Update PolicyEngine branding (#6)

Author: MaxGhenis

README.md

@@ -1,6 +1,6 @@
 # Arch
 
-Arch is Cosilico's source-data foundation for social simulation. It captures
+Arch is PolicyEngine's source-data foundation for social simulation. It captures
 source publications, preserves provenance, and represents published values as
 structured, queryable facts.
 
@@ -29,7 +29,7 @@ This repository provides:
   FRS, and related datasets.
 - **Jurisdiction loaders**: US and UK source-specific ETL.
 
-Arch facts are not Cosilico's assertion that a source claim is ultimately true.
+Arch facts are not PolicyEngine's assertion that a source claim is ultimately true.
 They are source-backed claims with provenance.
 
 ## Boundary
@@ -77,9 +77,9 @@ and calibration code belongs under `micro/`.
 ### 1. Install
 
 ```bash
-pip install cosilico-arch
+pip install policyengine-arch-data
 # Or for development:
-git clone https://github.com/CosilicoAI/arch-data arch
+git clone https://github.com/PolicyEngine/arch-data arch
 cd arch
 pip install -e ".[dev]"
 ```
@@ -194,7 +194,7 @@ target_input = as_target(
 
 ## Related Repositories
 
-- [microplex](https://github.com/CosilicoAI/microplex) - Core microsimulation
+- [microplex](https://github.com/PolicyEngine/microplex) - Core microsimulation
   abstractions and calibration interfaces.
-- [microplex-us](https://github.com/CosilicoAI/microplex-us) - US-specific
+- [microplex-us](https://github.com/PolicyEngine/microplex-us) - US-specific
   simulation adapters and calibration profiles.

calibration/variables.py

@@ -1,5 +1,5 @@
 """
-Variable entity resolution using cosilico-engine.
+Variable entity resolution using a RuleSpec engine package when available.
 
 Resolves fully qualified variable references to their entity type
 (person, tax_unit, household, family) by parsing the source .rac file.
@@ -15,19 +15,19 @@
 from pathlib import Path
 from typing import Optional
 
-# Try to import from cosilico-engine
+# Try to import a legacy RuleSpec engine API.
 try:
-    from cosilico.dependency_resolver import PackageRegistry, ModuleResolver
-    from cosilico.dsl_parser import parse_file
-    COSILICO_AVAILABLE = True
+    from policyengine.dependency_resolver import PackageRegistry, ModuleResolver
+    from policyengine.dsl_parser import parse_file
+    POLICYENGINE_AVAILABLE = True
 except ImportError:
-    COSILICO_AVAILABLE = False
+    POLICYENGINE_AVAILABLE = False
 
 
 # Default workspace path (can be overridden)
-DEFAULT_WORKSPACE = Path.home() / "CosilicoAI"
+DEFAULT_WORKSPACE = Path.home() / "PolicyEngine"
 
-# Fallback entity mapping for common variables when cosilico-engine not available
+# Fallback entity mapping for common variables when a RuleSpec engine is not available.
 FALLBACK_ENTITIES = {
     # Person-level
     "age": "person",
@@ -110,7 +110,7 @@ def get_entity(
 
     Args:
         variable_ref: Fully qualified reference like "us:statute/26/32#eitc"
-        workspace: Optional workspace path (defaults to ~/CosilicoAI)
+        workspace: Optional workspace path (defaults to ~/PolicyEngine)
 
     Returns:
         Entity type: "person", "tax_unit", "household", or "family"
@@ -125,8 +125,8 @@ def get_entity(
     """
     package, path, var_name = parse_variable_ref(variable_ref)
 
-    # Try cosilico-engine first
-    if COSILICO_AVAILABLE:
+    # Try the RuleSpec engine first.
+    if POLICYENGINE_AVAILABLE:
         try:
             return _get_entity_from_rac(package, path, var_name, workspace)
         except Exception:
@@ -150,14 +150,14 @@ def _get_entity_from_rac(
     """
     Get entity by parsing the actual .rac file.
 
-    Uses cosilico-engine's PackageRegistry to resolve paths.
+    Uses the legacy RuleSpec engine's PackageRegistry to resolve paths.
     """
     if workspace is None:
         workspace = DEFAULT_WORKSPACE
 
     # Map short package name to repo name
-    # us → cosilico-us, us-ca → cosilico-us-ca, uk → cosilico-uk
-    repo_name = f"cosilico-{package}"
+    # us → policyengine-us, us-ca → policyengine-us-ca, uk → policyengine-uk
+    repo_name = f"policyengine-{package}"
 
     # Get package registry
     registry = PackageRegistry.from_workspace(workspace)

data/targets/README.md

@@ -1,6 +1,6 @@
 # State-Level Calibration Targets
 
-This directory contains state-level calibration targets for use with the Cosilico microsimulation system. Targets are used to calibrate (reweight) microdata samples to match official administrative statistics.
+This directory contains state-level calibration targets for use with the PolicyEngine microsimulation system. Targets are used to calibrate (reweight) microdata samples to match official administrative statistics.
 
 ## Data Files
 
@@ -16,7 +16,7 @@ This directory contains state-level calibration targets for use with the Cosilic
 Run the build script to generate/update all target files:
 
 ```bash
-cd cosilico-data-sources
+cd arch-data
 python data/targets/build_state_targets.py
 ```
 

db/etl_soi.py

@@ -177,7 +177,7 @@ def _table_content(year: int, file_spec_fn, package_dir: str) -> bytes:
     else:
         request = Request(
             spec["source_url"],
-            headers={"User-Agent": "cosilico-arch/0.1", "Accept": "*/*"},
+            headers={"User-Agent": "policyengine-arch-data/0.1", "Accept": "*/*"},
         )
         with urlopen(request, timeout=120) as response:
             content = response.read()

db/source_files.py

@@ -94,7 +94,7 @@ def _fetch_url(url: str) -> tuple[bytes, str | None, str]:
     request = Request(
         url,
         headers={
-            "User-Agent": "cosilico-arch/0.1",
+            "User-Agent": "policyengine-arch-data/0.1",
             "Accept": "*/*",
         },
     )

db/supabase_client.py

@@ -1,7 +1,7 @@
 """
 Supabase client for Arch.
 
-Provides connection to Cosilico Supabase database for:
+Provides connection to PolicyEngine Supabase database for:
 - Source metadata and dataset registries
 - Raw microdata tables (e.g., microdata.us_census_cps_asec_2024_person)
 - Target inputs
@@ -22,9 +22,9 @@
 from supabase import create_client, Client
 
 
-ARCH_SCHEMA = os.environ.get("COSILICO_ARCH_SCHEMA", "arch")
-MICRODATA_SCHEMA = os.environ.get("COSILICO_MICRODATA_SCHEMA", "microdata")
-TARGETS_SCHEMA = os.environ.get("COSILICO_TARGETS_SCHEMA", "targets")
+ARCH_SCHEMA = os.environ.get("POLICYENGINE_ARCH_SCHEMA", "arch")
+MICRODATA_SCHEMA = os.environ.get("POLICYENGINE_MICRODATA_SCHEMA", "microdata")
+TARGETS_SCHEMA = os.environ.get("POLICYENGINE_TARGETS_SCHEMA", "targets")
 
 
 @dataclass
@@ -40,23 +40,23 @@ def from_env(cls) -> "SupabaseConfig":
         Load configuration from environment variables.
 
         Required:
-            COSILICO_SUPABASE_URL: Supabase project URL
-            COSILICO_SUPABASE_SECRET_KEY: Service role key for full access
+            POLICYENGINE_SUPABASE_URL: Supabase project URL
+            POLICYENGINE_SUPABASE_SECRET_KEY: Service role key for full access
 
         Raises:
             ValueError: If required environment variables are missing
         """
-        url = os.environ.get("COSILICO_SUPABASE_URL")
+        url = os.environ.get("POLICYENGINE_SUPABASE_URL")
         if not url:
             raise ValueError(
-                "COSILICO_SUPABASE_URL not set. "
+                "POLICYENGINE_SUPABASE_URL not set. "
                 "Set this to your Supabase project URL."
             )
 
-        secret_key = os.environ.get("COSILICO_SUPABASE_SECRET_KEY")
+        secret_key = os.environ.get("POLICYENGINE_SUPABASE_SECRET_KEY")
         if not secret_key:
             raise ValueError(
-                "COSILICO_SUPABASE_SECRET_KEY not set. "
+                "POLICYENGINE_SUPABASE_SECRET_KEY not set. "
                 "Set this to your service role key."
             )
 

docs/PUF_INTEGRATION.md

@@ -88,15 +88,15 @@ def add_synthetic_high_income(df, pareto_alpha=1.5):
 If IRS PUF license obtained:
 
 ```python
-class CosilicoPUF:
+class PolicyEnginePUF:
     """Load and process IRS PUF."""
 
     def __init__(self, puf_path: str):
         self.raw = pd.read_csv(puf_path)
         self.records = self._build_tax_units()
 
     def _build_tax_units(self):
-        """Map PUF variables to Cosilico schema."""
+        """Map PUF variables to PolicyEngine schema."""
         return pd.DataFrame({
             'weight': self.raw['S006'] / 100,  # PUF weights are x100
             'adjusted_gross_income': self.raw['E00100'],

docs/architecture.md

@@ -2,7 +2,7 @@
 
 ## Overview
 
-Arch is Cosilico's source-data foundation for social simulation. It captures
+Arch is PolicyEngine's source-data foundation for social simulation. It captures
 source publications, preserves provenance, and represents published values as
 structured, queryable facts. Microplex consumes Arch facts to produce final
 calibrated simulation inputs.
@@ -134,7 +134,7 @@ target_input = as_target(
 ```
 
 Projection facts from official sources such as CBO, OBR, and ONS can be loaded
-as source facts directly. Cosilico-owned inflation, aging, projection, or
+as source facts directly. PolicyEngine-owned inflation, aging, projection, or
 cross-source reconciliation assumptions belong in Microplex Targets, not Arch.
 
 ## Calibration Pipeline

docs/cps-variable-coverage.md

@@ -131,9 +131,9 @@ The ETL pipeline (`db/etl_soi.py`) loads IRS SOI targets for calibration:
 python micro/us/census/download_cps.py --year 2024
 ```
 
-### 2. Convert to Cosilico Format
+### 2. Convert to PolicyEngine Format
 ```bash
-python scripts/cps_to_cosilico.py --year 2024 --calibrate --summary
+python scripts/cps_to_policyengine.py --year 2024 --calibrate --summary
 ```
 
 ### 3. Validate Against Targets
@@ -149,8 +149,8 @@ with Session(get_engine()) as session:
 
 ### 4. Run Microsimulation
 ```bash
-# In cosilico-us repository
-python -m cosilico_us.microsim --input cosilico_input_2024.parquet
+# In policyengine-us repository
+python -m policyengine_us.microsim --input policyengine_input_2024.parquet
 ```
 
 ## Data Quality Recommendations
@@ -199,7 +199,7 @@ definition: "What this variable measures"
 maps_to:
   - jurisdiction: us
     statute: "26 USC section"
-    variable: cosilico_variable_name
+    variable: policyengine_variable_name
     coverage: full | partial
     notes: "Mapping notes"
 
@@ -244,7 +244,7 @@ db/
 
 ```
 scripts/
-├── cps_to_cosilico.py      # Main conversion script
+├── cps_to_policyengine.py      # Main conversion script
 └── export_to_json.py       # JSON export utility
 
 micro/us/

docs/pe-calibration-targets.md

@@ -227,7 +227,7 @@ PolicyEngine-US-Data uses a three-table schema:
 
 ## Target Count Comparison
 
-| Category | PolicyEngine (est.) | cosilico (current) | Gap |
+| Category | PolicyEngine (est.) | policyengine (current) | Gap |
 |----------|---------------------|-------------------|-----|
 | IRS SOI Tax | ~500 | ~80 | ~420 |
 | Demographics | ~900 | ~50 | ~850 |