"""What the derived tables must say about a company that changed business.""" from __future__ import annotations from datetime import date import polars as pl from recipe.build import ( build_by_ticker, build_classification, build_spans, build_taxonomy_table, entity_fallback, ) from recipe.schema import CONFIG_SCHEMAS def test_spans_are_runs_not_groups(observations): spans = build_spans(observations) first = spans.filter(pl.col("cik") == "0000000001").sort("valid_from") assert first["sic"].to_list() == ["6770", "3711"] assert first["valid_from"].to_list() == [date(2020, 3, 2), date(2021, 5, 2)] # valid_to is the last filing that said so, not the day before the next. assert first["valid_to"].to_list() == [date(2020, 8, 2), date(2024, 5, 2)] assert first["observations"].to_list() == [2, 2] def test_a_company_reclassified_back_keeps_both_spans(): """A groupby on (filer, code) would merge these and lose the order.""" rows = [ {"cik": "1", "sic": "6770", "stated_on": date(2020, 1, 1), "knowledge_time": None, "source": "xbrl", "source_ref": "a", "is_dated": True, "inserted_at": None}, {"cik": "1", "sic": "3711", "stated_on": date(2021, 1, 1), "knowledge_time": None, "source": "xbrl", "source_ref": "b", "is_dated": True, "inserted_at": None}, {"cik": "1", "sic": "6770", "stated_on": date(2022, 1, 1), "knowledge_time": None, "source": "xbrl", "source_ref": "c", "is_dated": True, "inserted_at": None}, ] spans = build_spans(pl.DataFrame(rows)).sort("valid_from") assert spans.height == 3 assert spans["rank_for_filer"].to_list() == [3, 2, 1] assert spans["is_latest"].to_list() == [False, False, True] def test_the_latest_span_is_the_one_marked(observations): spans = build_spans(observations) latest = spans.filter(pl.col("is_latest")).sort("cik") assert latest["cik"].to_list() == ["0000000001", "0000000002", "0000000003"] assert latest["sic"].to_list() == ["3711", "2834", "6022"] def test_classification_is_one_row_per_filer(observations, directory): spans = build_spans(observations) reference = pl.DataFrame({ "sic": ["3711", "2834", "6022"], "title": ["MOTOR VEHICLES", "PHARMACEUTICAL PREPARATIONS", "STATE COMMERCIAL BANKS"], "sic_level": ["industry"] * 3, "sec_office": [None] * 3, "division": ["D", "D", "H"], "division_title": ["Manufacturing"] * 2 + ["Finance"], "major_group": ["37", "28", "60"], "major_group_title": [None] * 3, "industry_group": ["371", "283", "602"], "sector_code": ["CONC", "HLTH", "FINS"], "sector": ["Consumer Cyclical", "Health Care", "Financials"], "industry_code": ["CONC_AUTO", "HLTH_PHARMA", "FINS_BANK"], "industry": ["Automobiles", "Pharmaceuticals", "Banks"], "naics_1997": [None] * 3, "naics_title": [None] * 3, "naics_sector": [None] * 3, "naics_sector_title": [None] * 3, "naics_candidates": [0, 0, 0], }) frame = build_classification(spans, directory, reference, entity_fallback(pl.DataFrame())) assert frame.height == frame["cik"].n_unique() == 3 car = frame.filter(pl.col("cik") == "0000000001").row(0, named=True) assert (car["sector_code"], car["sic"]) == ("CONC", "3711") assert car["is_dated"] is True bank = frame.filter(pl.col("cik") == "0000000003").row(0, named=True) # Its only code came from today's snapshot, so it carries no history. assert bank["is_dated"] is False def test_by_ticker_clips_to_the_overlap(observations, tickers, directory): spans = build_spans(observations) frame = build_by_ticker(tickers, spans, directory) spac = frame.filter(pl.col("ticker") == "SPAC").row(0, named=True) assert spac["sector_code"] == "SHEL" assert spac["valid_to"] == date(2020, 8, 2) # the SIC span ends first assert spac["date_basis"] == "dated" carz = frame.filter(pl.col("ticker") == "CARZ").row(0, named=True) assert (carz["sector_code"], carz["is_current"]) == ("CONC", True) def test_a_ticker_that_predates_the_evidence_still_gets_a_row(tickers, observations, directory): """Delisted in 2007, so no filing overlaps; dropping it would leave the universe made of survivors.""" frame = build_by_ticker(tickers, build_spans(observations), directory) gone = frame.filter(pl.col("ticker") == "GONE").row(0, named=True) assert gone["date_basis"] == "undated" assert gone["sector_code"] == "FINS" assert (gone["valid_from"], gone["valid_to"]) == (date(2006, 4, 1), date(2007, 9, 1)) def test_a_ticker_with_no_code_at_all_is_present_and_unclassified( tickers, observations, directory ): frame = build_by_ticker(tickers, build_spans(observations), directory) huh = frame.filter(pl.col("ticker") == "HUH").row(0, named=True) assert (huh["date_basis"], huh["sector_code"], huh["sic"]) == ("unknown", "UNCL", None) def test_is_current_marks_exactly_one_row_per_live_ticker(tickers, observations, directory): """A live ticker whose company was reclassified must not come back current under both its old sector and its new one.""" frame = build_by_ticker(tickers, build_spans(observations), directory) current = frame.filter(pl.col("is_current")) assert current.height == current["ticker"].n_unique() assert set(current["ticker"]) == {"CARZ", "PILL"} def test_taxonomy_table_lists_every_industry(): frame = build_taxonomy_table() assert set(frame.columns) <= set(CONFIG_SCHEMAS["taxonomy"]) assert frame["industry_code"].n_unique() == frame.height assert frame.filter(pl.col("industry_code") == "HLTH_PHARMA")["sic_ranges"].item() def test_a_filer_known_only_by_its_forms_still_gets_classified( observations, tickers, directory ): """A closed-end fund has no industry code and never will. Saying "fund" beats a null, which reads the same as a failure.""" kinds = pl.DataFrame({ "cik": ["0000000004"], "entity_kind": ["investment_company"], "source_ref": ["CIK0000000004.json"], }) fallback = entity_fallback(kinds) assert fallback.row(0, named=True)["sector_code"] == "FUND" frame = build_by_ticker(tickers, build_spans(observations), directory, fallback) huh = frame.filter(pl.col("ticker") == "HUH").row(0, named=True) assert (huh["sector_code"], huh["industry_code"]) == ("FUND", "FUND_INVEST") assert huh["date_basis"] == "unknown" # still no date behind it assert huh["sic"] is None # and no code was invented for it def test_the_fallback_never_overrides_an_assigned_code(observations, tickers, directory): kinds = pl.DataFrame({ "cik": ["0000000002"], "entity_kind": ["investment_company"], "source_ref": ["x"], }) frame = build_by_ticker( tickers, build_spans(observations), directory, entity_fallback(kinds) ) pill = frame.filter(pl.col("ticker") == "PILL").row(0, named=True) assert pill["sector_code"] == "HLTH"