your-favourite-notebooks-sorted-by-date-upvoted.ipynb

{"cells":[{"source":"<a href=\"https://www.kaggle.com/code/sahidvelji/your-favourite-notebooks-sorted-by-date-upvoted?scriptVersionId=98954341\" target=\"_blank\"><img align=\"left\" alt=\"Kaggle\" title=\"Open in Kaggle\" src=\"https://kaggle.com/static/images/open-in-kaggle.svg\"></a>","metadata":{},"cell_type":"markdown","outputs":[],"execution_count":0},{"cell_type":"markdown","id":"b4f309b5","metadata":{"papermill":{"duration":0.004001,"end_time":"2022-06-21T13:25:43.323798","exception":false,"start_time":"2022-06-21T13:25:43.319797","status":"completed"},"tags":[]},"source":["# Your favourite notebooks sorted by date upvoted"]},{"cell_type":"markdown","id":"63db2d59","metadata":{"papermill":{"duration":0.002849,"end_time":"2022-06-21T13:25:43.329863","exception":false,"start_time":"2022-06-21T13:25:43.327014","status":"completed"},"tags":[]},"source":["Since there is currently no option to sort notebooks by date upvoted in the \"Favorites\" tab, I decided that it wouldn't take long for me to implement this using [Meta Kaggle](https://www.kaggle.com/kaggle/meta-kaggle)."]},{"cell_type":"code","execution_count":1,"id":"fe8c3fd2","metadata":{"_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","_kg_hide-input":true,"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","execution":{"iopub.execute_input":"2022-06-21T13:25:43.337854Z","iopub.status.busy":"2022-06-21T13:25:43.337237Z","iopub.status.idle":"2022-06-21T13:25:43.354101Z","shell.execute_reply":"2022-06-21T13:25:43.353321Z"},"papermill":{"duration":0.023424,"end_time":"2022-06-21T13:25:43.356187","exception":false,"start_time":"2022-06-21T13:25:43.332763","status":"completed"},"tags":[]},"outputs":[{"data":{"application/javascript":["IPython.OutputArea.prototype._should_scroll = function(lines) {\n","    return false;\n","}\n"],"text/plain":["<IPython.core.display.Javascript object>"]},"metadata":{},"output_type":"display_data"}],"source":["%%javascript\n","IPython.OutputArea.prototype._should_scroll = function(lines) {\n","    return false;\n","}"]},{"cell_type":"code","execution_count":2,"id":"96f35e39","metadata":{"_cell_guid":"79c7e3d0-c299-4dcb-8224-4455121ee9b0","_kg_hide-input":true,"_uuid":"d629ff2d2480ee46fbb7e2d37f6b5fab8052498a","execution":{"iopub.execute_input":"2022-06-21T13:25:43.364246Z","iopub.status.busy":"2022-06-21T13:25:43.363761Z","iopub.status.idle":"2022-06-21T13:25:43.370431Z","shell.execute_reply":"2022-06-21T13:25:43.369824Z"},"papermill":{"duration":0.013041,"end_time":"2022-06-21T13:25:43.372407","exception":false,"start_time":"2022-06-21T13:25:43.359366","status":"completed"},"tags":[]},"outputs":[],"source":["import numpy as np\n","import pandas as pd\n","from IPython.display import display, HTML, Markdown\n","from pathlib import Path\n","        \n","KAGGLE_BASE_URL = \"https://www.kaggle.com/\"\n","PERFORMANCE_TIERS = {0: 'Novice',\n","                     1: 'Contributor',\n","                     2: 'Expert',\n","                     3: 'Master',\n","                     4: 'Grandmaster',\n","                     5: 'Staff'\n","                    }\n","MEDAL_TIERS = {1: 'golds',\n","               2: 'silvers',\n","               3: 'bronzes'\n","              }\n","medals = {i: f'<img style=\"float:left;padding-right:2px\" src=\"https://kaggle.com/static/images/medals/notebooks/{MEDAL_TIERS[i]}@1x.png\">' for i in range(1, 4)}\n","avatiers = {i: f'<img src=\"https://kaggle.com/static/images/avatier/avatier-{PERFORMANCE_TIERS[i].lower()}@2x.png\">' for i in range(6)}"]},{"cell_type":"code","execution_count":3,"id":"6b292690","metadata":{"_kg_hide-input":true,"execution":{"iopub.execute_input":"2022-06-21T13:25:43.38301Z","iopub.status.busy":"2022-06-21T13:25:43.382636Z","iopub.status.idle":"2022-06-21T13:27:32.775801Z","shell.execute_reply":"2022-06-21T13:27:32.775025Z"},"papermill":{"duration":109.402443,"end_time":"2022-06-21T13:27:32.778286","exception":false,"start_time":"2022-06-21T13:25:43.375843","status":"completed"},"tags":[]},"outputs":[],"source":["path = Path('/kaggle/input/meta-kaggle')\n","\n","kernels = pd.read_csv(path/'Kernels.csv', \n","                      parse_dates=['CreationDate', 'MadePublicDate', 'MedalAwardDate'],\n","                      infer_datetime_format=True\n","                     )\n","kernel_versions = pd.read_csv(path/'KernelVersions.csv', \n","                              parse_dates=['CreationDate'],\n","                              infer_datetime_format=True\n","                             )\n","kernel_votes = pd.read_csv(path/'KernelVotes.csv', \n","                           parse_dates=['VoteDate'], infer_datetime_format=True\n","                          )\n","\n","users = pd.read_csv(path/'Users.csv',\n","                    parse_dates=['RegisterDate'], \n","                    infer_datetime_format=True\n","                   )"]},{"cell_type":"markdown","id":"47c30128","metadata":{"papermill":{"duration":0.003224,"end_time":"2022-06-21T13:27:32.785462","exception":false,"start_time":"2022-06-21T13:27:32.782238","status":"completed"},"tags":[]},"source":["To use this notebook:\n","1. Fork this notebook by clicking on `Copy and Edit`.\n","1. Set the username variable to your own username.\n","1. Select sorting and filtering options below and run the notebook."]},{"cell_type":"code","execution_count":4,"id":"5962a4a2","metadata":{"execution":{"iopub.execute_input":"2022-06-21T13:27:32.793842Z","iopub.status.busy":"2022-06-21T13:27:32.793323Z","iopub.status.idle":"2022-06-21T13:27:32.797093Z","shell.execute_reply":"2022-06-21T13:27:32.796481Z"},"papermill":{"duration":0.01028,"end_time":"2022-06-21T13:27:32.798928","exception":false,"start_time":"2022-06-21T13:27:32.788648","status":"completed"},"tags":[]},"outputs":[],"source":["username = 'sahidvelji'\n","\n","MOST_RECENT_FIRST = True\n","INCLUDE_SELF_VOTES = True\n","NUM_RESULTS = 20"]},{"cell_type":"code","execution_count":5,"id":"b0498091","metadata":{"execution":{"iopub.execute_input":"2022-06-21T13:27:32.807119Z","iopub.status.busy":"2022-06-21T13:27:32.806692Z","iopub.status.idle":"2022-06-21T13:27:39.665757Z","shell.execute_reply":"2022-06-21T13:27:39.664881Z"},"papermill":{"duration":6.866105,"end_time":"2022-06-21T13:27:39.668385","exception":false,"start_time":"2022-06-21T13:27:32.80228","status":"completed"},"tags":[]},"outputs":[{"data":{"text/markdown":["# Notebooks upvoted by Sahid Velji"],"text/plain":["<IPython.core.display.Markdown object>"]},"metadata":{},"output_type":"display_data"},{"data":{"text/html":["<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th>VoteDate</th>\n","      <th>TotalVotes</th>\n","      <th>User</th>\n","      <th>URL</th>\n","      <th>TotalComments</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <td style=\"text-align:left\">2022-06-20</td>\n","      <td style=\"text-align:left\">450</td>\n","      <td style=\"text-align:left\"><a href=\"https://www.kaggle.com/jhoward\">Jeremy Howard</a><img src=\"https://kaggle.com/static/images/avatier/avatier-grandmaster@2x.png\"></td>\n","      <td style=\"text-align:left\"><img style=\"float:left;padding-right:2px\" src=\"https://kaggle.com/static/images/medals/notebooks/golds@1x.png\"><a href=\"https://www.kaggle.com/jhoward/iterate-like-a-grandmaster\">Iterate like a grandmaster!</a></td>\n","      <td style=\"text-align:left\">30</td>\n","    </tr>\n","    <tr>\n","      <td style=\"text-align:left\">2022-06-18</td>\n","      <td style=\"text-align:left\">19</td>\n","      <td style=\"text-align:left\"><a href=\"https://www.kaggle.com/sahidvelji\">Sahid Velji</a><img src=\"https://kaggle.com/static/images/avatier/avatier-expert@2x.png\"></td>\n","      <td style=\"text-align:left\"><img style=\"float:left;padding-right:2px\" src=\"https://kaggle.com/static/images/medals/notebooks/bronzes@1x.png\"><a href=\"https://www.kaggle.com/sahidvelji/self-follows-on-kaggle\">Self-follows on Kaggle</a></td>\n","      <td style=\"text-align:left\">2</td>\n","    </tr>\n","    <tr>\n","      <td style=\"text-align:left\">2020-10-13</td>\n","      <td style=\"text-align:left\">1293</td>\n","      <td style=\"text-align:left\"><a href=\"https://www.kaggle.com/rohanrao\">Vopani</a><img src=\"https://kaggle.com/static/images/avatier/avatier-grandmaster@2x.png\"></td>\n","      <td style=\"text-align:left\"><img style=\"float:left;padding-right:2px\" src=\"https://kaggle.com/static/images/medals/notebooks/golds@1x.png\"><a href=\"https://www.kaggle.com/rohanrao/tutorial-on-reading-large-datasets\">Tutorial on reading large datasets</a></td>\n","      <td style=\"text-align:left\">106</td>\n","    </tr>\n","    <tr>\n","      <td style=\"text-align:left\">2020-10-06</td>\n","      <td style=\"text-align:left\">31</td>\n","      <td style=\"text-align:left\"><a href=\"https://www.kaggle.com/raghaw\">Raghawendra Singh</a><img src=\"https://kaggle.com/static/images/avatier/avatier-master@2x.png\"></td>\n","      <td style=\"text-align:left\"><img style=\"float:left;padding-right:2px\" src=\"https://kaggle.com/static/images/medals/notebooks/silvers@1x.png\"><a href=\"https://www.kaggle.com/raghaw/panda-medium-resolution-dataset-25x256x256\">PANDA_medium_resolution_dataset_25x256x256</a></td>\n","      <td style=\"text-align:left\">9</td>\n","    </tr>\n","    <tr>\n","      <td style=\"text-align:left\">2020-09-06</td>\n","      <td style=\"text-align:left\">362</td>\n","      <td style=\"text-align:left\"><a href=\"https://www.kaggle.com/yasufuminakama\">Y.Nakama</a><img src=\"https://kaggle.com/static/images/avatier/avatier-grandmaster@2x.png\"></td>\n","      <td style=\"text-align:left\"><img style=\"float:left;padding-right:2px\" src=\"https://kaggle.com/static/images/medals/notebooks/golds@1x.png\"><a href=\"https://www.kaggle.com/yasufuminakama/moa-pytorch-nn-starter\">MoA / PyTorch NN starter</a></td>\n","      <td style=\"text-align:left\">26</td>\n","    </tr>\n","    <tr>\n","      <td style=\"text-align:left\">2020-09-04</td>\n","      <td style=\"text-align:left\">227</td>\n","      <td style=\"text-align:left\"><a href=\"https://www.kaggle.com/dansbecker\">DanB</a><img src=\"https://kaggle.com/static/images/avatier/avatier-grandmaster@2x.png\"></td>\n","      <td style=\"text-align:left\"><img style=\"float:left;padding-right:2px\" src=\"https://kaggle.com/static/images/medals/notebooks/golds@1x.png\"><a href=\"https://www.kaggle.com/dansbecker/what-is-log-loss\">What is Log Loss?</a></td>\n","      <td style=\"text-align:left\">25</td>\n","    </tr>\n","    <tr>\n","      <td style=\"text-align:left\">2020-08-31</td>\n","      <td style=\"text-align:left\">14</td>\n","      <td style=\"text-align:left\"><a href=\"https://www.kaggle.com/sahidvelji\">Sahid Velji</a><img src=\"https://kaggle.com/static/images/avatier/avatier-expert@2x.png\"></td>\n","      <td style=\"text-align:left\"><img style=\"float:left;padding-right:2px\" src=\"https://kaggle.com/static/images/medals/notebooks/bronzes@1x.png\"><a href=\"https://www.kaggle.com/sahidvelji/your-favourite-notebooks-sorted-by-date-upvoted\">Your favourite notebooks sorted by date upvoted</a></td>\n","      <td style=\"text-align:left\">5</td>\n","    </tr>\n","    <tr>\n","      <td style=\"text-align:left\">2020-08-31</td>\n","      <td style=\"text-align:left\">12</td>\n","      <td style=\"text-align:left\"><a href=\"https://www.kaggle.com/jtrotman\">James Trotman</a><img src=\"https://kaggle.com/static/images/avatier/avatier-master@2x.png\"></td>\n","      <td style=\"text-align:left\"><img style=\"float:left;padding-right:2px\" src=\"https://kaggle.com/static/images/medals/notebooks/bronzes@1x.png\"><a href=\"https://www.kaggle.com/jtrotman/discussion-hotness-plots\">Discussion Hotness Plots</a></td>\n","      <td style=\"text-align:left\">2</td>\n","    </tr>\n","    <tr>\n","      <td style=\"text-align:left\">2020-08-28</td>\n","      <td style=\"text-align:left\">83</td>\n","      <td style=\"text-align:left\"><a href=\"https://www.kaggle.com/ruchi798\">Ruchi Bhatia</a><img src=\"https://kaggle.com/static/images/avatier/avatier-grandmaster@2x.png\"></td>\n","      <td style=\"text-align:left\"><img style=\"float:left;padding-right:2px\" src=\"https://kaggle.com/static/images/medals/notebooks/golds@1x.png\"><a href=\"https://www.kaggle.com/ruchi798/movies-data-collection-eda-using-tableau\">Movies on streaming platforms-EDA using Tableau</a></td>\n","      <td style=\"text-align:left\">4</td>\n","    </tr>\n","    <tr>\n","      <td style=\"text-align:left\">2020-08-25</td>\n","      <td style=\"text-align:left\">10</td>\n","      <td style=\"text-align:left\"><a href=\"https://www.kaggle.com/sahidvelji\">Sahid Velji</a><img src=\"https://kaggle.com/static/images/avatier/avatier-expert@2x.png\"></td>\n","      <td style=\"text-align:left\"><img style=\"float:left;padding-right:2px\" src=\"https://kaggle.com/static/images/medals/notebooks/bronzes@1x.png\"><a href=\"https://www.kaggle.com/sahidvelji/mnist-digits-with-pytorch\">MNIST digits with PyTorch</a></td>\n","      <td style=\"text-align:left\">1</td>\n","    </tr>\n","    <tr>\n","      <td style=\"text-align:left\">2020-08-20</td>\n","      <td style=\"text-align:left\">113</td>\n","      <td style=\"text-align:left\"><a href=\"https://www.kaggle.com/rtatman\">Rachael Tatman</a><img src=\"https://kaggle.com/static/images/avatier/avatier-grandmaster@2x.png\"></td>\n","      <td style=\"text-align:left\"><img style=\"float:left;padding-right:2px\" src=\"https://kaggle.com/static/images/medals/notebooks/golds@1x.png\"><a href=\"https://www.kaggle.com/rtatman/bigquery-machine-learning-tutorial\">BigQuery Machine Learning Tutorial</a></td>\n","      <td style=\"text-align:left\">40</td>\n","    </tr>\n","    <tr>\n","      <td style=\"text-align:left\">2020-08-12</td>\n","      <td style=\"text-align:left\">101</td>\n","      <td style=\"text-align:left\"><a href=\"https://www.kaggle.com/mariapushkareva\">Marie</a><img src=\"https://kaggle.com/static/images/avatier/avatier-master@2x.png\"></td>\n","      <td style=\"text-align:left\"><img style=\"float:left;padding-right:2px\" src=\"https://kaggle.com/static/images/medals/notebooks/golds@1x.png\"><a href=\"https://www.kaggle.com/mariapushkareva/world-development-indicators-with-sql\">World Development Indicators with SQL</a></td>\n","      <td style=\"text-align:left\">46</td>\n","    </tr>\n","    <tr>\n","      <td style=\"text-align:left\">2020-08-09</td>\n","      <td style=\"text-align:left\">664</td>\n","      <td style=\"text-align:left\"><a href=\"https://www.kaggle.com/cdeotte\">Chris Deotte</a><img src=\"https://kaggle.com/static/images/avatier/avatier-grandmaster@2x.png\"></td>\n","      <td style=\"text-align:left\"><img style=\"float:left;padding-right:2px\" src=\"https://kaggle.com/static/images/medals/notebooks/golds@1x.png\"><a href=\"https://www.kaggle.com/cdeotte/25-million-images-0-99757-mnist\">25 Million Images! [0.99757] MNIST</a></td>\n","      <td style=\"text-align:left\">160</td>\n","    </tr>\n","    <tr>\n","      <td style=\"text-align:left\">2020-08-09</td>\n","      <td style=\"text-align:left\">602</td>\n","      <td style=\"text-align:left\"><a href=\"https://www.kaggle.com/cdeotte\">Chris Deotte</a><img src=\"https://kaggle.com/static/images/avatier/avatier-grandmaster@2x.png\"></td>\n","      <td style=\"text-align:left\"><img style=\"float:left;padding-right:2px\" src=\"https://kaggle.com/static/images/medals/notebooks/golds@1x.png\"><a href=\"https://www.kaggle.com/cdeotte/how-to-choose-cnn-architecture-mnist\">How to choose CNN Architecture MNIST</a></td>\n","      <td style=\"text-align:left\">111</td>\n","    </tr>\n","    <tr>\n","      <td style=\"text-align:left\">2020-08-06</td>\n","      <td style=\"text-align:left\">17</td>\n","      <td style=\"text-align:left\"><a href=\"https://www.kaggle.com/carlmcbrideellis\">Carl McBride Ellis</a><img src=\"https://kaggle.com/static/images/avatier/avatier-grandmaster@2x.png\"></td>\n","      <td style=\"text-align:left\"><img style=\"float:left;padding-right:2px\" src=\"https://kaggle.com/static/images/medals/notebooks/bronzes@1x.png\"><a href=\"https://www.kaggle.com/carlmcbrideellis/the-kaggle-working-week\">The kaggle working week</a></td>\n","      <td style=\"text-align:left\">4</td>\n","    </tr>\n","    <tr>\n","      <td style=\"text-align:left\">2020-08-06</td>\n","      <td style=\"text-align:left\">199</td>\n","      <td style=\"text-align:left\"><a href=\"https://www.kaggle.com/andradaolteanu\">Andrada Olteanu</a><img src=\"https://kaggle.com/static/images/avatier/avatier-grandmaster@2x.png\"></td>\n","      <td style=\"text-align:left\"><img style=\"float:left;padding-right:2px\" src=\"https://kaggle.com/static/images/medals/notebooks/golds@1x.png\"><a href=\"https://www.kaggle.com/andradaolteanu/melanoma-competiton-aug-resnet-effnet-lb-0-91\">Melanoma Competiton: Aug + ResNet/EffNet (LB 0.91)</a></td>\n","      <td style=\"text-align:left\">39</td>\n","    </tr>\n","    <tr>\n","      <td style=\"text-align:left\">2020-08-05</td>\n","      <td style=\"text-align:left\">106</td>\n","      <td style=\"text-align:left\"><a href=\"https://www.kaggle.com/abhinand05\">Abhinand</a><img src=\"https://kaggle.com/static/images/avatier/avatier-master@2x.png\"></td>\n","      <td style=\"text-align:left\"><img style=\"float:left;padding-right:2px\" src=\"https://kaggle.com/static/images/medals/notebooks/golds@1x.png\"><a href=\"https://www.kaggle.com/abhinand05/mnist-introduction-to-computervision-with-pytorch\">MNIST: Introduction to ComputerVision with PyTorch</a></td>\n","      <td style=\"text-align:left\">10</td>\n","    </tr>\n","    <tr>\n","      <td style=\"text-align:left\">2020-08-05</td>\n","      <td style=\"text-align:left\">123</td>\n","      <td style=\"text-align:left\"><a href=\"https://www.kaggle.com/juiyangchang\">Ryan Chang</a><img src=\"https://kaggle.com/static/images/avatier/avatier-novice@2x.png\"></td>\n","      <td style=\"text-align:left\"><img style=\"float:left;padding-right:2px\" src=\"https://kaggle.com/static/images/medals/notebooks/golds@1x.png\"><a href=\"https://www.kaggle.com/juiyangchang/cnn-with-pytorch-0-995-accuracy\">CNN with PyTorch (0.995 Accuracy)</a></td>\n","      <td style=\"text-align:left\">18</td>\n","    </tr>\n","    <tr>\n","      <td style=\"text-align:left\">2020-07-31</td>\n","      <td style=\"text-align:left\">46</td>\n","      <td style=\"text-align:left\"><a href=\"https://www.kaggle.com/philippsinger\">Psi</a><img src=\"https://kaggle.com/static/images/avatier/avatier-grandmaster@2x.png\"></td>\n","      <td style=\"text-align:left\"><img style=\"float:left;padding-right:2px\" src=\"https://kaggle.com/static/images/medals/notebooks/silvers@1x.png\"><a href=\"https://www.kaggle.com/philippsinger/xlm-roberta-large-pytorch-pytorch-tpu\">XLM-Roberta-Large Pytorch Pytorch TPU</a></td>\n","      <td style=\"text-align:left\">1</td>\n","    </tr>\n","    <tr>\n","      <td style=\"text-align:left\">2020-07-28</td>\n","      <td style=\"text-align:left\">77</td>\n","      <td style=\"text-align:left\"><a href=\"https://www.kaggle.com/jack89roberts\">Jack Roberts</a><img src=\"https://kaggle.com/static/images/avatier/avatier-contributor@2x.png\"></td>\n","      <td style=\"text-align:left\"><img style=\"float:left;padding-right:2px\" src=\"https://kaggle.com/static/images/medals/notebooks/golds@1x.png\"><a href=\"https://www.kaggle.com/jack89roberts/the-journey-of-an-image-through-a-neural-network\">The Journey of an Image Through a Neural Network</a></td>\n","      <td style=\"text-align:left\">10</td>\n","    </tr>\n","  </tbody>\n","</table>"],"text/plain":["<IPython.core.display.HTML object>"]},"execution_count":5,"metadata":{},"output_type":"execute_result"}],"source":["userid, displayname = users.loc[users['UserName'].eq(username), ['Id', 'DisplayName']].iloc[0]\n","\n","df = (kernel_votes\n","      .loc[kernel_votes['UserId'].eq(userid), ['KernelVersionId', 'VoteDate']]\n","      .merge(kernel_versions[['Id', 'ScriptId', 'Title']], left_on='KernelVersionId', right_on='Id')\n","      .merge(kernels, left_on='ScriptId', right_on='Id')\n","      .merge(users, left_on='AuthorUserId', right_on='Id')\n","      .sort_values('VoteDate', ascending=not MOST_RECENT_FIRST)\n","      .pipe(lambda x: x.loc[x['UserName'].ne(username)] if not INCLUDE_SELF_VOTES else x)\n","      .head(NUM_RESULTS)\n","      .replace({'PerformanceTier': avatiers, 'Medal': medals})\n","      .assign(URL=lambda x: x['Medal'].fillna('') + f'<a href=\"{KAGGLE_BASE_URL}' + x['UserName'] + '/' + x['CurrentUrlSlug'] + '\">' + x['Title'] + '</a>',\n","              User=lambda x: f'<a href=\"{KAGGLE_BASE_URL}' + x['UserName'] + '\">' + x['DisplayName'] + '</a>' + x['PerformanceTier'])\n","      .reindex(columns=['VoteDate', 'TotalVotes', 'User', 'URL', 'TotalComments'])\n","     )\n","\n","display(Markdown(f'# Notebooks upvoted by {displayname}'))\n","HTML(df.to_html(escape=False, index=False).replace('<td>', '<td style=\"text-align:left\">'))"]}],"metadata":{"kernelspec":{"display_name":"Python 3","language":"python","name":"python3"},"language_info":{"codemirror_mode":{"name":"ipython","version":3},"file_extension":".py","mimetype":"text/x-python","name":"python","nbconvert_exporter":"python","pygments_lexer":"ipython3","version":"3.7.12"},"papermill":{"default_parameters":{},"duration":127.826334,"end_time":"2022-06-21T13:27:41.197231","environment_variables":{},"exception":null,"input_path":"__notebook__.ipynb","output_path":"__notebook__.ipynb","parameters":{},"start_time":"2022-06-21T13:25:33.370897","version":"2.3.4"}},"nbformat":4,"nbformat_minor":5}