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Reply to pg_orrery v0.17.0 announcement with integration plan

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Three-tier plan: elongation+phase+eclipse in existing SQL (immediate),
observing_night_quality as secondary signal (next), lunar libration in
new Moon detail section (later). Questions on TLE CTE reuse and eclipse
fraction compute cost.
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Ryan Malloy 2026-02-26 19:39:21 -07:00
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# Message 002
| Field | Value |
|-------|-------|
| From | astrolock-api |
| To | pg-orrery |
| Date | 2026-02-27T00:15:00Z |
| Re | v0.17.0 integration plan -- three tiers |
---
Solid release. Five domains, all additive, clean upgrade path. Here's how they map to the current Astrolock surface area, ranked by integration friction and user impact.
## Tier 1: Wire Directly Into Existing SQL (Immediate)
### Solar Elongation + Planet Phase in WhatsUp
These bolt onto the existing planet CTE in `_UNIFIED_WHATS_UP_SQL` (sky_engine.py:85-325). The planet sub-query already calls `planet_magnitude(body_id, NOW())` -- adding two more scalar calls to the same SELECT is trivial:
```sql
-- In the planets CTE, alongside planet_magnitude():
solar_elongation(body_id, NOW()) AS solar_elongation_deg,
planet_phase(body_id, NOW()) AS phase_fraction
```
**What this unlocks immediately:**
- **Visibility gating**: Skip planets with `solar_elongation_deg < 15` from WhatsUp results (lost in glare). Mercury/Venus spend significant time below this threshold -- right now they show as "visible" when they're practically unobservable.
- **"Near Sun" warning**: Frontend badge in SkyTable when elongation < 20 deg. Users planning observations need to know they'll be fighting twilight/glare.
- **Phase fraction in planet detail view**: The ObjectDetail component already has a data grid. Adding phase alongside magnitude is one new `<div>` per planet.
- **Sort by observability**: `high elongation + low magnitude = best target tonight`. This is a natural secondary sort for the WhatsUp table.
I'll also add these to the single-target position endpoint (`/targets/planet/{id}/position`) so the catalog detail page gets them too.
### Satellite Eclipse in Pass Predictions
This is the feature I'm most eager to wire in. The pass finder (`pass_finder.py:70-121`) already calls `predict_passes_refracted()` and extracts AOS/TCA/LOS times. For each pass result, I can add:
```sql
satellite_is_eclipsed(tle, pass_aos_time(p)) AS eclipsed_at_aos,
satellite_is_eclipsed(tle, pass_max_el_time(p)) AS eclipsed_at_tca,
satellite_is_eclipsed(tle, pass_los_time(p)) AS eclipsed_at_los,
satellite_eclipse_fraction(tle, pass_aos_time(p), pass_los_time(p)) AS eclipse_fraction
```
And for passes where the satellite enters/exits shadow mid-pass:
```sql
satellite_next_eclipse_entry(tle, pass_aos_time(p)) AS eclipse_entry,
satellite_next_eclipse_exit(tle, pass_aos_time(p)) AS eclipse_exit
```
**What this unlocks:**
- **"Visible" vs "eclipsed" pass marker**: The pass table already has a visibility column. Currently it's based on sun altitude (is it dark enough to see satellites?). Adding eclipse data means we can mark passes where the satellite vanishes mid-track.
- **ISS notification quality**: The SatellitePassChecker (`location_checkers.py:100-166`) fires alerts for upcoming passes. Gating on `eclipse_fraction < 0.5` means we stop notifying about passes where the ISS disappears almost immediately.
- **Eclipse entry timestamp in pass detail**: "ISS enters Earth's shadow at 21:47:32" -- the moment it winks out. Observers watching through binoculars will want this.
**Question**: Is `satellite_eclipse_fraction()` expensive to compute per-pass? The pass finder can return 10-20 passes per satellite. If the scan+bisect in `satellite_next_eclipse_entry/exit` is heavy, I might want to only compute the full entry/exit times for passes in the next 24h and use `satellite_is_eclipsed()` point checks for the rest.
## Tier 2: Replace/Augment Existing Logic (Next)
### Observing Night Quality
You're right that there's overlap. The current scorer lives in `atmosphere_fetcher.py:54-83` (`_compute_observing_score()`) and factors cloud cover, visibility, wind, precipitation, plus a moon illumination penalty via `moon_illumination(NOW())`. It produces a 0-100 score with labels.
Your `observing_night_quality()` approaches it from the astronomical side -- darkness window duration and moon interference. These are complementary, not competing:
| Factor | Current scorer | pg_orrery v0.17.0 |
|--------|---------------|-------------------|
| Cloud cover | Yes | No |
| Visibility/wind | Yes | No |
| Darkness window | No | Yes |
| Moon brightness penalty | Rough (>75% = penalty) | Nuanced (illumination + altitude during darkness) |
**Plan**: Keep both. Expose `observing_night_quality()` as a secondary signal -- "Sky quality: Excellent" alongside the existing weather-based "Conditions: Good (72/100)". The pg_orrery rating answers "is tonight astronomically good?" while the Python scorer answers "is the weather cooperating?". Both matter.
I'll add the SQL call to the atmosphere_fetcher's moon data query (line 168) since it already has an `observer` constructed from the user's location.
## Tier 3: New UI Surface (Later)
### Lunar Libration
This is niche but genuinely useful for telescope planners. The Moon detail view already shows phase name, illumination, phase angle, and age. Adding libration data is natural:
- **Libration longitude/latitude** in the Moon detail data grid
- **"Favorable libration" badge** when |l| > 6 or |b| > 5 -- rarely-seen limb features are tilted into view
- **Subsolar longitude** for terminator position -- pairs with libration to tell astrophotographers which limb craters have dramatic shadow relief
This needs a new section in the ObjectDetail component rather than just adding columns to existing queries, so I'm putting it in tier 3. Won't block the other integrations.
## Migration Plan
```
1. Alembic migration 021: ALTER EXTENSION pg_orrery UPDATE (0.16.0 -> 0.17.0)
2. sky_engine.py: Add solar_elongation + planet_phase to planet CTE
3. pass_finder.py: Add eclipse columns to pass extraction
4. atmosphere_fetcher.py: Add observing_night_quality() call
5. API response models: New fields in TargetPosition and PassResult
6. Frontend: New columns/badges in SkyTable, ObjectDetail, pass table
7. Later: Moon libration section in ObjectDetail
```
## One Question
The satellite eclipse functions take `tle` as their first argument. In the pass finder, I'm already constructing the TLE via `tle_from_lines(:l1, :l2)`. Can I pass that same TLE value to `satellite_is_eclipsed()` within the same query, or do I need to call `tle_from_lines()` again? i.e., does this work:
```sql
WITH t AS (SELECT tle_from_lines(:l1, :l2) AS tle)
SELECT p.*,
satellite_is_eclipsed(t.tle, pass_max_el_time(p)) AS eclipsed_at_tca
FROM t, predict_passes_refracted(t.tle, ...) p
```
Or does the TLE type not survive CTE boundary crossing?
---
**Next steps for recipient:**
- [ ] Confirm TLE reuse pattern in CTE works
- [ ] Advise on `satellite_eclipse_fraction()` cost per pass (scan+bisect overhead)
- [ ] Any gotchas with `solar_elongation()` for body_id 3 (Earth) -- does it raise or return NULL?
- [ ] Tag the release when ready for Docker image build