from typing import List, Optional, Union
from pydantic import BaseModel, Field
from lomas_server.constants import (
DPLibraries,
SSynthGanSynthesizer,
SSynthMarginalSynthesizer,
)
from lomas_server.utils.error_handler import InternalServerException
[docs]
class GetDbData(BaseModel):
"""Model input to get information about a dataset"""
dataset_name: str
[docs]
class GetDummyDataset(BaseModel):
"""Model input to get a dummy dataset"""
dataset_name: str
dummy_nb_rows: int = Field(..., gt=0)
dummy_seed: int
[docs]
class RequestModel(BaseModel):
"""
Base input model for any request on a dataset.
We differentiate between requests and queries:
- a request does not necessarily require an algorithm
to be executed on the private dataset (e.g. some cost requests).
- a query requires executing an algorithm on a private
dataset (or a potentially a dummy).
"""
dataset_name: str
[docs]
class QueryModel(RequestModel):
"""
Base input model for any query on a dataset.
We differentiate between requests and queries:
- a request does not necessarily require an algorithm
to be executed on the private dataset (e.g. some cost requests).
- a query requires executing an algorithm on a private
dataset (or a potentially a dummy).
"""
[docs]
class DummyQueryModel(QueryModel):
"""
Input model for a query on a dummy dataset.
"""
dummy_nb_rows: int = Field(..., gt=0)
dummy_seed: int
# SmartnoiseSQL
# ----------------------------------------------------------------------------
[docs]
class SmartnoiseSQLRequestModel(RequestModel):
"""Base input model for a smarnoise-sql request"""
query_str: str
epsilon: float = Field(..., gt=0)
delta: float = Field(..., gt=0)
mechanisms: dict
[docs]
class SmartnoiseSQLQueryModel(SmartnoiseSQLRequestModel, QueryModel):
"""Base input model for a smartnoise-sql query"""
postprocess: bool
[docs]
class SmartnoiseSQLDummyQueryModel(SmartnoiseSQLQueryModel, DummyQueryModel):
"""Input model for a smartnoise-sql query on a dummy dataset."""
# SmartnoiseSynth
# ----------------------------------------------------------------------------
[docs]
class SmartnoiseSynthRequestModel(RequestModel):
"""Base input model for a SmartnoiseSynth request"""
synth_name: Union[SSynthMarginalSynthesizer, SSynthGanSynthesizer]
epsilon: float = Field(..., gt=0)
delta: Optional[float] = None
select_cols: List
synth_params: dict
nullable: bool
constraints: str
[docs]
class SmartnoiseSynthQueryModel(SmartnoiseSynthRequestModel, QueryModel):
"""Base input model for a smarnoise-synth query"""
return_model: bool
condition: str
nb_samples: int
[docs]
class SmartnoiseSynthDummyQueryModel(
SmartnoiseSynthQueryModel, DummyQueryModel
):
"""Input model for a smarnoise-synth query on a dummy dataset"""
# Same as normal query.
return_model: bool
condition: str
nb_samples: int
# OpenDP
# ----------------------------------------------------------------------------
[docs]
class OpenDPRequestModel(RequestModel):
"""Base input model for an opendp request"""
opendp_json: str
fixed_delta: Optional[float] = None
[docs]
class OpenDPQueryModel(OpenDPRequestModel, QueryModel):
"""Base input model for an opendp query"""
[docs]
class OpenDPDummyQueryModel(OpenDPRequestModel, DummyQueryModel):
"""Input model for an opendp query on a dummy dataset"""
# DiffPrivLib
# ----------------------------------------------------------------------------
[docs]
class DiffPrivLibRequestModel(RequestModel):
"""Base input model for a diffprivlib request"""
diffprivlib_json: str
feature_columns: list
target_columns: Optional[list]
test_size: float = Field(..., gt=0.0, lt=1.0)
test_train_split_seed: int
imputer_strategy: str
[docs]
class DiffPrivLibQueryModel(DiffPrivLibRequestModel, QueryModel):
"""Base input model for a diffprivlib query"""
[docs]
class DiffPrivLibDummyQueryModel(DiffPrivLibQueryModel, DummyQueryModel):
"""Input model for a DiffPrivLib query on a dummy dataset"""
# Utils
# ----------------------------------------------------------------------------