包阅导读总结
1.
关键词：Datalore 2024.3、Quality Improvements、Enhancements、Bug Fixes、Update
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总结：Datalore 2024.3 着重进行质量改进，社区、专业和团队用户已自动接收更新，企业用户可按说明升级。更新包括增强文件处理、优化 R 和 Scala 环境设置、提前终端访问等，还涵盖其他改进和错误修复。
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主要内容：
– 2024.3 版本聚焦 Datalore 质量提升
– 增强的文件处理
– 可将定时运行生成的文件保存到特定目录，可覆盖，方便查找
– 更顺畅的 R 和 Scala 环境设置
– 相关环境设置在执行 init.sh 前完成
– 早期终端访问
– 环境设置未完成时可访问终端，便于早期故障排查
– 其他改进和错误修复
– 导出工作空间包含更多内容
– 支持新的 ipydatagrid 版本
– 新增报告链接字段等
– 改进数据库模式刷新体验
– 限制部分计划的 Git 库拉取大小
– 修复一些显示和链接问题
– 优化不可访问 PyPi 服务器时的处理
– 解决渲染问题
– 定时报告可更新 Markdown 单元格变量
– 社区、专业和团队用户自动接收更新，企业用户按说明升级
思维导图：
文章地址：https://blog.jetbrains.com/datalore/2024/06/25/what-s-new-in-datalore-2024-3-quality-improvements/
文章来源：blog.jetbrains.com
作者：Alena Guzharina
发布时间：2024/6/25 9:41
语言：英文
总字数：441字
预计阅读时间：2分钟
评分：86分
标签：发布
以下为原文内容
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What’s New in Datalore 2024.3: Quality Improvements
Following a feature-rich 2024.2 release, we’ve focused on enhancing the quality and reliability of Datalore in our 2024.3 update. Datalore Community, Professional, and Team customers have already received the new update automatically, and Datalore Enterprise customers can upgrade by following these instructions.
Enhanced file handling for scheduled runs
We’ve added an option that lets you save files generated by scheduled runs directly to /data/notebook_files, just like you can for files generated during regular notebook sessions. This new feature allows files to be overwritten, and you can easily find files from all of your previous runs in one directory. The option to save files to isolated artifacts still exists, giving you more flexibility for your scheduled workflows.
Smoother environment setup for R and Scala
From now on, the necessary environment setup for R and Scala will be completed before the execution of init.sh, ensuring a smoother initial run. This enhancement allows you to make meaningful changes to init.sh scripts with the knowledge that they will be applied correctly, streamlining environment configuration.
Early terminal access during setup
The terminal is now accessible before environment setup is complete, allowing for early troubleshooting.
Other improvements and bug fixes
- Exported workspaces now include both notebooks and their associated reports in the downloaded .zip file.
- Datalore now supports ipydatagrid versions 1.3.0 and 1.3.1.
- A new reportLink field has been added to the top-level metadata of downloaded notebooks.
- When refreshing a database schema, you will now see a spinner during the refresh process and receive a clear notification when it is finished, alerting you to any errors.
- For improved security, Git repository pulls are now limited to 100 MB for Datalore Community, Professional, and Team plans. Datalore Enterprise customers can configure the maximum pull size via the GIT_REPOSITORY_SIZE_LIMIT environment variable.
- Notebooks created by non-owners of a workspace no longer have incorrect report links in the workspace view.
- The correlation chart in the Visualize tab no longer blinks.
- In scenarios where PyPi servers are not accessible, Datalore now provides clear messages to admins about connectivity issues, prevents infinite loading, and offers an improved troubleshooting process.Only Enterprise plan users were affected.
- We’ve fixed a rendering issue that was causing ipywidgets outputs to shake in the report builder and on the report page. Only Community, Professional, and Team plans were affected.
- Scheduled reports now update variables in Markdown cells.
Datalore Community, Professional, and Team customers have already received these updates automatically. Datalore Enterprise customers can upgrade by following these instructions:
Upgrade to 2024.3
Kind regards,
The Datalore team
