Oh My Data (OMD)

ohmydata is a provisional, offline-first market-data SDK. Tushare endpoint adapters accept an already initialized official-compatible client; credentials are never loaded by this library.

Supported Python and installation

Python 3.11 and 3.12 are supported (>=3.11,<3.13). From a source checkout:

uv sync
uv run python -c "import ohmydata; print(ohmydata.__version__)"

The core has no runtime dependencies. Install ohmydata[tushare] for the Pandas-backed adapter. Provider tests use fake clients and never call a network.

The optional ohmydata[polars] extra provides explicit, eager representation adapters:

from ohmydata.adapters.polars import pandas_to_polars, polars_to_pandas

polars_frame = pandas_to_polars(pandas_frame)
# For validated empty/all-null Pandas object columns, opt into String:
polars_frame = pandas_to_polars(pandas_frame, empty_object_policy="string")
pandas_frame = polars_to_pandas(polars_frame)

Conversions preserve columns and row order, provider-native values, nulls, NaN/infinities, and supported temporal timezones. They do not parse dates, rename or sort columns, scale units, deduplicate, impute, or apply consumer schemas. Unsupported or potentially lossy dtypes fail with SchemaMismatchError; the adapter never contacts a provider or reads credentials. The default empty_object_policy="error" rejects ambiguous empty object columns; the explicit "string" policy casts only empty/all-null object columns to nullable Pandas strings before conversion and never changes populated object columns or imputes missing values.

Phase 2 Tushare adapter (offline and injected)

Pass an already initialized official-client-compatible object. The adapter does not create clients or read credentials; this fake-client example is safe to run offline:

import pandas as pd
from ohmydata.providers.tushare import EmptyPolicy, FundDailyRequest, TushareClient


class FakeClient:
    def fund_daily(self, **kwargs):
        return pd.DataFrame(
            {
                "ts_code": ["FAKE.ETF"],
                "trade_date": ["20240102"],
                "open": [1.0],
                "high": [1.1],
                "low": [0.9],
                "close": [1.05],
                "pre_close": [1.0],
                "change": [0.05],
                "pct_chg": [5.0],
                "vol": [100],
                "amount": [250.0],
            }
        )


request = FundDailyRequest(
    empty_policy=EmptyPolicy.ERROR, ts_code="FAKE.ETF", start_date="20240101", end_date="20240102"
)
result = TushareClient(FakeClient()).fetch_fund_daily(request)

The typed etf_basic endpoint preserves Tushare's provider-native metadata and requires an explicit empty policy. Its official filters are ts_code, index_code, list_date, list_status, exchange, and mgr; market is forwarded only as a compatibility filter for callers that already use it.

from ohmydata.providers.tushare import EtfBasicRequest

request = EtfBasicRequest(empty_policy=EmptyPolicy.ERROR, market="E", list_status="L")
result = TushareClient(FakeClient()).fetch_etf_basic(request)

Typed stock dividend events are available through StockDividendRequest and fetch_stock_dividend. Select at least one of ts_code, ann_date, record_date, ex_date, or imp_ann_date; selectors may be combined. The response preserves provider-native dates, process states, values, units, nulls, and revision or duplicate rows, and does not infer point-in-time availability.

Values and nulls retain Tushare's native semantics: fund daily OHLC and change/pct_chg are provider values, vol is in hands, and amount is in thousand yuan. Empty responses must be selected explicitly with EmptyPolicy.ALLOW or EmptyPolicy.ERROR. fund_share.fd_share remains provider-native in ten-thousand shares (万份); fund_adj and fund_nav values are likewise preserved without adjustment or imputation. FundNavRequest and FundShareRequest validate real calendar dates and reject provider rows outside the requested symbol/date scope. NAV revisions (including exact duplicates) remain intact; a 2,000-row fund_share response is rejected as an ambiguous provider cap. Announcement and trade dates are date-only evidence and do not prove an intraday availability timestamp.

Adjusted ETF bars recipe

fetch_adjusted_etf_bars composes fund_daily with provider-native fund_adj factors. Choose AdjustmentCoveragePolicy.STRICT (the default) or PRESERVE_MISSING_FACTOR; raw OHLC and adj_factor remain available beside the explicitly derived adjusted OHLC columns. The recipe is offline-testable when supplied an injected TushareClient and does not claim point-in-time availability. Tushare adjustment responses may contain extra dates for the requested symbol; the recipe ignores those factor-only dates while strict coverage still requires a finite factor for every returned daily bar. Rows for foreign symbols fail.

from ohmydata.providers.tushare import (
    AdjustmentCoveragePolicy,
    AdjustedEtfBarsRequest,
    EmptyPolicy,
)

request = AdjustedEtfBarsRequest(
    "FAKE.ETF",
    EmptyPolicy.ERROR,
    AdjustmentCoveragePolicy.STRICT,
    start_date="20240101",
    end_date="20240131",
)

Offline weighted dividend yield recipes

build_portfolio_dividend_yield and build_index_dividend_yield calculate a provider-semantic weighted yield from already-downloaded Pandas frames. Portfolio mkv is yuan; index weight and daily_basic.dv_ttm are provider percentages. The returned dividend_yield is a decimal ratio (sum((w_i / W) * dv_ttm_i) / 100), where W is the provider-native total weight. Choose DividendYieldCoveragePolicy.REQUIRE_COMPLETE to reject missing finite yield coverage, PRESERVE_INCOMPLETE to return None, or the explicitly named NORMALIZE_SUPPORTED policy to divide only by finite supported weight while still reporting the original finite_weight_coverage. Callers own any minimum coverage threshold and must not present a normalized partial estimate as full coverage. Zero supported coverage remains unknown. Inputs are not modified, and dates are identity checks only: the recipe does not infer point-in-time availability or report selection.

from ohmydata.providers.tushare import (
    DividendYieldCoveragePolicy,
    build_index_dividend_yield,
)

result = build_index_dividend_yield(
    index_weights_df,
    daily_basic_df,
    DividendYieldCoveragePolicy.REQUIRE_COMPLETE,
)
print(result.dividend_yield)

The typed IndexWeightRequest accepts either one exact observation date or a complete inclusive range within one calendar month. Responses are checked for the requested index and date scope and sorted by index, observation date, and constituent. weight remains the provider-native percentage, including null or non-finite values; no effective period, availability timestamp, or weight renormalization is inferred.

Local checks

uv lock
uv run pytest
uv run ruff check .
uv run ruff format --check .
uv run pyright
uv build
git diff --check

Behavioral evidence for the initial consumers is in docs/behavioral-inventory.md. The adjusted ETF characterization is test-only and uses synthetic JSON fixtures. The public-contract changes and consumer-owned migration boundaries in v0.1.0 are summarized in docs/v0.1.0-migration.md.

Phase 1 core is offline and explicit:

Availability evidence is represented by the dataframe-free AvailabilityEvidence value object. Source-declared timestamps are the only evidence marked pit_proven; inferred schedules, date-only declarations, and provider-first-observed fallbacks remain conservative. Snapshot construction uses validated observation receipts and normalizes datetimes to UTC.

from datetime import UTC, datetime
from pathlib import Path
from ohmydata.core import RequestSpec, RetryPolicy, RateLimitPolicy, RateLimiter, execute_with_retry
from ohmydata.core import SnapshotMode, SnapshotStore

try:
    RequestSpec("demo", "bars", {"api_token": "never-serialize"})
except ValueError:
    pass
limiter = RateLimiter(RateLimitPolicy(0.1))
limiter.acquire()
result = execute_with_retry(lambda: "ok", RetryPolicy(max_attempts=1))
store = SnapshotStore(Path("snapshots"))
store.write(
    RequestSpec("demo", "bars", {}), b"[]", datetime.now(UTC), "json-v1", SnapshotMode.APPEND
)
store.write(
    RequestSpec("demo", "bars", {}), b"[]", datetime.now(UTC), "json-v1", SnapshotMode.FROZEN
)

RetryPolicy(max_attempts=3) counts the first call. APPEND preserves distinct observations; FROZEN permits one response identity. SnapshotStore.observe() adds immutable, ordered fetch receipts without changing snapshot bytes; SnapshotRef.fact_version identifies the exact request, payload, and serialization. provider_first_observed_at() reports when OMD first persisted those exact bytes, not provider publication time or consumer usability. Limiter state is per instance.

Raw provider rows can be wrapped in RawFactEnvelope, preserving the response-level fact_version separately from a canonical row hash. Revision status remains conservative until an explicit same-key prior row is supplied; point-in-time and date-only availability quality flags are serialized too. The offline characterization matrix in tests/characterization/test_pit_fail_closed.py also proves that late arrivals, date-only evidence, replay mismatches, pagination truncation, and historical-vintage claims remain fail-closed. OMD does not choose consumer cutoffs, calendars, dataset commits, or usable sessions.

Phase 1 core (offline)

ohmydata.core provides canonical request identities, classified retry with total-attempt semantics, explicit instance-scoped rate limiters, dataframe-free provenance, and immutable APPEND/FROZEN snapshots. Request parameters reject secret-bearing keys before serialization. Snapshot callers provide exact bytes; the core never contacts providers or loads credentials.

Phase 2b Tushare endpoints

The Tushare adapter exposes typed requests for fund dividends, fund portfolios, daily basics, and index weights through injected clients. Requests always send an explicit ordered field list and preserve provider-native values and missing data. fund_portfolio requires a bounded report selector (ann_date, exact period, or a same-year start_date/end_date range); unbounded holdings are rejected. Native units remain unchanged: dividend cash is yuan per share, portfolio market value is yuan and amount is shares, daily-basic share and market-value fields use Tushare's ten-thousand units, and index weights remain provider percentages. daily_basic accepts either a symbol with optional inclusive calendar-date bounds or one exact trade date; responses are scope-checked, stably ordered by symbol/date, and exactly 6000 rows are rejected as an ambiguous provider cap. No availability timestamp or consumer normalization is inferred.

Stock daily and adjustment endpoints

The Tushare adapter also exposes typed, injected-client daily and adj_factor requests:

from ohmydata.providers.tushare import (
    EmptyPolicy,
    StockAdjustmentRequest,
    StockDailyRequest,
    TushareClient,
)

daily = TushareClient(client).fetch_stock_daily(
    StockDailyRequest(empty_policy=EmptyPolicy.ALLOW, ts_code="000001.SZ")
)
adjustment = TushareClient(client).fetch_stock_adjustment(
    StockAdjustmentRequest(empty_policy=EmptyPolicy.ALLOW, trade_date="20240102")
)

Both requests require exactly one symbol (optionally date-bounded) or one exact trade date, and return stable ts_code/trade_date ordering. Fields are explicit and ordered; custom lists must retain both identity fields. Values, units, and nulls remain provider-native: daily pct_chg is a percentage, vol is hands, amount is thousand yuan, and adj_factor is unmodified. Suspended rows are not synthesized, and no adjusted-price calculation or point-in-time availability claim is made.

ETF PCF constituent endpoints (v0.1.1)

EtfShConsRequest and EtfSzConsRequest expose the exchange-native etf_sh_cons and etf_sz_cons schemas. Shanghai uses sca (CNY replacement amount); Shenzhen uses sub_cc and red_cc (CNY subscription/redemption replacement amounts). Quantities are shares and cpr/rdr are percentages. Provider values, nulls, sentinels, and duplicate observations remain unchanged.

Each endpoint rejects an ambiguous exactly-3000-row response. Use fetch_etf_pcf_history with an explicit exchange, date range, and EmptyPolicy to recursively bisect calendar windows without offsets. The recipe reports successful leaf provenances, request and truncation counts, and returns a defensive provider-native Pandas frame. A trade_date is date-only provider evidence; availability timestamps, point-in-time lag, cross-exchange normalization, and published dataset policy remain consumer responsibilities.

The recipe accepts an injected offline-capable client; the library performs no credential or environment lookup:

from ohmydata.providers.tushare import (
    EmptyPolicy,
    EtfPcfHistoryRequest,
    fetch_etf_pcf_history,
)

history = fetch_etf_pcf_history(
    client,
    EtfPcfHistoryRequest(
        ts_code="510050.SH",
        exchange="SH",
        start_date="20240101",
        end_date="20240131",
        empty_policy=EmptyPolicy.ALLOW,
    ),
)
frame = history.frame