automation: establish an automation framework

app/terraform/terraform.py

@@ -1,6 +1,6 @@
 import json
 import subprocess
-from typing import Dict, Any, Optional
+from typing import Any, Dict, List, Optional, Tuple
 
 import jinja2
 
@@ -18,20 +18,27 @@ class TerraformAutomation(BaseAutomation):
     Default parallelism for remote API calls.
     """
 
-    def automate(self):
-        self.tf_prehook()
+    def automate(self, full: bool = False):
+        prehook_result = self.tf_prehook()
         self.tf_generate()
         self.tf_init()
-        self.tf_apply(refresh=False)
-        self.tf_posthook()
+        returncode, logs = self.tf_apply(refresh=full)
+        self.tf_posthook(prehook_result=prehook_result)
+        return True if returncode == 0 else False, logs
 
-    def tf_apply(self, refresh: bool = True, parallelism: Optional[int] = None):
+    def tf_apply(self, refresh: bool = True, parallelism: Optional[int] = None) -> Tuple[int, List[Dict[str, Any]]]:
         if not parallelism:
             parallelism = self.parallelism
-        subprocess.run(
+        tf = subprocess.run(
             ['terraform', 'apply', f'-refresh={str(refresh).lower()}', '-auto-approve',
-             f'-parallelism={str(parallelism)}'],
-            cwd=self.working_directory())
+             f'-parallelism={str(parallelism)}', '-json'],
+            cwd=self.working_directory(),
+            stdout=subprocess.PIPE)
+        logs = []
+        for line in tf.stdout.decode('utf-8').split('\n'):
+            if line.strip():
+                logs.append(json.loads(line))
+        return tf.returncode, logs
 
     def tf_generate(self):
         raise NotImplementedError()
@@ -56,7 +63,7 @@ class TerraformAutomation(BaseAutomation):
         # more like JSON-ND, task is to figure out how to yield those records
         # as plan runs, the same is probably also true for apply
 
-    def tf_posthook(self, prehook_result: Any = None) -> None:
+    def tf_posthook(self, *, prehook_result: Any = None) -> None:
         """
         This hook function is called as part of normal automation, after the
         completion of :func:`tf_apply`.