Very long delay (10–20 s) on first plot in a fresh environment: Matplotlib font-cache build
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评估
- 难度
- 2/5
- 预计耗时
- 1-3 小时
- 新手友好度
- 74/100
- Issue 类型
- 文档
- 描述清晰度
- 基本清楚
- 活跃度
- 活跃
- 技术栈
- python
调研方向
首先定位项目的 troubleshooting 或安装文档，并了解其中如何组织特定于环境的说明。添加一条简短的“Slow first plot”说明，涵盖 Matplotlib 冷启动时字体缓存导致的原因，以及 issue 中描述的 Docker、CI 和 sandbox 缓存持久化修复方案；当用户能够理解延迟原因并选择缓存解决方案时，即表示完成。
由索引模型根据 Issue 内容生成。
描述
Symptom
In a fresh environment, the first plot (or, before #198, plain import spatialmath) can take 10–20 s. Later runs on the same machine are fast, so the delay is hard to reproduce on a long-lived development machine, but it can recur on every run in containers or CI.
Cause
This is Matplotlib behaviour, not spatialmath code. The first time Matplotlib's font manager runs with no font cache, it scans every font installed on the system to build one. That's the "Matplotlib is building the font cache; this may take a moment" message. The cache is stored in MPLCONFIGDIR, which by default is ~/.cache/matplotlib on Linux and ~/.matplotlib on macOS. If that directory doesn't persist between runs, every run pays the full cost. This commonly happens with:
- Docker containers and CI runners started fresh each time
- sandboxed build/test tools that don't keep the home directory's cache
- new virtual environments or users with a different
MPLCONFIGDIR
Measurements
Apple M1 (8 GB), macOS, Python 3.12. "Empty cache" means MPLCONFIGDIR pointed at an empty directory.
| Empty font cache | Cache already built | |
|---|---|---|
import matplotlib.pyplot |
17.0 s | — |
import spatialmath, before #198 (f6a572c6^) |
17.6 s | 1.1 s |
import spatialmath, after #198 (current master) |
0.75 s | 0.7 s |
Before #198, import spatialmath imported matplotlib.pyplot, so every spatialmath user paid this on a cold cache, including code that never plots. Since #198 the import is lazy, so the cost appears only at the first plot, and code that never plots never pays it.
How long the scan takes depends on how many fonts are installed. A minimal Linux container will usually be faster than macOS, but several seconds is typical.
Fix
spatialmath can't avoid this without dropping Matplotlib. If you plot in a fresh environment, keep the cache between runs:
- Docker: build the cache when building the image, so it's baked in:
RUN python -c "import matplotlib.pyplot" - CI: cache the
MPLCONFIGDIRdirectory between jobs (e.g.actions/cacheon~/.cache/matplotlib), or run the line above in a setup step. - Sandboxes: set
MPLCONFIGDIRto a persistent, writable directory.
Proposed docs change
Add a short "Slow first plot" troubleshooting note to the docs, with the explanation and fixes above.
Related: #198 (lazy Matplotlib import), #234 (remaining import-time costs from SciPy/SymPy).
- 主要语言
- Python
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- 平均合并
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环境准备
这个项目没有提供开发容器、Dockerfile 或贡献指南，环境需要你自己搭建：先看它的 README，通用步骤见我们的新手贡献指南。
从这里开始
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- Fork 仓库，在一个分支上完成修改。
- 提交 Pull Request，并在描述里引用这个 Issue 编号。
rai-opensource/spatialmath-python 的其他 Issue
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enhancement
难度 2/5 1-3 小时 新手友好度 65/100
rai-opensource/spatialmath-python#32 · 4 条评论 ·
维护者通常 1 天内回复
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难度 3/5 1-2 天 新手友好度 66/100
rai-opensource/spatialmath-python#236 ·
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enhancement
难度 4/5 3-5 天 新手友好度 68/100
rai-opensource/spatialmath-python#234 ·
维护者通常 1 天内回复
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rai-opensource/spatialmath-python#231 ·
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难度 2/5 1-3 小时 新手友好度 50/100
rai-opensource/spatialmath-python#177 ·
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