remove most recent year import

setup.py

@@ -34,7 +34,6 @@
         "pytest",
         "pytest-mock",
         "hypothesis",
-        "vivarium-gbd-access",
     ]
 
     doc_requirements = [

src/vivarium_inputs/core.py

@@ -5,7 +5,6 @@
 import pandas as pd
 from gbd_mapping import Cause, Covariate, Etiology, RiskFactor, Sequela, causes
 from loguru import logger
-from vivarium_gbd_access.constants import MOST_RECENT_YEAR
 
 from vivarium_inputs import extract, utilities, utility_data
 from vivarium_inputs.globals import (
@@ -163,7 +162,8 @@ def get_disability_weight(
     if entity.kind == "cause":
         data = utility_data.get_demographic_dimensions(location_id, draws=True, value=0.0)
         if not get_all_years:
-            data = data.query("year_id==@MOST_RECENT_YEAR")
+            most_recent_year = utility_data.get_most_recent_year()
+            data = data.query("year_id==@most_recent_year")
         data = data.set_index(
             utilities.get_ordered_index_cols(data.columns.difference(DRAW_COLUMNS))
         )
@@ -198,7 +198,7 @@ def get_disability_weight(
             )
             # add year id with single year so normalization doesn't fill in all years
             if not get_all_years:
-                data["year_id"] = MOST_RECENT_YEAR
+                data["year_id"] = utility_data.get_most_recent_year()
             data = utilities.normalize(data)
 
             cause = [c for c in causes if c.sequelae and entity in c.sequelae][0]

src/vivarium_inputs/utility_data.py

@@ -11,6 +11,10 @@ def get_estimation_years(*_, **__) -> pd.Series:
     return data
 
 
+def get_most_recent_year() -> int:
+    return get_estimation_years().max()
+
+
 def get_year_block(*_, **__) -> pd.DataFrame:
     estimation_years = get_estimation_years()
     year_block = pd.DataFrame(

src/vivarium_inputs/validation/sim.py

@@ -11,7 +11,6 @@
     Sequela,
     causes,
 )
-from vivarium_gbd_access.constants import MOST_RECENT_YEAR
 
 from vivarium_inputs import utilities, utility_data
 from vivarium_inputs.globals import (
@@ -148,8 +147,9 @@ def validate_for_simulation(
     if measure not in validators:
         raise NotImplementedError()
 
+    most_recent_year = utility_data.get_most_recent_year()
     context_args["years"] = pd.DataFrame(
-        {"year_start": MOST_RECENT_YEAR, "year_end": MOST_RECENT_YEAR + 1}, index=[0]
+        {"year_start": most_recent_year, "year_end": most_recent_year + 1}, index=[0]
     )
     context = SimulationValidationContext(location, **context_args)
     validators[measure](data, entity, context)