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https://github.com/computerim/impactflow-discovery.git
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Joel Salmon
b9d7b0e22b
Final roadmap phase. No DB migration — it reads data already captured.
- Goal-evolution history: GET /discovery/profile/me/goal-history derives a
per-goal timeline from the profile_revision snapshots (pure aggregator in
app/services/profile_history.py).
- Smart tagging: POST /discovery/integration/suggest-foundation suggests which
foundation a task builds toward + rationale/confidence (FoundationTagger,
app/services/tagging.py). Suggestion only; the person confirms by posting the
task mapping.
- Deeper goal-refinement: the reflect loop accepts an optional focus ("goals")
that steers the coach toward sharpening goals — still mirror, not compass.
- Visualizations: visuals.html renders an Ikigai Venn and an Enneagram diagram
(plain-language callouts, not the raw type number) plus the goal-evolution
timeline; linked from profile.html.
Tests: 99 passing (added pure goal-history tests, goal-history + suggest
endpoint tests, reflect-focus passthrough; run in-container). README updated.
This completes the ImpactFlow Vision roadmap (Phases 1-5) on the Discovery side.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
48 lines
1.6 KiB
Python
48 lines
1.6 KiB
Python
"""Unit tests for the pure goal-evolution aggregator."""
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from datetime import datetime, timezone
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from app.services.profile_history import goal_history
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def _rev(short, long_, source, day):
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return {
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"fields": {"short_term_goals": short, "long_term_goals": long_},
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"source": source,
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"created_at": datetime(2026, 6, day, tzinfo=timezone.utc),
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}
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def test_collapses_consecutive_identical_values():
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revs = [
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_rev("a", "x", "extraction", 1),
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_rev("a", "x", "manual_edit", 2), # no change -> skipped
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_rev("b", "x", "reflection", 3), # short changed
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]
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h = goal_history(revs)
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assert [e["value"] for e in h["short_term_goals"]] == ["a", "b"]
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assert [e["value"] for e in h["long_term_goals"]] == ["x"]
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assert h["short_term_goals"][1]["source"] == "reflection"
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def test_each_field_tracked_independently():
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revs = [
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_rev("a", "x", "extraction", 1),
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_rev("a", "y", "reflection", 2), # only long changed
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]
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h = goal_history(revs)
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assert len(h["short_term_goals"]) == 1
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assert [e["value"] for e in h["long_term_goals"]] == ["x", "y"]
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def test_empty_revisions_yield_empty_timelines():
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h = goal_history([])
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assert h == {"short_term_goals": [], "long_term_goals": []}
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def test_first_value_emitted_even_if_none():
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revs = [_rev(None, None, "extraction", 1), _rev("a", None, "reflection", 2)]
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h = goal_history(revs)
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assert [e["value"] for e in h["short_term_goals"]] == [None, "a"]
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# long stayed None throughout -> a single None entry
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assert [e["value"] for e in h["long_term_goals"]] == [None]
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