pipeline/src/isora_hf/config.py

"""Constants shared by the pipeline: API endpoints, dataflows, rounds, sentinel codes, paths."""

from __future__ import annotations

from dataclasses import dataclass
from pathlib import Path

PROJECT_ROOT = Path(__file__).resolve().parents[2]
RAW_DIR = PROJECT_ROOT / "raw"
RAW_DATA_DIR = RAW_DIR / "data"
RAW_STRUCTURES_DIR = RAW_DIR / "structures"
OUT_DIR = PROJECT_ROOT / "hf_dataset"

SDMX3_BASE = "https://api.imf.org/external/sdmx/3.0"
SDMX21_BASE = "https://api.imf.org/external/sdmx/2.1"
AGENCY = "ISORA"
USER_AGENT = "isora-hf/0.1 (+https://huggingface.co; data pipeline; contact via dataset card)"

ISORA_PORTAL_URL = "https://data.imf.org/en/datasets/ISORA:ISORA_LATEST_DATA_PUB"
TERMS_URL = "https://data.imf.org/en/Datasets/RAFIT-Consolidated/Terms-and-Conditions"
DISCLAIMER_URL = "https://data.imf.org/en/Datasets/RAFIT-Consolidated/Disclaimer"
ABOUT_URL = "https://data.imf.org/en/Datasets/RAFIT-Consolidated/About-RA-FIT"


@dataclass(frozen=True)
class Dataflow:
    """One published ISORA dataflow (a questionnaire generation)."""

    id: str
    version: str
    dsd_version: str
    generation: str  # human-readable questionnaire generation
    fiscal_years: tuple[int, ...]
    geo_dimension: str  # COUNTRY (numeric IMF codes) or JURISDICTION (alpha-3)
    indicator_codelist: str
    form_status_attr: str


DATAFLOWS: tuple[Dataflow, ...] = (
    Dataflow(
        id="ISORA_2016_DATA_PUB",
        version="2.0.0",
        dsd_version="1.0.0",
        generation="ISORA 2016",
        fiscal_years=(2014, 2015),
        geo_dimension="COUNTRY",
        indicator_codelist="CL_INDICATOR",
        form_status_attr="FORM_STATUS",
    ),
    Dataflow(
        id="ISORA_2018_DATA_PUB",
        version="2.0.0",
        dsd_version="2.0.0",
        generation="ISORA 2018",
        fiscal_years=(2016, 2017),
        geo_dimension="JURISDICTION",
        indicator_codelist="CL_ISORA_TAX",
        form_status_attr="FORMSTATUS",
    ),
    Dataflow(
        id="ISORA_LATEST_DATA_PUB",
        version="5.0.0",
        dsd_version="6.0.0",
        generation="ISORA 2020+",
        fiscal_years=(2018, 2019, 2020, 2021, 2022, 2023, 2024),
        geo_dimension="JURISDICTION",
        indicator_codelist="CL_ISORA_TAX",
        form_status_attr="FORMSTATUS",
    ),
)

# Older published versions of the consolidated dataflow, still served by the API.
# They are earlier release vintages of the same FY2018+ series and let us track revisions.
VINTAGES: tuple[tuple[str, str, str], ...] = (
    # (dataflow version, release label, fiscal years covered)
    ("2.0.0", "ISORA 2023 release (FY2018-FY2022)", "2018-2022"),
    ("4.0.0", "ISORA 2024 release (FY2018-FY2023)", "2018-2023"),
    ("5.0.0", "ISORA 2025 release (FY2018-FY2024)", "2018-2024"),
)

# Fiscal year -> survey round in which that fiscal year was first collected.
FISCAL_YEAR_TO_ROUND: dict[int, str] = {
    2014: "ISORA 2016",
    2015: "ISORA 2016",
    2016: "ISORA 2018",
    2017: "ISORA 2018",
    2018: "ISORA 2020",
    2019: "ISORA 2020",
    2020: "ISORA 2021",
    2021: "ISORA 2022",
    2022: "ISORA 2023",
    2023: "ISORA 2024",
    2024: "ISORA 2025",
}

# Published participation counts (About ISORA page + ISORA 2025 news item), for the card.
ROUND_PARTICIPATION: dict[str, int] = {
    "ISORA 2016": 135,
    "ISORA 2018": 159,
    "ISORA 2020": 156,
    "ISORA 2021": 156,
    "ISORA 2022": 165,
    "ISORA 2023": 166,
    "ISORA 2024": 164,
    "ISORA 2025": 166,
}

# Sentinel strings found in the OBSERVATION column.
NOT_AVAILABLE_CODES = frozenset({"D"})
NOT_APPLICABLE_STRINGS = frozenset({"not applicable", "n/a", "na"})
UNRECOGNIZED_CODES = frozenset({"P"})  # ISORA 2016 only; not documented in surviving material

# DissemScale annotation -> normalized indicator type
INDICATOR_TYPE_MAP: dict[str, str] = {
    "binary": "binary",
    "counting": "count",
    "currency": "currency",
    "percent": "percent",
    "nominal": "nominal",
    "ordinal": "ordinal",
    "text": "text",
    "date": "date",
    "na": "unspecified",
    "": "unspecified",
}

# Derived level aggregates in the consolidated dataflow that are published in thousands of local
# currency with SCALE=0 (verified: they equal ~1/1000 of net revenue x cost-of-collection ratio),
# unlike the raw money questions which carry SCALE=3 and are already in base units.
LATEST_THOUSANDS_CODES = frozenset({"337_176", "337_177", "337_178", "337_179"})