wandb-workspaces

import os import wandb from wandb_workspaces.reports import Report, H1, P, PanelGrid from wandb_workspaces.panels import LinePlot, BarPlot, ScalarChart # Ensure you are logged into W&B (e.g., via `wandb login` or WANDB_API_KEY env var) # For a runnable example, ensure WANDB_API_KEY is set in your environment # os.environ['WANDB_API_KEY'] = 'YOUR_API_KEY' # os.environ['WANDB_ENTITY'] = 'your-entity' # os.environ['WANDB_PROJECT'] = 'your-project' entity = os.environ.get('WANDB_ENTITY', 'your-entity') # Replace with your W&B entity project = os.environ.get('WANDB_PROJECT', 'your-project') # Replace with your W&B project # Initialize a dummy W&B run to ensure authentication if not already logged in # Not strictly necessary for report creation if API key is set, but good practice. # try: # wandb.init(project=project, entity=entity, mode='offline') # finally: # wandb.finish() # Create a W&B Report report = Report( entity=entity, project=project, title="My Programmatic Report Example", description="A report created entirely with wandb-workspaces." ) # Add blocks and panels to the report report.blocks = [ H1("Introduction"), P("This report demonstrates how to programmatically generate W&B reports with various visualizations."), H1("Key Metrics"), PanelGrid( panels=[ LinePlot(x="Step", y=["val_loss", "train_loss"], title="Loss Over Steps"), BarPlot(metrics=["val_accuracy"], title="Validation Accuracy"), ScalarChart(metric="f1_score", groupby_aggfunc="mean", title="Mean F1 Score") ] ) ] # Save the report report.save() print(f"Report saved: {report.url}")