Merge branch 'main' into ml-flow

src/config.py

@@ -1,3 +1,4 @@
+import re
 from enum import Enum
 from typing import Any, Literal, TypedDict
 
@@ -32,6 +33,33 @@ class AwsConfig(BaseModel):
         return {"profile_name": self.profile, "region_name": self.region}
 
 
+DEFAULT_BOOTSTRAP_QUALIFIER = "hnb659fds"
+GENERATED_STACK_PREFIX = "qc-cli-mlops-"
+
+
+class InfraConfig(BaseModel):
+    stack_name: str
+
+    @property
+    def effective_bootstrap_qualifier(self) -> str:
+        sanitized = re.sub(r"[^a-z0-9]", "", self.stack_name.lower())
+        if not sanitized:
+            return DEFAULT_BOOTSTRAP_QUALIFIER
+        if self.stack_name.startswith(GENERATED_STACK_PREFIX):
+            suffix = re.sub(r"[^a-z0-9]", "", self.stack_name.removeprefix(GENERATED_STACK_PREFIX).lower())
+            if suffix:
+                return f"q{suffix}"[:10]
+        return f"q{sanitized}"[:10]
+
+    @property
+    def effective_toolkit_stack_name(self) -> str:
+        if self.stack_name.startswith(GENERATED_STACK_PREFIX):
+            suffix = re.sub(r"[^A-Za-z0-9-]", "", self.stack_name.removeprefix(GENERATED_STACK_PREFIX))
+            if suffix:
+                return f"{self.stack_name}-bootstrap"
+        return f"{self.stack_name}-bootstrap"
+
+
 class S3Config(BaseModel):
     bucket: str = "my-qc-mlops-bucket"
     data_prefix: str = "data/"
@@ -48,7 +76,7 @@ class TrainingConfig(BaseModel):
 
 
 class SageMakerConfig(BaseModel):
-    role_name: str = "qc-cli-sagemaker-role"
+    role_name: str = ""
     training: TrainingConfig = Field(default_factory=TrainingConfig)
 
 
@@ -72,6 +100,7 @@ class MlflowConfig(BaseModel):
 
 
 class Config(BaseModel):
+    infra: InfraConfig
     aws: AwsConfig = Field(default_factory=AwsConfig)
     s3: S3Config = Field(default_factory=S3Config)
     sagemaker: SageMakerConfig = Field(default_factory=SageMakerConfig)