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* Add Unstructured engagement report as uv workspace member Three-tier Plotly Dash app (Executive Brief, Engineering Team, Full Detail) with data in JSON, theme constants in theme.py, and Dash production improvements (Google Fonts, clientside callbacks, meta tags). Also: add .playwright-mcp/ to .gitignore, add reports/* ruff overrides, remove tracked .codeflash/observability/read-tracker. * Rewrite statusline to derive context from git state Detects active area from changed files (reports, packages, plugin, .codeflash, case-studies, evals), falls back to branch name convention (perf/*, feat/*, fix/*), shows dirty indicator. Uses whoami for cross-platform user detection. * Add pre-push lint rule to commit guidelines * Exclude .codeflash/ from ruff linting Benchmark and profiling scripts in .codeflash/ are scratch work, not package source. Excluding them prevents CI failures from ad-hoc scripts. * Run ruff format across packages, scripts, evals, and plugin refs * Fix github-app async test failures in CI Add asyncio_mode = "auto" to root pytest config so async tests are detected when running from the repo root via uv run pytest packages/.
32 lines
1.1 KiB
Python
32 lines
1.1 KiB
Python
from pipeline.aggregator import aggregate_by_category
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def test_aggregate_basic():
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events = [
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{"category": "web", "source": "s1", "value": 10.0},
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{"category": "web", "source": "s2", "value": 20.0},
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{"category": "api", "source": "s1", "value": 5.0},
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{"category": "api", "source": "s1", "value": 15.0},
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]
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result = aggregate_by_category(events)
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assert len(result) == 2
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assert result["web"]["count"] == 2
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assert result["api"]["count"] == 2
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def test_aggregate_large_batch():
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"""Large event batch — uses too much memory for production volumes."""
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categories = [f"cat-{i}" for i in range(500)]
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sources = [f"source-{i}" for i in range(50)]
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events = []
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for i in range(200_000):
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events.append(
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{
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"category": categories[i % len(categories)],
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"source": sources[i % len(sources)],
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"value": float(i % 1000),
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}
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)
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result = aggregate_by_category(events)
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assert len(result) == 500
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assert all(r["count"] == 400 for r in result.values())
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