phase: 9, status: plan-as-execute, persona: platform-engineer, task: T-9.5..T-9.7+T-9.9

---ci---
project: acdl
phase: 9
milestone: v1.1
status: plan-as-execute
persona: platform-engineer
task: [T-9.5, T-9.6, T-9.7, T-9.9]
requirements.covered: [REQ-26]
---/ci---

Waves 2+3: Terraform adapter + generated spike TF + run script.

- T-9.5: adapters/terraform/adapter.py - compiles an IR instance to a
  Terraform root module. TYPE_MAP {aws:s3:bucket -> aws_s3_bucket}. Thin
  layer; does not own L1 content. Emits main.tf (resource + outputs) +
  terraform.tf (required_version/providers + S3 backend, NO
  dynamodb_table per D-P09-1) + providers.tf (aws provider region from
  the IR). CLI: adapter.py <ir_instance.json> <out_dir>.

- T-9.6: terraform/spike/{main.tf,terraform.tf,providers.tf} - generated
  by running the adapter against modules-ir/l1/l1-s3/spike_instance.json.
  Committed so verify_phase09.sh can validate/plan without regenerating
  (D-P09-4); the verify script will regenerate + diff to prove
  reproducibility.

- T-9.7: scripts/run_spike_plan.sh - loads rotated spike key from
  gitignored .env.secrets, exports AWS env vars, cd terraform/spike,
  terraform init -lock=false, terraform validate, terraform plan
  -lock=false -out=tfplan. Plan-only; no apply.

- T-9.9: .gitignore - add terraform/spike/.terraform/ + tfplan +
  *.tfstate*.

EXECUTE: ran scripts/run_spike_plan.sh against real AWS via the rotated
spike key (D-039). terraform plan succeeded: 1 to add (the S3 bucket),
outputs computed. One non-blocking deprecation warning (aws_s3_bucket
versioning block -> use aws_s3_bucket_versioning in v1.2). No long-lived
credential in the workflow (key loaded from .env.secrets at runtime).

adapters/terraform/adapter.py

@@ -0,0 +1,131 @@
+"""ACDL Terraform adapter — compile a Target Stack IR instance to Terraform.
+
+ARCHITECTURE.md §12.2: the adapter translates the IR-typed L1 interface
+to a Terraform variable/output block, the L2 thin-composition tree to a
+root module that calls the L1 modules, the IR-typed relationships to
+Terraform module references, and emits a Terraform plan from the IR.
+
+The adapter is a THIN LAYER; it does not own L1/L2 content — it only
+translates. Substrate-agnostic in, Terraform out.
+
+Spike scope (Phase 09): handles one L1 (l1-s3, IR type aws:s3:bucket).
+L2 thin-composition + relationships land in Phase 10.
+
+CLI: adapter.py <ir_instance.json> <out_dir>
+"""
+
+import json
+import os
+import sys
+
+
+# IR type -> Terraform resource type. The only substrate-specific table.
+# As more L1s land, this grows; the L1 content + IR do not change.
+TYPE_MAP = {
+    "aws:s3:bucket": "aws_s3_bucket",
+}
+
+
+def _tf_block(block_type, name, body_lines, indent=2):
+    head = f'{block_type} "{name}" {{'
+    body = "\n".join(f"  {l}" for l in body_lines)
+    return f"{head}\n{body}\n}}\n"
+
+
+def _emit_resource(resource):
+    rtype = resource["type"]
+    rid = resource["id"]
+    tf_type = TYPE_MAP.get(rtype)
+    if not tf_type:
+        raise ValueError(f"unknown IR type {rtype!r} (adapter spike handles aws:s3:bucket only)")
+    body = []
+    inputs = resource.get("inputs", {})
+    # S3 bucket: bucket_name -> bucket arg; region -> provider (handled separately)
+    if "bucket_name" in inputs:
+        body.append(f'bucket = "{inputs["bucket_name"]}"')
+    # NFR: versioning (default true)
+    nfrs = resource.get("nfrs", {})
+    versioning = nfrs.get("versioning", True) if isinstance(nfrs, dict) else True
+    body.append("versioning {")
+    body.append(f'  enabled = {"true" if versioning else "false"}')
+    body.append("}")
+    return _tf_block("resource", f'aws_s3_bucket.{rid}', body) if False else _resource_block(rid, tf_type, body)
+
+
+def _resource_block(rid, tf_type, body):
+    """Emit a top-level resource block."""
+    head = f'resource "{tf_type}" "{rid}" {{'
+    body_str = "\n".join(f"  {l}" for l in body)
+    return f"{head}\n{body_str}\n}}\n"
+
+
+def _emit_output(output_name, value_expr):
+    return f'output "{output_name}" {{\n  value = {value_expr}\n}}\n'
+
+
+def adapt(ir_instance, out_dir):
+    """Emit main.tf + terraform.tf + providers.tf to out_dir for the IR instance."""
+    os.makedirs(out_dir, exist_ok=True)
+    stack = ir_instance["stack"]
+    resources = ir_instance["resources"]
+
+    # --- providers.tf: aws provider, region from the first resource's inputs.region ---
+    region = "us-east-1"
+    for r in resources:
+        if "region" in r.get("inputs", {}):
+            region = r["inputs"]["region"]
+            break
+    providers_tf = (
+        f'provider "aws" {{\n'
+        f'  region = "{region}"\n'
+        f'}}\n'
+    )
+
+    # --- terraform.tf: required_version + required_providers + S3 backend (no DynamoDB lock per D-P09-1) ---
+    terraform_tf = (
+        'terraform {\n'
+        '  required_version = ">= 1.9, < 1.10"\n'
+        '  required_providers {\n'
+        '    aws = {\n'
+        '      source  = "hashicorp/aws"\n'
+        '      version = "~> 5.0"\n'
+        '    }\n'
+        '  }\n'
+        '  backend "s3" {\n'
+        '    bucket = "acdl-tfstate-581513795199-us-east-1"\n'
+        '    key    = "spike/l1-s3/terraform.tfstate"\n'
+        '    region = "us-east-1"\n'
+        '  }\n'
+        '}\n'
+    )
+
+    # --- main.tf: resources + outputs ---
+    main_tf_parts = []
+    for r in resources:
+        main_tf_parts.append(_emit_resource(r))
+        rid = r["id"]
+        outputs = r.get("outputs", {})
+        for out_name in outputs:
+            if out_name == "bucket_arn":
+                main_tf_parts.append(_emit_output("bucket_arn", f"aws_s3_bucket.{rid}.arn"))
+            elif out_name == "bucket_name":
+                main_tf_parts.append(_emit_output("bucket_name", f"aws_s3_bucket.{rid}.id"))
+    main_tf = "\n".join(main_tf_parts)
+
+    with open(os.path.join(out_dir, "main.tf"), "w") as fh:
+        fh.write(main_tf)
+    with open(os.path.join(out_dir, "terraform.tf"), "w") as fh:
+        fh.write(terraform_tf)
+    with open(os.path.join(out_dir, "providers.tf"), "w") as fh:
+        fh.write(providers_tf)
+    return out_dir
+
+
+if __name__ == "__main__":
+    if len(sys.argv) != 3:
+        print("usage: adapter.py <ir_instance.json> <out_dir>", file=sys.stderr)
+        sys.exit(2)
+    with open(sys.argv[1], "r") as fh:
+        ir = json.load(fh)
+    adapt(ir, sys.argv[2])
+    print(f"adapter: emitted terraform to {sys.argv[2]}", file=sys.stderr)