arctic-incr-cache 0.1.19

ArcticDB-backed time series cache with incremental updates — fetch once, upsert the gap.

arctic-incr-cache

ArcticDB-backed time series cache with incremental updates.

First call fetches the full window from your data source and stores it in ArcticDB. Subsequent calls only fetch the gap between the cached tail and the requested end — then merge and upsert. Incomplete (still-updating) bars are automatically excluded from storage so they never overwrite finalised data.

Install

pip install arctic-incr-cache
# or
uv add arctic-incr-cache

Quick start

import datetime
import arcticdb as adb
from zoneinfo import ZoneInfo
from arctic_incr_cache import IncrCache

arctic = adb.Arctic("lmdb://data/arcticdb")
lib = arctic.get_library("ohlcv-1d", create_if_missing=True)

cache = IncrCache(
    lib,
    fetch=lambda symbol, end, count: your_api.get_daily_bars(symbol, end=end, count=count),
    get_tz=lambda symbol: ZoneInfo("America/New_York"),
)

df = cache.get("AAPL", end=datetime.date(2024, 6, 1), count=60)

• First call — fetches 60 bars from your API, stores in ArcticDB, returns.
• Second call (same or later end) — serves from ArcticDB; fetches only the gap if the cache is stale.

Intraday data

Set bar_minutes to the bar width and provide get_tz to return the market timezone:

from zoneinfo import ZoneInfo

intraday = IncrCache(
    lib,
    fetch=lambda symbol, end, count: your_api.get_minute_bars(symbol, end=end, count=count),
    bar_minutes=1,
    default_count=390 * 5,
    get_tz=lambda symbol: ZoneInfo("America/New_York"),
)

Concurrency

By default writes run in a daemon thread. Pass spawn and lock_class for gevent or other async runtimes:

import gevent
import gevent.lock

cache = IncrCache(
    lib,
    fetch=my_fetch,
    spawn=gevent.spawn,
    lock_class=gevent.lock.BoundedSemaphore,
)

Timezone handling

When get_tz returns a timezone for a symbol:

• fetch return — must be tz-aware. Timestamps are converted to the configured market timezone internally.
• Storage — data is stored in ArcticDB as tz-aware in the configured timezone.
• Return — get() returns a tz-aware DataFrame in the configured timezone.
• end parameter — date becomes end-of-day in market timezone; naive datetime is interpreted as local timezone, then converted; tz-aware is converted directly.

Interval convention

• Data & return — both ends inclusive (index <= end). The returned DataFrame includes the bar at end if it exists.
• Freshness check — left-closed right-open. The cache considers data fresh when the last cached bar reaches end - bar_width, since the bar at end itself may not yet exist.

Index convention

fetch() must return a DataFrame with a DatetimeIndex as the index — this is the time axis for all cache operations (querying, merging, freshness checks). ArcticDB's date_range queries operate on the index, so no column name configuration is needed. If your data source returns time as a regular column, call df.set_index("date") (or similar) inside your fetch function.

Constructor parameters

Parameter	Required	Description
library	yes	ArcticDB library instance
fetch(symbol, end, count)	yes	Fetch raw data from upstream; must return tz-aware timestamps
get_tz(symbol)	yes	Market timezone (tzinfo) for each symbol
bar_minutes	no	Bar width in minutes (default 1440 = daily)
default_count	no	Bars returned when count is omitted (default 252)
spawn	no	Fire-and-forget callable for async writes (default: daemon thread)
lock_class	no	Lock constructor (default: threading.Lock)

License

MIT