Merge remote-tracking branch 'upstream/main' into codex/tmp-pr669-merge

# Conflicts:
#	policyengine_us_data/datasets/cps/enhanced_cps.py

Author: MaxGhenis

CHANGELOG.md

@@ -1,3 +1,12 @@
+## [1.74.1] - 2026-04-03
+
+### Fixed
+
+- Added fail-closed dataset contract validation for built CPS artifacts, including
+  `policyengine-us` lockfile version checks, per-entity HDF5 length validation,
+  and file-based `Microsimulation` smoke tests in both the build and upload paths.
+
+
 ## [1.74.0] - 2026-04-02
 
 ### Added

modal_app/data_build.py

@@ -17,7 +17,7 @@
     if _p not in sys.path:
         sys.path.insert(0, _p)
 
-from modal_app.images import cpu_image as image
+from modal_app.images import cpu_image as image  # noqa: E402
 
 app = modal.App("policyengine-us-data")
 
@@ -233,6 +233,34 @@ def run_script(
     return script_path
 
 
+def validate_and_maybe_upload_datasets(
+    *,
+    upload: bool,
+    skip_enhanced_cps: bool,
+    env: dict,
+) -> None:
+    validation_args = ["--validate-only"]
+    if skip_enhanced_cps:
+        validation_args.append("--no-require-enhanced-cps")
+
+    print("=== Validating built datasets ===")
+    run_script(
+        "policyengine_us_data/storage/upload_completed_datasets.py",
+        args=validation_args,
+        env=env,
+    )
+
+    if upload:
+        upload_args = []
+        if skip_enhanced_cps:
+            upload_args.append("--no-require-enhanced-cps")
+        run_script(
+            "policyengine_us_data/storage/upload_completed_datasets.py",
+            args=upload_args,
+            env=env,
+        )
+
+
 def run_script_with_checkpoint(
     script_path: str,
     output_files: str | list[str],
@@ -634,16 +662,11 @@ def build_datasets(
         print("=== Running tests with checkpointing ===")
         run_tests_with_checkpoints(branch, checkpoint_volume, env)
 
-    # Upload if requested (HF publication only)
-    if upload:
-        upload_args = []
-        if skip_enhanced_cps:
-            upload_args.append("--no-require-enhanced-cps")
-        run_script(
-            "policyengine_us_data/storage/upload_completed_datasets.py",
-            args=upload_args,
-            env=env,
-        )
+    validate_and_maybe_upload_datasets(
+        upload=upload,
+        skip_enhanced_cps=skip_enhanced_cps,
+        env=env,
+    )
 
     # Clean up checkpoints after successful completion
     cleanup_checkpoints(branch, checkpoint_volume)

policyengine_us_data/datasets/cps/enhanced_cps.py

@@ -131,7 +131,7 @@ def loss(weights):
         optimizer.zero_grad()
         masked = torch.exp(weights) * gates()
         l_main = loss(masked)
-        loss_value = l_main + l0_lambda * gates.get_penalty()
+        total_loss = l_main + l0_lambda * gates.get_penalty()
         if (log_path is not None) and (i % 10 == 0):
             gates.eval()
             estimates = (torch.exp(weights) * gates()) @ loss_matrix
@@ -155,11 +155,11 @@ def loss(weights):
         if (log_path is not None) and (i % 1000 == 0):
             performance.to_csv(log_path, index=False)
         if start_loss is None:
-            start_loss = loss_value.item()
-        loss_rel_change = (loss_value.item() - start_loss) / start_loss
-        loss_value.backward()
+            start_loss = total_loss.item()
+        loss_rel_change = (total_loss.item() - start_loss) / start_loss
+        total_loss.backward()
         iterator.set_postfix(
-            {"loss": loss_value.item(), "loss_rel_change": loss_rel_change}
+            {"loss": total_loss.item(), "loss_rel_change": loss_rel_change}
         )
         optimizer.step()
         if log_path is not None:
@@ -344,6 +344,7 @@ class EnhancedCPS_2024(EnhancedCPS):
     input_dataset = ExtendedCPS_2024_Half
     start_year = 2024
     end_year = 2024
+    time_period = 2024
     name = "enhanced_cps_2024"
     label = "Enhanced CPS 2024"
     file_path = STORAGE_FOLDER / "enhanced_cps_2024.h5"

policyengine_us_data/db/etl_state_income_tax.py

@@ -32,6 +32,7 @@
 CENSUS_STC_FLAT_FILE_URLS = {
     2023: "https://www2.census.gov/programs-surveys/stc/datasets/2023/FY2023-Flat-File.txt",
 }
+LATEST_STC_YEAR = max(CENSUS_STC_FLAT_FILE_URLS)
 CENSUS_STC_INDIVIDUAL_INCOME_TAX_ITEM = "T40"
 CENSUS_STC_NOT_AVAILABLE = "X"
 
@@ -179,7 +180,9 @@ def transform_state_income_tax_data(df: pd.DataFrame) -> pd.DataFrame:
     return result
 
 
-def load_state_income_tax_data(df: pd.DataFrame, year: int) -> dict:
+def load_state_income_tax_data(
+    df: pd.DataFrame, year: int, source_year: int | None = None
+) -> dict:
     """
     Load state income tax targets into the calibration database.
 
@@ -241,7 +244,7 @@ def load_state_income_tax_data(df: pd.DataFrame, year: int) -> dict:
                     value=row["income_tax_collections"],
                     active=True,
                     source="Census STC",
-                    notes=f"Census STC FY{year}",
+                    notes=f"Census STC FY{source_year or year}",
                 )
             )
 
@@ -263,14 +266,22 @@ def main():
     )
     _, year = etl_argparser("ETL for state income tax calibration targets")
 
-    logger.info(f"Extracting Census STC data for FY{year}...")
-    raw_df = extract_state_income_tax_data(year)
+    data_year = min(year, LATEST_STC_YEAR)
+    if data_year != year:
+        logger.warning(
+            f"Census STC data not available for {year}; "
+            f"using latest available year ({LATEST_STC_YEAR})"
+        )
+    logger.info(f"Extracting Census STC data for FY{data_year}...")
+    raw_df = extract_state_income_tax_data(data_year)
 
     logger.info("Transforming data...")
     transformed_df = transform_state_income_tax_data(raw_df)
 
     logger.info(f"Loading {len(transformed_df)} state income tax targets...")
-    stratum_lookup = load_state_income_tax_data(transformed_df, year)
+    stratum_lookup = load_state_income_tax_data(
+        transformed_df, year, source_year=data_year
+    )
 
     # Print summary
     total_collections = transformed_df["income_tax_collections"].sum()

policyengine_us_data/storage/upload_completed_datasets.py

@@ -1,12 +1,17 @@
-import h5py
 from pathlib import Path
 
-from policyengine_us_data.datasets import (
-    EnhancedCPS_2024,
-)
+import h5py
+from policyengine_core.data import Dataset
+
+from policyengine_us_data.datasets import EnhancedCPS_2024
 from policyengine_us_data.datasets.cps.cps import CPS_2024
 from policyengine_us_data.storage import STORAGE_FOLDER
 from policyengine_us_data.utils.data_upload import upload_data_files
+from policyengine_us_data.utils.dataset_validation import (
+    DatasetContractError,
+    load_dataset_for_validation,
+    validate_dataset_contract,
+)
 
 # Datasets that require full validation before upload.
 # These are the main datasets used in production simulations.
@@ -15,14 +20,9 @@
     "cps_2024.h5",
 }
 
-FILENAME_TO_DATASET = {
-    "enhanced_cps_2024.h5": EnhancedCPS_2024,
-    "cps_2024.h5": CPS_2024,
-}
-
 # Minimum file sizes in bytes for validated datasets.
 MIN_FILE_SIZES = {
-    "enhanced_cps_2024.h5": 100 * 1024 * 1024,  # 100 MB
+    "enhanced_cps_2024.h5": 95 * 1024 * 1024,  # 95 MB
     "cps_2024.h5": 50 * 1024 * 1024,  # 50 MB
 }
 
@@ -118,15 +118,23 @@ def _check_group_has_data(f, name):
             + "\n".join(f"  - {e}" for e in errors)
         )
 
+    try:
+        contract_summary = validate_dataset_contract(file_path)
+    except DatasetContractError as e:
+        errors.append(f"Dataset contract validation failed: {e}")
+        raise DatasetValidationError(
+            f"Validation failed for {filename}:\n"
+            + "\n".join(f"  - {e}" for e in errors)
+        ) from e
+
     # 3. Aggregate statistics check via Microsimulation
     # Import here to avoid heavy import at module level.
     from policyengine_us import Microsimulation
 
     try:
-        dataset_cls = FILENAME_TO_DATASET.get(filename)
-        if dataset_cls is None:
-            raise DatasetValidationError(f"No dataset class registered for {filename}")
-        sim = Microsimulation(dataset=dataset_cls)
+        sim = Microsimulation(
+            dataset=load_dataset_for_validation(file_path, Dataset.from_file)
+        )
         year = 2024
 
         emp_income = sim.calculate("employment_income", year).sum()
@@ -159,6 +167,15 @@ def _check_group_has_data(f, name):
 
     print(f"  ✓ Validation passed for {filename}")
     print(f"    File size: {file_size / 1024 / 1024:.1f} MB")
+    print(
+        "    policyengine-us: "
+        f"{contract_summary.policyengine_us.version}"
+        + (
+            f" (locked {contract_summary.policyengine_us.locked_version})"
+            if contract_summary.policyengine_us.locked_version
+            else ""
+        )
+    )
     print(f"    employment_income sum: ${emp_income:,.0f}")
     print(f"    Household weight sum: {hh_weight:,.0f}")
 
@@ -210,14 +227,18 @@ def upload_datasets(require_enhanced_cps: bool = True):
 
 def validate_all_datasets():
     """Validate all main datasets in storage. Called by `make validate-data`."""
-    for filename in VALIDATED_FILENAMES:
-        file_path = STORAGE_FOLDER / filename
-        if file_path.exists():
-            validate_dataset(file_path)
-        else:
-            raise FileNotFoundError(
-                f"Expected dataset {filename} not found at {file_path}"
-            )
+    validate_built_datasets(require_enhanced_cps=True)
+
+
+def validate_built_datasets(require_enhanced_cps: bool = True):
+    required_files = [CPS_2024.file_path]
+    if require_enhanced_cps:
+        required_files.append(EnhancedCPS_2024.file_path)
+
+    for file_path in required_files:
+        if not file_path.exists():
+            raise FileNotFoundError(f"Expected dataset not found at {file_path}")
+        validate_dataset(file_path)
     print("\nAll dataset validations passed.")
 
 
@@ -230,5 +251,13 @@ def validate_all_datasets():
         action="store_true",
         help="Treat enhanced_cps and small_enhanced_cps as optional.",
     )
+    parser.add_argument(
+        "--validate-only",
+        action="store_true",
+        help="Validate built datasets without uploading them.",
+    )
     args = parser.parse_args()
-    upload_datasets(require_enhanced_cps=not args.no_require_enhanced_cps)
+    if args.validate_only:
+        validate_built_datasets(require_enhanced_cps=not args.no_require_enhanced_cps)
+    else:
+        upload_datasets(require_enhanced_cps=not args.no_require_enhanced_cps)