Format SOI target refresh changes

Author: MaxGhenis

policyengine_us_data/db/etl_national_targets.py

@@ -251,15 +251,15 @@ def extract_national_targets(dataset: str = DEFAULT_DATASET):
         # Retirement contribution targets — see issue #553
         {
             "variable": "traditional_ira_contributions",
-            "value": RETIREMENT_CONTRIBUTION_TARGETS[
-                "traditional_ira_contributions"
-            ]["value"],
-            "source": RETIREMENT_CONTRIBUTION_TARGETS[
-                "traditional_ira_contributions"
-            ]["source"],
-            "notes": RETIREMENT_CONTRIBUTION_TARGETS[
-                "traditional_ira_contributions"
-            ]["notes"],
+            "value": RETIREMENT_CONTRIBUTION_TARGETS["traditional_ira_contributions"][
+                "value"
+            ],
+            "source": RETIREMENT_CONTRIBUTION_TARGETS["traditional_ira_contributions"][
+                "source"
+            ],
+            "notes": RETIREMENT_CONTRIBUTION_TARGETS["traditional_ira_contributions"][
+                "notes"
+            ],
             "year": HARDCODED_YEAR,
         },
         {
@@ -291,15 +291,11 @@ def extract_national_targets(dataset: str = DEFAULT_DATASET):
         },
         {
             "variable": "roth_ira_contributions",
-            "value": RETIREMENT_CONTRIBUTION_TARGETS["roth_ira_contributions"][
-                "value"
-            ],
+            "value": RETIREMENT_CONTRIBUTION_TARGETS["roth_ira_contributions"]["value"],
             "source": RETIREMENT_CONTRIBUTION_TARGETS["roth_ira_contributions"][
                 "source"
             ],
-            "notes": RETIREMENT_CONTRIBUTION_TARGETS["roth_ira_contributions"][
-                "notes"
-            ],
+            "notes": RETIREMENT_CONTRIBUTION_TARGETS["roth_ira_contributions"]["notes"],
             "year": HARDCODED_YEAR,
         },
     ]

policyengine_us_data/storage/calibration_targets/refresh_soi_table_targets.py

@@ -259,7 +259,10 @@ def build_target_year_rows(
         refreshed["Year"] = target_year
 
         semantic_columns = _semantic_columns(refreshed)
-        if refreshed["SOI table"] in {"Table 1.4", "Table 2.1"} and semantic_columns is None:
+        if (
+            refreshed["SOI table"] in {"Table 1.4", "Table 2.1"}
+            and semantic_columns is None
+        ):
             skipped_rows.append((refreshed["SOI table"], refreshed["Variable"]))
             continue
 
@@ -283,7 +286,9 @@ def build_target_year_rows(
         refreshed_rows.append(refreshed)
 
     if skipped_rows:
-        skipped = ", ".join(sorted({f"{table}/{variable}" for table, variable in skipped_rows}))
+        skipped = ", ".join(
+            sorted({f"{table}/{variable}" for table, variable in skipped_rows})
+        )
         print(f"Skipped unsupported SOI rows for {target_year}: {skipped}")
 
     return pd.DataFrame(refreshed_rows, columns=all_targets.columns)

policyengine_us_data/utils/loss.py

@@ -98,9 +98,9 @@
     # (TY 2022, latest published). Total Roth IRA contributions =
     # $34.95B (10.04M contributors). Direct administrative source.
     # https://www.irs.gov/statistics/soi-tax-stats-accumulation-and-distribution-of-individual-retirement-arrangements
-    "roth_ira_contributions": RETIREMENT_CONTRIBUTION_TARGETS[
-        "roth_ira_contributions"
-    ]["value"],
+    "roth_ira_contributions": RETIREMENT_CONTRIBUTION_TARGETS["roth_ira_contributions"][
+        "value"
+    ],
 }
 
 

policyengine_us_data/utils/soi.py

@@ -248,24 +248,26 @@ def get_soi(year: int) -> pd.DataFrame:
     latest_uprating_year = int(uprating_years.max())
 
     uprating_factors = {}
-    for variable, source_year in soi[["Variable", "Year"]].drop_duplicates().itertuples(
-        index=False
+    for variable, source_year in (
+        soi[["Variable", "Year"]].drop_duplicates().itertuples(index=False)
     ):
         source_year_for_uprating = min(
             max(int(source_year), earliest_uprating_year),
             latest_uprating_year,
         )
-        target_year_for_uprating = min(max(int(year), earliest_uprating_year), latest_uprating_year)
+        target_year_for_uprating = min(
+            max(int(year), earliest_uprating_year), latest_uprating_year
+        )
         pe_name = SOI_UPRATING_MAP.get(variable)
         if pe_name in uprating.index:
-            uprating_factors[variable] = uprating.loc[
-                pe_name, target_year_for_uprating
-            ] / uprating.loc[pe_name, source_year_for_uprating]
+            uprating_factors[variable] = (
+                uprating.loc[pe_name, target_year_for_uprating]
+                / uprating.loc[pe_name, source_year_for_uprating]
+            )
         else:
-            uprating_factors[variable] = uprating.loc[
-                "employment_income", target_year_for_uprating
-            ] / (
-                uprating.loc["employment_income", source_year_for_uprating]
+            uprating_factors[variable] = (
+                uprating.loc["employment_income", target_year_for_uprating]
+                / (uprating.loc["employment_income", source_year_for_uprating])
             )
 
     for variable, uprating_factor in uprating_factors.items():

tests/test_soi_utils.py

@@ -116,9 +116,7 @@ def test_get_soi_uses_best_available_year_per_variable(monkeypatch):
         index=["interest_deduction", "taxable_interest_income"],
     )
 
-    monkeypatch.setattr(
-        soi_module, "load_tracked_soi_targets", lambda: fake_soi.copy()
-    )
+    monkeypatch.setattr(soi_module, "load_tracked_soi_targets", lambda: fake_soi.copy())
     monkeypatch.setattr(
         soi_module,
         "create_policyengine_uprating_factors_table",
@@ -176,16 +174,10 @@ def test_get_tracked_soi_row_selects_requested_best_year(monkeypatch):
             },
         ]
     )
-    monkeypatch.setattr(
-        soi_module, "load_tracked_soi_targets", lambda: fake_soi.copy()
-    )
+    monkeypatch.setattr(soi_module, "load_tracked_soi_targets", lambda: fake_soi.copy())
 
-    row_2022 = soi_module.get_tracked_soi_row(
-        "business_net_profits", 2022, count=False
-    )
-    row_2024 = soi_module.get_tracked_soi_row(
-        "business_net_profits", 2024, count=False
-    )
+    row_2022 = soi_module.get_tracked_soi_row("business_net_profits", 2022, count=False)
+    row_2024 = soi_module.get_tracked_soi_row("business_net_profits", 2024, count=False)
 
     assert row_2022["Year"] == 2021
     assert row_2024["Year"] == 2023
@@ -225,9 +217,7 @@ def test_get_national_soi_aggregate_rows_filters_to_all_returns(monkeypatch):
             },
         ]
     )
-    monkeypatch.setattr(
-        soi_module, "load_tracked_soi_targets", lambda: fake_soi.copy()
-    )
+    monkeypatch.setattr(soi_module, "load_tracked_soi_targets", lambda: fake_soi.copy())
 
     result = soi_module.get_national_soi_aggregate_rows(2024)