Implement pg-orrery-catalog: TLE catalog builder for pg_orrery

Core modules:
- tle.py: NORAD decoding (Alpha-5 + Super-5, matching get_el.c),
  3LE/2LE parsing, TLERecord dataclass with epoch-based dedup
- config.py: TOML config + env var overlay (XDG-compliant paths)
- cache.py: File-based cache with staleness checking
- catalog.py: Multi-source merge with MergeStats tracking
- regime.py: LEO/MEO/GEO/HEO classification by mean motion

Source downloaders (httpx):
- celestrak.py: Active catalog + supplemental GP groups
- satnogs.py: JSON API with 3LE conversion
- spacetrack.py: POST auth flow, bulk GP download

Output formatters:
- sql.py: pg_orrery-compatible INSERT generation (E'' strings)
- tle_file.py: Standard 3LE text output
- json_out.py: JSON with orbital metadata and regime

CLI (Click + Rich):
- download: Cache TLEs from all sources
- build: Merge + output SQL/3LE/JSON (pipes to psql)
- load: Direct DB load via psycopg (optional [pg] extra)
- info: Cache stats and configuration display

58 tests covering NORAD decoding (all 4 encoding cases),
parsing, merge/dedup, SQL escaping, regime classification.

tests/test_regime.py

@@ -0,0 +1,53 @@
+"""Tests for orbital regime classification."""
+
+from pg_orrery_catalog.regime import classify_regime, regime_summary
+from pg_orrery_catalog.tle import TLERecord
+
+
+def _make_record_with_mm(norad_id: int, mean_motion: float) -> TLERecord:
+    """Create a TLERecord with a specific mean motion in line2."""
+    line1 = f"1 {norad_id:05d}U 98067A   24001.50000000  .00000000  00000-0  00000-0 0  9990"
+    mm_str = f"{mean_motion:011.8f}"
+    line2 = f"2 {norad_id:05d}  51.6400 100.0000 0007417  30.0000 330.1234 {mm_str}999990"
+    return TLERecord(
+        line1=line1, line2=line2, name=f"SAT-{norad_id}",
+        norad_id=norad_id, epoch=24001.0,
+    )
+
+
+class TestClassifyRegime:
+    def test_leo(self):
+        assert classify_regime(15.5) == "LEO"   # ISS-like
+        assert classify_regime(11.26) == "LEO"   # boundary
+
+    def test_meo(self):
+        assert classify_regime(2.0) == "MEO"    # GPS-like
+        assert classify_regime(11.25) == "MEO"   # just below LEO
+
+    def test_geo(self):
+        assert classify_regime(1.0) == "GEO"    # near-synchronous
+        assert classify_regime(0.91) == "GEO"
+
+    def test_heo(self):
+        assert classify_regime(0.5) == "HEO"    # Molniya-like
+        assert classify_regime(0.9) == "HEO"    # boundary
+        assert classify_regime(0.1) == "HEO"    # deep space
+
+
+class TestRegimeSummary:
+    def test_mixed(self):
+        records = {
+            1: _make_record_with_mm(1, 15.5),   # LEO
+            2: _make_record_with_mm(2, 2.0),    # MEO
+            3: _make_record_with_mm(3, 1.0),    # GEO
+            4: _make_record_with_mm(4, 0.5),    # HEO
+        }
+        summary = regime_summary(records)
+        assert summary["LEO"] == 1
+        assert summary["MEO"] == 1
+        assert summary["GEO"] == 1
+        assert summary["HEO"] == 1
+
+    def test_empty(self):
+        summary = regime_summary({})
+        assert summary == {"LEO": 0, "MEO": 0, "GEO": 0, "HEO": 0}