Ubuntu – How to upload a file from Google Colab to GitHub or Kaggle

githubgoogleupload

As you all know we are able to load a file from a site such as Kaggle and GitHub to Google Collab, we apply the bellow code to download from other sites into Google Collab:

wget nlp.stanford.edu/data/glove.6B.zip

but I am very curious to know if I am able to upload a saved file in Google Collab to another site through some commands like the above? I mean I can do it manually in some multiple steps but please let me know if there are some commands to upload a file directly from Google Collab into another site such as GitHub.

Best Answer

To add a file to a Git repository and upload it to GitHub please refer to its official help articles Creating a new repository, Cloning a repository, and Adding a file to a repository using the command line. I’ll include the most important steps below:

Install Git:
```
sudo apt install git
```
Create a repository on GitHub.

Import (or “clone”) the Git repository and enter its top directory:

git clone https://github.com/YOUR-USERNAME/YOUR-REPOSITORY
cd YOUR-REPOSITORY

Place the desired file into the repository directory (or one of its sub-directories) e. g. by moving or copying it from another place or downloading it from an external resource.
Add the file to the Git repository:
```
git add my-file
```
Commit the changes to the repository:
```
git commit --message="Add my-file"
```
Upload (or “push”) the committed changes to the upstream repository (here: at GitHub):
```
git push
```

Obviously you don’t need to repeat steps 1–3 if you did them before.

1 Preparation

Based on the official Kaggle API documentation:

Install the Kaggle command-line interface (here via PIP, a Python package manager):
```
sudo apt install python3-pip
pip3 install --user kaggle
```
Create a configuration directory for the next step:
```
mkdir ~/.kaggle
```
Authentication:

In order to use the Kaggle’s public API, you must first authenticate using an API token. From the site header, click on your user profile picture, then on “My Account” from the dropdown menu. This will take you to your account settings at https://www.kaggle.com/account. Scroll down to the section of the page labelled API:

To create a new token, click on the “Create New API Token” button. This will download a fresh authentication token onto your machine.

Store it as ~/.kaggle/kaggle.json, since that’s where the CLI will look for it by default. You can simply copy and paste that path into the file selection dialogue of your web browser.

2 Dataset Upload

Again from the same official API documentation:

Create a new Dataset

Here are the steps you can follow to create a new dataset on Kaggle:
Create a folder containing the files you want to upload.
Run
kaggle datasets init -p /path/to/dataset
to generate a metadata file.
Add your dataset’s metadata to the generated file, datapackage.json.
Run
kaggle datasets create -p /path/to/dataset
to create the dataset.
Your dataset will be private by default. You can also add a -u flag to make it public when you create it, or navigate to “Settings” > “Sharing” from your dataset’s page to make it public or share with collaborators.

Create a new Dataset version

If you’d like to upload a new version of an existing dataset, follow these steps:
Run
kaggle datasets init -p /path/to/dataset
to generate a metadata file (if you don’t already have one).
Make sure the id field in dataset-metadata.json (or datapackage.json) points to your dataset.
Run:
kaggle datasets version -p /path/to/dataset -m "Your message here"

These instructions are the basic commands required to get started with creating and updating Datasets on Kaggle. You can find out more details from the official documentation on GitHub:

Initializing metadata

Create a Dataset

Update a Dataset

Looking at my answer it turned out to be a nice way to tell you to RTFM. ;-]

Best Answer

Related Solutions

Ubuntu – How to upload songs into Google Music on Ubuntu

Ubuntu – How to upload a data set from a command-line (such as Google Collaboratory) into Kaggle

1 Preparation

2 Dataset Upload

Create a new Dataset

Create a new Dataset version

Related Question