A work around to free some memory in google colab can be done by deleting variables that are not needed any more. Click on the Variables inspector window on the left side. See what variables you do not need and just delete them. I suspect by merely opening that Variables inspector, it chewed up a bunch of memory.
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I am using the Goole colab for data analytics and I have several notebooks. Sometimes I need to quickly make a copy/clone of my working notebook to make some changes and experiment. So is there a quick easy way to like a shortcut or menu option to do this? other than downloading the notebook as a .ipynb file and loading again with new name?
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Google colab's UI is updated occasionally. Until the time this answer was written, you could change the theme using the following steps: From the top menu, select settings. From settings, select site. You can choose one of the three listed options: light, dark or adaptive. Illustrating Screenshot. let your eyes enjoy the dark theme!
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Here is a solution to get interactive matplotlib figure : Support for third party widgets (widgets outside of the ipywidgets package) needs to be enabled separately. Support for these widgets will be loaded from a CDN external from Colab. from google.colab import output. output.enable_custom_widget_manager()
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These commands will ensure that you have the necessary packages, including Google Chrome and ChromeDriver, set up for Selenium in Google Colab. # Install dependencies %%shell sudo apt -y update sudo apt install -y wget curl unzip. # Now, you can use the 'driver' object to interact with the web page.
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Colab includes a text editor you can use to create, open, and delete .py files directly. All is done in the Files view (see below). To create or delete a file, right click and choose"New file" or"Delete file". To edit a file, double click on it. It appears on the right portion of your screen. Make any changes you wish. Changes are saved ...
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which will list the files and folders in your google drive and their id that you will need for the following step. file = drive.CreateFile({'parents':[{u'id': ' id of folder you want to save in '}]}) file.SetContentFile("mydataframe.csv") file.Upload() It will now be in your google drive in the given folder.
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If you don't use GPU but remain connected with GPU, after some time Colab will give you a warning message like Warning: You are connected to a GPU runtime, but not utilising the GPU. Change to a standard runtime. A good practice is to change the runtime on that time, otherwise, you may get blocked on this day.
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Three steps to use git to sync colab with github or gitlab. Generate a private-public key pair. Copy the private key to the system clibboard for use in step 2. Paste the public key to github or gitlab as appropriate. In Linux, ssh-keygen can be used to generate the key-pair in ~/.ssh.
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AFAIK, you can execute the module 'google.colab' from within the notebook environment of colab.research.google.com (it is not a publicly available package) OFF-TOPIC: Looking at the tag conda in your question. I assume that you are running the code from your local machine. Please make use of PyDrive to read from google drive on your local machine.
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