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Configuration constants for the SCB-only employment data pipeline.
"""
from typing import Dict, List, Literal, Tuple
# ======================================================
# DATA SOURCES / CONSTANTS
# ======================================================
TAXONOMY: Literal["ssyk2012"] = "ssyk2012"
TRANSLATION_URL: str = (
"https://raw.githubusercontent.com/joseph-data/07_translate_ssyk/main/"
"02_translation_files/ssyk2012_en.xlsx"
)
# SCB table definitions
TABLES: Dict[str, Tuple[str, str, str, str, str]] = {
"14_to_18": ("en", "AM", "AM0208", "AM0208E", "YREG51"),
"19_to_21": ("en", "AM", "AM0208", "AM0208E", "YREG51N"),
"20_to_23": ("en", "AM", "AM0208", "AM0208E", "YREG51BAS"),
}
AGE_EXCLUSIONS: List[str] = ["65-69 years"]
EXCLUDED_CODES: List[str] = ["0002", "0000"]
# ======================================================
# UI DEFAULTS
# ======================================================
# Shiny inputs return strings, so level values are stored as strings ("1".."4").
LEVEL_OPTIONS: List[Tuple[str, str]] = [
("Level 4 (4-digit)", "4"),
("Level 3 (3-digit)", "3"),
("Level 2 (2-digit)", "2"),
("Level 1 (1-digit)", "1"),
]
DEFAULT_LEVEL: str = "3"
GLOBAL_YEAR_MIN: int = 2014
GLOBAL_YEAR_MAX: int = 2023
DEFAULT_YEAR_RANGE: Tuple[int, int] = (GLOBAL_YEAR_MIN, GLOBAL_YEAR_MAX)
AGE_ORDER: List[str] = [
# Controls the subplot ordering in `plot_helper.employment_multi_plot`.
"16-24",
"25-29",
"30-34",
"35-39",
"40-44",
"45-49",
"50-54",
"55-59",
"60-64",
]
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