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Readme
whylogs is an open source library for logging any kind of data. With whylogs, users are able to generate summaries of their datasets (called whylogs profiles) which they can use to:
These three functionalities enable a variety of use cases for data scientists, machine learning engineers, and data engineers:
Install whylogs using the pip package manager in a terminal by running:
pip install whylogs
Then you can log data in python as simply as this:
import whylogs as why
import pandas as pd
df = pd.read_csv("path/to/file.csv")
results = why.log(df)
And voilà, you now have a whylogs profile. To learn more about what a whylogs profile is and what you can do with it, check out our docs and our examples.
FAQs
Profile and monitor your ML data pipeline end-to-end
We found that whylogs demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 4 open source maintainers collaborating on the project.
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Socket for GitHub automatically highlights issues in each pull request and monitors the health of all your open source dependencies. Discover the contents of your packages and block harmful activity before you install or update your dependencies.
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