neptune-query

import os import neptune_query as nq import pandas as pd # Set your Neptune API token and project name as environment variables. # Example: export NEPTUNE_API_TOKEN="YOUR_API_TOKEN" # Example: export NEPTUNE_PROJECT="workspace-name/project-name" # Ensure environment variables are set or pass them explicitly neptune_api_token = os.environ.get('NEPTUNE_API_TOKEN', 'YOUR_API_TOKEN_HERE') neptune_project = os.environ.get('NEPTUNE_PROJECT', 'your_workspace/your_project') if neptune_api_token == 'YOUR_API_TOKEN_HERE' or neptune_project == 'your_workspace/your_project': print("Warning: Please set NEPTUNE_API_TOKEN and NEPTUNE_PROJECT environment variables or provide them explicitly.") # For demonstration, we'll skip further execution if credentials aren't set. # In a real application, handle this appropriately (e.g., raise an error, prompt user). exit() # Set the API token for the session (optional if NEPTUNE_API_TOKEN env var is set) nq.set_api_token(api_token=neptune_api_token) # List experiments in a project print(f"Listing experiments in project: {neptune_project}") experiment_names = nq.list_experiments(project=neptune_project) print(f"Found {len(experiment_names)} experiments: {experiment_names[:5]}...") # Fetch a table of experiments with specific attributes # Fetch runs as rows and attributes as columns table_df: pd.DataFrame = nq.fetch_experiments_table( project=neptune_project, columns=['sys/name', 'sys/creation_time', 'params/*', 'metrics/loss'] ) print("\nFetched experiments table (first 5 rows):\n") print(table_df.head()) # Fetch a specific metric series for an experiment if not table_df.empty: first_experiment_name = table_df.iloc[0]['sys/name'] print(f"\nFetching 'metrics/loss' for experiment: {first_experiment_name}") metric_series_df = nq.fetch_metrics( experiments=[first_experiment_name], attributes=['metrics/loss'] ) print("\nFetched metric series (first 5 rows):\n") print(metric_series_df.head())