Kaggle API

Official API for https://www.kaggle.com, accessible using a command line tool implemented in Python 3.

Beta release - Kaggle reserves the right to modify the API functionality currently offered.

IMPORTANT: Competitions submissions using an API version prior to 1.5.0 may not work. If you are encountering difficulties with submitting to competitions, please check your version with kaggle --version. If it is below 1.5.0, please update with pip install kaggle --upgrade.

Installation

Ensure you have Python 3 and the package manager pip installed.

Run the following command to access the Kaggle API using the command line:

pip install kaggle (You may need to do pip install --user kaggle on Mac/Linux. This is recommended if problems come up during the installation process.) Installations done through the root user (i.e. sudo pip install kaggle) will not work correctly unless you understand what you're doing. Even then, they still might not work. User installs are strongly recommended in the case of permissions errors.

You can now use the kaggle command as shown in the examples below.

If you run into a kaggle: command not found error, ensure that your python binaries are on your path. You can see where kaggle is installed by doing pip uninstall kaggle and seeing where the binary is (then cancel the uninstall when prompted). For a local user install on Linux, the default location is ~/.local/bin. On Windows, the default location is $PYTHON_HOME/Scripts.

IMPORTANT: We do not offer Python 2 support. Please ensure that you are using Python 3 before reporting any issues.

API credentials

To use the Kaggle API, sign up for a Kaggle account at https://www.kaggle.com. Then go to the 'Account' tab of your user profile (https://www.kaggle.com/<username>/account) and select 'Create API Token'. This will trigger the download of kaggle.json, a file containing your API credentials. Place this file in the location appropriate for your operating system:

Linux: $XDG_CONFIG_HOME/kaggle/kaggle.json (defaults to ~/.config/kaggle/kaggle.json). The path ~/.kaggle/kaggle.json which was used by older versions of the tool is also still supported.
Windows: C:\Users\<Windows-username>\.kaggle\kaggle.json - you can check the exact location, sans drive, with echo %HOMEPATH%.
Other: ~/.kaggle/kaggle.json

You can define a shell environment variable KAGGLE_CONFIG_DIR to change this location to $KAGGLE_CONFIG_DIR/kaggle.json (on Windows it will be %KAGGLE_CONFIG_DIR%\kaggle.json).

For your security, ensure that other users of your computer do not have read access to your credentials. On Unix-based systems you can do this with the following command:

chmod 600 ~/.config/kaggle/kaggle.json

You can also choose to export your Kaggle username and token to the environment:

export KAGGLE_USERNAME=datadinosaur
export KAGGLE_KEY=xxxxxxxxxxxxxx

In addition, you can export any other configuration value that normally would be in the kaggle.json in the format 'KAGGLE_' (note uppercase).
For example, if the file had the variable "proxy" you would export KAGGLE_PROXY and it would be discovered by the client.

Commands

The command line tool supports the following commands:

kaggle competitions {list, files, download, submit, submissions, leaderboard}
kaggle datasets {list, files, download, create, version, init, metadata, status}
kaggle kernels {list, init, push, pull, output, status}
kaggle models {get, list, init, create, delete, update}
kaggle models instances {get, init, create, delete, update}
kaggle models instances versions {init, create, download, delete}
kaggle config {view, set, unset}

See more details below for using each of these commands.

Competitions

The API supports the following commands for Kaggle Competitions.

usage: kaggle competitions [-h]
                           {list,files,download,submit,submissions,leaderboard}
                           ...

optional arguments:
  -h, --help            show this help message and exit

commands:
  {list,files,download,submit,submissions,leaderboard}
    list                List available competitions
    files               List competition files
    download            Download competition files
    submit              Make a new competition submission
    submissions         Show your competition submissions
    leaderboard         Get competition leaderboard information

List competitions

usage: kaggle competitions list [-h] [--group GROUP] [--category CATEGORY] [--sort-by SORT_BY] [-p PAGE] [-s SEARCH] [-v]

optional arguments:
  -h, --help            show this help message and exit
  --group GROUP         Search for competitions in a specific group. Default is 'general'. Valid options are 'general', 'entered', and 'inClass'
  --category CATEGORY   Search for competitions of a specific category. Default is 'all'. Valid options are 'all', 'featured', 'research', 'recruitment', 'gettingStarted', 'masters', and 'playground'
  --sort-by SORT_BY     Sort list results. Default is 'latestDeadline'. Valid options are 'grouped', 'prize', 'earliestDeadline', 'latestDeadline', 'numberOfTeams', and 'recentlyCreated'
  -p PAGE, --page PAGE  Page number for results paging. Page size is 20 by default 
  -s SEARCH, --search SEARCH
                        Term(s) to search for
  -v, --csv             Print results in CSV format
                        (if not set then print in table format)

Example:

kaggle competitions list -s health

kaggle competitions list --category gettingStarted

List competition files

usage: kaggle competitions files [-h] [-v] [-q] [competition]

optional arguments:
  -h, --help   show this help message and exit
  competition  Competition URL suffix (use "kaggle competitions list" to show options)
               If empty, the default competition will be used (use "kaggle config set competition")"
  -v, --csv    Print results in CSV format (if not set then print in table format)
  -q, --quiet  Suppress printing information about the upload/download progress

Example:

kaggle competitions files favorita-grocery-sales-forecasting

Download competition files

usage: kaggle competitions download [-h] [-f FILE_NAME] [-p PATH] [-w] [-o]
                                    [-q]
                                    [competition]

optional arguments:
  -h, --help            show this help message and exit
  competition           Competition URL suffix (use "kaggle competitions list" to show options)
                        If empty, the default competition will be used (use "kaggle config set competition")"
  -f FILE_NAME, --file FILE_NAME
                        File name, all files downloaded if not provided
                        (use "kaggle competitions files -c <competition>" to show options)
  -p PATH, --path PATH  Folder where file(s) will be downloaded, defaults to current working directory
  -w, --wp              Download files to current working path
  -o, --force           Skip check whether local version of file is up to date, force file download
  -q, --quiet           Suppress printing information about the upload/download progress

Examples:

kaggle competitions download favorita-grocery-sales-forecasting

kaggle competitions download favorita-grocery-sales-forecasting -f test.csv.7z

Note: you will need to accept competition rules at https://www.kaggle.com/c/<competition-name>/rules.

Submit to a competition

usage: kaggle competitions submit [-h] -f FILE_NAME -m MESSAGE [-q]
                                  [competition]

required arguments:
  -f FILE_NAME, --file FILE_NAME
                        File for upload (full path)
  -m MESSAGE, --message MESSAGE
                        Message describing this submission

optional arguments:
  -h, --help            show this help message and exit
  competition           Competition URL suffix (use "kaggle competitions list" to show options)
                        If empty, the default competition will be used (use "kaggle config set competition")"
  -q, --quiet           Suppress printing information about the upload/download progress

Example:

kaggle competitions submit favorita-grocery-sales-forecasting -f sample_submission_favorita.csv.7z -m "My submission message"

Note: you will need to accept competition rules at https://www.kaggle.com/c/<competition-name>/rules.

List competition submissions

usage: kaggle competitions submissions [-h] [-v] [-q] [competition]

optional arguments:
  -h, --help   show this help message and exit
  competition  Competition URL suffix (use "kaggle competitions list" to show options)
               If empty, the default competition will be used (use "kaggle config set competition")"
  -v, --csv    Print results in CSV format (if not set then print in table format)
  -q, --quiet  Suppress printing information about the upload/download progress

Example:

kaggle competitions submissions favorita-grocery-sales-forecasting

Note: you will need to accept competition rules at https://www.kaggle.com/c/<competition-name>/rules.

Get competition leaderboard

usage: kaggle competitions leaderboard [-h] [-s] [-d] [-p PATH] [-v] [-q]
                                       [competition]

optional arguments:
  -h, --help            show this help message and exit
  competition           Competition URL suffix (use "kaggle competitions list" to show options)
                        If empty, the default competition will be used (use "kaggle config set competition")"
  -s, --show            Show the top of the leaderboard
  -d, --download        Download entire leaderboard
  -p PATH, --path PATH  Folder where file(s) will be downloaded, defaults to current working directory
  -v, --csv             Print results in CSV format (if not set then print in table format)
  -q, --quiet           Suppress printing information about the upload/download progress

Example:

kaggle competitions leaderboard favorita-grocery-sales-forecasting -s

Datasets

The API supports the following commands for Kaggle Datasets.

usage: kaggle datasets [-h]
                       {list,files,download,create,version,init,metadata,status} ...

optional arguments:
  -h, --help            show this help message and exit

commands:
  {list,files,download,create,version,init,metadata, status}
    list                List available datasets
    files               List dataset files
    download            Download dataset files
    create              Create a new dataset
    version             Create a new dataset version
    init                Initialize metadata file for dataset creation
    metadata            Download metadata about a dataset
    status              Get the creation status for a dataset

List datasets

usage: kaggle datasets list [-h] [--sort-by SORT_BY] [--min-size MIN_SIZE] [--max-size MAX_SIZE] [--file-type FILE_TYPE] [--license LICENSE_NAME] [--tags TAG_IDS] [-s SEARCH] [-m] [--user USER] [-p PAGE] [-v]

optional arguments:
  -h, --help            show this help message and exit
  --sort-by SORT_BY     Sort list results. Default is 'hottest'. Valid options are 'hottest', 'votes', 'updated', and 'active'
  --max-size MAX_SIZE   Specify the maximum size of the dataset to return (bytes)
  --min-size MIN_SIZE   Specify the minimum size of the dataset to return (bytes)
  --file-type FILE_TYPE Search for datasets with a specific file type. Default is 'all'. Valid options are 'all', 'csv', 'sqlite', 'json', and 'bigQuery'. Please note that bigQuery datasets cannot be downloaded
  --license LICENSE_NAME 
                        Search for datasets with a specific license. Default is 'all'. Valid options are 'all', 'cc', 'gpl', 'odb', and 'other'
  --tags TAG_IDS        Search for datasets that have specific tags. Tag list should be comma separated                      
  -s SEARCH, --search SEARCH
                        Term(s) to search for
  -m, --mine            Display only my items
  --user USER           Find public datasets owned by a specific user or organization
  -p PAGE, --page PAGE  Page number for results paging. Page size is 20 by default
  -v, --csv             Print results in CSV format (if not set then print in table format)

Example:

kaggle datasets list -s demographics

kaggle datasets list --sort-by votes

List files for a dataset

usage: kaggle datasets files [-h] [-v] [dataset]

required arguments:
  dataset               Dataset URL suffix in format <owner>/<dataset-name> (use "kaggle datasets list" to show options), or <owner>/<dataset-name>/<version-number> for a specific version

optional arguments:
  -h, --help  show this help message and exit
  -v, --csv   Print results in CSV format (if not set then print in table format)

Example:

kaggle datasets files zillow/zecon

kaggle datasets files zillow/zecon/3

Download dataset files

usage: kaggle datasets download [-h] [-f FILE_NAME] [-p PATH] [-w] [--unzip]
                                [-o] [-q]
                                [dataset]

required arguments:
  dataset               Dataset URL suffix in format <owner>/<dataset-name> (use "kaggle datasets list" to show options), or <owner>/<dataset-name>/<version-number> for a specific version

optional arguments:
  -h, --help            show this help message and exit
  -f FILE_NAME, --file FILE_NAME
                        File name, all files downloaded if not provided
                        (use "kaggle datasets files -d <dataset>" to show options)
  -p PATH, --path PATH  Folder where file(s) will be downloaded, defaults to current working directory
  -w, --wp              Download files to current working path
  --unzip               Unzip the downloaded file. Will delete the zip file when completed.
  -o, --force           Skip check whether local version of file is up to date, force file download
  -q, --quiet           Suppress printing information about the upload/download progress

Examples:

kaggle datasets download zillow/zecon

kaggle datasets download zillow/zecon/3

kaggle datasets download zillow/zecon -f State_time_series.csv

Please note that BigQuery datasets cannot be downloaded.

Initialize metadata file for dataset creation

usage: kaggle datasets init [-h] [-p FOLDER]

optional arguments:
  -h, --help            show this help message and exit
  -p FOLDER, --path FOLDER
                        Folder where the special dataset-metadata.json file (https://github.com/Kaggle/kaggle-api/wiki/Dataset-Metadata) will be created. Defaults to current working directory

Example:

kaggle datasets init -p /path/to/dataset

Create a new dataset

If you want to create a new dataset, you need to initialize metadata file at first. You could fulfill this by running kaggle datasets init as describe above.

usage: kaggle datasets create [-h] [-p FOLDER] [-u] [-q] [-t] [-r {skip,zip,tar}]

optional arguments:
  -h, --help            show this help message and exit
  -p FOLDER, --path FOLDER
                        Folder for upload, containing data files and a special dataset-metadata.json file (https://github.com/Kaggle/kaggle-api/wiki/Dataset-Metadata). Defaults to current working directory
  -u, --public          Create publicly (default is private)
  -q, --quiet           Suppress printing information about the upload/download progress
  -t, --keep-tabular    Do not convert tabular files to CSV (default is to convert)
  -r {skip,zip,tar}, --dir-mode {skip,zip,tar}
                        What to do with directories: "skip" - ignore; "zip" - compressed upload; "tar" - uncompressed upload

Example:

kaggle datasets create -p /path/to/dataset

Create a new dataset version

usage: kaggle datasets version [-h] -m VERSION_NOTES [-p FOLDER] [-q] [-t]
                               [-r {skip,zip,tar}] [-d]

required arguments:
  -m VERSION_NOTES, --message VERSION_NOTES
                        Message describing the new version

optional arguments:
  -h, --help            show this help message and exit
  -p FOLDER, --path FOLDER
                        Folder for upload, containing data files and a special dataset-metadata.json file (https://github.com/Kaggle/kaggle-api/wiki/Dataset-Metadata). Defaults to current working directory
  -q, --quiet           Suppress printing information about the upload/download progress
  -t, --keep-tabular    Do not convert tabular files to CSV (default is to convert)
  -r {skip,zip,tar}, --dir-mode {skip,zip,tar}
                        What to do with directories: "skip" - ignore; "zip" - compressed upload; "tar" - uncompressed upload
  -d, --delete-old-versions
                        Delete old versions of this dataset

Example:

kaggle datasets version -p /path/to/dataset -m "Updated data"

Download metadata for an existing dataset

usage: kaggle datasets metadata [-h] [-p PATH] [dataset]

required arguments:
  dataset               Dataset URL suffix in format <owner>/<dataset-name> (use "kaggle datasets list" to show options)

optional arguments:
  -h, --help            show this help message and exit
  -p PATH, --path PATH  Location to download dataset metadata to. Defaults to current working directory

Example:

kaggle datasets metadata -p /path/to/download zillow/zecon

Get dataset creation status

usage: kaggle datasets status [-h] [dataset]

required arguments:
  dataset     Dataset URL suffix in format <owner>/<dataset-name> (use "kaggle datasets list" to show options)

optional arguments:
  -h, --help  show this help message and exit

Example:

kaggle datasets status zillow/zecon

Kernels

The API supports the following commands for Kaggle Kernels.

usage: kaggle kernels [-h] {list,init,push,pull,output,status} ...

optional arguments:
  -h, --help            show this help message and exit

commands:
  {list,init,push,pull,output,status}
    list                List available kernels
    init                Initialize metadata file for a kernel
    push                Push new code to a kernel and run the kernel
    pull                Pull down code from a kernel
    output              Get data output from the latest kernel run
    status              Display the status of the latest kernel run

List kernels

usage: kaggle kernels list [-h] [-m] [-p PAGE] [--page-size PAGE_SIZE] [-s SEARCH] [-v]
                           [--parent PARENT] [--competition COMPETITION]
                           [--dataset DATASET]
                           [--user USER] [--language LANGUAGE]
                           [--kernel-type KERNEL_TYPE]
                           [--output-type OUTPUT_TYPE] [--sort-by SORT_BY]

optional arguments:
  -h, --help            show this help message and exit
  -m, --mine            Display only my items
  -p PAGE, --page PAGE  Page number for results paging. Page size is 20 by default
  --page-size PAGE_SIZE Number of items to show on a page. Default size is 20, max is 100
  -s SEARCH, --search SEARCH
                        Term(s) to search for
  -v, --csv             Print results in CSV format (if not set then print in table format)
  --parent PARENT       Find children of the specified parent kernel
  --competition COMPETITION
                        Find kernels for a given competition
  --dataset DATASET     Find kernels for a given dataset
  --user USER           Find kernels created by a given user
  --language LANGUAGE   Specify the language the kernel is written in. Default is 'all'. Valid options are 'all', 'python', 'r', 'sqlite', and 'julia'
  --kernel-type KERNEL_TYPE
                        Specify the type of kernel. Default is 'all'. Valid options are 'all', 'script', and 'notebook'
  --output-type OUTPUT_TYPE
                        Search for specific kernel output types. Default is 'all'. Valid options are 'all', 'visualizations', and 'data'
  --sort-by SORT_BY     Sort list results. Default is 'hotness'.  Valid options are 'hotness', 'commentCount', 'dateCreated', 'dateRun', 'relevance', 'scoreAscending', 'scoreDescending', 'viewCount', and 'voteCount'. 'relevance' is only applicable if a search term is specified.

Example:

kaggle kernels list -s titanic

kaggle kernels list --language python

Initialize metadata file for a kernel

usage: kaggle kernels init [-h] [-p FOLDER]

optional arguments:
  -h, --help            show this help message and exit
  -p FOLDER, --path FOLDER
                        Folder where the special kernel-metadata.json file (https://github.com/Kaggle/kaggle-api/wiki/Kernel-Metadata) will be created. Defaults to current working directory

Example:

kaggle kernels init -p /path/to/folder

Push a kernel

usage: kaggle kernels push [-h] -p FOLDER

optional arguments:
  -h, --help            show this help message and exit
  -p FOLDER, --path FOLDER
                        Folder for upload, containing data files and a special kernel-metadata.json file (https://github.com/Kaggle/kaggle-api/wiki/Kernel-Metadata). Defaults to current working directory

Example:

kaggle kernels push -p /path/to/folder

Pull a kernel

usage: kaggle kernels pull [-h] [-p PATH] [-w] [-m] [kernel]

optional arguments:
  -h, --help            show this help message and exit
  kernel                Kernel URL suffix in format <owner>/<kernel-name> (use "kaggle kernels list" to show options)
  -p PATH, --path PATH  Folder where file(s) will be downloaded, defaults to current working directory
  -w, --wp              Download files to current working path
  -m, --metadata        Generate metadata when pulling kernel

Example:

kaggle kernels pull rtatman/list-of-5-day-challenges -p /path/to/dest

Retrieve a kernel's output

usage: kaggle kernels output [-h] [-p PATH] [-w] [-o] [-q] [kernel]

required arguments:
  kernel      Kernel URL suffix in format <owner>/<kernel-name> (use "kaggle kernels list" to show options)

optional arguments:
  -h, --help            show this help message and exit
  -p PATH, --path PATH  Folder where file(s) will be downloaded, defaults to current working directory
  -w, --wp              Download files to current working path
  -o, --force           Skip check whether local version of file is up to date, force file download
  -q, --quiet           Suppress printing information about the upload/download progress

Example:

kaggle kernels output mrisdal/exploring-survival-on-the-titanic -p /path/to/dest

Get the status of the latest kernel run

usage: kaggle kernels status [-h] [kernel]

required arguments:
  kernel      Kernel URL suffix in format <owner>/<kernel-name> (use "kaggle kernels list" to show options)

optional arguments:
  -h, --help  show this help message and exit

Example:

kaggle kernels status mrisdal/exploring-survival-on-the-titanic

Models

The API supports the following commands for Kaggle Models.

usage: kaggle models [-h]
                     {get, list, init, create} ...

optional arguments:
  -h, --help            show this help message and exit

commands:
  {get, list, init, create}
    get                 Get the model
    list                List models
    init                Initialize metadata file for model creation
    create              Create a new model

Get model

usage: kaggle models get [-h] [-p FOLDER] [model]

required arguments:
  model                 Model URL suffix in format <owner>/<model-name>

optional arguments:
  -h, --help            show this help message and exit
  -p PATH, --path PATH  Folder where the special model-metadata.json file (https://github.com/Kaggle/kaggle-api/wiki/Model-Metadata) will be downloaded (if specified).

Example:

kaggle models get tensorflow/toxicity

List models

usage: kaggle models list [--sort-by SORT_BY] [-s SEARCH] [--owner OWNER] [--page-token PAGE_TOKEN] [--page-size PAGE_SIZE] [--csv]

optional arguments:
  -h, --help            show this help message and exit
  --sort-by SORT_BY     Sort list results. Default is 'hotness'. Valid options are 'hotness', 'downloadCount', 'voteCount', 'notebookCount' and 'createTime'
  -s SEARCH, --search SEARCH
                        Term(s) to search for
  --owner OWNER         Find models owned by a specific user or organization
  --page-token PAGE_TOKEN  
                        Page token for pagination
  --page-size PAGE_SIZE Number of items to show on a page. Default size is 20, max is 50
  -v, --csv             Print results in CSV format (if not set then print in table format)

Example:

kaggle models list -s llm

kaggle models list --sort-by downloadCount

Initialize metadata file for a model

usage: kaggle models init [-h] [-p FOLDER]

optional arguments:
  -h, --help            show this help message and exit
  -p FOLDER, --path FOLDER
                        Folder to create the model-metadata.json file (https://github.com/Kaggle/kaggle-api/wiki/Model-Metadata). Defaults to current working directory

Example:

kaggle models init -p /path/to/model

Create a new model

If you want to create a new model, you need to initiate metadata file at first. You could fulfill this by running kaggle models init as describe above.

usage: kaggle models create [-h] [-p FOLDER]

optional arguments:
  -h, --help            show this help message and exit
  -p FOLDER, --path FOLDER
                        Folder containing the special model-metadata.json file (https://github.com/Kaggle/kaggle-api/wiki/Model-Metadata). Defaults to current working directory

Example:

kaggle models create -p /path/to/model

Delete model

usage: kaggle models delete [-h] [model]

required arguments:
  model       Model URL suffix in format <owner>/<model-name>

optional arguments:
  -h, --help  show this help message and exit

Example:

kaggle models delete tensorflow/toxicity

Update a model

If you want to update a model, you need a metadata file at first. You can fetch the data by running kaggle models get owner/slug -p folder.

usage: kaggle models update [-h] [-p FOLDER]

optional arguments:
  -h, --help            show this help message and exit
  -p FOLDER, --path FOLDER
                        Folder containing the special model-metadata.json file (https://github.com/Kaggle/kaggle-api/wiki/Model-Metadata). Defaults to current working directory

Example:

kaggle models update -p /path/to/model

Model Instances

The API supports the following commands for Kaggle Model Instances.

usage: kaggle models instances [-h]
                             {init, create, delete, update} ...

optional arguments:
  -h, --help            show this help message and exit

commands:
  {get, init, create, delete}
    get                 Get a model instance
    init                Initialize metadata file for model instance creation
    create              Create a new model instance
    delete              Delete a model instance
    update              Update a model instance

Get model instance

usage: kaggle models instances get [-h] [-p FOLDER] [modelInstance]

required arguments:
  modelInstance         Model Instance URL suffix in format <owner>/<model-name>/<framework>/<instance-slug>

optional arguments:
  -h, --help            show this help message and exit
  -p PATH, --path PATH  Folder where the special model-instance-metadata.json file (https://github.com/Kaggle/kaggle-api/wiki/Model-Metadata) will be downloaded (if specified).

Example:

kaggle models instances get tensorflow/toxicity/tfjs/default

Initialize metadata file for a model instance

usage: kaggle models instances init [-h] [-p FOLDER]

optional arguments:
  -h, --help            show this help message and exit
  -p FOLDER, --path FOLDER
                        Folder to create the model-instance-metadata.json file (https://github.com/Kaggle/kaggle-api/wiki/Model-Metadata). Defaults to current working directory

Example:

kaggle models instances init -p /path/to/modelinstance

Create a new model instance

If you want to create a new model instance, you need to initialize metadata file at first. You could fulfill this by running kaggle models instances init as describe above.

usage: kaggle models instances create [-h] [-p FOLDER]

optional arguments:
  -h, --help            show this help message and exit
  -p FOLDER, --path FOLDER
                        Folder containing the special model-instance-metadata.json file (https://github.com/Kaggle/kaggle-api/wiki/Model-Metadata). Defaults to current working directory
  -q, --quiet           Suppress printing information about the upload progress
  -r {skip,zip,tar}, --dir-mode {skip,zip,tar}
                        What to do with directories: "skip" - ignore; "zip" - compressed upload; "tar" - uncompressed upload

Example:

kaggle models instances create -p /path/to/modelinstance

Delete model instance

usage: kaggle models instances delete [-h] [modelInstance]

required arguments:
  modelInstance         Model Instance URL suffix in format <owner>/<model-name>/<framework>/<instance-slug>

optional arguments:
  -h, --help     show this help message and exit

Example:

kaggle models instances delete tensorflow/toxicity/tfjs/default

Update a model instance

If you want to update a model instance, you need a metadata file at first. You can fetch the data by running kaggle models instances get owner-slug/model-slug/framework/instance-slug -p folder.

usage: kaggle models instances update [-h] [-p FOLDER]

optional arguments:
  -h, --help            show this help message and exit
  -p FOLDER, --path FOLDER
                        Folder containing the special model-instance-metadata.json file (https://github.com/Kaggle/kaggle-api/wiki/Model-Metadata). Defaults to current working directory

Example:

kaggle models instances update -p /path/to/model

Model Instance Versions

The API supports the following commands for Kaggle Model Instance Versions.

usage: kaggle models instances versions [-h]
                             {init, create, download, delete} ...

optional arguments:
  -h, --help            show this help message and exit

commands:
  {create, download, delete}
    create              Create a new model instance version
    download            Download a model instance version
    delete              Delete a model instance version

Create a new model instance version

usage: kaggle models instances versions create [-h] [modelInstance] [-p FOLDER] [-n NOTES]

required arguments:
  modelInstance         Model Instance URL suffix in format <owner>/<model-name>/<framework>/<instance-slug>

optional arguments:
  -h, --help            show this help message and exit
  -p FOLDER, --path FOLDER
                        Folder containing the model files to upload
  -n, --version-notes NOTES
                        Version notes to record for this new version
  -q, --quiet           Suppress printing information about the upload progress
  -r {skip,zip,tar}, --dir-mode {skip,zip,tar}
                        What to do with directories: "skip" - ignore; "zip" - compressed upload; "tar" - uncompressed upload

Example:

kaggle models instances versions create tensorflow/toxicity/tfjs/default -p /path/to/files -n "updated weights"

Download a model instance version

usage: kaggle models instances versions download [-h] [-p PATH] [--untar] [-f] [-q] [modelInstanceVersion]

required arguments:
  modelInstanceVersion  Model Instance version URL suffix in format <owner>/<model-name>/<framework>/<instance-slug>/<version_number>

optional arguments:
  -h, --help            show this help message and exit
  -p PATH, --path PATH  Folder where file(s) will be downloaded, defaults to current working directory
  --untar               Untar the downloaded file. Will delete the tar file when completed.
  -f, --force           Skip check whether local version of file is up to date, force file download
  -q, --quiet           Suppress printing information about the download progress

Examples:

kaggle models instances versions download tensorflow/toxicity/tfjs/default/1

Delete model instance

usage: kaggle models instances versions delete [-h] [modelInstanceVersion]

required arguments:
  modelInstanceVersion  Model Instance version URL suffix in format <owner>/<model-name>/<framework>/<instance-slug>/<version_number>

optional arguments:
  -h, --help            show this help message and exit

Example:

kaggle models instances versions delete tensorflow/toxicity/tfjs/default/1

Config

The API supports the following commands for configuration.

usage: kaggle config [-h] {view,set,unset} ...

optional arguments:
  -h, --help        show this help message and exit

commands:
  {view,set,unset}
    view            View current config values
    set             Set a configuration value
    unset           Clear a configuration value

View current config values

usage: kaggle config path [-h] [-p PATH]

optional arguments:
  -h, --help            show this help message and exit
  -p PATH, --path PATH  folder where file(s) will be downloaded, defaults to current working directory

Example:

kaggle config path -p C:\

View current config values

usage: kaggle config view [-h]

optional arguments:
  -h, --help  show this help message and exit

Example:

kaggle config view

Set a configuration value

usage: kaggle config set [-h] -n NAME -v VALUE

required arguments:
  -n NAME, --name NAME  Name of the configuration parameter
                        (one of competition, path, proxy)
  -v VALUE, --value VALUE
                        Value of the configuration parameter, valid values depending on name
                        - competition: Competition URL suffix (use "kaggle competitions list" to show options)
                        - path: Folder where file(s) will be downloaded, defaults to current working directory
                        - proxy: Proxy for HTTP requests

Example:

kaggle config set -n competition -v titanic

Clear a configuration value

usage: kaggle config unset [-h] -n NAME

required arguments:
  -n NAME, --name NAME  Name of the configuration parameter
                        (one of competition, path, proxy)

Example:

kaggle config unset -n competition

License

The Kaggle API is released under the Apache 2.0 license.

Files

README.md

Latest commit

History

README.md

File metadata and controls

Kaggle API

Installation

API credentials

Commands

Competitions

List competitions

List competition files

Download competition files

Submit to a competition

List competition submissions

Get competition leaderboard

Datasets

List datasets

List files for a dataset

Download dataset files

Initialize metadata file for dataset creation

Create a new dataset

Create a new dataset version

Download metadata for an existing dataset

Get dataset creation status

Kernels

List kernels

Initialize metadata file for a kernel

Push a kernel

Pull a kernel

Retrieve a kernel's output

Get the status of the latest kernel run

Models

Get model

List models

Initialize metadata file for a model

Create a new model

Delete model

Update a model

Model Instances

Get model instance

Initialize metadata file for a model instance

Create a new model instance

Delete model instance

Update a model instance

Model Instance Versions

Create a new model instance version

Download a model instance version

Delete model instance

Config

View current config values

View current config values

Set a configuration value

Clear a configuration value

License