moved models to separate folder

app/main.py

@@ -2,66 +2,10 @@ from fastapi import FastAPI, __version__
 from pydantic import BaseModel
 from typing import Set, List, Optional, Dict
 
+from models.solver_content import SolverContent
+
 app = FastAPI()
 
-class MetaData(BaseModel):
-  key: str
-  value: str
-  field_id: Optional[int]
-  option_id: Optional[int]
-
-class Item(BaseModel):
-  id: int
-  metadata: List[MetaData]
-
-class Constraint(BaseModel):
-  key: str
-  value: str
-  field_id: Optional[int]
-  option_id: Optional[int]
-  minimum: int
-  maximum: int
-
-class IRTModel(BaseModel):
-  a_param: float
-  b_param: float
-  c_param: float
-  model: str
-
-class Targets(BaseModel):
-  neg_2_5: int
-  neg_1_5: int
-  neg_0_5: int
-  _0_5: int
-  _1: int
-
-class ObjectiveFunction(BaseModel):
-  # minimizing tif/tcc target value is only option currently
-  # as we add more we can build this out to be more dynamic
-  # likely with models representing each objective function type
-  tif_targets: Targets
-  tcc_targets: Targets
-  weight: Dict = {'tif': 1, 'tcc': 1}
-
-class AdvancedOptions(BaseModel):
-  # will supported currently
-  linearity_check: bool
-  show_progress: bool
-  max_solution_time: Optional[int]
-  brand_bound_tolerance: Optional[float]
-  max_forms: Optional[int]
-  precision: Optional[float]
-  extra_param_range: Optional[List[Dict]]
-
-class SolverContent(BaseModel):
-  items: List[Item]
-  constraints: List[Constraint]
-  irt_model: IRTModel
-  objective_fuction: ObjectiveFunction
-  total_form_items: int
-  advanced_options: Optional[List[AdvancedOptions]]
-  engine: str
-
 @app.get("/")
 async def root():
   return {"message": "Welcome to Measures LOFT solver service. v0.1"}

app/models/advanced_options.py

@@ -0,0 +1,12 @@
+from pydantic import BaseModel
+from typing import List, Optional, Dict
+
+class AdvancedOptions(BaseModel):
+  # will supported currently
+  linearity_check: bool
+  show_progress: bool
+  max_solution_time: Optional[int]
+  brand_bound_tolerance: Optional[float]
+  max_forms: Optional[int]
+  precision: Optional[float]
+  extra_param_range: Optional[List[Dict]]

app/models/constraint.py

@@ -0,0 +1,10 @@
+from pydantic import BaseModel
+from typing import Optional
+
+class Constraint(BaseModel):
+  key: str
+  value: str
+  field_id: Optional[int]
+  option_id: Optional[int]
+  minimum: int
+  maximum: int

app/models/irt_model.py

@@ -0,0 +1,7 @@
+from pydantic import BaseModel
+
+class IRTModel(BaseModel):
+  a_param: float
+  b_param: float
+  c_param: float
+  model: str

app/models/item.py

@@ -0,0 +1,8 @@
+from pydantic import BaseModel
+from typing import List
+
+from models.metadata import MetaData
+
+class Item(BaseModel):
+  id: int
+  metadata: List[MetaData]

app/models/metadata.py

@@ -0,0 +1,8 @@
+from pydantic import BaseModel
+from typing import Optional
+
+class MetaData(BaseModel):
+  key: str
+  value: str
+  field_id: Optional[int]
+  option_id: Optional[int]

app/models/objective_function.py

@@ -0,0 +1,12 @@
+from pydantic import BaseModel
+from typing import Dict
+
+from models.targets import Targets
+
+class ObjectiveFunction(BaseModel):
+  # minimizing tif/tcc target value is only option currently
+  # as we add more we can build this out to be more dynamic
+  # likely with models representing each objective function type
+  tif_targets: Targets
+  tcc_targets: Targets
+  weight: Dict = {'tif': 1, 'tcc': 1}

app/models/solver_content.py

@@ -0,0 +1,17 @@
+from pydantic import BaseModel
+from typing import List, Optional
+
+from models.item import Item
+from models.constraint import Constraint
+from models.irt_model import IRTModel
+from models.objective_function import ObjectiveFunction
+from models.advanced_options import AdvancedOptions
+
+class SolverContent(BaseModel):
+  items: List[Item]
+  constraints: List[Constraint]
+  irt_model: IRTModel
+  objective_fuction: ObjectiveFunction
+  total_form_items: int
+  advanced_options: Optional[List[AdvancedOptions]]
+  engine: str

app/models/targets.py

@@ -0,0 +1,8 @@
+from pydantic import BaseModel
+
+class Targets(BaseModel):
+  neg_2_5: int
+  neg_1_5: int
+  neg_0_5: int
+  _0_5: int
+  _1: int