Picture by the writer
The Kagal CLI (command line interface) allows you to interact with your terminal directly with Kagal datases, competitions, notebooks and models. It is useful for automating downloads, submissions, and dataset management without the need for a web browser. Most of my Gut Hub Action Work Floose uses CLI to download or forward the datases, as this is the fastest and efficient way.
1. Installation and setup
Make sure you have 3.10+ installed. Subsequently, run the following command in your terminal to install the official Kegal API:
To get your kagal credentials, download the Kaggle.json file from your Kagle account settings by clicking “Create a New Token”.
Next, set the environmental variables in your local system:
- kaggle_username =
- Kaggle_api_Key =
- Kaggle_api_Key =
2. Contests
There are challenges in hosting Kagal competitions where you can solve machine learning problems, download data, offer predictions, and view your results on the leader board.
CLI helps you automatically automatically: Browse competitions, download files, offer solutions, and more.
List of list competitions
kaggle competitions list -s Kagal shows a list of competitions, which is optionally filtered by the search term. Useful for discovering new challenges to join.
Create a list of competitive files
kaggle competitions files Displays all files available for a specific competition, so you know what data is provided.
Download competition files
kaggle competitions download (-f ) (-p ) The competition downloads all or specific files to your local machine. Use -F to describe the file to set the download folder.
Submit in a competition
kaggle competitions submit -f -m "" Upload your solution file with an optional message that describes your submission.
Make a list of your requests
kaggle competitions submissions You show all your previous requests for a competition, including the score and the time stamp.
View Leader Board
kaggle competitions leaderboard (-s) The current leader shows the board for the competition. Use only to display high entries.
3. Datasis
Kagal Datasitis is a combination of the Community Statistics. Datastate CLI Command helps you find, download and upload datases, as well as manage the data version.
Create a list of datasis
Finding datases on Kagal, the search term is optionally filtered. Great to discover data for your plans.
Create a list of files in dataset
Displays all the files contained in a specific dataset, so you can see what is available before downloading.
Download Dataset Files
kaggle datasets download / (-f ) (--unzip) Downloads all or specific files from the dataset. Use -to automatically remove zip files.
Start the Dataset Metal data
Makes a metad data file in a folder, producing it to create a datastate or version of the version.
Create a new dataset
kaggle datasets create -p Uploads a new datastate from a folder containing your data and metadata.
Create a new dataset version
kaggle datasets version -p -m "" Uploads a new version of the current dataset, which describes the changes.
4. Notebook
Kagal notebooks are viable code pieces or notebooks. CLI allows you to, download, upload and test these notebooks, which is useful for sharing analysis or automatically.
Make a list of kernels
The public Kagal Notebook is found in your search term.
Get the kernel code
Download the code for a specific kernel in your local machine.
Start the kernel metad data
Makes a metadata file in a folder, producing it for kernel or update.
Update Colonel
Uploads a new code and runs the kernel, updates it on Kagal.
Get the production of kernel
kaggle kernels output / -p Downloads output files produced by Dana Run.
Check the status of the kernel
Shows the current status of the kernel (such as, running, complete, unsuccessful).
5. Model
Kagal models are manufactured by machine learning models you can share, reuse or deploy. CLI helps handle these models from handling and downloading these models and updating them.
The model list
Find a public model on the kagal that meets your search term.
Get a model
A model and its metad data downloads on your local machine.
Start the Model Metaata
The model creates a metadata file in a folder, producing the preparing of the creation.
Create a new model
Upload a new model to Kagal from your local folder.
Update a model
Uploads a new version of the current model.
Delete a model
Removes a model from Kagal.
6. Configures
The Kagal CLI configuration controls the default behavior, such as download locations and your default competition. Adjust these settings to make your work flu smooth.
See the structure
Your current Kagal shows CLI configuration settings (eg, default competition, download path).
Set the configuration
The setting price fixes, such as the default competition or download path.
format the formation
Returning to the default behavior, removes the cost of the sequence.
7. Indicators
- Use -h or Help after any command of detailed options and use of Any
- Use -v for CSV output, for calm mode -Q
- Before you can download or submit competitions, you have to accept competition rules on the Kagal website
Abid Ali Owan For,,,,,,,,,, for,, for,,,, for,,,, for,,, for,,,, for,,,, for,,,, for,,, for,,, for,,, for,,, for,,,, for,,, for,,, for,,,, for,,, for,,,, for,,, for,,, for,,,, for,,, for,,, for,,,, for,,, for,,,, for,,, for,,,, for,,, for,,,, for,,, for,,,, for,,,, for,,,, for,,,, for,,,, for,,,, for,,,, for,,, for,,, for,,, for,,, for,,,,, for,,,, for,,,, for,,,, for,, for,.@1abidaliawan) A certified data scientist is a professional who loves to create a machine learning model. Currently, he is focusing on creating content and writing technical blogs on machine learning and data science technologies. Abid has a master’s degree in technology management and a bachelor’s degree in telecommunications engineering. Its vision is to create AI products using a graph neural network for students with mental illness.