Google Colab:关于VM上文件的生存期 [英] Google Colab: about lifetime of files on VM

问题描述

有人知道colab虚拟机上文件的生存期吗?例如，在colab笔记本中，我将数据另存为csv文件:

  data.to_csv('data.csv') 

那么data.csv将存在多长时间?

这是方案:我想每天维护和更新3000多个小型数据集，但是似乎通过使用pydrive来进行colab和google drive之间的交互非常慢(因为我需要每天检查每个数据集)，因此虚拟机上文件的生命周期是否合理足够长了，我可以每天更新虚拟机上的文件(这会更快)，然后一次而不是每天数天将它们同步到google驱动器.

解决方案

一段时间不活动后，将丢弃虚拟机，因此，最好的选择是将文件保存到要保留为生成状态的云端硬盘中.

使用 pydrive 可以实现，但有点麻烦.一种更简单的方法是使用FUSE界面驱动器，以便您可以自动同步正常保存的文件.

有关示例，请参见: https://colab.research.google.com/drive/1srw_HFWQ2SMgmWIawucXfusGzrj1_U0q>

is there anyone knows the lifetime of files on the colab virtual machine? for example, in a colab notebook, I save the data to a csv file as:

data.to_csv('data.csv')

then how long will the data.csv exist?

This is the scenario: I want to maintain and update over 3000 small datasets everyday, but it seems that the interaction between colab and google drive by using pydrive is pretty slow(as I need to check every dataset everyday), so if the lifetime of files on the virtual machine is long enough, I can update the files on virtual machine everyday(which would be much faster) then synchronize them to google drive several days a time rather than everyday.

解决方案

VMs are discarded after a period of inactivity, so your best bet is to save files to Drive that you'd like to keep as generated.

With pydrive, this is possible, but a bit cumbersome. An easier method is to use a FUSE interface to Drive so that you can automatically sync files as they are saved normally.

For an example, see: https://colab.research.google.com/drive/1srw_HFWQ2SMgmWIawucXfusGzrj1_U0q

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