Defer SciPy and SymPy imports to cut `import spatialmath` time (~800 ms → ~150 ms)
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- 难度
- 4/5
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- 3-5 天
- 新手友好度
- 68/100
- Issue 类型
- 重构
- 描述清晰度
- 描述清楚
- 活跃度
- 活跃
- 技术栈
- python
- 领域
- performance, testing
调研方向
Start by reading the top-level imports and mentioned methods in base/quaternions.py, spline.py, base/symbolic.py, and base/argcheck.py. Compare the import-time regression approach from #198, then verify that import spatialmath leaves neither scipy nor sympy in sys.modules while the affected feature and SymPy-supported paths still work.
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描述
Follow-up to #198, which deferred matplotlib.pyplot until something actually plots. Its description noted that scipy.interpolate and sympy cost about as much. They are now the main remaining costs of import spatialmath.
Where the time goes
Measured with python -X importtime -c "import spatialmath" on Python 3.12, macOS, Apple M1 (8 GB), warm cache. Cold-start times will be higher.
| Module | Cost | Imported by |
|---|---|---|
scipy.interpolate + scipy.spatial.transform |
~455 ms | base/quaternions.py:19, spline.py:14-15 (both at top level) |
sympy (when installed) |
~200 ms | base/symbolic.py:19, via base/argcheck.py |
matplotlib (no pyplot) |
~100 ms | geom2d.py:13 from matplotlib.path import Path. #198 kept this on purpose because Polygon2 needs it for its geometry |
numpy |
~40 ms | |
| Total | ~800 ms |
SciPy: nothing needs it at import time
base/quaternions.py: the only user isqrand(). When the angle is limited, it does inverse-CDF sampling through_generate_inv_cdf_sin_squared_interp(), which is already@lru_cache'd. Every user pays ~440 ms for this one option.qslerpand the rest of the module don't use SciPy. Fix: move the import into that function, and make the-> interpolate.interp1dannotation a string or put it underTYPE_CHECKING.spline.py:CubicSpline,RotationSpline,RotationandBSplineare only used inside methods. Fix: import them inside those methods.- Both must change. If only one does, the other still loads
scipy.interpolate. SciPy stays a hard dependency; only when it loads changes. - #129 (open) adds more top-level SciPy imports to
spline.py(scipy.optimize,splrep) and would need the same treatment.
SymPy: avoid importing it just to check types
SymPy is optional. base/symbolic.py imports it inside a try so that issymbol() can check for sympy.Expr. But if "sympy" not in sys.modules, no argument can possibly be a SymPy expression. So issymbol() can return False without importing SymPy, and only import it once the user has imported SymPy themselves. This is a separate change from the SciPy one because argcheck is on almost every code path, so it needs its own testing (including the :SymPy: supported paths).
Expected result
About 150 ms for import spatialmath, and none of SciPy or SymPy loaded until a feature actually uses them. A regression test along the lines of #198's could assert that neither scipy nor sympy is in sys.modules after import spatialmath.
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