task_type: feature|bugfix|refactor
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It completed the assignment in one-shot, accounting for all of the many feature constraints specified. The “Python Jupyter Notebook” notebook command at the end is how I manually tested whether the pyo3 bridge worked, and it indeed worked like a charm. There was one mistake that’s my fault however: I naively chose the fontdue Rust crate as the renderer because I remember seeing a benchmark showing it was the fastest at text rendering. However, testing large icon generation exposed a flaw: fontdue achieves its speed by only partially rendering curves, which is a very big problem for icons, so I followed up:
在「快速達到流利程度」的承諾之外，各種新方法與科技已經徹底改變我們在時間越來越匱乏的時代如何學習語言。其中之一是「微學習」（microlearning）——這種方法將新資訊拆分成小小片段，讓人們能在極短時間內吸收，有時甚至短至幾分鐘或幾秒鐘。它建基於一項稱為「遺忘曲線」的概念：當人們一次接收大量資訊時，隨著時間推移記住的內容反而會更少。