f4aa7caaa9
Brings up the documented target architecture as a docker-compose stack — a modular monolith with the Ghidra step split into its own async worker. - worker/: RQ queue (lazy redis import) + run_acquisition task (Job status queued→started→finished/failed, drives ams.acquire with sink=db) - Job model + JobOut schema; Snapshot.data is JSONB on Postgres - POST/GET /jobs: stream an upload to a shared volume, enqueue, poll status - docker/api.Dockerfile (slim) + docker/worker.Dockerfile (JDK21 + Ghidra fetched at build, overridable via GHIDRA_URL) + docker-compose.yml - ghidra.py: AMS_GHIDRA_SCRIPTS override for in-container script path - pyproject: [worker] extra (rq/redis/psycopg), python-multipart in [api] - tests: 4 new (task success/failure + endpoint enqueue/503) -> 22/22 Verified: API image builds, container serves /health + /ui + /jobs; compose config validates. Worker image (downloads ~1 GB Ghidra) not built here. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
58 lines
1.1 KiB
Python
58 lines
1.1 KiB
Python
"""Pydantic request/response models."""
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from __future__ import annotations
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from datetime import datetime
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from pydantic import BaseModel, ConfigDict
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class GameCreate(BaseModel):
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name: str
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notes: str | None = None
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class GameOut(BaseModel):
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model_config = ConfigDict(from_attributes=True)
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id: int
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name: str
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notes: str | None = None
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class SnapshotOut(BaseModel):
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model_config = ConfigDict(from_attributes=True)
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id: int
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game_id: int | None
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binary_name: str
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sha256: str
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engine: str | None
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compiler: str | None
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schema_version: int | None
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n_types: int
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n_methods: int
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n_events: int
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n_fields: int
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created_at: datetime
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class SnapshotDetail(SnapshotOut):
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data: dict
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class GameDetail(GameOut):
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snapshots: list[SnapshotOut] = []
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class JobOut(BaseModel):
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model_config = ConfigDict(from_attributes=True)
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id: int
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rq_id: str | None
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status: str
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source_name: str
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game_name: str | None
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snapshot_id: int | None
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dll_name: str | None
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error: str | None
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created_at: datetime
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updated_at: datetime
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