A python library to note ml experiments on google sheet
Project description
labgsheet: Labnotes on Google Sheet
A python library to note ml experiments on google sheet.
labgsheet
provides an easy way to note ml experiments on Google Sheet.
At a Glance
You can use labgsheet
in cosole like following:
# prepare for worksheet by gspread >>> import gspread >>> from oauth2client.service_account import ServiceAccountCredentials >>> scope = ['https://spreadsheets.google.com/feeds', 'https://www.googleapis.com/auth/drive'] # download credentials.json previously from Google Developers Console >>> credentials = ServiceAccountCredentials.from_json_keyfile_name('credentials.json', scope) >>> gc = gspread.authorize(credentials) >>> ws = gc.create("Test for labgsheets").sheet1 # note an experiment where params and a metric are used >>> from labgsheet import Experiment >>> exp = Experiment(ws) >>> exp.log_multi_params({'l1': 0.5, 'C': 10}) >>> exp.log_metric('aupr', 0.2345)
You can also use labgsheet
in Google Colaboratory like following:
! pip install labgsheet ! pip install --upgrade -q gspread from google.colab import auth auth.authenticate_user() import gspread from oauth2client.client import GoogleCredentials gc = gspread.authorize(GoogleCredentials.get_application_default()) ws = gc.create("Test for labgsheets").sheet1 from labgsheet import Experiment exp = Experiment(ws) exp.log_multi_params({'l1': 0.5, 'C': 10}) exp.log_metric('aupr', 0.2345)
After logging, you can get a google sheet like below:
Installation
To install labgsheet
, use pipenv (or pip):
$ pipenv install labgsheet
Contribution
- Fork
- Create a feature branch
- Commit your changes
- Rebase your local changes against the master branch
- Create new Pull Request
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