This may be a dumb question, but does a job stop running on a Colab instance when I close my browser? If not, is there a way to keep it running (i.e until it&#39;s complete)

In that same vein of thought, if I were to give someone edit access to my Colab notebook, would it be running on my instance of Colab with all my installed libraries or on theirs?

Does Google Colab stay connected when I close my browser?

Is it possible to use any datasets available via the `kaggle` API in Google Colab? I see the Kaggle API is used in [this Colab notebook][1], but it&#39;s a bit unclear to me what datasets it provides access to. 


  [1]: https://colab.research.google.com/drive/1eufc8aNCdjHbrBhuy7M7X6BGyzAyRbrF
 

Using Kaggle Datasets in Google Colab

How to export data frames which are created in google colab to your local machine? 

I have cleaned a data set on google colab. Now I want to export the data frame to my local machine. 
`df.to_csv` is saving file to the virtual machine and not my local machine.

Exporting Data from google colab to local machine

I want to use Selenium Webdriver of Chrome in colab.research.google.com for fast processing. I was able to install Selenium using `!pip install selenium` but the webdriver of chrome needs a path to webdriverChrome.exe. How am I suppose to use it? 

P.S.- colab.research.google.com is an online platform which provides GPU for fast computational problems related to deep learning. Please refrain from solutions such as webdriver.Chrome(path). 

How can we use Selenium Webdriver in colab.research.google.com?

How do I change the current theme to the dark theme in Google Colab?

I need a dark theme like Jupyter notebook has.

How to change the theme to dark in Google Colab?

Normally in a jupyter notebook I would use `%matplotlib notebook` magic to display an interactive window, however this doesn&#39;t seem to work with google colab. Is there a solution, or is it not possible to display interactive windows in google colab?

Interactive matplotlib figures in Google Colab

**Q:** Is there any way to programmatically prevent [Google Colab][1] from disconnecting on a timeout?

[&lt;img src=&quot;https://i.stack.imgur.com/lkvoo.jpg&quot; height=&quot;420&quot;&gt;][2]

The following describes the conditions causing a notebook to automatically disconnect:

&gt; *Google Colab notebooks have an idle timeout of 90 minutes and absolute timeout of 12 hours. This means, if user does not interact with his Google Colab notebook for more than 90 minutes, its instance is automatically terminated. Also, maximum lifetime of a Colab instance is 12 hours.*

Naturally, we want to automatically squeeze the maximum out of the instance, [without having to manually interact with it constantly][2]. Here I will assume commonly seen system requirements:

 * Ubuntu 18 LTS / Windows 10 / Mac Operating systems
 * In case of Linux-based systems, using popular DEs like Gnome 3 or Unity
 * Firefox or Chromium browsers

I should point out here that such behavior **does not violate** [Google Colab&#39;s Terms of Use][3], although it is not encouraged according to their [FAQ][4] (in short: morally it is not okay to use up all of the GPUs if you don&#39;t really need it). 

------------------------------------

My current solution is very dumb:

* First, I turn the screensaver off, so my sreen is always on.
* I have an Arduino board, so I just turned it into a [rubber ducky usb][5] and make it emulate primitive user interaction while I sleep (just because I have it at hand for other use-cases). 

Are there better ways?


  [1]: https://colab.research.google.com/
  [2]: https://i.stack.imgur.com/lkvoo.jpg
  [3]: https://colab.one/terms-of-use
  [4]: https://research.google.com/colaboratory/faq.html
  [5]: https://www.quora.com/What-is-a-USB-Rubber-Ducky

How to prevent Google Colab from disconnecting?

What are the common ways to import private data into Google Colaboratory notebooks? Is it possible to import a non-public Google sheet? You can&#39;t read from system files. The introductory docs link to a [guide on using BigQuery](https://colab.research.google.com/notebook#fileId=/v2/external/notebooks/bigquery.ipynb&amp;scrollTo=KcAZ2RHCg_Ze), but that seems a bit... much.

Import data into Google Colaboratory

The problem is simple: I have some data on gDrive, for example at 
`/projects/my_project/my_data*`.

Also I have a simple notebook in gColab.

So, I would like to do something like:

    for file in glob.glob(&quot;/projects/my_project/my_data*&quot;):
        do_something(file)

Unfortunately, all examples (like this - https://colab.research.google.com/notebook#fileId=/v2/external/notebooks/io.ipynb, for example) suggests to only mainly load all necessary data to notebook.

But, if I have a lot of pieces of data, it can be quite complicated. 
Is there any opportunities to solve this issue?

Thanks for help!


Google Colab: how to read data from my google drive?

Is there any way to upload my code in .py files and import them in colab code cells? 

The other way I found is to create a local Jupyter notebook then upload it to Colab, is it the only way?

Importing .py files in Google Colab

update: this question is related to Google Colab&#39;s &quot;Notebook settings: Hardware accelerator: GPU&quot;. This question was written before the &quot;TPU&quot; option was added.

Reading multiple excited announcements about Google Colaboratory providing free Tesla K80 GPU, I tried to run [fast.ai][1] lesson on it for it to never complete - quickly running out of memory. I started investigating of why.

The bottom line is that “free Tesla K80” is not &quot;free&quot; for all - for some only a small slice of it is &quot;free&quot;. 

I connect to Google Colab from West Coast Canada and I get only 0.5GB of what supposed to be a 24GB GPU RAM. Other users get access to 11GB of GPU RAM.

Clearly 0.5GB GPU RAM is insufficient for most ML/DL work.

If you&#39;re not sure what you get, here is little debug function I scraped together (only works with the GPU setting of the notebook):

    # memory footprint support libraries/code
    !ln -sf /opt/bin/nvidia-smi /usr/bin/nvidia-smi
    !pip install gputil
    !pip install psutil
    !pip install humanize
    import psutil
    import humanize
    import os
    import GPUtil as GPU
    GPUs = GPU.getGPUs()
    # XXX: only one GPU on Colab and isn’t guaranteed
    gpu = GPUs[0]
    def printm():
     process = psutil.Process(os.getpid())
     print(&quot;Gen RAM Free: &quot; + humanize.naturalsize( psutil.virtual_memory().available ), &quot; | Proc size: &quot; + humanize.naturalsize( process.memory_info().rss))
     print(&quot;GPU RAM Free: {0:.0f}MB | Used: {1:.0f}MB | Util {2:3.0f}% | Total {3:.0f}MB&quot;.format(gpu.memoryFree, gpu.memoryUsed, gpu.memoryUtil*100, gpu.memoryTotal))
    printm()
    
Executing it in a jupyter notebook before running any other code gives me:

    Gen RAM Free: 11.6 GB  | Proc size: 666.0 MB
    GPU RAM Free: 566MB | Used: 10873MB | Util  95% | Total 11439MB

The lucky users who get access to the full card will see:

    Gen RAM Free: 11.6 GB  | Proc size: 666.0 MB
    GPU RAM Free: 11439MB | Used: 0MB | Util  0% | Total 11439MB

Do you see any flaw in my calculation of the GPU RAM availability, borrowed from GPUtil?

Can you confirm that you get similar results if you run this code on Google Colab notebook?

If my calculations are correct, is there any way to get more of that GPU RAM on the free box?

update: I&#39;m not sure why some of us get 1/20th of what other users get. e.g. the person who helped me to debug this is from India and he gets the whole thing!

**note**: please don&#39;t send any more suggestions on how to kill the potentially stuck/runaway/parallel notebooks that might be consuming parts of the GPU. No matter how you slice it, if you are in the same boat as I and were to run the debug code you&#39;d see that you still get a total of 5% of GPU RAM (as of this update still).

  [1]: http://course.fast.ai/

Google Colaboratory: misleading information about its GPU (only 5% RAM available to some users)

In a project, I have e.g. two different packages, How can I use the setup.py to install these two packages in the Google&#39;s Colab, so that I can import the packages?

How do I install Python packages in Google&#39;s Colab?

So I&#39;m trying to git clone and cd into that directory using Google collab  - but I cant cd into it. What am I doing wrong?

&gt;!rm -rf SwitchFrequencyAnalysis &amp;&amp; git clone https://github.com/ACECentre/SwitchFrequencyAnalysis.git
&gt;
&gt;!cd SwitchFrequencyAnalysis
&gt;
&gt;!ls
&gt; datalab/  SwitchFrequencyAnalysis/

You would expect it to output the directory contents of SwitchFrequencyAnalysis - but instead its the root. I&#39;m feeling I&#39;m missing something obvious - Is it something to do with being within the python interpreter? (where is the documentation??)

[Demo here.][1] 


  [1]: https://drive.google.com/file/d/13zTMSRipeLewfpVS5k4O5fMuebagqO5o/view?usp=sharing

Changing directory in Google colab (breaking out of the python interpreter)

Are there any recommended methods to integrate git with colab?

For example, is it possible to work off code from google source repositories or the likes?

Neither google drive nor cloud storage can be used for git functionality.

So I was wondering if there is a way to still do it?


Methods for using Git with Google Colab

Can I run a google colab (free edition) script and then shut down my computer?

I am training several deeplearning models with crossvalidation, and therefore I would like to know if I can close the window or the computer with the training running at the same time in the cloud.



Can I run a Google Colab (free edition) script and then shut down my computer?

Is there any way to use TensorBoard when training a TensorFlow model on Google Colab?

Can I use TensorBoard with Google Colab?

I&#39;m trying to download a file from google drive in a script, and I&#39;m having a little trouble doing so. The files I&#39;m trying to download are [here](https://drive.google.com/folderview?id=0Bz-w5tutuZIYeHJTWjR5WW1pa1E&amp;usp=sharing).

I&#39;ve looked online extensively and I finally managed to get one of them to download. I got the UIDs of the files and the smaller one (1.6MB) downloads fine, however the larger file (3.7GB) always redirects to a page which asks me whether I want to proceed with the download without a virus scan. Could someone help me get past that screen?

Here&#39;s how I got the first file working - 

    curl -L &quot;https://docs.google.com/uc?export=download&amp;id=0Bz-w5tutuZIYeDU0VDRFWG9IVUE&quot; &gt; phlat-1.0.tar.gz

When I run the same on the other file, 

    curl -L &quot;https://docs.google.com/uc?export=download&amp;id=0Bz-w5tutuZIYY3h5YlMzTjhnbGM&quot; &gt; index4phlat.tar.gz

I get the the following output -
[![enter image description here][1]][1]

I notice on the third-to-last line in the link, there a `&amp;confirm=JwkK` which is a random 4 character string but suggests there&#39;s a way to add a confirmation to my URL. One of the links I visited suggested `&amp;confirm=no_antivirus` but that&#39;s not working.

I hope someone here can help with this!


  [1]: http://i.stack.imgur.com/Szcq2.jpg

wget/curl large file from google drive

I found many hints how to upload data into [Colaboratory](https://colab.research.google.com).

But now I want to do opposite -&gt; I want to download .csv I&#39;ve created in Colaboratory workspace.

How to do this?

How to download file created in Colaboratory workspace?

Google Colaboratory supports Python version 2.7 and 3.6

I saw an example how to use Swift in Colab a while ago.

Today, I happened to run

    !jupyter-kernelspec list

And found a new kernel: IRkernel

    Available kernels:
      ir         /usr/local/share/jupyter/kernels/ir
      python2    /usr/local/share/jupyter/kernels/python2
      python3    /usr/local/share/jupyter/kernels/python3
      swift      /usr/local/share/jupyter/kernels/swift

Is it now possible to use R in Colab as well? No hassle in installing R kernel?

How to use R with Google Colaboratory?

Currently, I can download files as individual files with the command 

    files.download(file_name)

I also tried uploading them to the drive with the below code snippet but it is uploading them as individual files.

    uploaded = drive.CreateFile({&#39;title&#39;: file_name})
    uploaded.SetContentString(&#39;Sample upload file content&#39;)
    uploaded.Upload()
    print(&#39;Uploaded file with ID {}&#39;.format(uploaded.get(&#39;id&#39;)))

How can I download multiple files as a folder to my local computer? Or how can I upload these files as a folder to my google drive?

How do I download multiple files or an entire folder from Google Colab?

I want to get access to the files in the Google Drive&#39;s &quot;Shared with me&quot; directory.

In the Colab python notebook the following commands:

    import os
    from google.colab import drive
    drive.mount(&#39;/content/drive&#39;)
    !ls &quot;/content/drive/My Drive&quot;

work well for &quot;My Drive&quot; directory however

    !ls &quot;/content/drive/My Drive&quot;

fails with

&gt; FileNotFoundError: [Errno 2] No such file or directory:

I am aware of the fact that I can add the folder to my drive manually and proceed ([as mentioned in here][1]), but I would like to have direct access to the shared folders for lets say I might need to automate the work with files that are shared with me real time.

I am also aware that same/similar problem exist with other cloud platforms like &quot;OneDrive&quot;.

The questions are:

 1. if there is no straightforward way of doing it, is there at least a
    workaround?
 2. do the people I share my code with get access to my drive too?


  [1]: https://stackoverflow.com/a/53887376/7769163

accessing &quot;Shared with me&quot; with Colab

When I open a new notebook on Google Colab I see a &quot;POWER LEVEL&quot; indicator with a battery symbol at the top.
I can click it and choose three different power levels: low, medium and high.

[![Google Colab snapshot with Power Level][1]][1]

I don&#39;t remember ever seeing this before on Google Colab. I believe this is a new undocumented feature.

Does anybody know what is the effect of changing power levels?


  [1]: https://i.stack.imgur.com/8wWMz.png

Meaning of &quot;Power Level&quot; on google colab

In Google Colaboratory, I can install a new library using `!pip install package-name`. But when I open the notebook again tomorrow, I need to re-install it every time.

Is there a way to install a library permanently? No need to spend time installing every time to use?

How do I install a library permanently in Colab?

I cloned a github repo using    `!git clone https://github.com/llSourcell/Pokemon_GAN.git`. I wanted to modify a .py  file inside Colab. So i used `%load filename.py` as suggested here (https://stackoverflow.com/questions/21034373/how-to-load-edit-run-save-text-files-py-into-an-ipython-notebook-cell). But whenever i run this command, i get disconnected after some time. I was wondering if there is some other way to edit .py file without undergoing the hassle of downloading it to pc,editing and then re uploading it. Thanks in advance.

How to edit and save text files (.py) in Google Colab?

Google Colaboratory is really cool, but it would be more useful if I can access all my google drive files, without using standard google drive API.


Is it possible and easy? and how?

All Google Colaboratory Solutions on Gang of Coders

Total of 25 Google Colaboratory Solutions