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data: manifest-based incremental refresh of the parquet cache

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The cache now tracks every file in the data dir (mtime_ns + size) in
.cache/manifest.json. On load, a directory scan is compared against the
manifest:
  - changed/added files are re-read and merged into the parquet panels
    (one read + one concat + one write per touched panel; new values
    win where present, old values kept where the new file is short)
  - removed files drop their symbols (and names)
  - an up-to-date cache is a ~30 ms memo hit

Measured on the real 4k-symbol set: full build 54 s, refresh of
5 modified + 1 added + 1 removed files 3.4 s. No scan TTL (a scan is
a few ms); a previous 5 s scan cache masked data updates.

Tests: tests/test_data.py (11 checks) added as step 1 of run_tests.sh.
This commit is contained in:
Greg Pomerantz 2026-08-24 17:28:20 -04:00
parent d8703a7a63
commit cba7291676
4 changed files with 328 additions and 55 deletions
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7
README.md
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@ -12,13 +12,16 @@ python3 -m venv .venv
```
First run builds a parquet cache in `.cache/` (~1 min for 4k symbols);
later runs load in well under a second.
later runs load in well under a second. The cache tracks the data dir
per-file (mtime + size in `.cache/manifest.json`), so when the download
is updated, only the changed/added/removed symbols are re-read — a
partial refresh takes seconds instead of a full ~1 min rebuild.
## Modules
| Module | Purpose |
|-----------------|---------|
| `data.py` | Ingest `{sym}-history/dividend/capitalGain.csv` -> cached parquet panels (date x symbol). `Adj Close` already includes distributions, so it drives pre-tax total returns. |
| `data.py` | Ingest `{sym}-history/dividend/capitalGain.csv` -> cached parquet panels (date x symbol), with manifest-based incremental refresh when the data dir changes. `Adj Close` already includes distributions, so it drives pre-tax total returns. |
| `metrics.py` | Total/annualized return, vol, Sharpe, Sortino, max drawdown, Calmar, CAPM beta/alpha. Pure pandas, all transparent. |
| `portfolio.py` | Weighted portfolios with drift and periodic rebalancing to target weights (`1W/1ME/QE/YE`), one-way cost in bps. Spec grammar: commas join the elements of ONE portfolio (`SYM` or `SYM:w`, bare = equal weight), spaces separate DISTINCT symbols/portfolios (`parse_items`). |
| `tax.py` | Simplified DAS after-tax engine: FIFO lots, 365-day long/short split, separate LT/ST/dividend rates. Headline curve = what you keep if you **sell everything today** (unrealized gains taxed daily by lot age). |

248
data.py
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@ -18,6 +18,8 @@ First call builds a parquet cache (default: .cache/) in ~1 min for
from __future__ import annotations
import json
import os
import threading
from dataclasses import dataclass
from pathlib import Path
@ -26,6 +28,9 @@ import pandas as pd
DEFAULT_ROOT = Path("~/prog/fin/stocks").expanduser()
CACHE_DIR = Path(__file__).parent / ".cache"
_SUFFIXES = ("history", "dividend", "capitalGain")
_PANELS = ("adj", "close", "div", "capg")
@dataclass
class Bundle:
@ -36,19 +41,24 @@ class Bundle:
names: dict # symbol -> long name (best effort)
def _read_csv_clean(f: Path) -> pd.DataFrame:
df = pd.read_csv(f, index_col=0)
df.index = pd.to_datetime(df.index, format="mixed", errors="coerce")
df = df[~df.index.isna()]
df = df[~df.index.duplicated(keep="last")].sort_index()
return df
def _read_panel(root: Path, suffix: str, col: str) -> pd.DataFrame:
cols = []
syms = []
cols, syms = [], []
for f in sorted(root.glob(f"*-{suffix}.csv")):
sym = f.name[: -len(f"-{suffix}.csv")]
df = pd.read_csv(f, index_col=0)
df.index = pd.to_datetime(df.index, format="mixed", errors="coerce")
df = df[~df.index.isna()]
df = df[~df.index.duplicated(keep="last")].sort_index()
if col not in df.columns:
try:
df = _read_csv_clean(f)
except Exception:
continue
cols.append(df[col])
syms.append(sym)
if col in df.columns:
cols.append(df[col])
syms.append(f.name[: -len(f"-{suffix}.csv")])
if not cols:
return pd.DataFrame()
out = pd.concat(cols, axis=1)
@ -56,58 +66,194 @@ def _read_panel(root: Path, suffix: str, col: str) -> pd.DataFrame:
return out.sort_index()
def _read_name(f: Path) -> str:
try:
meta = json.loads(f.read_text())["chart"]["result"][0]["meta"]
return meta.get("longName", f.stem)
except Exception:
return f.stem
def _read_names(root: Path, max_files: int = 5000) -> dict:
names = {}
for f in root.glob("*.json"):
try:
meta = json.loads(f.read_text())["chart"]["result"][0]["meta"]
names[f.stem] = meta.get("longName", f.stem)
except Exception:
names[f.stem] = f.stem
return names
files = sorted(root.glob("*.json"))[:max_files]
return {f.stem: _read_name(f) for f in files}
# ---------------------------------------------------------------- caching
# a bundle is ~2 GB resident; memoize the last one so Streamlit re-runs
# (every widget change!) don't reload the parquet panels
_BUNDLE_CACHE: dict[tuple, Bundle] = {}
_LOCK = threading.Lock()
def _scan_files(root: Path) -> dict:
"""{filename: (mtime_ns, size)} for every csv/json file in the data root."""
out = {}
with os.scandir(root) as it:
for e in it:
if e.is_file() and e.name.endswith((".csv", ".json")):
st = e.stat()
out[e.name] = (st.st_mtime_ns, st.st_size)
return out
def _manifest_path(cache: Path) -> Path:
return cache / "manifest.json"
def _cache_up_to_date(root: Path, cache: Path) -> bool:
"""Cheap staleness check: dir scan vs manifest.
A scan is a handful of milliseconds for ~16k files, so this is done on
every call (caching the scan result would mask data updates)."""
new = _scan_files(root)
try:
old = json.loads(_manifest_path(cache).read_text())
except Exception:
return False
return {f: tuple(v) for f, v in old.items()} == new
def _full_build(root: Path, cache: Path, cache_files: list) -> None:
"""(Re)read every CSV and write all parquet panels + manifest."""
adj = _read_panel(root, "history", "Adj Close")
close = _read_panel(root, "history", "Close")
div = _read_panel(root, "dividend", "Dividends").fillna(0.0)
capg = _read_panel(root, "capitalGain", "Capital Gains").fillna(0.0)
for df, f in zip((adj, close, div, capg), cache_files):
df.to_parquet(f)
_manifest_path(cache).write_text(json.dumps(_scan_files(root)))
def _apply_changes(root: Path, cache: Path, old: dict, new: dict) -> None:
"""Incremental refresh: re-read only files that were added/changed,
drop symbols whose files vanished, refresh names, rewrite the touched
parquet panels.
Per touched panel this is ONE read + ONE concat + ONE write (inserting
column-by-column into a ~500 MB frame is prohibitively slow).
"""
old = {f: tuple(v) for f, v in old.items()} # JSON round-trip turns tuples into lists
changed = [f for f, v in new.items() if old.get(f) != v]
removed = [f for f in old if f not in new]
if not changed and not removed:
return
def _suffix(fname: str):
for sfx in _SUFFIXES:
if fname.endswith(f"-{sfx}.csv"):
return sfx, fname[: -len(f"-{sfx}.csv")]
return None, None
updates: dict[str, dict] = {k: {} for k in _PANELS} # panel -> {sym: series}
drops: set[str] = set()
for fname in changed:
sfx, sym = _suffix(fname)
if sfx is None:
continue
try:
df = _read_csv_clean(root / fname)
except Exception:
continue # e.g. a file mid-download
if sfx == "history":
if "Adj Close" in df.columns:
updates["adj"][sym] = df["Adj Close"]
if "Close" in df.columns:
updates["close"][sym] = df["Close"]
elif sfx == "dividend" and "Dividends" in df.columns:
updates["div"][sym] = df["Dividends"].fillna(0.0)
elif sfx == "capitalGain" and "Capital Gains" in df.columns:
updates["capg"][sym] = df["Capital Gains"].fillna(0.0)
for fname in removed:
sfx, sym = _suffix(fname)
if sfx is not None:
drops.add(sym)
# names: only the json metadata files that changed
j_changed = [f for f in changed if f.endswith(".json")]
j_removed = [f for f in removed if f.endswith(".json")]
if j_changed or j_removed:
names_path = cache / "names.json"
try:
names = json.loads(names_path.read_text())
except Exception:
names = {}
for f in j_removed:
names.pop(f[:-5], None)
for f in j_changed:
names[f[:-5]] = _read_name(root / f)
names_path.write_text(json.dumps(names))
for k in _PANELS:
upd = {s: ser for s, ser in updates[k].items() if s not in drops}
if not upd and not drops:
continue
panel = pd.read_parquet(cache / f"panel_{k}.parquet")
old = {s: panel[s] for s in upd if s in panel.columns}
drop_cols = [s for s in (drops | set(upd)) if s in panel.columns]
if drop_cols:
panel = panel.drop(columns=drop_cols)
if upd:
extras = []
for sym, s in upd.items():
s = s.rename(sym)
if sym in old:
# new values win where present; keep old values for dates
# the new file doesn't cover (e.g. a partial re-download)
uidx = panel.index.union(s.index)
s = s.reindex(uidx).combine_first(old[sym].reindex(uidx))
extras.append(s)
extra = pd.concat(extras, axis=1)
extra.columns = list(upd)
panel = pd.concat([panel, extra], axis=1).sort_index()
panel.to_parquet(cache / f"panel_{k}.parquet")
def load_bundle(root: Path = DEFAULT_ROOT, cache: Path = CACHE_DIR,
rebuild: bool = False) -> Bundle:
"""Load the full dataset, using (or building) a parquet cache."""
key = (str(root), rebuild)
hit = _BUNDLE_CACHE.get(key)
if hit is not None:
return hit
cache = Path(cache)
cache.mkdir(parents=True, exist_ok=True)
cache_files = [cache / f"panel_{k}.parquet" for k in ("adj", "close", "div", "capg")]
"""Load the full dataset, using (or building) a parquet cache.
if not rebuild and all(f.exists() for f in cache_files):
adj = pd.read_parquet(cache_files[0])
close = pd.read_parquet(cache_files[1])
div = pd.read_parquet(cache_files[2])
capg = pd.read_parquet(cache_files[3])
else:
adj = _read_panel(root, "history", "Adj Close")
close = _read_panel(root, "history", "Close")
div = _read_panel(root, "dividend", "Dividends").fillna(0.0)
capg = _read_panel(root, "capitalGain", "Capital Gains").fillna(0.0)
adj.to_parquet(cache_files[0])
close.to_parquet(cache_files[1])
div.to_parquet(cache_files[2])
capg.to_parquet(cache_files[3])
names_path = cache / "names.json"
if names_path.exists():
names = json.loads(names_path.read_text())
else:
names = _read_names(root)
names_path.write_text(json.dumps(names))
bundle = Bundle(adj, close, div, capg, names)
# keep only the newest bundle: there is no room for two
_BUNDLE_CACHE.clear()
_BUNDLE_CACHE[key] = bundle
return bundle
The cache tracks the data dir via a manifest of (mtime, size) per file:
changed/added files are re-read and merged in incrementally, removed
files are dropped, so an updated download refreshes in seconds instead
of the ~1 min full rebuild. `rebuild=True` forces the full rebuild.
"""
root, cache = Path(root), Path(cache)
key = (str(root), rebuild)
with _LOCK:
hit = _BUNDLE_CACHE.get(key)
if hit is not None and not rebuild and _cache_up_to_date(root, cache):
return hit
cache.mkdir(parents=True, exist_ok=True)
cache_files = [cache / f"panel_{k}.parquet" for k in _PANELS]
cache_ok = all(f.exists() for f in cache_files)
if rebuild or not cache_ok:
_full_build(root, cache, cache_files)
else:
try:
old = json.loads(_manifest_path(cache).read_text())
except Exception:
old = None
new = _scan_files(root)
if old is None:
# parquet without a manifest: state unknown -> rebuild once
_full_build(root, cache, cache_files)
else:
_apply_changes(root, cache, old, new)
_manifest_path(cache).write_text(json.dumps(new))
panels = {k: pd.read_parquet(f) for k, f in zip(_PANELS, cache_files)}
names_path = cache / "names.json"
if names_path.exists():
names = json.loads(names_path.read_text())
else:
names = _read_names(root)
names_path.write_text(json.dumps(names))
bundle = Bundle(panels["adj"], panels["close"], panels["div"],
panels["capg"], names)
# keep only the newest bundle: there is no room for two
_BUNDLE_CACHE.clear()
_BUNDLE_CACHE[key] = bundle
return bundle
def search_symbols(bundle: Bundle, query: str, limit: int = 200) -> list[str]:

8
run_tests.sh
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@ -9,11 +9,15 @@ cd "$(dirname "$0")"
fail=0
echo "=== 1/2 app tests (AppTest, no browser) ==="
echo "=== 1/3 data cache tests (incremental refresh) ==="
.venv/bin/python tests/test_data.py || fail=1
echo
echo "=== 2/3 app tests (AppTest, no browser) ==="
.venv/bin/python tests/test_app.py || fail=1
echo
echo "=== 2/2 browser e2e (Playwright, needs the server) ==="
echo "=== 3/3 browser e2e (Playwright, needs the server) ==="
if curl -s -m 3 -o /dev/null http://localhost:8599/healthz; then
.venv/bin/python tests/test_e2e_browser.py || fail=1
else

120
tests/test_data.py Normal file
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@ -0,0 +1,120 @@
"""Data-cache tests: incremental refresh from changed data files.
Uses a small synthetic data root in a temp dir — no real data, no server.
Run: .venv/bin/python tests/test_data.py
"""
from __future__ import annotations
import json
import os
import pathlib
import shutil
import sys
import tempfile
sys.path.insert(0, str(pathlib.Path(__file__).resolve().parent.parent))
import data as D # noqa: E402
PASS, FAIL = 0, 0
def check(name: str, cond: bool, extra: str = "") -> None:
global PASS, FAIL
if cond:
PASS += 1
print(f" ok {name}", flush=True)
else:
FAIL += 1
print(f" FAIL {name} {extra}", flush=True)
def write_history(root: pathlib.Path, sym: str, last_price: float | None = None,
days: int = 10) -> pathlib.Path:
"""Prices 100.00, 101.00, ..., 109.00 (last day overridable)."""
f = root / f"{sym}-history.csv"
lines = ["Date,Open,High,Low,Close,Adj Close,Volume"]
for i in range(days):
p = last_price if (last_price is not None and i == days - 1) \
else 100.0 + i
lines.append(f"2024-01-{i + 1:02d},{p:.2f},{p:.2f},{p:.2f},{p:.2f},{p:.2f},1000")
f.write_text("\n".join(lines) + "\n")
return f
def touch(p: pathlib.Path) -> None:
"""Bump mtime so the manifest sees the file as changed."""
st = p.stat()
os.utime(p, ns=(st.st_atime_ns + 10**9, st.st_mtime_ns + 10**9))
def reload(d: pathlib.Path) -> D.Bundle:
return D.load_bundle(root=d["root"], cache=d["cache"])
def main() -> int:
tmp = pathlib.Path(tempfile.mkdtemp(prefix="fdatatest-"))
root, cache = tmp / "stocks", tmp / "cache"
root.mkdir()
d = {"root": root, "cache": cache}
try:
write_history(root, "aaa")
write_history(root, "bbb")
write_history(root, "ccc")
(root / "aaa-dividend.csv").write_text("Date,Dividends\n2024-01-05,0.5\n")
(root / "bbb.json").write_text(
json.dumps({"chart": {"result": [{"meta": {"longName": "Bee Bee Corp"}}]}}))
b = reload(d)
check("initial full build", list(b.adj.columns) == ["aaa", "bbb", "ccc"]
and b.adj["aaa"].iloc[-1] == 109.0, str(list(b.adj.columns)))
check("names from json", b.names.get("bbb") == "Bee Bee Corp")
check("dividend panel", b.div["aaa"].loc["2024-01-05"] == 0.5)
# --- modified file: last price changes
f = write_history(root, "aaa", last_price=200.0)
touch(f)
b = reload(d)
check("changed file re-read incrementally", b.adj["aaa"].iloc[-1] == 200.0)
check("untouched symbols intact", b.adj["bbb"].iloc[-1] == 109.0)
# --- new file: symbol added
write_history(root, "ddd")
b = reload(d)
check("new symbol added", "ddd" in b.adj.columns)
# --- deleted file: symbol dropped
(root / "ccc-history.csv").unlink()
b = reload(d)
check("deleted symbol dropped", "ccc" not in b.adj.columns
and "ccc" not in b.div.columns)
# --- name file added for a new symbol
(root / "ddd.json").write_text(
json.dumps({"chart": {"result": [{"meta": {"longName": "Dee Dee"}}]}}))
b = reload(d)
check("name added incrementally", b.names.get("ddd") == "Dee Dee")
# --- dividend file modified
(root / "aaa-dividend.csv").write_text(
"Date,Dividends\n2024-01-05,0.5\n2024-01-06,1.25\n")
b = reload(d)
check("dividend change picked up", b.div["aaa"].loc["2024-01-06"] == 1.25)
# --- no-change reload: cheap, no rewrite
before = (cache / "panel_adj.parquet").stat().st_mtime_ns
b = reload(d)
after = (cache / "panel_adj.parquet").stat().st_mtime_ns
check("no-op reload does not rewrite parquet", before == after)
# --- forced full rebuild still works
b = D.load_bundle(root=root, cache=cache, rebuild=True)
check("forced full rebuild", list(b.adj.columns) == ["aaa", "bbb", "ddd"])
finally:
shutil.rmtree(tmp, ignore_errors=True)
print(f"\n{PASS} passed, {FAIL} failed")
return 1 if FAIL else 0
if __name__ == "__main__":
sys.exit(main())