wandb
A CLI and library for interacting with the Weights & Biases API.
Decision gist · record as of 2026-08-14
Yes. wandb is actively maintained, widely used (top 1000 on PyPI with monthly downloads in the millions), has no known vulnerabilities, and is MIT-licensed. The medium install friction is justified by its comprehensive feature set. Install it if you need centralized experiment tracking, comparison, and visualization for machine learning projects; skip it if you prefer local-only logging or have strict data residency requirements.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires a W&B account (free signup available) and API key; can be configured via `wandb login` or provided interactively on first use.
- Medium install friction with 10 runtime dependencies including protobuf, pydantic, and requests.
- Active maintenance with a release 2 days old and last commit on 2026-08-14.
License · maintenance · safety
permissive license (permissive) — MIT License permits free use, modification, and distribution with minimal restrictions. Suitable for both open-source and commercial projects.
last release 2026-08-12 (2 days) · last repo commit 2026-08-14 · 11,230 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 26,350,683 downloads/mo, #882 on PyPI
Alternatives
Verify before relying
pip install wandb
import wandb
with wandb.init(project="my-project", config={"lr": 3e-4}) as run:
run.log({"accuracy": 0.9, "loss": 0.1})- Whether the package supports offline mode or requires continuous network connectivity during training.
- Performance overhead of logging and network communication on training speed.
- Data retention and privacy policies for metrics and model artifacts stored on W&B servers.
What it is and what it does
wandb is a Python client library for Weights & Biases, a hosted platform for tracking machine learning experiments. It integrates into training scripts to capture metrics, hyperparameters, datasets, and model checkpoints, sending them to a centralized web dashboard where you can visualize trends, compare runs, and manage your ML pipeline. The library handles the logging and API communication; the actual storage and visualization happen on W&B's servers (available in multi-tenant cloud, dedicated cloud, or self-managed deployments).
You initialize a run with `wandb.init()`, configure your hyperparameters, and call `run.log()` to record metrics at each training step. The package integrates with popular ML frameworks and supports both notebook and script workflows. It depends on click, pydantic, protobuf, requests, and several other utilities for CLI interaction, configuration validation, and telemetry.
Use it for
- Track metrics across multiple training runs to identify the best model configuration.
- Compare hyperparameter experiments side-by-side to understand which settings produce the best results.
- Version and log datasets and model checkpoints alongside training metrics for reproducibility.
- Monitor long-running training jobs in real-time from a web dashboard without polling logs.
- Debug LLM applications with Weave, the package's suite of tools for GenAI evaluation and monitoring.
- Integrate experiment tracking into existing ML workflows with native support for popular frameworks.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
wandb is actively maintained, widely used (top 1000 on PyPI with monthly downloads in the millions), has no known vulnerabilities, and is MIT-licensed. The medium install friction is justified by its comprehensive feature set. Install it if you need centralized experiment tracking, comparison, and visualization for machine learning projects; skip it if you prefer local-only logging or have strict data residency requirements.
Install
wandb on PyPI
Before you install
Medium install friction with 10 runtime dependencies including protobuf, pydantic, and requests. Active maintenance with a release 2 days old and last commit on 2026-08-14. Supports Python 3.10 through 3.14 with wheels available for macOS, Linux, and Windows.
Requires a W&B account (free signup available) and API key; can be configured via `wandb login` or provided interactively on first use.
License in practice
MIT License permits free use, modification, and distribution with minimal restrictions. Suitable for both open-source and commercial projects.
Quickstart
pip install wandb
import wandb
with wandb.init(project="my-project", config={"lr": 3e-4}) as run:
run.log({"accuracy": 0.9, "loss": 0.1})Verify before relying
- Whether the package supports offline mode or requires continuous network connectivity during training.
- Performance overhead of logging and network communication on training speed.
- Data retention and privacy policies for metrics and model artifacts stored on W&B servers.
Package facts
| License | permissive license permissive |
| Python support | Supports the current Python release >=3.10 |
| Install friction | Medium. Platform-specific wheel |
| Runtime dependencies | 10 packagesclickopentelemetry-apipackagingplatformdirsprotobufpydanticpyyamlrequestssentry-sdktyping-extensions |
| Maintenance | Actively maintained 2 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 26,350,683 / month, #882 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 5 - Production/StableIntended Audience :: DevelopersIntended Audience :: Science/ResearchLicense :: OSI Approved :: MIT LicenseNatural Language :: EnglishProgramming Language :: GoProgramming Language :: Python :: 3Programming Language :: Python :: 3 :: OnlyProgramming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.14Programming Language :: RustTopic :: Scientific/Engineering :: Artificial IntelligenceTopic :: Software Development :: Libraries :: Python ModulesTopic :: System :: LoggingTopic :: System :: Monitoring |
Evidence: wandb-0.28.2-py3-none-macosx_12_0_arm64.whl; wandb-0.28.2-py3-none-macosx_12_0_x86_64.whl; wandb-0.28.2-py3-none-manylinux_2_28_aarch64.whl; wandb-0.28.2-py3-none-manylinux_2_28_x86_64.whl; wandb-0.28.2-py3-none-musllinux_1_2_aarch64.whl; wandb-0.28.2-py3-none-musllinux_1_2_x86_64.whl; wandb-0.28.2-py3-none-win_amd64.whl; wandb-0.28.2-py3-none-win_arm64.whl
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