mirror of
https://github.com/mblanke/ThreatHunt.git
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mblanke
9b98ab9614
- NetworkMap: hunt-scoped force-directed graph with click-to-inspect popover - NetworkMap: zoom/pan (wheel, drag, buttons), viewport transform - NetworkMap: clickable IP/Host/Domain/URL legend chips to filter node types - NetworkMap: brighter colors, 20% smaller nodes - DatasetViewer: IOC columns highlighted with colored headers + cell tinting - AUPScanner: hunt dropdown replacing dataset checkboxes, auto-select all - Rename 'Social Media (Personal)' theme to 'Social Media' with DB migration - Fix /api/hunts timeout: Dataset.rows lazy='noload' (was selectin cascade) - Add OS column mapping to normalizer - Full backend services, DB models, alembic migrations, new routes - New components: Dashboard, HuntManager, FileUpload, NetworkMap, etc. - Docker Compose deployment with nginx reverse proxy
128 lines
4.3 KiB
Python
128 lines
4.3 KiB
Python
"""Dataset repository — CRUD operations for datasets and their rows."""
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import logging
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from typing import Sequence
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from sqlalchemy import select, func, delete
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from sqlalchemy.ext.asyncio import AsyncSession
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from app.db.models import Dataset, DatasetRow
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logger = logging.getLogger(__name__)
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class DatasetRepository:
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"""Typed CRUD for Dataset and DatasetRow models."""
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def __init__(self, session: AsyncSession):
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self.session = session
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# ── Dataset CRUD ──────────────────────────────────────────────────
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async def create_dataset(self, **kwargs) -> Dataset:
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ds = Dataset(**kwargs)
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self.session.add(ds)
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await self.session.flush()
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return ds
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async def get_dataset(self, dataset_id: str) -> Dataset | None:
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result = await self.session.execute(
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select(Dataset).where(Dataset.id == dataset_id)
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)
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return result.scalar_one_or_none()
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async def list_datasets(
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self,
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hunt_id: str | None = None,
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limit: int = 100,
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offset: int = 0,
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) -> Sequence[Dataset]:
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stmt = select(Dataset).order_by(Dataset.created_at.desc())
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if hunt_id:
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stmt = stmt.where(Dataset.hunt_id == hunt_id)
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stmt = stmt.limit(limit).offset(offset)
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result = await self.session.execute(stmt)
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return result.scalars().all()
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async def count_datasets(self, hunt_id: str | None = None) -> int:
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stmt = select(func.count(Dataset.id))
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if hunt_id:
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stmt = stmt.where(Dataset.hunt_id == hunt_id)
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result = await self.session.execute(stmt)
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return result.scalar_one()
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async def delete_dataset(self, dataset_id: str) -> bool:
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ds = await self.get_dataset(dataset_id)
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if not ds:
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return False
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await self.session.delete(ds)
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await self.session.flush()
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return True
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# ── Row CRUD ──────────────────────────────────────────────────────
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async def bulk_insert_rows(
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self,
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dataset_id: str,
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rows: list[dict],
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normalized_rows: list[dict] | None = None,
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batch_size: int = 500,
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) -> int:
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"""Insert rows in batches. Returns count inserted."""
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count = 0
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for i in range(0, len(rows), batch_size):
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batch = rows[i : i + batch_size]
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norm_batch = normalized_rows[i : i + batch_size] if normalized_rows else [None] * len(batch)
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objects = [
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DatasetRow(
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dataset_id=dataset_id,
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row_index=i + j,
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data=row,
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normalized_data=norm,
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)
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for j, (row, norm) in enumerate(zip(batch, norm_batch))
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]
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self.session.add_all(objects)
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await self.session.flush()
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count += len(objects)
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return count
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async def get_rows(
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self,
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dataset_id: str,
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limit: int = 1000,
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offset: int = 0,
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) -> Sequence[DatasetRow]:
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stmt = (
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select(DatasetRow)
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.where(DatasetRow.dataset_id == dataset_id)
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.order_by(DatasetRow.row_index)
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.limit(limit)
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.offset(offset)
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)
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result = await self.session.execute(stmt)
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return result.scalars().all()
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async def count_rows(self, dataset_id: str) -> int:
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stmt = select(func.count(DatasetRow.id)).where(
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DatasetRow.dataset_id == dataset_id
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)
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result = await self.session.execute(stmt)
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return result.scalar_one()
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async def get_row_by_index(
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self, dataset_id: str, row_index: int
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) -> DatasetRow | None:
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stmt = select(DatasetRow).where(
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DatasetRow.dataset_id == dataset_id,
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DatasetRow.row_index == row_index,
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)
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result = await self.session.execute(stmt)
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return result.scalar_one_or_none()
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async def delete_rows(self, dataset_id: str) -> int:
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result = await self.session.execute(
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delete(DatasetRow).where(DatasetRow.dataset_id == dataset_id)
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)
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return result.rowcount # type: ignore[return-value]
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