使用Kaggle内核立即运行任何Jupyter Notebook

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使用Kaggle内核立即运行任何Jupyter Notebook

2023-03-29 04:09| 来源: 网络整理| 查看: 265

kernel-run 🔥 🚀

Instantly create and run a Kaggle kernel from any Jupyter notebook (local file or URL).

kaggle-run-demo

$ pip install kernel-run --upgrade $ kernel-run path/to/notebook.ipynb Kernel created successfully: https://www.kaggle.com/aakashns/kr-notebook/edit $ kernel-run http://cs231n.stanford.edu/notebooks/pytorch_tutorial.ipynb Kernel created successfully: https://www.kaggle.com/aakashns/kr-pytorch-tutorial/edit

kernel-run uploads the Jupyter notebook to a private kernel in your Kaggle account, and launches a browser window so you can start editing/executing the code immediately.

Installation pip install kernel-run --upgrade

The above command install a command-line tool called kernel-run which can be invoked from the terminal/command prompt.

Note: To allow kaggle-run to upload the notebook to your Kaggle account, you need to download the Kaggle API credentials file kaggle.json. To download the kaggle.json file:

Go to https://kaggle.com Log in and go to your account page Click the "Create New API Token" button in the "API" section Move the downloaded kaggle.json file to the folder ~/.kaggle/ CLI Usage & Options

Run the kernel-run command on your terminal/command prompt with a Jupyter notebook's path (or URL) as the argument:

$ kernel-run path/to/notebook.ipynb Kernel created successfully: https://www.kaggle.com/aakashns/kr-notebook/edit $ kernel-run http://cs231n.stanford.edu/notebooks/pytorch_tutorial.ipynb Kernel created successfully: https://www.kaggle.com/aakashns/kr-pytorch-tutorial/edit

There are various options you can configure. Run kernel-run -h to see the options:

usage: kernel-run notebook_path_or_url [-h] [--public] [--new] [--no-browser] [--strip-output] [--prefix PREFIX] positional arguments: notebook_path_or_url Path/URL of the Jupyter notebook optional arguments: -h, --help show this help message and exit --public Create a public kernel --new Create a new kernel, if a kernel with the same name exists --no-browser Don't open a browser window automatically --strip-output Clear output cells before uploading notebook (useful for large files) --prefix PREFIX Prefix added to kernel title to easy identification (defaults to 'kr/') Python API

You can also use the library form a Python script or Jupyter notebook. It can be imported as kernel_run.

from kernel_run import create_kernel create_kernel('path/to/notebook.ipynb', public=True, no_browser=True) # Kernel created successfully: https://www.kaggle.com/aakashns/kr-notebook/edit

The arguments to create_kernel are identical to the CLI options:

def create_kernel(path_or_url, public=False, no_browser=False, new=False, strip_output=False, prefix='kr/', creds_path=None): """Instantly create and run a Kaggle kernel from a Jupyter notebook (local file or URL) Arguments: path_or_url (string): Path/URL to the Jupyter notebook public (bool, optional): If true, creates a public kernel. A private kernel is created by default. no_browser (bool, optional): If true, does not attempt to automatically open a browser tab to edit the created Kernel new (bool, optional): If true, creates a new Kernel by adding a random 5-letter string at the end of the title prefix (string, optional): A prefix added to the Kernel title, to indicate that the Kernel was created using kernel-run creds_path (string, optional): Path to the 'kaggle.json' credentials file (defaults to '~/.kaggle/kaggle.json') strip_output (bool, optional): Clear output cells before uploading notebook. """ Credits

Developed with love by the Jovian team ( https://www.jvn.io )! Contributions welcome.

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使用Kaggle内核立即运行任何Jupyter Notebook

使用Kaggle内核立即运行任何Jupyter Notebook

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