File size: 2,137 Bytes
715a633 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 |
from typing import List, Optional, Literal, Dict, Any
from pydantic import BaseModel, Field
import platform, sys
class Limits(BaseModel):
timeout_seconds: int = Field(12, ge=1, le=120)
max_stdout_chars: int = Field(10000, ge=256, le=200_000)
max_stderr_chars: int = Field(10000, ge=256, le=200_000)
max_plots: int = Field(4, ge=0, le=10)
max_dataframes: int = Field(3, ge=0, le=10)
max_df_rows: int = Field(20, ge=1, le=200)
max_df_cols: int = Field(20, ge=1, le=200)
plot_dpi: int = Field(120, ge=72, le=300)
max_pixels: int = Field(25_000_000, ge=1) # если вдруг юзер генерит большие изображения
class CodeRunRequest(BaseModel):
language: Literal["python"] = "python"
code: str
# Явный allowlist модулей (верхнеуровневые имена)
allowed_modules: List[str] = Field(
default_factory=lambda: [
"math","random","statistics","datetime","re","json","fractions","decimal",
"numpy","pandas","cmath","matplotlib","matplotlib.pyplot", "seaborn","sklearn","sklearn.datasets","sklearn.model_selection", "sympy"
]
)
# Флаги, что возвращать
return_plots: bool = True
return_dataframes: bool = True
# Ограничения
limits: Limits = Field(default_factory=Limits)
class PlotArtifact(BaseModel):
data_base64: str
format: Literal["png"] = "png"
class DataFrameArtifact(BaseModel):
name: str
head: List[Dict[str, Any]]
shape: List[int]
dtypes: Dict[str, str]
class EnvInfo(BaseModel):
python: str = Field(default_factory=lambda: sys.version.split()[0])
numpy: Optional[str] = None
pandas: Optional[str] = None
platform: str = Field(default_factory=platform.platform)
class CodeRunResult(BaseModel):
execution_id: str
status: Literal["success","error","timeout"]
stdout: str = ""
stderr: str = ""
result_repr: Optional[str] = None
plots: List[PlotArtifact] = Field(default_factory=list)
dataframes: List[DataFrameArtifact] = Field(default_factory=list)
env: EnvInfo |