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.
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. 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.
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 ~/.kaggle/kaggle.json (on Windows in the location C:\Users\<Windows-username>\.kaggle\kaggle.json - you can check the exact location, sans drive, with echo %HOMEPATH%). 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 ~/.kaggle/kaggle.json
You can also choose to export your Kaggle username and token to the environment:
export KAGGLE_USERNAME=datadinosaur export KAGGLE_KEY=xxxxxxxxxxxxxxIn addition, you can export any other configuration value that normally would be in the $HOME/.kaggle/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.
The command line tool supports the following commands:
kaggle competitions {list, files, download, submit, submissions, leaderboard} kaggle datasets {list, files, download, create, version, init} 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 models instances {get, init, create, delete, update} kaggle config {view, set, unset} See more details below for using each of these commands.
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 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 print in table format) Example:
kaggle competitions list -s health
kaggle competitions list --category gettingStarted
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 print in table format) -q, --quiet Suppress printing information about the upload/download progress Example:
kaggle competitions files favorita-grocery-sales-forecasting
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.
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.
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 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.
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 print in table format) -q, --quiet Suppress printing information about the upload/download progress Example:
kaggle competitions leaderboard favorita-grocery-sales-forecasting -s
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 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 print in table format) Example:
kaggle datasets list -s demographics
kaggle datasets list --sort-by votes
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) optional arguments: -h, --help show this help message and exit -v, --csv Print results in CSV format (if not set print in table format) Example:
kaggle datasets files zillow/zecon
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) 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 -f State_time_series.csv
Please note that BigQuery datasets cannot be downloaded.
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
If you want to create a new dataset, you need to initiate 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
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"
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
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
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 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 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
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/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/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
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
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
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 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
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 print in table format) Example:
kaggle models list -s llm
kaggle models list --sort-by downloadCount
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
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
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
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
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 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
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
If you want to create a new model instance, you need to initiate 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
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
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
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 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"
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
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
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 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:\
usage: kaggle config view [-h] optional arguments: -h, --help show this help message and exit Example:
kaggle config view
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
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
The Kaggle API is released under the Apache 2.0 license.