CEF app tab + server watchdog + full-universe verification batch
- Fund Lab tab: CEF tax-arb shortlist table (char actual-vs-model, discount, 5y return/vol, scenario hits, tenders, score) built from cef_character.json + cef_annual.json. - fundlab/server_watchdog.sh: relaunches Streamlit on :8599 if the health endpoint stops answering (the old watchdog only covered the overnight screen and had exited). - fundlab/cef_universe_run.py: resumable batch extending per-share verification to all 295 CEFs -> cef_annual_all.json.
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49
app.py
49
app.py
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@ -1109,3 +1109,52 @@ with tab_fundlab:
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"counted where the layout exposes a dollar value; the bucket "
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"table is a rough keyword classification. N-PORT holdings are "
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"quarterly and up to ~60 days stale.")
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# --- closed-end funds (tax-arb shortlist) ---------------------------
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import pandas as _pd
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_fl_dir = Path(__file__).parent / "fundlab"
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_char_path = _fl_dir / "cef_character.json"
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if _char_path.exists():
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_char = json.loads(_char_path.read_text())
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_annual = {}
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_ann_path = _fl_dir / "cef_annual.json"
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if _ann_path.exists():
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_annual = json.loads(_ann_path.read_text())
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_rows = []
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for _s, _c in _char.items():
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_a = _annual.get(_s.upper(), {})
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_ch = _c.get("character")
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_actual = False
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if _a.get("char_actual") is not None:
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_ch = _a["char_actual"]
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_actual = True
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_t5, _vol = _c.get("t5"), _c.get("vol5")
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_score = (None if _ch is None or _t5 is None or _vol is None
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else round(_ch * (_t5 + 0.4 * _vol), 4))
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_disc = _a.get("disc_now_approx")
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_rows.append({
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"sym": _s.upper(),
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"name": (_a.get("name") or _c.get("name") or "")[:44],
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"char": _ch,
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"actual": _actual,
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"disc%": None if _disc is None else round(100 * _disc, 1),
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"t5%": None if _t5 is None else round(100 * _t5, 1),
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"vol5%": None if _vol is None else round(100 * _vol, 1),
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"pos_scen": _c.get("n_pos_scen"),
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"tenders": _a.get("n_tender"),
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"score": _score})
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_cef_df = _pd.DataFrame(_rows)
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st.divider()
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st.subheader("Closed-end funds — tax-arb shortlist")
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st.dataframe(
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_cef_df.sort_values("score", ascending=False, na_position="last"),
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width="stretch", height=460)
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st.caption(
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"char = distribution character 0–1 (0 = all ordinary income, 1 = "
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"all capital-gains/ROC). actual = verified from the fund's own "
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"per-share financial highlights (divs + gains + ROC == total "
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"distributions per year, plus the full NAV chain); otherwise the "
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"return-sleeve model. disc% = market vs NAV. pos_scen = severe-"
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"drawdown scenarios with a positive 5y return. score = char × "
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"(5y total return + 0.4 × 5y vol) — harvestable character "
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"weighted by damage potential.")
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1
fundlab/cef_universe_run.log
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1
fundlab/cef_universe_run.log
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@ -0,0 +1 @@
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[2026-08-28 14:56:15] universe=295 done=0 todo=295
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75
fundlab/cef_universe_run.py
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fundlab/cef_universe_run.py
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@ -0,0 +1,75 @@
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"""Extend per-share verification to the FULL CEF universe (295 tickers).
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The 50-fund shortlist run (fundlab.cef_annual) wrote fundlab/cef_annual.json.
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This batch runs the same analyze() over every ticker in
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fundlab/cef_universe.json and writes fundlab/cef_annual_all.json —
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incrementally, so a killed run resumes by re-running this script (cached
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funds are skipped, as are those already in the output file).
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Usage:
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.venv/bin/python -m fundlab.cef_universe_run # all, resumable
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.venv/bin/python -m fundlab.cef_universe_run --retry-err # redo failed ones
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"""
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from __future__ import annotations
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import json
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import sys
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import time
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from pathlib import Path
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from fundlab.cef_annual import (CACHE, analyze, character_score,
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current_nav_discount)
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HERE = Path(__file__).parent
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UNIVERSE = HERE / "cef_universe.json"
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OUT = HERE / "cef_annual_all.json"
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LOG = HERE / "cef_universe_run.log"
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def log(msg: str) -> None:
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line = f"[{time.strftime('%Y-%m-%d %H:%M:%S')}] {msg}"
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print(line, flush=True)
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with LOG.open("a") as f:
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f.write(line + "\n")
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def run(retry_err: bool = False) -> dict:
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uni = json.loads(UNIVERSE.read_text())
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prev: dict = {}
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if OUT.exists():
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prev = json.loads(OUT.read_text())
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todo = []
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for s in sorted(uni):
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p = prev.get(s)
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if p is None or (retry_err and "error" in p):
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todo.append(s)
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log(f"universe={len(uni)} done={len(uni) - len(todo)} todo={len(todo)}"
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+ (" [retry-err]" if retry_err else ""))
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res = dict(prev)
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for i, s in enumerate(todo, 1):
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u = uni[s]
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cik = int(u.get("cik", 0))
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try:
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a = analyze(s, cik)
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except Exception as e: # noqa: BLE001 - batch must not die
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a = {"sym": s, "error": f"analyze exception: {e}"}
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a["char_actual"] = (round(character_score(a, u.get("name", "")), 2)
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if "share_div" in a else None)
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if "nav_end" in a:
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d = current_nav_discount(a)
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a["disc_now_approx"] = round(d, 4) if d is not None else None
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res[s] = a
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if "share_div" in a:
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log(f"{i:3}/{len(todo)} {s:7} div {a['share_div']:.0%} "
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f"gain {a['share_gains']:.0%} roc {a['share_roc']:.0%} "
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f"char={a['char_actual']}")
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else:
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log(f"{i:3}/{len(todo)} {s:7} -- {a.get('error', 'no data')}")
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OUT.write_text(json.dumps(res, indent=1, default=str))
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log(f"done: parsed={sum(1 for v in res.values() if 'share_div' in v)} "
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f"of {len(res)}")
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return res
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if __name__ == "__main__":
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run(retry_err="--retry-err" in sys.argv)
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2
fundlab/server_watchdog.log
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2
fundlab/server_watchdog.log
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@ -0,0 +1,2 @@
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2026-08-28 14:52:00
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server_watchdog: no answer on :8599 - relaunching
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31
fundlab/server_watchdog.sh
Executable file
31
fundlab/server_watchdog.sh
Executable file
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@ -0,0 +1,31 @@
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#!/usr/bin/env bash
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# Keep the Streamlit app alive on port 8599.
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#
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# The server (or the machine) can drop it at any time, so every 5 minutes
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# this checks whether something is answering on the port and, if not,
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# relaunches it detached. Streamlit only hot-reloads app.py, so module
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# changes need this relaunch (or a manual one) to take effect.
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#
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# Usage: setsid nohup fundlab/server_watchdog.sh </dev/null >>fundlab/server_watchdog.log 2>&1 &
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set -u
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cd "$(dirname "$0")/.."
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PORT=8599
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INTERVAL=300
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alive() {
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curl -s -o /dev/null --max-time 8 "http://127.0.0.1:${PORT}/_stcore/health" \
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&& [ "$(curl -s --max-time 8 "http://127.0.0.1:${PORT}/_stcore/health")" = "ok" ]
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}
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while true; do
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if ! alive; then
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{ date "+%Y-%m-%d %H:%M:%S"
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echo "server_watchdog: no answer on :${PORT} - relaunching"
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} >> fundlab/server_watchdog.log
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setsid nohup .venv/bin/streamlit run app.py \
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--server.port "${PORT}" --server.headless true \
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--browser.gatherUsageStats false >> fundlab/streamlit.log 2>&1 < /dev/null &
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sleep 15
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fi
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sleep "${INTERVAL}"
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done
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