When we run timeTravel(checkoutFlow, traceLog), it will actually exercise our checkout workflow, and produce the following output. With that, we’ve successfully executed a production execution trace locally, all without touching any database or external service:
近日，《广东新闻联播》记者探访了 OPPO 手机生产一线，释出了即将发布的折叠屏新品 Find N6 的真机视频，显示其折痕「浅到几乎看不见」。
，详情可参考下载安装 谷歌浏览器 开启极速安全的 上网之旅。
The resulting Jupyter Notebook is…indeed thorough. That’s on me for specifying “for all columns”, although it was able to infer the need for temporal analysis (e.g. total monthly video uploads over time) despite not explicitly being mentioned in the prompt.
Kevin Church/BBC News