asof-store
An in-memory versioned store for retrieving the latest value written at or before a specified timestamp.
Install
uv add asof-store
Usage
from asof_store import AsOfStore
store = AsOfStore.from_memory()
store.put(as_of=10, key="price", value=100)
store.put(as_of=20, key="price", value=125)
assert store.get(as_of=15, key="price") == 100
with store.as_of(20) as snapshot:
assert snapshot.get("price") == 125
Both get methods return None when no value exists at or before the
requested timestamp. For each key, writes must use strictly increasing
timestamps. put returns False without recording a new version when the
value equals that key's latest value, or when the exact latest
(timestamp, key, value) is repeated. Otherwise, it records the value and
returns True. Reusing a timestamp with a different value or going back to an
earlier timestamp raises ValueError.
Passing None as as_of to get or store.as_of(None) selects the latest
available value, matching get_all(None) and get_unique_set(field, None).
SQL storage (optional)
Install the optional extra matching your database:
python -m pip install "asof-store[sql-sqlite]"
# or, for PostgreSQL:
python -m pip install "asof-store[sql-postgres]"
Pass the table name and timestamp, key, and value types when creating a SQL-backed store:
from asof_store import AsOfStore
sqlite_store = AsOfStore.from_sql(
"sqlite:///asof.db", "price_versions", int, str, dict
)
postgres_store = AsOfStore.from_sql(
"postgresql+psycopg://user:password@localhost/database",
"price_versions",
int,
str,
dict,
)
Native SQL types are used where supported, including JSONB for dict, list,
tuple, and Pydantic BaseModel subclasses on PostgreSQL (JSON on SQLite).
Tuples are stored as JSON arrays and restored as tuples. Pydantic models are
serialized with model_dump(mode="json", exclude_unset=True) and restored to
their declared model type when read. Other Python types use pickle. SQL stores
validate writes against the declared types. SQL-backed datetime values must
be timezone-aware.
When value_type is NoneType, SQL tables omit the value column; the memory
backend does not allocate per-version value storage for None values.
Use a distinct table name for each type combination; an existing table is not
altered if its schema differs. Other Python values are stored with pickle, so
only use SQL stores with databases you trust, since loading a database
containing untrusted pickle data can execute code. Call store.close() when
finished to release SQLAlchemy's pooled connections.
SQL timestamps must use sortable scalar types supported by the database (such
as integers, strings, dates, datetimes, decimals, and UUIDs); compound JSON and
arbitrary pickle-backed timestamps are rejected. Boolean timestamps are not
supported because PostgreSQL does not provide ordering comparisons for them.
SQL tables use (key, timestamp) as a composite primary key, which also
provides the index used for efficient latest-version lookups.
PostgreSQL SQL stores provide get_all(as_of=None) to return each key's latest
value, and get_unique_set(field, as_of=None) to return distinct values of a
JSON field from those latest values. Supplying as_of limits each query to
versions at or before that timestamp. Missing or JSON null fields appear as
None in the set.
Interactive Brokers data (optional)
Install the Zapros extra to query the Interactive Brokers UK web API:
uv add "asof-store[scraper]"
Functions in asof_store.ib create and close a Zapros client when one is not
provided. Pass an existing sync or async client to reuse its connection.
get_exchanges fetches the exchange catalogue, while get_instrument_summary
fetches product counts by type. get_products_by_filters fetches one page, and
scrape_instruments fetches every reported page and yields instruments.
get_funds_by_filters and scrape_funds use IB's dedicated funds endpoint.
Async equivalents have an _async suffix; scrape_instruments_async is an
async iterator.
The API returns Pydantic models: ExchangeResponse, InstrumentSummaryItem,
ProductsResponse, Instrument, and Fund. Request models
InstrumentSummaryRequest, ProductsByFiltersRequest, and
FundProductsRequest serialize field names to the format expected by IB.
Instrument and fund models allow additional IB fields so new or
product-specific response fields are retained. Instrument.conid and
Fund.conid are IB contract IDs and are used as their primary keys. Instruments
or funds without a contract ID have primary_key == None. Exchanges use the
composite primary key (id, country_code).
from asof_store.ib import InstrumentScrapeSummary, get_exchanges, scrape_instruments
exchanges = get_exchanges()
for item in scrape_instruments(page_size=500):
if isinstance(item, InstrumentScrapeSummary):
print("Summary:", item.products)
else:
print(item)
us_stocks = scrape_instruments(
page_size=500,
product_type=["STK"],
product_country=["US"],
new_product="T",
)
import asyncio
from asof_store.ib import (
InstrumentScrapeSummary,
get_exchanges_async,
scrape_instruments_async,
)
async def main():
exchanges = await get_exchanges_async()
async for item in scrape_instruments_async(page_size=500):
if isinstance(item, InstrumentScrapeSummary):
print("Summary:", item.products)
else:
print(item)
async for instrument in scrape_instruments_async(
product_type=["STK"],
product_country=["US"],
new_product="F",
):
print(instrument)
asyncio.run(main())
product_type and product_country accept lists of IB product types and
countries. If both lists are empty, the scraper uses all keys from
product_id2name (including CFD) as product types; otherwise, the provided
filters are passed through. new_product accepts "all" (default), "T", or
"F" to select all, new, or non-new products. These filters are sent to both
the summary used to determine pages and the products requests. Requests use
the live IB API and
are not cached or persisted. Product page sizes must be 100, 200, 300, 400, or
500. Both instrument scrape iterators yield an InstrumentScrapeSummary
tagged event first (event == "summary", with products containing
InstrumentSummaryItem values), before requesting product pages, followed by
Instrument objects and a page-complete event after each page. The persistence
API invokes on_summary before processing, then calls on_progress once for
each completed page with that page's instrument ordinal range.
Live integration tests
Opt-in integration tests are kept in tests/integration/. The IB tests call the
real IB UK API, including each endpoint and the synchronous and asynchronous
scrapers. Install the Zapros and test extras, then enable those tests explicitly:
uv sync --extra zapros --extra dev
$env:ASOF_STORE_RUN_IB_INTEGRATION = "1"
uv run pytest -m integration tests/integration/test_ib_live.py
The PostgreSQL tests use postgresql://louis@fre.local/louis. Install the
PostgreSQL and test extras, then enable them explicitly:
uv sync --extra sql-postgres --extra dev
$env:ASOF_STORE_RUN_POSTGRES_INTEGRATION = "1"
uv run pytest -m integration tests/integration/test_asof_store_postgres.py
Without the corresponding environment variable, live integration tests are skipped and the default test suite makes no live IB or PostgreSQL requests. The live IB tests also exercise the dedicated funds endpoint.
Scraping instruments into an as-of store
Install the scraper and SQL extras, then run the explicit scraper command:
uv sync --extra scraper --extra sql-sqlite
uv run ass scrape-instruments --sql-uri "sqlite:///ib-instruments.db"
Use --sql-uri with --table-name (default ib_instruments) to choose the
destination. Optional repeated --product-type and --product-country
arguments filter the scrape; --new-product accepts all, T, or F.
--sort-field selects the product-page sort field (currency, country,
symbol, or exchange_id; default symbol).
--sort-direction selects asc or desc (default asc).
--start-page-number resumes pagination at a given page and requires exactly
one --product-type; pages before it are not requested. --end-page-number
sets an inclusive last page and also requires exactly one --product-type.
--print-new prints each new instrument as JSON, and --print-changes prints
field-level JSON diffs for changed instruments. Progress is reported after
every page by default; --progress-every changes the number of page reports
between progress messages. Each message includes the product type and
instrument ordinal range, calculated from the page number and page size. The
final summary reports total and disjoint counts for new, changed, and unchanged
instruments with primary keys, plus new and unchanged instruments without
primary keys. Instruments without an IB conid are stored in a second
table, ib_instrument_templates by default, keyed by the complete
Instrument model; choose another table with
--missing-primary-key-table-name.
Use --dry-run to request and report only the filtered instrument summary;
this mode does not require --sql-uri, fetch product pages, or write to a
store.
Scraping funds into an as-of store
IB uses a dedicated funds scanner endpoint and returns a total count with
each page of funds. Scrape and persist those pages with:
uv run ass scrape-funds --sql-uri "sqlite:///ib-funds.db"
The primary table defaults to ib_funds, keyed by each fund's CONID; funds
without a contract ID are stored in ib_fund_templates by default. Use
--table-name and --missing-primary-key-table-name to select different
tables. --product-country can be repeated, and --product-symbol,
--new-product, --page-size, --start-page-number, and --end-page-number
filter or limit the scrape. Progress is reported after each page by default;
--progress-every selects how many pages to skip between reports. New records
and changes can be printed with --print-new and --print-changes.
Scrape and store the exchange catalogue with:
uv run ass scrape-exchanges --sql-uri "sqlite:///ib-exchanges.db"
Exchanges use (id, country_code) as their composite primary key. Exchanges
missing either component are stored in ib_exchange_templates by default;
use --missing-primary-key-table-name to select another table. The exchange
scraper also supports --print-new, --print-changes, and --progress-every.
The Python API provides scrape_and_store_instruments(store, ...) and
async_scrape_and_store_instruments(store, ...). Both accept an instrument
store, plus a missing_primary_key_store of type
AsOfStore[datetime, Instrument, NoneType], and return a ScrapeReport.
Pass start_page_number and end_page_number to resume or limit a
single-product-type scrape.
Use scrape_and_store_exchanges(store, ...) or
async_scrape_and_store_exchanges(store, ...) for exchanges, with an
AsOfStore[datetime, tuple[str, str], Exchange] and a separate
AsOfStore[datetime, Exchange, NoneType] for exchanges missing key components.
Use scrape_and_store_funds(store, ...) or
async_scrape_and_store_funds(store, ...) with an
AsOfStore[datetime, int, Fund] and a separate
AsOfStore[datetime, Fund, NoneType] for funds without a contract ID.
Publishing
Releases published on GitHub are built and published to PyPI by
.github/workflows/publish.yml. Before the first release, configure a PyPI
Trusted Publisher for this GitHub repository with workflow
publish.yml and environment pypi. Create the matching pypi environment
in the repository's GitHub Actions settings.
To publish a new version, update the version in pyproject.toml, push the
change, and publish a GitHub Release for that version. The workflow runs the
test suite before building and publishing the package.
Development
Install the development tools, tests, and optional dependencies with uv:
uv sync --all-packages --all-extras
uv run pytest
Install the Git commit hooks with uv run prek install. The hooks run Ruff
on changed Python files and check project types with ty when Python files
change. Run them manually with uv run prek run --all-files.
Metadata
Release files for asof-store 0.5.0
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