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Author: Weights & Biases

Requires Python: >=3.8

Classifiers

Development Status

5 - Production/Stable

Intended Audience

Developers
Science/Research

License

OSI Approved :: MIT License

Natural Language

English

Programming Language

Go
Python :: 3
Python :: 3 :: Only
Python :: 3.8
Python :: 3.9
Python :: 3.10
Python :: 3.11
Python :: 3.12
Python :: 3.13

Topic

Scientific/Engineering :: Artificial Intelligence
Software Development :: Libraries :: Python Modules
System :: Logging
System :: Monitoring

Weights and Biases

Use W&B to build better models faster. Track and visualize all the pieces of your machine learning pipeline, from datasets to production machine learning models. Get started with W&B today, sign up for an account!

See the W&B Developer Guide and API Reference Guide for a full technical description of the W&B platform.

Quickstart

Get started with W&B in four steps:

First, sign up for a W&B account.
Second, install the W&B SDK with pip. Navigate to your terminal and type the following command:

pip install wandb

Third, log into W&B:

wandb.login()

Use the example code snippet below as a template to integrate W&B to your Python script:

import wandb

# Start a W&B Run with wandb.init
run = wandb.init(project="my_first_project")

# Save model inputs and hyperparameters in a wandb.config object
config = run.config
config.learning_rate = 0.01

# Model training code here ...

# Log metrics over time to visualize performance with wandb.log
for i in range(10):
    run.log({"loss": ...})

# Mark the run as finished, and finish uploading all data
run.finish()

For example, if the preceding code was stored in a script called train.py:

python train.py

You will see a URL in your terminal logs when your script starts and finishes. Data is staged locally in a directory named wandb relative to your script. Navigate to the W&B App to view a dashboard of your first W&B Experiment. Use the W&B App to compare multiple experiments in a unified place, dive into the results of a single run, and much more!

Integrations

Use your favorite framework with W&B. W&B integrations make it fast and easy to set up experiment tracking and data versioning inside existing projects. For more information on how to integrate W&B with the framework of your choice, see W&B Integrations in the W&B Developer Guide.

Python Version Support

We are committed to supporting our minimum required Python version for at least six months after its official end-of-life (EOL) date, as defined by the Python Software Foundation. You can find a list of Python EOL dates here.

When we discontinue support for a Python version, we will increment the library’s minor version number to reflect this change.

Contribution guidelines

Weights & Biases ❤️ open source, and we welcome contributions from the community! See the Contribution guide for more information on the development workflow and the internals of the wandb library. For wandb bugs and feature requests, visit GitHub Issues or contact support@wandb.com.

Academic Researchers

Reach out to W&B Support at support@wandb.com to get a free academic license for you and your research group.

W&B Community

Be a part of the growing W&B Community and interact with the W&B team in our Discord. Stay connected with the latest ML updates and tutorials with W&B Fully Connected.

Platform	Python 3
macosx_12_0_arm64
macosx_12_0_x86_64
manylinux2014_aarch64
manylinux2014_x86_64
manylinux_2_17_aarch64
manylinux_2_17_x86_64
musllinux_1_2_aarch64
musllinux_1_2_x86_64
win32
win_amd64
win_arm64

wandb 0.22.2

Development Status

Intended Audience

License

Natural Language

Programming Language

Topic

Weights and Biases

Quickstart

Integrations

Python Version Support

Contribution guidelines

Academic Researchers

W&B Community

License

Wheel compatibility matrix

Files in release