,449,450,451,452,443,453,454,455,456,457,458,459,460,461,462,463,453,178,178,464,465,466,467,468,445,469,470,178,471,472,473,474,178,178,475,476,477,478,479,480,481,482,483,484,485,486,487,488,178,489,490,178,491,490,178,492,493,494,495,494,496,178,497,498,178,499,500,178,501,502,503,178,504,505,178,506,507,178,508,509,178,510,511,178,512,513,178,514,515,178,516,517,178,518,519,178,520,521,178,522,523,178,178,524,525,526,373,527,375,528,178,529,530,531,444,532,533,534,535,536,443,445,537,538,373,539,540,541,542,543,544,545,546,547,375,178,548,549,178,550,551,552,553,178,178,554,525,526,373,527,375,528,555,556,178,557,558,178,559,560,178,548,549,178,561,178,178,562,525,563,564,526,373,527,375,528,178,565,530,532,533,534,535,480,445,537,538,560,178,548,549,178,566,567,178,178,568,525,526,373,527,375,528,178,565,537,178,569,570,178,571,572,560,178,548,549,178,573],"contains_end_of_file","from __future__ import annotations","import gc","import sys","from types import ModuleType, SimpleNamespace","import pandas as pd","import pytest","import trend_portfolio_app.app as app","def test_pipeline_proxy_prefers_gc_patched_module(monkeypatch):"," monkeypatch.delenv(\"TREND_PIPELINE_PROXY_SIMPLE\", raising=False)"," base_module = SimpleNamespace(run=lambda cfg: \"base\")"," monkeypatch.setitem(sys.modules, \"trend_analysis.pipeline\", base_module)"," pkg_module = SimpleNamespace(run=lambda cfg: \"pkg\")"," monkeypatch.setattr(app, \"_trend_pkg\", SimpleNamespace(pipeline=pkg_module))"," patched_module = ModuleType(\"trend_analysis.pipeline\")"," patched_module.run = lambda cfg: \"patched\""," monkeypatch.setattr(gc, \"get_objects\", lambda: [patched_module])"," result = app.pipeline.run(object())"," assert result == \"patched\""," assert app._PIPELINE_DEBUG[-1][:2] == (\"run\", False)","def test_pipeline_proxy_falls_back_to_package(monkeypatch):"," monkeypatch.setitem(sys.modules, \"trend_analysis.pipeline\", None)"," monkeypatch.setattr(app, \"_resolve_pipeline\", lambda fresh=False: pkg_module)"," monkeypatch.setattr(gc, \"get_objects\", lambda: [])"," assert result == \"pkg\"","def test_pipeline_proxy_uses_package_attribute(monkeypatch):"," module = ModuleType(\"trend_analysis.pipeline\")"," monkeypatch.setitem(sys.modules, \"trend_analysis.pipeline\", module)"," pkg_module = SimpleNamespace(run=lambda cfg: \"package\")"," monkeypatch.setattr("," app, \"_resolve_pipeline\", lambda fresh=False, simple=False: module"," )"," assert result == \"package\"","def test_pipeline_proxy_handles_gc_errors(monkeypatch):"," monkeypatch.setattr(app, \"_trend_pkg\", SimpleNamespace(pipeline=base_module))"," def raising_get_objects() -> list[object]:"," raise RuntimeError(\"boom\")"," monkeypatch.setattr(gc, \"get_objects\", raising_get_objects)"," assert result == \"base\"","def test_pipeline_proxy_simple_mode_direct_import(monkeypatch):"," module.run = lambda cfg: \"direct\""," called = {\"gc\": False, \"imports\": 0}"," def fake_get_objects():"," called[\"gc\"] = True"," return []"," def resolve_stub(*, fresh=False, simple=False):"," called[\"imports\"] += 1"," return module"," monkeypatch.setattr(app, \"_resolve_pipeline\", resolve_stub)"," monkeypatch.setattr(app, \"_trend_pkg\", SimpleNamespace(pipeline=None))"," monkeypatch.setattr(gc, \"get_objects\", fake_get_objects)"," monkeypatch.setenv(\"TREND_PIPELINE_PROXY_SIMPLE\", \"1\")"," app._PIPELINE_DEBUG.clear()"," assert result == \"direct\""," assert called[\"gc\"] is False"," assert called[\"imports\"] == 1"," assert app._PIPELINE_DEBUG[-1][:2] == (\"run\", True)","def test_pipeline_proxy_simple_mode_ignores_sys_modules_patch(monkeypatch):"," patched = ModuleType(\"trend_analysis.pipeline\")"," patched.run = lambda cfg: \"patched\""," canonical = ModuleType(\"trend_analysis.pipeline\")"," canonical.run = lambda cfg: \"direct\""," monkeypatch.setitem(sys.modules, \"trend_analysis.pipeline\", patched)"," def import_module_stub(mod: str):"," sys.modules[mod] = canonical"," return canonical"," monkeypatch.setattr(app, \"import_module\", import_module_stub)"," monkeypatch.setenv(\"TREND_PIPELINE_PROXY_SIMPLE\", \"true\")"," assert sys.modules.get(\"trend_analysis.pipeline\") is canonical"," assert called.get(\"gc\", False) is False"," assert sys.modules[\"trend_analysis.pipeline\"] is canonical","def test_pipeline_proxy_simple_mode_caches_direct_import(monkeypatch):"," module.run = lambda cfg: \"cached\""," calls = {\"imports\": 0}"," def resolve_stub(*, fresh: bool = False, simple: bool = False):"," calls[\"imports\"] += 1"," monkeypatch.setenv(\"TREND_PIPELINE_PROXY_SIMPLE\", \"yes\")"," first = app.pipeline.run(object())"," second = app.pipeline.run(object())"," assert first == \"cached\" == second"," assert calls[\"imports\"] == 1","def test_columns_normalisation_uses_placeholders(monkeypatch):"," class StubColumns:"," def __call__(self, spec):"," return []"," monkeypatch.setattr(app.st, \"columns\", StubColumns())"," placeholder = object()"," monkeypatch.setattr(app.st, \"empty\", lambda: placeholder)"," cols = app._columns(2)"," assert len(cols) == 2"," assert cols[0] is placeholder","def test_summary_helpers_and_multi_rounding():"," df = pd.DataFrame({\"Sharpe\": [0.12345, 0.98765]})"," summary = app._summarise_run_df(df)"," assert summary.iloc[0, 0] == pytest.approx(0.1234)"," result = {"," \"out_sample_stats\": {"," \"user\": SimpleNamespace(cagr=0.1, sharpe=0.8),"," \"equal\": {\"cagr\": 0.05, \"sharpe\": 0.6},"," },"," \"benchmark_ir\": {\"user\": {\"FundA\": 0.3, \"equal_weight\": 0.1}},"," }"," summary_table = app._build_summary_from_result(result)"," assert \"ir_user\" in summary_table.columns"," multi_results = ["," {"," \"period\": (\"2020-01\", \"2020-12\", \"2021-01\", \"2021-12\"),"," \"out_ew_stats\": {\"sharpe\": 0.8, \"cagr\": 0.1},"," \"out_user_stats\": SimpleNamespace(sharpe=0.9, cagr=0.12),"," ]"," multi_summary = app._summarise_multi(multi_results)"," assert list(multi_summary.columns) == ["," \"in_start\","," \"in_end\","," \"out_start\","," \"out_end\","," \"ew_sharpe\","," \"user_sharpe\","," \"ew_cagr\","," \"user_cagr\",","def test_apply_session_state_merges_nested(monkeypatch):"," state = {"," \"data.csv_path\": \"data.csv\","," \"portfolio.mode\": \"rank\","," \"sample_split.window._months\": \"3\","," monkeypatch.setattr(app.st, \"session_state\", state)"," cfg: dict[str, object] = {}"," app._apply_session_state(cfg)"," assert cfg[\"data\"][\"csv_path\"] == \"data.csv\""," assert cfg[\"portfolio\"][\"mode\"] == \"rank\""," assert cfg[\"sample_split\"][\"window\"][\"length\"] == 63","class StubStreamlit:"," def __init__(self):"," self.session_state = {"," \"data.csv_path\": \"input.csv\","," \"portfolio.mode\": \"rank\","," }"," self.warnings: list[str] = []"," self.successes: list[str] = []"," self.dataframes: list[pd.DataFrame] = []"," self.downloads: list[tuple[str, bytes]] = []"," self.captions: list[str] = []"," self.line = []"," self.bar = []"," self.infos: list[str] = []"," def header(self, text: str) -> None:"," pass"," def subheader(self, text: str) -> None:"," def button(self, label: str, **_: object) -> bool:"," if label == \"Run Single Period\":"," return True"," if label == \"Run Multi-Period\":"," return False"," def text_input(self, label: str, **_: object) -> str:"," return \"input.csv\""," def download_button(self, label: str, *, data: bytes, **_: object) -> None:"," self.downloads.append((label, data))"," class _Spinner:"," def __enter__(self) -> None:"," return None"," def __exit__(self, exc_type, exc, tb) -> bool:"," return False"," def spinner(self, message: str) -> \"StubStreamlit._Spinner\":"," return StubStreamlit._Spinner()"," def dataframe(self, df: pd.DataFrame, **_: object) -> None:"," self.dataframes.append(df.copy())"," def warning(self, message: str) -> None:"," self.warnings.append(message)"," def success(self, message: str) -> None:"," self.successes.append(message)"," def caption(self, text: str) -> None:"," self.captions.append(text)"," def line_chart(self, df: pd.DataFrame) -> None:"," self.line.append(df.copy())"," def bar_chart(self, df: pd.DataFrame) -> None:"," self.bar.append(df.copy())"," def info(self, message: str) -> None:"," self.infos.append(message)"," def empty(self):"," return app._NullContext()","def test_render_run_section_success(monkeypatch):"," stub = StubStreamlit()"," monkeypatch.setattr(app, \"st\", stub)"," app, \"_columns\", lambda spec: [app._NullContext(), app._NullContext()]"," monkeypatch.setattr(app, \"_build_cfg\", lambda cfg: cfg)"," summary_df = pd.DataFrame({\"Sharpe\": [0.8], \"CAGR\": [0.12]})"," full_result = {"," \"out_sample_stats\": {\"user\": SimpleNamespace(cagr=0.1, sharpe=0.8)},"," \"risk_diagnostics\": {"," \"asset_volatility\": pd.DataFrame({\"FundA\": [0.2]}),"," \"portfolio_volatility\": pd.Series([0.1], index=pd.Index([\"2024-01\"])),"," \"turnover\": pd.Series([0.05], index=pd.Index([\"2024-01\"])),"," \"turnover_value\": 0.1234,"," monkeypatch.setattr(app.pipeline, \"run\", lambda cfg: summary_df)"," monkeypatch.setattr(app.pipeline, \"run_full\", lambda cfg: full_result)"," app,"," \"run_multi\","," lambda cfg: ["," {"," \"period\": (\"2020-01\", \"2020-12\", \"2021-01\", \"2021-12\"),"," \"out_ew_stats\": {\"sharpe\": 0.5, \"cagr\": 0.07},"," \"out_user_stats\": {\"sharpe\": 0.6, \"cagr\": 0.08},"," }"," ],"," cfg_dict = {\"data\": {}, \"portfolio\": {}}"," app._render_run_section(cfg_dict)"," assert stub.successes"," assert stub.downloads"," assert any(\"Realised asset volatility\" in text for text in stub.captions)"," assert stub.line and stub.bar","def test_render_run_section_failure_message(monkeypatch):"," monkeypatch.setattr(app, \"_summarise_run_df\", lambda *_: None)"," monkeypatch.setattr(app.pipeline, \"run\", lambda cfg: None)"," def raise_full(cfg):"," raise FileNotFoundError(\"missing.csv\")"," monkeypatch.setattr(app.pipeline, \"run_full\", raise_full)"," monkeypatch.setattr(app, \"run_multi\", lambda cfg: [])"," assert stub.warnings and \"missing.csv\" in stub.warnings[0]","def test_render_run_section_uses_dataframe_fallback(monkeypatch):"," stub.line_chart = \"not-callable\""," stub.bar_chart = \"not-callable\""," summary_df = pd.DataFrame({\"Sharpe\": [0.8]})"," # Fallback should record dataframes for each diagnostic"," assert len(stub.dataframes) >= 3","def test_render_run_section_logs_info_on_partial_results(monkeypatch):"," def raise_error(cfg: object) -> None:"," raise ValueError(\"failed run_full\")"," monkeypatch.setattr(app.pipeline, \"run_full\", raise_error)"," monkeypatch.setattr(app, \"_summarise_run_df\", lambda df: summary_df)"," assert any(\"failed run_full\" in message for message in stub.infos)","src/trend_portfolio_app/app.py",[576],{"_338":339,"_340":577,"_342":578,"_344":70},674,[345,178,346,579,580,581,347,582,583,584,585,586,178,349,587,588,178,589,590,591,592,593,594,595,178,596,597,598,178,178,599,600,601,602,603,604,605,606,607,608,178,178,609,178,610,178,178,611,612,178,613,614,615,616,617,618,619,620,621,178,622,623,624,178,625,178,626,627,628,629,630,631,632,633,178,634,178,178,635,636,178,637,638,178,178,639,640,178,641,642,643,178,644,645,178,646,647,648,649,650,178,651,652,653,654,178,655,656,657,658,659,660,661,662,663,664,665,666,667,668,669,661,178,670,671,178,672,673,674,675,676,677,678,679,178,680,178,681,682,683,684,685,178,686,687,688,689,690,691,692,693,178,694,178,695,696,697,672,673,674,675,676,677,698,699,700,701,702,703,704,661,677,178,705,706,707,708,709,710,711,712,713,714,715,716,717,716,718,719,720,721,722,723,178,724,178,725,726,727,728,729,178,730,731,178,732,178,178,733,178,734,735,736,737,738,739,740,741,178,742,743,744,745,178,178,746,747,178,178,748,749,178,750,751,178,752,496,178,178,753,754,178,755,756,757,758,759,760,178,761,762,763,764,621,178,765,766,178,178,767,768,769,178,770,771,772,178,773,774,775,178,776,777,778,779,178,780,178,178,781,782,178,783,784,178,178,785,786,178,787,788,789,790,791,792,793,794,178,178,795,796,797,798,799,800,178,178,801,802,803,804,805,806,807,178,808,809,810,811,792,812,813,178,814,815,816,178,817,178,178,818,819,820,178,178,821,822,823,824,178,178,825,826,178,827,828,178,829,830,831,832,833,178,178,834,835,178,836,828,178,837,838,828,178,839,840,841,842,843,844,178,845,846,847,848,849,542,850,851,852,546,729,853,178,854,178,178,855,856,178,857,178,858,859,860,861,862,627,863,864,860,865,178,866,867,868,869,870,871,792,872,627,873,864,868,178,874,875,876,877,178,878,542,879,880,881,882,883,884,885,886,546,729,178,887,888,889,890,891,892,178,178,746,893,178,178,894,895,178,896,897,898,899,900,901,902,903,904,905,178,906,907,908,909,910,911,912,913,375,178,914,915,916,917,916,918,713,919,920,921,922,923,924,916,925,178,926,927,928,929,178,178,930,931,178,932,933,934,178,935,936,937,938,939,375,940,178,941,942,943,375,178,178,944,945,946,947,948,949,950,178,951,952,953,627,954,955,956,957,178,958,959,713,960,961,962,963,964,965,713,966,967,968,969,970,968,969,971,972,973,661,178,974,975,729,976,977,178,978,979,980,981,982,983,661,984,985,986,792,987,988,989,990,991,992,993,994,995,996,997,998,999,661,178,1000,1001,1002,1003,1004,1005,178,1006,1007,1008,1009,1010,1011,1012,178,1013,1014,1015,1016,1009,1017,1011,1018,178,1019,1020,1021,1022,1023,1024,1025,1026,1027,1011,1028,178,1029,1030,1031,1032,1033,1034,1035,1036,661,1037,1038,1039,661,178,1040,1041,1042,1043,1044,1045,1046,1047,1048,1049,1050,1051,1052,677,1053,1054,1055,1056,1057,1058,729,178,178,1059,1060,1061,1062,1063,1064,178,1065,178,1066,1067,178,1068,178,178,1069,1070],"import importlib","import json","import os","import types","from collections.abc import Mapping, Sequence","from importlib import import_module","from pathlib import Path","from typing import TYPE_CHECKING, Any, Dict, List, Literal, cast","import streamlit as st","import yaml","import trend_analysis as _trend_pkg","from trend_analysis.config import DEFAULTS as DEFAULT_CFG_PATH","from trend_analysis.config import Config, validate_trend_config","from trend_analysis.diagnostics import coerce_pipeline_result","from trend_analysis.logging_setup import setup_logging","from trend_analysis.multi_period import run_from_config as run_multi","from utils.paths import proj_path","_STREAMLIT_LOG_ENV = \"TREND_STREAMLIT_LOG_PATH\"","_PIPELINE_SIMPLE_ENV = \"TREND_PIPELINE_PROXY_SIMPLE\"","_STREAMLIT_LOG_PATH: Path | None = None","def _ensure_streamlit_logging() -> Path | None:"," disable = os.environ.get(\"TREND_DISABLE_PERF_LOGS\", \"\").strip().lower()"," if disable in {\"1\", \"true\", \"yes\"}:"," return None"," existing = os.environ.get(_STREAMLIT_LOG_ENV)"," if existing:"," return Path(existing)"," log_path = setup_logging(app_name=\"app\")"," os.environ[_STREAMLIT_LOG_ENV] = str(log_path)"," return log_path","_STREAMLIT_LOG_PATH = _ensure_streamlit_logging()","_PIPELINE_DEBUG: list[tuple[str, bool, int, int, int]] = []","def _resolve_pipeline(*, fresh: bool = False, simple: bool = False) -> Any:"," \"\"\"Return the preferred ``trend_analysis.pipeline`` module."," When ``simple`` is set the module cache entry is dropped so we import a"," clean copy without attempting to honour patched module objects or GC"," scanning. Otherwise this consults the live module cache so tests that swap"," ``sys.modules['trend_analysis.pipeline']`` continue to work. When the"," cached module differs from the originally imported instance (for example if"," another test reloaded the package) we prefer whichever version exposes"," patched attributes. This mirrors the previous eager-import behaviour while"," allowing lazy resolution."," \"\"\""," if simple:"," sys.modules.pop(\"trend_analysis.pipeline\", None)"," return import_module(\"trend_analysis.pipeline\")"," module = import_module(\"trend_analysis.pipeline\")"," if fresh:"," try:"," module = importlib.reload(module)"," except Exception:"," # Best-effort reload; fall back to the already imported module if"," # reload fails (for example when the module is a stub without a"," # loader during tests)."," pass"," return module","def _pipeline_proxy_simple() -> bool:"," \"\"\"Return ``True`` when the simple proxy mode is enabled via env flag.\"\"\""," flag = os.environ.get(_PIPELINE_SIMPLE_ENV, \"\")"," return flag.strip().lower() in {\"1\", \"true\", \"yes\", \"on\"}","class _PipelineProxy:"," \"\"\"Lazy proxy that favours patched pipeline attributes when reloaded.\"\"\""," def __init__(self) -> None:"," self._simple_cache: Any | None = None"," self._simple_cache_env: str = \"\""," def __getattr__(self, name: str) -> Any:"," missing = object()"," if _pipeline_proxy_simple():"," current_flag = os.environ.get(_PIPELINE_SIMPLE_ENV, \"\")"," if current_flag != self._simple_cache_env:"," self._simple_cache = None"," self._simple_cache_env = current_flag"," if self._simple_cache is None:"," self._simple_cache = _resolve_pipeline(fresh=True, simple=True)"," module = self._simple_cache"," attr = getattr(module, name, missing)"," if name == \"run\":"," pkg_module = getattr(_trend_pkg, \"pipeline\", None)"," pkg_attr = ("," getattr(pkg_module, name, missing)"," if pkg_module is not None"," else missing"," )"," _PIPELINE_DEBUG.append("," ("," name,"," True,"," id(module),"," id(pkg_module) if pkg_module is not None else 0,"," id(pkg_attr) if pkg_attr is not missing else 0,"," )"," if attr is not missing:"," return attr"," pkg_module = getattr(_trend_pkg, \"pipeline\", None)"," pkg_attr = ("," getattr(pkg_module, name, missing)"," if pkg_module is not None"," else missing"," )"," if pkg_attr is not missing:"," return pkg_attr"," raise AttributeError(name)"," # Clear any cached simple-mode module when returning to default mode so"," # we don't keep a stale direct-import around if the environment flag is"," # toggled off."," self._simple_cache = None"," self._simple_cache_env = \"\""," # Prefer attributes from the live module object in sys.modules. Tests"," # commonly monkeypatch `trend_analysis.pipeline` in-place, so returning"," # the attribute from the cached module ensures those patches are"," # honoured. Only if the attribute is missing from the cached module do"," # we fall back to the package-level `trend_analysis.pipeline` attr."," module = sys.modules.get(\"trend_analysis.pipeline\")"," if module is None:"," module = _resolve_pipeline()"," attr = getattr(module, name, missing)"," # Instrumentation for tests — keep a lightweight trace when 'run' is"," # resolved so debugging info is available if needed."," if name == \"run\":"," _PIPELINE_DEBUG.append("," ("," name,"," False,"," id(module),"," id(pkg_module) if pkg_module is not None else 0,"," id(pkg_attr) if pkg_attr is not missing else 0,"," # If the live module exposes the attribute, we still check for any"," # other in-memory module objects named \"trend_analysis.pipeline\" that"," # might have been monkeypatched (tests sometimes patch an earlier"," # imported module instance that no longer lives in sys.modules). If"," # we find a different attribute on one of those module objects, prefer"," # that patched attribute. Otherwise return the current module attr."," if attr is not missing:"," # Search GC for other module instances named 'trend_analysis.pipeline'"," try:"," for obj in gc.get_objects():"," if not isinstance(obj, types.ModuleType):"," continue"," if getattr(obj, \"__name__\", None) != \"trend_analysis.pipeline\":"," cand = getattr(obj, name, missing)"," if cand is not missing and cand is not attr:"," return cand"," except Exception:"," # GC inspection is best-effort; fall back to the module attr."," pass"," return attr"," # Otherwise attempt to resolve via the package attribute as a fallback."," pkg_module = getattr(_trend_pkg, \"pipeline\", None)"," pkg_attr = ("," getattr(pkg_module, name, missing) if pkg_module is not None else missing"," )"," if pkg_attr is not missing:"," return pkg_attr"," raise AttributeError(name)","pipeline = _PipelineProxy()","# Instrumentation globals (mutated during _render_app) used by tests.","page_config_calls: list[bool] = []","titles: list[str] = []","# Re-export for tests that access globals directly after import","__all__ = ["," \"page_config_calls\","," \"titles\",","]","if TYPE_CHECKING: # pragma: no cover - type-only alias for static checkers"," from trend_analysis.config.models import ConfigProtocol as ConfigType","else: # pragma: no cover - runtime fallback when pydantic models are optional"," from typing import Any as ConfigType","# ---------------------------------------------------------------------------","# Helper primitives used across the Streamlit app","class _NullContext:"," \"\"\"Minimal context manager used when Streamlit is mocked in tests.\"\"\""," def __enter__(self) -> \"_NullContext\": # pragma: no cover - trivial"," return self"," def __exit__(self, *_exc: Any) -> Literal[False]: # pragma: no cover - trivial","def _is_mock_streamlit(module: Any) -> bool:"," \"\"\"Best‑effort detection for a real ``unittest.mock.MagicMock`` instance."," The previous implementation relied solely on ``type(module).__name__ =="," 'MagicMock'`` which allowed tests (or any code) to suppress the application"," bootstrap simply by reassigning ``__name__`` on an arbitrary stub class."," That made the import side‑effect (page configuration) disappear and caused"," the ``test_render_app_executes_with_dummy_streamlit`` test to fail because"," the app never ran."," We tighten the heuristic to only treat genuine ``unittest.mock`` MagicMock"," objects as mocks. A lightweight subclass that merely renames its"," ``__name__`` no longer short‑circuits the render path, restoring the"," expected behaviour under test."," cls = type(module)"," return cls.__module__ == \"unittest.mock\" and cls.__name__ == \"MagicMock\"","def _read_defaults() -> Dict[str, Any]:"," \"\"\"Load the default YAML configuration bundled with the analysis"," package.\"\"\""," data = yaml.safe_load(Path(DEFAULT_CFG_PATH).read_text(encoding=\"utf-8\"))"," if not isinstance(data, dict): # pragma: no cover - defensive"," raise TypeError(\"Default configuration must be a mapping\")"," defaults: Dict[str, Any] = dict(data)"," defaults.setdefault(\"data\", {})"," defaults.setdefault(\"portfolio\", {})"," demo_csv = Path(\"demo/demo_returns.csv\")"," if demo_csv.exists():"," defaults[\"data\"].setdefault(\"csv_path\", str(demo_csv))"," defaults[\"portfolio\"].setdefault(\"policy\", \"\")"," return defaults","def _to_yaml(d: Dict[str, Any]) -> str:"," \"\"\"Serialise a mapping to YAML while preserving insertion order.\"\"\""," dumped: str = yaml.safe_dump(d, sort_keys=False, allow_unicode=True)"," return dumped","def _merge_update(base: Dict[str, Any], updates: Dict[str, Any]) -> Dict[str, Any]:"," \"\"\"Recursively merge ``updates`` into a shallow copy of ``base``.\"\"\""," merged: Dict[str, Any] = dict(base)"," for key, value in updates.items():"," base_value = merged.get(key)"," if isinstance(base_value, dict) and isinstance(value, Mapping):"," merged[key] = _merge_update(cast(Dict[str, Any], base_value), dict(value))"," else:"," merged[key] = value"," return merged","def _expected_columns(spec: Any) -> int:"," if isinstance(spec, int):"," return max(0, spec)"," if isinstance(spec, Sequence):"," return len(spec)"," return 1","def _normalize_columns(cols: Any, expected: int) -> List[Any]:"," if isinstance(cols, (list, tuple)):"," normalised = list(cols)"," elif cols is None:"," normalised = []"," else:"," normalised = [cols]"," if not normalised:"," placeholder_factory = getattr(st, \"empty\", None)"," if callable(placeholder_factory):"," placeholder = placeholder_factory()"," placeholder = _NullContext()"," normalised = [placeholder]"," if len(normalised) < expected:"," filler = normalised[-1]"," normalised.extend([filler] * (expected - len(normalised)))"," return normalised[:expected]","def _columns(spec: Any) -> List[Any]:"," expected = max(1, _expected_columns(spec))"," return _normalize_columns(st.columns(spec), expected)","def _build_cfg(d: Dict[str, Any]) -> ConfigType:"," \"\"\"Instantiate the flexible ``Config`` object used by the pipeline.\"\"\""," validate_trend_config(d, base_path=proj_path())"," return Config(**d)","def _summarise_run_df(df: pd.DataFrame | None) -> pd.DataFrame:"," \"\"\"Round numeric columns for presentation after a single-period run.\"\"\""," if df is None or df.empty:"," return pd.DataFrame()"," disp = df.copy()"," for column in disp.columns:"," if pd.api.types.is_numeric_dtype(disp[column]):"," disp[column] = pd.to_numeric(disp[column], errors=\"coerce\").round(4)"," return disp","def _build_summary_from_result(result: Mapping[str, Any] | None) -> pd.DataFrame:"," \"\"\"Construct a summary DataFrame from ``pipeline.run_full`` results.\"\"\""," if not result:"," out_stats = result.get(\"out_sample_stats\")"," if not isinstance(out_stats, Mapping) or not out_stats:"," rows: Dict[str, Dict[str, Any]] = {}"," for key, value in out_stats.items():"," if hasattr(value, \"__dict__\"):"," rows[key] = dict(vars(value))"," elif isinstance(value, Mapping):"," rows[key] = dict(value)"," summary = pd.DataFrame(rows).T"," for label, ir_map in cast("," Mapping[str, Mapping[str, float]], result.get(\"benchmark_ir\", {})"," ).items():"," series = pd.Series("," asset: score"," for asset, score in ir_map.items()"," if asset not in {\"equal_weight\", \"user_weight\"}"," summary[f\"ir_{label}\"] = series"," return summary","def _summarise_multi(results: List[Dict[str, Any]]) -> pd.DataFrame:"," \"\"\"Create a tidy summary table from multi-period back-test results.\"\"\""," rows: List[Dict[str, Any]] = []"," def _period_value(period: Any, index: int) -> Any:"," if period is None:"," return \"\""," if isinstance(period, (list, tuple)):"," return period[index] if len(period) > index else \"\""," seq = list(period)"," except (TypeError, ValueError):"," return seq[index] if len(seq) > index else \"\""," def _coerce_metric(container: Any, key: str) -> float:"," if container is None:"," return float(\"nan\")"," value: Any"," if isinstance(container, Mapping):"," value = container.get(key)"," value = getattr(container, key, None)"," return float(value)"," for result in results:"," period = result.get(\"period\")"," out_ew = result.get(\"out_ew_stats\") or {}"," out_user = result.get(\"out_user_stats\") or {}"," rows.append("," \"in_start\": _period_value(period, 0),"," \"in_end\": _period_value(period, 1),"," \"out_start\": _period_value(period, 2),"," \"out_end\": _period_value(period, 3),"," \"ew_sharpe\": _coerce_metric(out_ew, \"sharpe\"),"," \"user_sharpe\": _coerce_metric(out_user, \"sharpe\"),"," \"ew_cagr\": _coerce_metric(out_ew, \"cagr\"),"," \"user_cagr\": _coerce_metric(out_user, \"cagr\"),"," df = pd.DataFrame(rows)"," if not df.empty:"," for col in [\"ew_sharpe\", \"user_sharpe\", \"ew_cagr\", \"user_cagr\"]:"," if col in df.columns:"," df[col] = pd.to_numeric(df[col], errors=\"coerce\").round(4)"," return df","# Streamlit UI wiring","def _apply_session_state(cfg_dict: Dict[str, Any]) -> None:"," \"\"\"Fold dotted session-state keys back into the nested configuration.\"\"\""," def _set_nested(target: Dict[str, Any], dotted: str, value: Any) -> None:"," parts = dotted.split(\".\")"," cursor: Dict[str, Any] = target"," for key in parts[:-1]:"," next_val = cursor.get(key)"," if not isinstance(next_val, dict):"," next_val = {}"," cursor[key] = next_val"," cursor = cast(Dict[str, Any], next_val)"," cursor[parts[-1]] = value"," prefixes = ("," \"data.\","," \"sample_split.\","," \"portfolio.\","," \"metrics.\","," \"multi_period.\","," \"preprocessing.\","," \"vol_adjust.\","," for raw_key, raw_value in list(st.session_state.items()):"," if not isinstance(raw_key, str) or \".\" not in raw_key:"," continue"," if not raw_key.startswith(prefixes):"," if raw_key.endswith(\"._months\"):"," months = int(raw_value)"," except (TypeError, ValueError):"," continue"," days = int(months * 21)"," base_key = raw_key.rsplit(\".\", 1)[0]"," _set_nested(cfg_dict, f\"{base_key}.length\", days)"," _set_nested(cfg_dict, raw_key, raw_value)"," # Ensure the canonical csv_path key mirrors the sidebar input."," csv_key = \"data.csv_path\""," if csv_key in st.session_state:"," _set_nested(cfg_dict, csv_key, st.session_state[csv_key])","def _render_sidebar(cfg_dict: Dict[str, Any]) -> None:"," st.header(\"Configuration\")"," if st.button(\"Reset to defaults\", use_container_width=True):"," st.session_state.config_dict = _read_defaults()"," cfg_dict.update(st.session_state.config_dict)"," csv_value = st.text_input("," \"CSV path\","," key=\"data.csv_path\","," value=str(cfg_dict.get(\"data\", {}).get(\"csv_path\", \"\")),"," help=\"Path to a CSV with manager returns\","," cfg_dict.setdefault(\"data\", {})[\"csv_path\"] = csv_value"," yaml_bytes = _to_yaml(cfg_dict).encode(\"utf-8\")"," st.download_button("," \"Download YAML\", data=yaml_bytes, file_name=\"config.yml\", mime=\"text/yaml\"","def _render_run_section(cfg_dict: Dict[str, Any]) -> None:"," st.subheader(\"Execute analysis\")"," col1, col2 = _columns(2)"," with col1:"," go_single = st.button(\"Run Single Period\", type=\"primary\")"," with col2:"," go_multi = st.button(\"Run Multi-Period\", type=\"primary\")"," cfg_obj: ConfigType | None = None"," if go_single or go_multi:"," _apply_session_state(cfg_dict)"," cfg_obj = _build_cfg(cfg_dict)"," except Exception as exc: # pragma: no cover - defensive UI feedback"," st.error(f\"Failed to build configuration: {exc}\")"," return"," if go_single and cfg_obj is not None:"," with st.spinner(\"Running single-period analysis...\"):"," summary_frame = pipeline.run(cfg_obj)"," except Exception: # pragma: no cover - UI fallthrough"," summary_frame = None"," run_full_error: Exception | None = None"," full_result_payload: dict[str, Any] | None = None"," full_result_diag = None"," full_result = pipeline.run_full(cfg_obj)"," except (FileNotFoundError, KeyError) as exc:"," run_full_error = exc"," full_result = None"," except Exception as exc: # pragma: no cover - defensive logging"," if full_result is not None:"," full_result_payload, full_result_diag = coerce_pipeline_result("," full_result"," summary = _summarise_run_df("," summary_frame if isinstance(summary_frame, pd.DataFrame) else None"," has_summary = isinstance(summary, pd.DataFrame)"," summary_rows = len(summary) if has_summary else 0"," if not full_result_payload and not has_summary:"," message = \"Analysis failed for the configured period. Please check your data and configuration settings.\""," if full_result_diag is not None:"," message = ("," f\"{message} ({full_result_diag.reason_code}: \""," f\"{full_result_diag.message})\""," elif run_full_error is not None:"," message = f\"{message} ({run_full_error})\""," st.warning(message)"," if summary.empty and full_result_payload:"," summary_raw = _build_summary_from_result(full_result_payload)"," summary = _summarise_run_df(summary_raw)"," summary_rows = len(summary)"," st.success(f\"Completed. {summary_rows} rows.\")"," if not summary.empty:"," st.dataframe(summary, use_container_width=True)"," csv_bytes = summary.to_csv(index=False).encode(\"utf-8\")"," st.download_button("," \"Download CSV\","," data=csv_bytes,"," file_name=\"single_period_summary.csv\","," mime=\"text/csv\","," if full_result_payload:"," risk_diag = full_result_payload.get(\"risk_diagnostics\")"," if isinstance(risk_diag, Mapping) and risk_diag:"," st.subheader(\"Risk diagnostics\")"," line_chart = getattr(st, \"line_chart\", None)"," bar_chart = getattr(st, \"bar_chart\", None)"," asset_vol = risk_diag.get(\"asset_volatility\")"," if isinstance(asset_vol, pd.DataFrame) and not asset_vol.empty:"," st.caption(\"Realised asset volatility\")"," if callable(line_chart):"," line_chart(asset_vol)"," else:"," st.dataframe(asset_vol)"," port_vol = risk_diag.get(\"portfolio_volatility\")"," if isinstance(port_vol, pd.Series) and not port_vol.empty:"," st.caption(\"Portfolio volatility\")"," port_df = port_vol.to_frame(\"portfolio_volatility\")"," line_chart(port_df)"," st.dataframe(port_df)"," turnover_series = risk_diag.get(\"turnover\")"," if ("," isinstance(turnover_series, pd.Series)"," and not turnover_series.empty"," ):"," st.caption(\"Turnover per rebalance\")"," turnover_df = turnover_series.to_frame(\"turnover\")"," if callable(bar_chart):"," bar_chart(turnover_df)"," st.dataframe(turnover_df)"," turnover_value = risk_diag.get(\"turnover_value\")"," if isinstance(turnover_value, (float, int)):"," st.caption(f\"Turnover applied: {turnover_value:.4f}\")"," elif run_full_error is not None or full_result_diag is not None:"," detail = ("," f\"{full_result_diag.reason_code}: {full_result_diag.message}\""," if full_result_diag is not None"," else str(run_full_error)"," st.info("," \"Partial results shown. Full diagnostics are unavailable because the detailed analysis failed: \""," f\"{detail}\""," if go_multi and cfg_obj is not None:"," with st.spinner(\"Running multi-period analysis...\"):"," results = run_multi(cfg_obj)"," summary = _summarise_multi(results)"," st.success(f\"Completed. Periods: {len(results)}\")"," if not summary.empty:"," st.dataframe(summary, use_container_width=True)"," csv_bytes = summary.to_csv(index=False).encode(\"utf-8\")"," st.download_button("," \"Download periods CSV\","," data=csv_bytes,"," file_name=\"multi_period_summary.csv\","," mime=\"text/csv\","," raw = json.dumps(results, default=str).encode(\"utf-8\")"," st.download_button("," \"Download raw JSON\","," data=raw,"," file_name=\"multi_period_raw.json\","," mime=\"application/json\",","def _render_app() -> None:"," # Instrumentation lists used by tests (harmless in production)"," st.set_page_config(page_title=\"Trend Portfolio App\", layout=\"wide\")"," page_config_calls.append(True)"," st.title(\"Trend Portfolio App\")"," titles.append(\"Trend Portfolio App\")"," cfg_dict = st.session_state.setdefault(\"config_dict\", _read_defaults())"," with st.sidebar:"," _render_sidebar(cfg_dict)"," _render_run_section(cfg_dict)","if not _is_mock_streamlit(st):"," _render_app()","message",[1073,1074,1075,1076,1077,1078],{"_1079":57,"_57":1091},{"_1079":1085,"_331":574,"_338":1089,"_340":1090},{"_1079":57,"_57":1088},{"_1079":1085,"_331":332,"_338":1086,"_340":1087},{"_1079":57,"_57":1084},{"_1079":1080,"_1081":1082,"_338":339,"_340":1083},"content_type","terminal_chunk_citation","terminal_chunk_id","02091c",2,"\n\n**Testing**\n* ✅ `pytest tests/app/test_portfolio_app_additional.py -k \"pipeline_proxy\" -q`","repo_file_citation",99,153,"\n* Expanded simple-mode tests to cover caching and sys.modules handling alongside the existing GC-scanning defaults.",86,143,"Checklist \n- [x] Add an environment flag that skips GC scanning and directly imports `trend_analysis.pipeline`. \n- [x] Ensure default behaviour remains unchanged (GC scanning enabled). \n- [x] Add tests covering both modes to assert correct pipeline resolution and instrumentation behaviour. \n\n**Summary**\n* Added simple-mode caching keyed by the environment flag so direct-import pipeline modules are reused while clearing the cache when the flag is disabled, preserving default GC-scanning behaviour otherwise.","pr","pr_title","feat: cache pipeline proxy simple imports","pr_message","## Summary\n- cache the simple-mode pipeline proxy module and reset it when the environment flag value changes or is disabled\n- keep default GC-scanning behaviour intact while ensuring simple mode bypasses repeated imports\n- add regression coverage to verify direct-import caching and sys.modules behaviour under the simple-mode flag\n\n## Testing\n- pytest tests/app/test_portfolio_app_additional.py -k \"pipeline_proxy\" -q","output_diff",{"_104":1097,"_1100":1101,"_139":140,"_1102":-5,"_306":1103,"_1104":1105,"_1106":1083,"_1107":1108,"_1109":339,"_1110":1111,"_1112":-5},"pre_apply_patch","repo_id","/workspace/Trend_Model_Project","preapply_patch_base_commit_sha","diff --git a/src/trend_portfolio_app/app.py b/src/trend_portfolio_app/app.py\nindex 31cdd3c9f24cf354bf23e93c06a59ad9f774c39a..fd564f1a584926b8588549ca1d2ac0f6468547e7 100644\n--- a/src/trend_portfolio_app/app.py\n+++ b/src/trend_portfolio_app/app.py\n@@ -64,88 +64,105 @@ def _resolve_pipeline(*, fresh: bool = False, simple: bool = False) -> Any:\n \n module = import_module(\"trend_analysis.pipeline\")\n \n if fresh:\n try:\n module = importlib.reload(module)\n except Exception:\n # Best-effort reload; fall back to the already imported module if\n # reload fails (for example when the module is a stub without a\n # loader during tests).\n pass\n \n return module\n \n \n def _pipeline_proxy_simple() -> bool:\n \"\"\"Return ``True`` when the simple proxy mode is enabled via env flag.\"\"\"\n \n flag = os.environ.get(_PIPELINE_SIMPLE_ENV, \"\")\n return flag.strip().lower() in {\"1\", \"true\", \"yes\", \"on\"}\n \n \n class _PipelineProxy:\n \"\"\"Lazy proxy that favours patched pipeline attributes when reloaded.\"\"\"\n \n+ def __init__(self) -> None:\n+ self._simple_cache: Any | None = None\n+ self._simple_cache_env: str = \"\"\n+\n def __getattr__(self, name: str) -> Any:\n missing = object()\n \n if _pipeline_proxy_simple():\n- module = _resolve_pipeline(fresh=True, simple=True)\n+ current_flag = os.environ.get(_PIPELINE_SIMPLE_ENV, \"\")\n+ if current_flag != self._simple_cache_env:\n+ self._simple_cache = None\n+ self._simple_cache_env = current_flag\n+\n+ if self._simple_cache is None:\n+ self._simple_cache = _resolve_pipeline(fresh=True, simple=True)\n+ module = self._simple_cache\n attr = getattr(module, name, missing)\n \n if name == \"run\":\n pkg_module = getattr(_trend_pkg, \"pipeline\", None)\n pkg_attr = (\n getattr(pkg_module, name, missing)\n if pkg_module is not None\n else missing\n )\n _PIPELINE_DEBUG.append(\n (\n name,\n True,\n id(module),\n id(pkg_module) if pkg_module is not None else 0,\n id(pkg_attr) if pkg_attr is not missing else 0,\n )\n )\n \n if attr is not missing:\n return attr\n \n pkg_module = getattr(_trend_pkg, \"pipeline\", None)\n pkg_attr = (\n getattr(pkg_module, name, missing)\n if pkg_module is not None\n else missing\n )\n if pkg_attr is not missing:\n return pkg_attr\n \n raise AttributeError(name)\n \n+ # Clear any cached simple-mode module when returning to default mode so\n+ # we don't keep a stale direct-import around if the environment flag is\n+ # toggled off.\n+ self._simple_cache = None\n+ self._simple_cache_env = \"\"\n+\n # Prefer attributes from the live module object in sys.modules. Tests\n # commonly monkeypatch `trend_analysis.pipeline` in-place, so returning\n # the attribute from the cached module ensures those patches are\n # honoured. Only if the attribute is missing from the cached module do\n # we fall back to the package-level `trend_analysis.pipeline` attr.\n module = sys.modules.get(\"trend_analysis.pipeline\")\n if module is None:\n module = _resolve_pipeline()\n \n attr = getattr(module, name, missing)\n \n # Instrumentation for tests — keep a lightweight trace when 'run' is\n # resolved so debugging info is available if needed.\n if name == \"run\":\n pkg_module = getattr(_trend_pkg, \"pipeline\", None)\n pkg_attr = (\n getattr(pkg_module, name, missing)\n if pkg_module is not None\n else missing\n )\n _PIPELINE_DEBUG.append(\n (\n name,\n False,\n id(module),\ndiff --git a/tests/app/test_portfolio_app_additional.py b/tests/app/test_portfolio_app_additional.py\nindex c907eabbd81db47f4d8fa43e89b6717457f7db07..13ae66a600b69226815213795158d0917749ef1f 100644\n--- a/tests/app/test_portfolio_app_additional.py\n+++ b/tests/app/test_portfolio_app_additional.py\n@@ -108,50 +108,73 @@ def test_pipeline_proxy_simple_mode_ignores_sys_modules_patch(monkeypatch):\n \n def import_module_stub(mod: str):\n called[\"imports\"] += 1\n sys.modules[mod] = canonical\n return canonical\n \n def fake_get_objects():\n called[\"gc\"] = True\n return []\n \n monkeypatch.setattr(app, \"import_module\", import_module_stub)\n monkeypatch.setattr(gc, \"get_objects\", fake_get_objects)\n monkeypatch.setenv(\"TREND_PIPELINE_PROXY_SIMPLE\", \"true\")\n app._PIPELINE_DEBUG.clear()\n \n result = app.pipeline.run(object())\n \n assert result == \"direct\"\n assert sys.modules.get(\"trend_analysis.pipeline\") is canonical\n assert called[\"imports\"] == 1\n assert called.get(\"gc\", False) is False\n assert app._PIPELINE_DEBUG[-1][:2] == (\"run\", True)\n assert sys.modules[\"trend_analysis.pipeline\"] is canonical\n \n \n+def test_pipeline_proxy_simple_mode_caches_direct_import(monkeypatch):\n+ module = ModuleType(\"trend_analysis.pipeline\")\n+ module.run = lambda cfg: \"cached\"\n+\n+ calls = {\"imports\": 0}\n+\n+ def resolve_stub(*, fresh: bool = False, simple: bool = False):\n+ calls[\"imports\"] += 1\n+ return module\n+\n+ monkeypatch.setenv(\"TREND_PIPELINE_PROXY_SIMPLE\", \"yes\")\n+ monkeypatch.setattr(app, \"_resolve_pipeline\", resolve_stub)\n+ monkeypatch.setattr(app, \"_trend_pkg\", SimpleNamespace(pipeline=None))\n+ app._PIPELINE_DEBUG.clear()\n+\n+ first = app.pipeline.run(object())\n+ second = app.pipeline.run(object())\n+\n+ assert first == \"cached\" == second\n+ assert calls[\"imports\"] == 1\n+ assert app._PIPELINE_DEBUG[-1][:2] == (\"run\", True)\n+\n+\n def test_columns_normalisation_uses_placeholders(monkeypatch):\n class StubColumns:\n def __call__(self, spec):\n return []\n \n monkeypatch.setattr(app.st, \"columns\", StubColumns())\n placeholder = object()\n monkeypatch.setattr(app.st, \"empty\", lambda: placeholder)\n \n cols = app._columns(2)\n assert len(cols) == 2\n assert cols[0] is placeholder\n \n \n def test_summary_helpers_and_multi_rounding():\n df = pd.DataFrame({\"Sharpe\": [0.12345, 0.98765]})\n summary = app._summarise_run_df(df)\n assert summary.iloc[0, 0] == pytest.approx(0.1234)\n \n result = {\n \"out_sample_stats\": {\n \"user\": SimpleNamespace(cagr=0.1, sharpe=0.8),\n \"equal\": {\"cagr\": 0.05, \"sharpe\": 0.6},\n },\n \"benchmark_ir\": {\"user\": {\"FundA\": 0.3, \"equal_weight\": 0.1}},\n","external_storage_diff",{"_1113":1114,"_1115":-5},"files_modified","lines_added",41,"lines_removed","commit_message","feat: cache simple pipeline imports","additional_parent_commit_shas","file_id","file_00000000689071f799f671771c44f62a","ttl",{"_104":307,"_53":96,"_108":307,"_1118":1119,"_1120":1121,"_1122":1123,"_143":-5,"_130":1124},[95],"input_items",[1143,1144,1145,1146,1147,1148,1149,1150,1151,1152,1153,1154,1155,1156,1157,1158,1159,1160,1161,1162,1163,1164,1165,1166,1167,1168,1169],"external_post_config",{"_1125":1126,"_239":175,"_1127":284,"_250":-5,"_1100":233,"_1128":18,"_1129":-5,"_1130":-5,"_1131":-5,"_1132":1133,"_1134":-5,"_1135":-5,"_1136":1137,"_1138":18,"_1139":70,"_1140":65,"_1141":18,"_1142":-5},"user_model_slug","slug",1764644749.011695,"installation_id",71148695,"pr_number","enable_internal_github_app_routing","gitlab_service_account_project_id","review_trigger","comment_id","comment_type","issue","pr_write_guard_token","pending_pr_reaction_id","pending_comment_reaction_id",317080432,"comment_if_no_findings","comment_on_error","share_url","is_parallel_review","review_summary_id",{"_104":1071,"_108":307,"_342":1203},{"_291":292,"_293":1198,"_1199":1200,"_1201":140,"_303":-5,"_104":1202},{"_104":1170,"_293":1197,"_331":-5,"_1172":-5,"_1173":-5},{"_104":1170,"_293":1194,"_331":1195,"_1172":1196,"_1173":339},{"_104":1170,"_293":1193,"_331":-5,"_1172":-5,"_1173":-5},{"_104":1170,"_293":1175,"_331":-5,"_1172":-5,"_1173":-5},{"_104":1170,"_293":1192,"_331":-5,"_1172":-5,"_1173":-5},{"_104":1170,"_293":1191,"_331":-5,"_1172":-5,"_1173":-5},{"_104":1170,"_293":1190,"_331":-5,"_1172":-5,"_1173":-5},{"_104":1170,"_293":1189,"_331":-5,"_1172":-5,"_1173":-5},{"_104":1170,"_293":1188,"_331":-5,"_1172":-5,"_1173":-5},{"_104":1170,"_293":1187,"_331":-5,"_1172":-5,"_1173":-5},{"_104":1170,"_293":1186,"_331":-5,"_1172":-5,"_1173":-5},{"_104":1170,"_293":1185,"_331":-5,"_1172":-5,"_1173":-5},{"_104":1170,"_293":1184,"_331":-5,"_1172":-5,"_1173":-5},{"_104":1170,"_293":1183,"_331":-5,"_1172":-5,"_1173":-5},{"_104":1170,"_293":1182,"_331":-5,"_1172":-5,"_1173":-5},{"_104":1170,"_293":1175,"_331":-5,"_1172":-5,"_1173":-5},{"_104":1170,"_293":1181,"_331":-5,"_1172":-5,"_1173":-5},{"_104":1170,"_293":1180,"_331":-5,"_1172":-5,"_1173":-5},{"_104":1170,"_293":1179,"_331":-5,"_1172":-5,"_1173":-5},{"_104":1170,"_293":1178,"_331":-5,"_1172":-5,"_1173":-5},{"_104":1170,"_293":1177,"_331":-5,"_1172":-5,"_1173":-5},{"_104":1170,"_293":1176,"_331":-5,"_1172":-5,"_1173":-5},{"_104":1170,"_293":1175,"_331":-5,"_1172":-5,"_1173":-5},{"_104":1170,"_293":1174,"_331":-5,"_1172":-5,"_1173":-5},{"_104":1170,"_293":1171,"_331":-5,"_1172":-5,"_1173":-5},"pull_request_comment","","side","line","**Summary**\n* Added proxy instrumentation to record whether pipeline resolution ran in simple or default mode while preserving cached module IDs for debugging. [src/trend_portfolio_app/app.pyL45-L154](https://github.com/stranske/Trend_Model_Project/blob/7920720b56493e1c531b314afd25d251c9bde542/src/trend_portfolio_app/app.py#L45-L154)\n* Updated pipeline proxy tests to assert the recorded mode for both GC-scanning default behaviour and simple-mode direct imports. [tests/app/test_portfolio_app_additional.pyL13-L129](https://github.com/stranske/Trend_Model_Project/blob/7920720b56493e1c531b314afd25d251c9bde542/tests/app/test_portfolio_app_additional.py#L13-L129)\n\n**Checklist**\n- [x] Add an environment flag that skips GC scanning and directly imports `trend_analysis.pipeline`.\n- [x] Ensure default behaviour remains unchanged (GC scanning enabled).\n- [x] Add tests covering both modes to assert correct pipeline resolution and instrumentation behaviour.\n\n**Testing**\n* ✅ `pytest tests/app/test_portfolio_app_additional.py -k \"pipeline_proxy\" -q`\n\n [View task →](https://chatgpt.com/s/cd_692e54effe588191ae036928aa26cfe9)","@codex Your objective is to satisfy the **Acceptance Criteria** by completing each **Task** within the defined **Scope**.\r\n\r\n**This round you MUST:**\r\n1. Implement actual code or test changes that advance at least one incomplete task toward acceptance.\r\n2. Commit meaningful source code (.py, .yml, .js, etc.)—not just status/docs updates.\r\n3. Mark a task checkbox complete ONLY after verifying the implementation works.\r\n\r\n**DO NOT:**\r\n- Commit only status files, markdown summaries, or documentation when tasks require code.\r\n- Re-post checklists without making implementation progress.\r\n- Close the round without source-code changes when acceptance criteria require them.\r\n\r\nReview the Scope/Tasks/Acceptance below, identify the next incomplete task that requires code, implement it, then re-post the updated checklist reflecting your verified progress.","\nClean-mode cosmetic autofix (`autofix:clean`) updated these files:\n\n- `tests/app/test_portfolio_app_additional.py`","**Checklist**\n- [x] Add an environment flag that skips GC scanning and directly imports `trend_analysis.pipeline`.\n- [x] Ensure default behaviour remains unchanged (GC scanning enabled).\n- [x] Add tests covering both modes to assert correct pipeline resolution and instrumentation behaviour.\n\n**Summary**\n* Added a simple-mode path that removes any cached `trend_analysis.pipeline` module and directly imports a fresh copy when the environment flag is set, while leaving the GC-scanning default untouched for test-friendly behaviour. [src/trend_portfolio_app/app.pyL61-L124](https://github.com/stranske/Trend_Model_Project/blob/085b8be48393bd174477032c16048f0b6dbe1c4f/src/trend_portfolio_app/app.py#L61-L124)\n* Updated pipeline proxy tests to exercise both the simple-mode import path and the default GC-scanning path, verifying instrumentation and cache handling outcomes. [tests/app/test_portfolio_app_additional.pyL70-L113](https://github.com/stranske/Trend_Model_Project/blob/085b8be48393bd174477032c16048f0b6dbe1c4f/tests/app/test_portfolio_app_additional.py#L70-L113)\n\n**Testing**\n* ✅ `pytest tests/app/test_portfolio_app_additional.py -k \"pipeline_proxy\" -q`\n\n [View task →](https://chatgpt.com/s/cd_692e40be3484819188fa10ffd96b6c1e)","","","\n\n\n\n@codex Your objective is to satisfy the **Acceptance Criteria** by completing each **Task** within the defined **Scope**.\n\n**This round you MUST:**\n1. Implement actual code or test changes that advance at least one incomplete task toward acceptance.\n2. Commit meaningful source code (.py, .yml, .js, etc.)—not just status/docs updates.\n3. Mark a task checkbox complete ONLY after verifying the implementation works.\n4. **POST A REPLY COMMENT** with the updated checklist showing `- [x]` for completed items.\n\n**DO NOT:**\n- Commit only status files, markdown summaries, or documentation when tasks require code.\n- Re-post checklists without making implementation progress.\n- Close the round without source-code changes when acceptance criteria require them.\n- Complete work without posting a reply comment showing which checkboxes are now checked.\n\nReview the Scope/Tasks/Acceptance below, identify the next incomplete task that requires code, implement it, then **post a reply comment** with the updated checklist showing your verified progress (change `- [ ]` to `- [x]` for completed items).\n\n#### Scope\n- [ ] `trend_portfolio_app.app._PipelineProxy` scans `gc.get_objects()` to prefer patched pipeline modules, which aids testing but adds overhead and magic. Production deployments could benefit from an opt-in simple mode that imports the pipeline directly.\n\n#### Tasks\n- [ ] Add an environment flag (e.g., `TREND_PIPELINE_PROXY_SIMPLE`) that, when set, skips GC scanning and directly imports `trend_analysis.pipeline`.\n- [ ] Ensure default behaviour remains unchanged (GC scanning enabled) to preserve test friendliness.\n- [ ] Add tests covering both modes to assert correct pipeline resolution and instrumentation behaviour.\n\n#### Acceptance Criteria\n- [ ] - Setting the new env flag yields a direct-import proxy path; default continues to honour GC-scanned modules.\n- [ ] - Tests cover simple and default modes and pass without changing existing app behaviour for users who do not set the flag.\n\n**Head SHA:** 085b8be48393bd174477032c16048f0b6dbe1c4f\n**Latest Runs:** ✅ success — Gate\n**Required:** gate: ✅ success\n\n| Workflow / Job | Result | Logs |\n|----------------|--------|------|\n| .github/workflows/agents-pr-meta-v2.yml | ❌ failure | [View run](https://github.com/stranske/Trend_Model_Project/actions/runs/19843411812) |\n| .github/workflows/agents-pr-meta.yml | ❌ failure | [View run](https://github.com/stranske/Trend_Model_Project/actions/runs/19843411887) |\n| Agents PR meta manager | ❔ in progress | [View run](https://github.com/stranske/Trend_Model_Project/actions/runs/19843515508) |\n| CI Autofix Loop | ✅ success | [View run](https://github.com/stranske/Trend_Model_Project/actions/runs/19843412491) |\n| Gate | ✅ success | [View run](https://github.com/stranske/Trend_Model_Project/actions/runs/19843412510) |\n| Health 40 Sweep | ✅ success | [View run](https://github.com/stranske/Trend_Model_Project/actions/runs/19843412502) |\n| Health 44 Gate Branch Protection | ✅ success | [View run](https://github.com/stranske/Trend_Model_Project/actions/runs/19843412447) |\n| Health 45 Agents Guard | ✅ success | [View run](https://github.com/stranske/Trend_Model_Project/actions/runs/19843412455) |\n| Health 50 Security Scan | ✅ success | [View run](https://github.com/stranske/Trend_Model_Project/actions/runs/19843412454) |\n| Maint 52 Validate Workflows | ✅ success | [View run](https://github.com/stranske/Trend_Model_Project/actions/runs/19843412468) |\n| PR 11 - Minimal invariant CI | ✅ success | [View run](https://github.com/stranske/Trend_Model_Project/actions/runs/19843412457) |","**Summary**\n* Added a simple-mode pipeline resolver that bypasses patched modules by dropping the cached entry and importing the canonical `trend_analysis.pipeline` when the opt-in flag is set, while preserving the existing GC-scanning path by default. [src/trend_portfolio_app/app.pyL48-L127](https://github.com/stranske/Trend_Model_Project/blob/085b8be48393bd174477032c16048f0b6dbe1c4f/src/trend_portfolio_app/app.py#L48-L127)\n* Expanded pipeline proxy tests to validate direct-import behaviour under the new flag and ensure GC scanning remains unused in simple mode. [tests/app/test_portfolio_app_additional.pyL69-L126](https://github.com/stranske/Trend_Model_Project/blob/085b8be48393bd174477032c16048f0b6dbe1c4f/tests/app/test_portfolio_app_additional.py#L69-L126)\n* Brought the Codex bootstrap file formatting in line with other agent placeholders by including the expected trailing blank line. [agents/codex-3915.mdL1-L3](https://github.com/stranske/Trend_Model_Project/blob/085b8be48393bd174477032c16048f0b6dbe1c4f/agents/codex-3915.md#L1-L3)\n\n**Checklist**\n- [x] Add an environment flag that skips GC scanning and directly imports `trend_analysis.pipeline`.\n- [x] Ensure default behaviour remains unchanged (GC scanning enabled).\n- [x] Add tests covering both modes to assert correct pipeline resolution and instrumentation behaviour.\n\n**Testing**\n* ✅ `pytest tests/app/test_portfolio_app_additional.py -k \"pipeline_proxy_simple\" -q`\n\n [View task →](https://chatgpt.com/s/cd_692e3fa9918881919d8fa10d157c566f)","","\n\n\n\n@codex Your objective is to satisfy the **Acceptance Criteria** by completing each **Task** within the defined **Scope**.\n\n**This round you MUST:**\n1. Implement actual code or test changes that advance at least one incomplete task toward acceptance.\n2. Commit meaningful source code (.py, .yml, .js, etc.)—not just status/docs updates.\n3. Mark a task checkbox complete ONLY after verifying the implementation works.\n\n**DO NOT:**\n- Commit only status files, markdown summaries, or documentation when tasks require code.\n- Re-post checklists without making implementation progress.\n- Close the round without source-code changes when acceptance criteria require them.\n\nReview the Scope/Tasks/Acceptance below, identify the next incomplete task that requires code, implement it, then re-post the updated checklist reflecting your verified progress.\n\n#### Scope\n- [ ] `trend_portfolio_app.app._PipelineProxy` scans `gc.get_objects()` to prefer patched pipeline modules, which aids testing but adds overhead and magic. Production deployments could benefit from an opt-in simple mode that imports the pipeline directly.\n\n#### Tasks\n- [ ] Add an environment flag (e.g., `TREND_PIPELINE_PROXY_SIMPLE`) that, when set, skips GC scanning and directly imports `trend_analysis.pipeline`.\n- [ ] Ensure default behaviour remains unchanged (GC scanning enabled) to preserve test friendliness.\n- [ ] Add tests covering both modes to assert correct pipeline resolution and instrumentation behaviour.\n\n#### Acceptance Criteria\n- [ ] - Setting the new env flag yields a direct-import proxy path; default continues to honour GC-scanned modules.\n- [ ] - Tests cover simple and default modes and pass without changing existing app behaviour for users who do not set the flag.\n\n**Head SHA:** 31c24af195d68beb13ccd2ea2ecb2ec1d605c0e3\n**Latest Runs:** ✅ success — Gate\n**Required:** gate: ✅ success\n\n| Workflow / Job | Result | Logs |\n|----------------|--------|------|\n| .github/workflows/agents-pr-meta-v2.yml | ❌ failure | [View run](https://github.com/stranske/Trend_Model_Project/actions/runs/19826238445) |\n| .github/workflows/agents-pr-meta.yml | ❌ failure | [View run](https://github.com/stranske/Trend_Model_Project/actions/runs/19826238261) |\n| Agents PR meta manager | ❔ in progress | [View run](https://github.com/stranske/Trend_Model_Project/actions/runs/19826478381) |\n| CI Autofix Loop | ✅ success | [View run](https://github.com/stranske/Trend_Model_Project/actions/runs/19826240052) |\n| Gate | ✅ success | [View run](https://github.com/stranske/Trend_Model_Project/actions/runs/19826240093) |\n| Health 40 Sweep | ✅ success | [View run](https://github.com/stranske/Trend_Model_Project/actions/runs/19826240041) |\n| Health 44 Gate Branch Protection | ✅ success | [View run](https://github.com/stranske/Trend_Model_Project/actions/runs/19826239971) |\n| Health 45 Agents Guard | ✅ success | [View run](https://github.com/stranske/Trend_Model_Project/actions/runs/19826239986) |\n| Health 50 Security Scan | ✅ success | [View run](https://github.com/stranske/Trend_Model_Project/actions/runs/19826240001) |\n| Maint 52 Validate Workflows | ✅ success | [View run](https://github.com/stranske/Trend_Model_Project/actions/runs/19826239966) |\n| PR 11 - Minimal invariant CI | ✅ success | [View run](https://github.com/stranske/Trend_Model_Project/actions/runs/19826239975) |","","","\n\n\n\n@codex Your objective is to satisfy the **Acceptance Criteria** by completing each **Task** within the defined **Scope**.\n\n**This round you MUST:**\n1. Implement actual code or test changes that advance at least one incomplete task toward acceptance.\n2. Commit meaningful source code (.py, .yml, .js, etc.)—not just status/docs updates.\n3. Mark a task checkbox complete ONLY after verifying the implementation works.\n\n**DO NOT:**\n- Commit only status files, markdown summaries, or documentation when tasks require code.\n- Re-post checklists without making implementation progress.\n- Close the round without source-code changes when acceptance criteria require them.\n\nReview the Scope/Tasks/Acceptance below, identify the next incomplete task that requires code, implement it, then re-post the updated checklist reflecting your verified progress.\n\n#### Scope\n- [ ] `trend_portfolio_app.app._PipelineProxy` scans `gc.get_objects()` to prefer patched pipeline modules, which aids testing but adds overhead and magic. Production deployments could benefit from an opt-in simple mode that imports the pipeline directly.\n\n#### Tasks\n- [ ] Add an environment flag (e.g., `TREND_PIPELINE_PROXY_SIMPLE`) that, when set, skips GC scanning and directly imports `trend_analysis.pipeline`.\n- [ ] Ensure default behaviour remains unchanged (GC scanning enabled) to preserve test friendliness.\n- [ ] Add tests covering both modes to assert correct pipeline resolution and instrumentation behaviour.\n\n#### Acceptance Criteria\n- [ ] - Setting the new env flag yields a direct-import proxy path; default continues to honour GC-scanned modules.\n- [ ] - Tests cover simple and default modes and pass without changing existing app behaviour for users who do not set the flag.\n\n**Head SHA:** 31c24af195d68beb13ccd2ea2ecb2ec1d605c0e3\n**Latest Runs:** ✅ success — Gate\n**Required:** gate: ✅ success\n\n| Workflow / Job | Result | Logs |\n|----------------|--------|------|\n| .github/workflows/agents-pr-meta-v2.yml | ❌ failure | [View run](https://github.com/stranske/Trend_Model_Project/actions/runs/19826238445) |\n| .github/workflows/agents-pr-meta.yml | ❌ failure | [View run](https://github.com/stranske/Trend_Model_Project/actions/runs/19826238261) |\n| Agents PR meta manager | ❔ in progress | [View run](https://github.com/stranske/Trend_Model_Project/actions/runs/19826402050) |\n| CI Autofix Loop | ✅ success | [View run](https://github.com/stranske/Trend_Model_Project/actions/runs/19826240052) |\n| Gate | ✅ success | [View run](https://github.com/stranske/Trend_Model_Project/actions/runs/19826240093) |\n| Health 40 Sweep | ✅ success | [View run](https://github.com/stranske/Trend_Model_Project/actions/runs/19826240041) |\n| Health 44 Gate Branch Protection | ✅ success | [View run](https://github.com/stranske/Trend_Model_Project/actions/runs/19826239971) |\n| Health 45 Agents Guard | ✅ success | [View run](https://github.com/stranske/Trend_Model_Project/actions/runs/19826239986) |\n| Health 50 Security Scan | ✅ success | [View run](https://github.com/stranske/Trend_Model_Project/actions/runs/19826240001) |\n| Maint 52 Validate Workflows | ✅ success | [View run](https://github.com/stranske/Trend_Model_Project/actions/runs/19826239966) |\n| PR 11 - Minimal invariant CI | ✅ success | [View run](https://github.com/stranske/Trend_Model_Project/actions/runs/19826239975) |","\n# Autofix Status\n\n*Run:* 2025-12-02 02:53:02 UTC\n\n| Metric | Value |\n|--------|-------|\n| Status | ✅ |\n| Mode | Clean-mode cosmetic (`autofix:clean`) |\n| Delivery | PAT push |\n| Changed files | False |\n| Remaining issues | 0 |\n| New issues | 0 |\n| Allowed (legacy) | 0 |\n| Delivery note | pat-available |\n\n## Autofix result\n\nClean-mode cosmetic sweep found no changes.\nLabels: `autofix:clean-only`, `autofix:clean`\n\n## Trend (last 40 runs)\n\nRemaining: **0** `∅`\nNew: **0** `∅`\n\n## Artifacts & Reports\n\n- JSON report: `autofix-report-pr-3929`\n\n_This comment auto-updates; do not edit manually._\n\n","","","\n\n\n\n@codex Your objective is to satisfy the **Acceptance Criteria** by completing each **Task** within the defined **Scope**.\n\n**This round you MUST:**\n1. Implement actual code or test changes that advance at least one incomplete task toward acceptance.\n2. Commit meaningful source code (.py, .yml, .js, etc.)—not just status/docs updates.\n3. Mark a task checkbox complete ONLY after verifying the implementation works.\n\n**DO NOT:**\n- Commit only status files, markdown summaries, or documentation when tasks require code.\n- Re-post checklists without making implementation progress.\n- Close the round without source-code changes when acceptance criteria require them.\n\nReview the Scope/Tasks/Acceptance below, identify the next incomplete task that requires code, implement it, then re-post the updated checklist reflecting your verified progress.\n\n#### Scope\n- [ ] `trend_portfolio_app.app._PipelineProxy` scans `gc.get_objects()` to prefer patched pipeline modules, which aids testing but adds overhead and magic. Production deployments could benefit from an opt-in simple mode that imports the pipeline directly.\n\n#### Tasks\n- [ ] Add an environment flag (e.g., `TREND_PIPELINE_PROXY_SIMPLE`) that, when set, skips GC scanning and directly imports `trend_analysis.pipeline`.\n- [ ] Ensure default behaviour remains unchanged (GC scanning enabled) to preserve test friendliness.\n- [ ] Add tests covering both modes to assert correct pipeline resolution and instrumentation behaviour.\n\n#### Acceptance Criteria\n- [ ] - Setting the new env flag yields a direct-import proxy path; default continues to honour GC-scanned modules.\n- [ ] - Tests cover simple and default modes and pass without changing existing app behaviour for users who do not set the flag.\n\n**Head SHA:** 7ab3ceb9d94ad0f6a1b5f0f15f89c228f236924e\n**Latest Runs:** ✅ success — Gate\n**Required:** gate: ✅ success\n\n| Workflow / Job | Result | Logs |\n|----------------|--------|------|\n| .github/workflows/agents-pr-meta-v2.yml | ❌ failure | [View run](https://github.com/stranske/Trend_Model_Project/actions/runs/19815175549) |\n| .github/workflows/agents-pr-meta.yml | ❌ failure | [View run](https://github.com/stranske/Trend_Model_Project/actions/runs/19815175415) |\n| Agents PR meta manager | ❔ in progress | [View run](https://github.com/stranske/Trend_Model_Project/actions/runs/19815304720) |\n| CI Autofix Loop | ❌ failure | [View run](https://github.com/stranske/Trend_Model_Project/actions/runs/19815176745) |\n| Gate | ✅ success | [View run](https://github.com/stranske/Trend_Model_Project/actions/runs/19815176739) |\n| Health 40 Sweep | ✅ success | [View run](https://github.com/stranske/Trend_Model_Project/actions/runs/19815176736) |\n| Health 44 Gate Branch Protection | ✅ success | [View run](https://github.com/stranske/Trend_Model_Project/actions/runs/19815176682) |\n| Health 45 Agents Guard | ✅ success | [View run](https://github.com/stranske/Trend_Model_Project/actions/runs/19815176671) |\n| Health 50 Security Scan | ✅ success | [View run](https://github.com/stranske/Trend_Model_Project/actions/runs/19815176673) |\n| Maint 52 Validate Workflows | ✅ success | [View run](https://github.com/stranske/Trend_Model_Project/actions/runs/19815176707) |\n| PR 11 - Minimal invariant CI | ✅ success | [View run](https://github.com/stranske/Trend_Model_Project/actions/runs/19815176665) |","","\n\n\n\n@codex Your objective is to satisfy the **Acceptance Criteria** by completing each **Task** within the defined **Scope**.\n\n**This round you MUST:**\n1. Implement actual code or test changes that advance at least one incomplete task toward acceptance.\n2. Commit meaningful source code (.py, .yml, .js, etc.)—not just status/docs updates.\n3. Mark a task checkbox complete ONLY after verifying the implementation works.\n\n**DO NOT:**\n- Commit only status files, markdown summaries, or documentation when tasks require code.\n- Re-post checklists without making implementation progress.\n- Close the round without source-code changes when acceptance criteria require them.\n\nReview the Scope/Tasks/Acceptance below, identify the next incomplete task that requires code, implement it, then re-post the updated checklist reflecting your verified progress.\n\n#### Scope\n- [ ] `trend_portfolio_app.app._PipelineProxy` scans `gc.get_objects()` to prefer patched pipeline modules, which aids testing but adds overhead and magic. Production deployments could benefit from an opt-in simple mode that imports the pipeline directly.\n\n#### Tasks\n- [ ] Add an environment flag (e.g., `TREND_PIPELINE_PROXY_SIMPLE`) that, when set, skips GC scanning and directly imports `trend_analysis.pipeline`.\n- [ ] Ensure default behaviour remains unchanged (GC scanning enabled) to preserve test friendliness.\n- [ ] Add tests covering both modes to assert correct pipeline resolution and instrumentation behaviour.\n\n#### Acceptance Criteria\n- [ ] - Setting the new env flag yields a direct-import proxy path; default continues to honour GC-scanned modules.\n- [ ] - Tests cover simple and default modes and pass without changing existing app behaviour for users who do not set the flag.\n\n**Head SHA:** f0de11b07a497cc8e74332aff9f265aaf575eb13\n**Latest Runs:** ⏹️ cancelled — Gate\n**Required:** gate: ⏹️ cancelled\n\n| Workflow / Job | Result | Logs |\n|----------------|--------|------|\n| Agents PR meta manager | ❔ in progress | [View run](https://github.com/stranske/Trend_Model_Project/actions/runs/19815045708) |\n| CI Autofix Loop | ✅ success | [View run](https://github.com/stranske/Trend_Model_Project/actions/runs/19814963433) |\n| Copilot code review | ✅ success | [View run](https://github.com/stranske/Trend_Model_Project/actions/runs/19814963133) |\n| Gate | ⏹️ cancelled | [View run](https://github.com/stranske/Trend_Model_Project/actions/runs/19814963328) |\n| Health 40 Sweep | ✅ success | [View run](https://github.com/stranske/Trend_Model_Project/actions/runs/19814963421) |\n| Health 44 Gate Branch Protection | ✅ success | [View run](https://github.com/stranske/Trend_Model_Project/actions/runs/19814963381) |\n| Health 45 Agents Guard | ✅ success | [View run](https://github.com/stranske/Trend_Model_Project/actions/runs/19814963386) |\n| Health 50 Security Scan | ✅ success | [View run](https://github.com/stranske/Trend_Model_Project/actions/runs/19814963348) |\n| Maint 52 Validate Workflows | ✅ success | [View run](https://github.com/stranske/Trend_Model_Project/actions/runs/19814963374) |\n| PR 11 - Minimal invariant CI | ✅ success | [View run](https://github.com/stranske/Trend_Model_Project/actions/runs/19814963354) |","## Pull request overview\n\nThis PR adds a bootstrap file for Codex agent guidance related to issue #3915. The file follows the established pattern used in the `agents/` directory for creating placeholder files that track open issues.\n\n### Key Changes\n- Adds a new bootstrap markdown file `codex-3915.md` in the `agents/` directory\n\n\n\n\n\n---\n\nYou can also share your feedback on Copilot code review for a chance to win a $100 gift card. [Take the survey](https://survey.alchemer.com/s3/8579117/Copilot-Code-Review-In-product-survey-Nov-2025).","The file is missing a trailing newline. All other bootstrap files in the `agents/` directory (e.g., `codex-3911.md`, `codex-3912.md`, `codex-3880.md`) include a blank line after the HTML comment. This should be added for consistency.","agents/codex-3915.md","RIGHT","\n## Automated Status Summary\n**Head SHA:** 5ec349a4a71fd8409c7bd83f136d457d670c0a6b\n**Latest Runs:** ⏳ pending — Gate\n**Required contexts:** Gate / gate, Health 45 Agents Guard / Enforce agents workflow protections\n**Required:** core tests (3.11): ⏳ pending, core tests (3.12): ⏳ pending, docker smoke: ⏳ pending, gate: ⏳ pending\n\n| Workflow / Job | Result | Logs |\n|----------------|--------|------|\n| _(no jobs reported)_ | ⏳ pending | — |\n\n### Coverage Overview\n- Coverage history entries: 1\n### Coverage Trend\n- Trend: 85.00% → 94.22% (+9.22 pts)\n- Current: 94.22%\n- Baseline: 85.00%\n- Change: +9.22 pts\n- Soft drop limit: 1.00 pts\n- Required minimum: 70.00%\n\n_Updated automatically; will refresh on subsequent CI/Docker completions._\n\n\n---\n### Keepalive checklist\n\n#### Scope\n- [ ] `trend_portfolio_app.app._PipelineProxy` scans `gc.get_objects()` to prefer patched pipeline modules, which aids testing but adds overhead and magic. Production deployments could benefit from an opt-in simple mode that imports the pipeline directly.\n\n#### Tasks\n- [ ] Add an environment flag (e.g., `TREND_PIPELINE_PROXY_SIMPLE`) that, when set, skips GC scanning and directly imports `trend_analysis.pipeline`.\n- [ ] Ensure default behaviour remains unchanged (GC scanning enabled) to preserve test friendliness.\n- [x] Add tests covering both modes to assert correct pipeline resolution and instrumentation behaviour.\n\n#### Acceptance criteria\n- [ ] - Setting the new env flag yields a direct-import proxy path; default continues to honour GC-scanned modules.\n- [ ] - Tests cover simple and default modes and pass without changing existing app behaviour for users who do not set the flag.","\n\n\n\n## Automated Status Summary\n#### Scope\n- [ ] `trend_portfolio_app.app._PipelineProxy` scans `gc.get_objects()` to prefer patched pipeline modules, which aids testing but adds overhead and magic. Production deployments could benefit from an opt-in simple mode that imports the pipeline directly.\n\n#### Tasks\n- [ ] Add an environment flag (e.g., `TREND_PIPELINE_PROXY_SIMPLE`) that, when set, skips GC scanning and directly imports `trend_analysis.pipeline`.\n- [ ] Ensure default behaviour remains unchanged (GC scanning enabled) to preserve test friendliness.\n- [x] Add tests covering both modes to assert correct pipeline resolution and instrumentation behaviour.\n\n#### Acceptance criteria\n- [ ] - Setting the new env flag yields a direct-import proxy path; default continues to honour GC-scanned modules.\n- [ ] - Tests cover simple and default modes and pass without changing existing app behaviour for users who do not set the flag.\n\n**Head SHA:** 1b31af727b6900c1f8f3c5d477286f904b13de13\n**Latest Runs:** ✅ success — Gate\n**Required:** gate: ✅ success\n\n| Workflow / Job | Result | Logs |\n|----------------|--------|------|\n| Agents PR meta manager | ❔ in progress | [View run](https://github.com/stranske/Trend_Model_Project/actions/runs/19845501856) |\n| CI Autofix Loop | ❌ failure | [View run](https://github.com/stranske/Trend_Model_Project/actions/runs/19845337812) |\n| Gate | ✅ success | [View run](https://github.com/stranske/Trend_Model_Project/actions/runs/19845337750) |\n| Health 40 Sweep | ✅ success | [View run](https://github.com/stranske/Trend_Model_Project/actions/runs/19845337772) |\n| Health 44 Gate Branch Protection | ✅ success | [View run](https://github.com/stranske/Trend_Model_Project/actions/runs/19845337603) |\n| Health 45 Agents Guard | ✅ success | [View run](https://github.com/stranske/Trend_Model_Project/actions/runs/19845337588) |\n| Health 50 Security Scan | ✅ success | [View run](https://github.com/stranske/Trend_Model_Project/actions/runs/19845337566) |\n| Maint 52 Validate Workflows | ✅ success | [View run](https://github.com/stranske/Trend_Model_Project/actions/runs/19845337553) |\n| PR 11 - Minimal invariant CI | ✅ success | [View run](https://github.com/stranske/Trend_Model_Project/actions/runs/19845337558) |\n","base_ref","6f41596e452e717db20f3cb6c31340cdb98244fe","head_ref","pull_request_info",[1204],{"_1079":57,"_57":1205},"\n\n\n\n@codex Your objective is to satisfy the **Acceptance Criteria** by completing each **Task** within the defined **Scope**.\n\n**This round you MUST:**\n1. Implement actual code or test changes that advance at least one incomplete task toward acceptance.\n2. Commit meaningful source code (.py, .yml, .js, etc.)—not just status/docs updates.\n3. Mark a task checkbox complete ONLY after verifying the implementation works.\n4. **POST A REPLY COMMENT** with the updated checklist showing `- [x]` for completed items.\n\n**DO NOT:**\n- Commit only status files, markdown summaries, or documentation when tasks require code.\n- Re-post checklists without making implementation progress.\n- Close the round without source-code changes when acceptance criteria require them.\n- Complete work without posting a reply comment showing which checkboxes are now checked.\n\nReview the Scope/Tasks/Acceptance below, identify the next incomplete task that requires code, implement it, then **post a reply comment** with the updated checklist showing your verified progress (change `- [ ]` to `- [x]` for completed items).\n\n#### Scope\n- [ ] `trend_portfolio_app.app._PipelineProxy` scans `gc.get_objects()` to prefer patched pipeline modules, which aids testing but adds overhead and magic. Production deployments could benefit from an opt-in simple mode that imports the pipeline directly.\n\n#### Tasks\n- [ ] Add an environment flag (e.g., `TREND_PIPELINE_PROXY_SIMPLE`) that, when set, skips GC scanning and directly imports `trend_analysis.pipeline`.\n- [ ] Ensure default behaviour remains unchanged (GC scanning enabled) to preserve test friendliness.\n- [x] Add tests covering both modes to assert correct pipeline resolution and instrumentation behaviour.\n\n#### Acceptance Criteria\n- [ ] - Setting the new env flag yields a direct-import proxy path; default continues to honour GC-scanned modules.\n- [ ] - Tests cover simple and default modes and pass without changing existing app behaviour for users who do not set the flag.\n\n**Head SHA:** 1b31af727b6900c1f8f3c5d477286f904b13de13\n**Latest Runs:** ✅ success — Gate\n**Required:** gate: ✅ success\n\n| Workflow / Job | Result | Logs |\n|----------------|--------|------|\n| Agents PR meta manager | ❔ in progress | [View run](https://github.com/stranske/Trend_Model_Project/actions/runs/19845497029) |\n| CI Autofix Loop | ❌ failure | [View run](https://github.com/stranske/Trend_Model_Project/actions/runs/19845337812) |\n| Gate | ✅ success | [View run](https://github.com/stranske/Trend_Model_Project/actions/runs/19845337750) |\n| Health 40 Sweep | ✅ success | [View run](https://github.com/stranske/Trend_Model_Project/actions/runs/19845337772) |\n| Health 44 Gate Branch Protection | ✅ success | [View run](https://github.com/stranske/Trend_Model_Project/actions/runs/19845337603) |\n| Health 45 Agents Guard | ✅ success | [View run](https://github.com/stranske/Trend_Model_Project/actions/runs/19845337588) |\n| Health 50 Security Scan | ✅ success | [View run](https://github.com/stranske/Trend_Model_Project/actions/runs/19845337566) |\n| Maint 52 Validate Workflows | ✅ success | [View run](https://github.com/stranske/Trend_Model_Project/actions/runs/19845337553) |\n| PR 11 - Minimal invariant CI | ✅ success | [View run](https://github.com/stranske/Trend_Model_Project/actions/runs/19845337558) 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