{"metadata":{"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"},"language_info":{"pygments_lexer":"ipython3","nbconvert_exporter":"python","version":"3.6.4","file_extension":".py","codemirror_mode":{"name":"ipython","version":3},"name":"python","mimetype":"text/x-python"}},"nbformat_minor":4,"nbformat":4,"cells":[{"cell_type":"code","source":"# This Python 3 environment comes with many helpful analytics libraries installed\n# It is defined by the kaggle/python Docker image: https://github.com/kaggle/docker-python\n# For example, here's several helpful packages to load\n\nimport numpy as np # linear algebra\nimport pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n\n# Input data files are available in the read-only \"../input/\" directory\n# For example, running this (by clicking run or pressing Shift+Enter) will list all files under the input directory\n\nimport os\nfor dirname, _, filenames in os.walk('/kaggle/input'):\n    for filename in filenames:\n        print(os.path.join(dirname, filename))\n\n# You can write up to 20GB to the current directory (/kaggle/working/) that gets preserved as output when you create a version using \"Save & Run All\" \n# You can also write temporary files to /kaggle/temp/, but they won't be saved outside of the current session","metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"from kaggle_datasets import KaggleDatasets","metadata":{"execution":{"iopub.status.busy":"2023-08-16T16:53:52.36011Z","iopub.execute_input":"2023-08-16T16:53:52.360795Z","iopub.status.idle":"2023-08-16T16:53:52.364868Z","shell.execute_reply.started":"2023-08-16T16:53:52.36075Z","shell.execute_reply":"2023-08-16T16:53:52.363935Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"print(KaggleDatasets().get_gcs_path('tfrecords-adddata3-public'))","metadata":{"execution":{"iopub.status.busy":"2023-08-16T16:53:59.965577Z","iopub.execute_input":"2023-08-16T16:53:59.965957Z","iopub.status.idle":"2023-08-16T16:54:02.384515Z","shell.execute_reply.started":"2023-08-16T16:53:59.965928Z","shell.execute_reply":"2023-08-16T16:54:02.383419Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"print(KaggleDatasets().get_gcs_path('tfrecords-adddata2-public'))","metadata":{"execution":{"iopub.status.busy":"2023-08-10T23:45:19.798629Z","iopub.execute_input":"2023-08-10T23:45:19.799064Z","iopub.status.idle":"2023-08-10T23:45:34.776948Z","shell.execute_reply.started":"2023-08-10T23:45:19.799033Z","shell.execute_reply":"2023-08-10T23:45:34.775564Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"print(KaggleDatasets().get_gcs_path('tfrecords-adddata1-public'))","metadata":{"execution":{"iopub.status.busy":"2023-08-11T00:43:05.638695Z","iopub.execute_input":"2023-08-11T00:43:05.639099Z","iopub.status.idle":"2023-08-11T00:43:20.353864Z","shell.execute_reply.started":"2023-08-11T00:43:05.639056Z","shell.execute_reply":"2023-08-11T00:43:20.352723Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"print(KaggleDatasets().get_gcs_path('tfrecordsuppledata'))","metadata":{"execution":{"iopub.status.busy":"2023-08-16T16:54:22.902017Z","iopub.execute_input":"2023-08-16T16:54:22.902389Z","iopub.status.idle":"2023-08-16T16:54:42.256933Z","shell.execute_reply.started":"2023-08-16T16:54:22.902359Z","shell.execute_reply":"2023-08-16T16:54:42.255718Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"","metadata":{},"execution_count":null,"outputs":[]}]}