Praxis CI
ec6fcc64bc
Phase 2 complete — Cohort Dashboard + Aggregation: - Cohort aggregation pipeline (k-anon ≥10 write-time suppression, async hook, nightly 03:00 CT reconcile) - 4 auth-gated operator API endpoints (cohort, mastery, failure-patterns, credentials) - React cohort dashboard (BrowserRouter, login, 3 views, inline SVG sparklines, auth gate) - SPA fallback via SpaStaticFiles subclass (G-041 — NOT catch-all route) - G-038 differencing-attack test (unit + API e2e) - 317 pytest pass, 36 skip, 0 fail; 17/17 vitest pass; npm build + typecheck clean ---ci--- project: praxis phase: 2 milestone: v0.4 status: complete requirements: covered: [REQ-DASH-01, REQ-NFR-DASH-01, REQ-NFR-DASH-02, REQ-MT-02] partial: [] ---/ci---
93 lines
2.9 KiB
Python
93 lines
2.9 KiB
Python
"""Shared helpers for operator API endpoints (SLICE-08).
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Common response models + the recent-aggregates query used by all 3 cohort
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view endpoints (cohort, mastery, failure-patterns). Kept here to avoid
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duplicating the Pydantic models + pool query across 3 files.
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"""
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from __future__ import annotations
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import datetime as _dt
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from typing import Any
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from fastapi import HTTPException, Request, status
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from pydantic import BaseModel
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class Cell(BaseModel):
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metric: str
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window_start: _dt.date | None = None
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window_end: _dt.date | None = None
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value: float | None = None
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cell_count: int = 0
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cell_suppressed: bool = False
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updated_at: _dt.datetime | None = None
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class PathView(BaseModel):
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path: str
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metrics: list[Cell]
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class ViewResponse(BaseModel):
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views: list[PathView]
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last_updated: _dt.datetime | None = None
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async def require_pg_store(request: Request):
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pg_store = getattr(request.app.state, "pg_store", None)
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if pg_store is None:
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raise HTTPException(
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status_code=status.HTTP_503_SERVICE_UNAVAILABLE,
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detail="operator tier unavailable (no Postgres)",
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)
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return pg_store
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async def all_recent_aggregates(pg_store, since: _dt.date) -> list[dict[str, Any]]:
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async with pg_store.pool.acquire() as conn:
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rows = await conn.fetch(
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"SELECT path, metric, window_start, window_end, value, "
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"cell_count, cell_suppressed, updated_at "
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"FROM cohort_aggregates WHERE window_start >= $1 "
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"ORDER BY path, metric, window_start",
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since,
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)
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return [dict(r) for r in rows]
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def cell_from_row(row: dict[str, Any]) -> Cell:
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return Cell(
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metric=row.get("metric", ""),
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window_start=row.get("window_start"),
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window_end=row.get("window_end"),
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value=float(row["value"]) if row.get("value") is not None else None,
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cell_count=int(row.get("cell_count") or 0),
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cell_suppressed=bool(row.get("cell_suppressed") or False),
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updated_at=row.get("updated_at"),
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)
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def group_by_path(
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rows: list[dict[str, Any]],
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metric_filter: set[str] | None = None,
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) -> tuple[list[PathView], _dt.datetime | None]:
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by_path: dict[str, list[dict[str, Any]]] = {}
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last_updated: _dt.datetime | None = None
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for r in rows:
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if metric_filter is not None and r.get("metric") not in metric_filter:
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continue
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by_path.setdefault(r["path"], []).append(r)
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ua = r.get("updated_at")
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if isinstance(ua, _dt.datetime) and (last_updated is None or ua > last_updated):
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last_updated = ua
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views = [PathView(path=p, metrics=[cell_from_row(c) for c in cells])
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for p, cells in by_path.items()]
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return views, last_updated
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__all__ = [
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"Cell", "PathView", "ViewResponse",
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"require_pg_store", "all_recent_aggregates",
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"cell_from_row", "group_by_path",
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] |