Skip to main content

A command-line tool for managing Weights & Biases (W&B) training logs

Project description

WandB Logger

A sleek CLI tool that transforms how you work with Weights & Biases. Create your training report in a single-line command!

GitHub stars PyPI version License

WandB Logger App is a sleek command-line tool that transforms how you work with Weights & Biases. Create beautiful, shareable reports of your ML experiments in seconds.

🚀 Key Features

WandB Logger offers two powerful ways to quickly access your experiments:

🔍 Find Your Experiments Without URLs

No more searching for run URLs or project names! WandB Logger makes finding your experiments effortless:

# Browse your recent projects
wandb-logger recent

# Browse your recent runs across all projects
wandb-logger recent-runs

This dual approach lets you quickly navigate through your work at both the project and individual run level - a huge productivity boost!

✨ Features

  • 🔐 Simple Authentication - Quick login with WandB credentials
  • 📈 Beautiful Visualizations - Fetch stunning graphs from any WandB run
  • 📝 Markdown Reports - Generate elegant reports for easy sharing and embedding
  • Lightning Fast - Parallel processing and caching make everything snappy
  • 🧠 Smart Metric Handling - Intelligently organizes complex metric paths
  • 🎯 Interactive Selection - Pick exactly which metrics matter to you

🚀 Installation

# Install from PyPI
pip install wandb-logger

# Or install from source
git clone https://github.com/SabaPivot/wandb-logger.git
cd wandb-logger
pip install -e .

🔑 WandB Account and Authentication

You'll need a Weights & Biases account to use this tool. If you don't already have one:

  1. Sign up at wandb.ai
  2. Get your API key from wandb.ai/authorize
  3. Login using the tool:
wandb-logger login

This will prompt you to enter your API key and securely store it for future sessions.

🏁 Quick Start

# Login to your WandB account
wandb-logger login

# MAIN WORKFLOWS:

# 1. Browse your recent PROJECTS (find the project you're looking for)
wandb-logger recent

# 2. Browse your recent RUNS (find the specific run you need)
wandb-logger recent-runs

# 3. Once you have a run URL, fetch detailed metrics
wandb-logger fetch https://wandb.ai/username/project/runs/run_id

📖 Commands

Main Commands

Command Description When to use
recent Browse and select from recent projects When you remember the project name but not specific runs
recent-runs Browse and select from recent runs When you want to find a specific run without knowing its URL
fetch URL Fetch details for a specific run URL When you already have the run URL and want to analyze specific metrics

Options and Filters

Command Key Options
recent --limit (default: 10)
--select (interactive selection)
recent-runs --project (filter by project)
--entity (filter by username/org)
--max-projects (default: 3)
--all-projects (fetch from all projects)
fetch URL --select (enabled by default)
--all (fetch all metrics without selection)
--metrics (specify comma-separated metrics)
--force-refresh (bypass cache)
metrics URL --force-refresh (bypass cache)
cache --clear (free disk space)

🎨 Interactive Metric Selection

The fetch command now defaults to interactive selection mode:

  1. Default Mode (interactive selection):
# Opens an interactive menu to choose specific metrics
wandb-logger fetch https://wandb.ai/username/project/runs/run_id
  1. All Metrics Mode (with --all):
# Fetches and plots ALL available metrics
wandb-logger fetch https://wandb.ai/username/project/runs/run_id --all

Select exactly what you want in your reports:

Available metrics:
1. [X] train/loss
2. [X] train/accuracy
3. [ ] validation/loss
4. [ ] validation/accuracy

Command (Type number to toggle, 'a'=all, 'n'=none, 'done'=finish):

📋 Example Workflows

Tracking a Training Run

# Login first
wandb-logger login

# Fetch your latest run and create a report
wandb-logger recent --limit 1 --select

Creating a Project Report

# Fetch multiple specific runs
wandb-logger fetch https://wandb.ai/username/project/runs/run_1
wandb-logger fetch https://wandb.ai/username/project/runs/run_2

# List your saved reports
wandb-logger list

🔍 Report Outputs

For each run, you'll get:

  • <run_name>.md: Clean report with selected metrics and graphs
  • metadata.md: Detailed configuration and all run information
  • Graph PNGs: Individual visualizations for each metric

🚀 Performance Features

  • ⚡ Caching: Blazing fast repeated access to run data
  • ⚙️ Parallel Processing: Generates multiple graphs simultaneously
  • 📊 Optimized Visualizations: Beautiful graphs with minimal code
  • 🧠 Smart Organization: Automatic categorization of complex metrics

🛠️ Requirements

  • Python 3.8+
  • WandB account

⭐ Support

Like this project? Please give it a star on GitHub to show your support and help others discover it!

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

wandb_logger-0.1.1.tar.gz (186.1 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

wandb_logger-0.1.1-py3-none-any.whl (189.0 kB view details)

Uploaded Python 3

File details

Details for the file wandb_logger-0.1.1.tar.gz.

File metadata

  • Download URL: wandb_logger-0.1.1.tar.gz
  • Upload date:
  • Size: 186.1 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.12.7

File hashes

Hashes for wandb_logger-0.1.1.tar.gz
Algorithm Hash digest
SHA256 ad1aad0f1a36a22ee202c0480a3916bb7eaeafcb18249cd709b6cb76035c3451
MD5 a1918bd37371eaed158323b101fdf0e8
BLAKE2b-256 f6a2e52b628dc976b1721f54fd9629356d25f7ba9a123262ff58ca5d3fe90382

See more details on using hashes here.

File details

Details for the file wandb_logger-0.1.1-py3-none-any.whl.

File metadata

  • Download URL: wandb_logger-0.1.1-py3-none-any.whl
  • Upload date:
  • Size: 189.0 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.12.7

File hashes

Hashes for wandb_logger-0.1.1-py3-none-any.whl
Algorithm Hash digest
SHA256 4ed2618ac5e426e1fda238eb52840fa1704dd011e8b271c86812e875341d79ee
MD5 14f7aa2df9dc145bc19d5ff02570e236
BLAKE2b-256 c461e3d941e30e43b1108c7a1997ae993828cb7b147f70843a68d9b306b76463

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page