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#!/usr/bin/env python3
"""
Test script for Hugging Face Datasets integration
"""
import os
import json
from datetime import datetime
def test_hf_datasets_integration():
"""Test the HF Datasets integration"""
print("🧪 Testing Hugging Face Datasets Integration")
print("=" * 50)
# Check HF_TOKEN
hf_token = os.environ.get('HF_TOKEN')
if hf_token:
print("✅ HF_TOKEN found")
else:
print("❌ HF_TOKEN not found")
print("Please set HF_TOKEN environment variable")
return False
# Test dataset loading
try:
from datasets import load_dataset
# Get dataset repository from environment variable
dataset_repo = os.environ.get('TRACKIO_DATASET_REPO', 'tonic/trackio-experiments')
print(f"📊 Loading dataset: {dataset_repo}")
dataset = load_dataset(dataset_repo, token=hf_token)
print(f"✅ Dataset loaded successfully")
# Check experiments
if 'train' in dataset:
experiments = {}
for row in dataset['train']:
exp_id = row.get('experiment_id')
if exp_id:
experiments[exp_id] = {
'id': exp_id,
'name': row.get('name', ''),
'metrics': json.loads(row.get('metrics', '[]')),
'parameters': json.loads(row.get('parameters', '{}'))
}
print(f"📈 Found {len(experiments)} experiments:")
for exp_id, exp_data in experiments.items():
metrics_count = len(exp_data['metrics'])
print(f" - {exp_id}: {exp_data['name']} ({metrics_count} metrics)")
# Show sample metrics
if exp_data['metrics']:
latest_metric = exp_data['metrics'][-1]
if 'metrics' in latest_metric:
sample_metrics = latest_metric['metrics']
print(f" Latest: {list(sample_metrics.keys())}")
return True
except Exception as e:
print(f"❌ Failed to load dataset: {e}")
return False
def test_backup_fallback():
"""Test the backup fallback mechanism"""
print("\n🔄 Testing Backup Fallback")
print("=" * 30)
# Simulate no HF_TOKEN
original_token = os.environ.get('HF_TOKEN')
os.environ['HF_TOKEN'] = ''
try:
# Import and test the TrackioSpace class
from templates.spaces.trackio.app import TrackioSpace
trackio = TrackioSpace()
experiments = trackio.experiments
print(f"✅ Backup fallback loaded {len(experiments)} experiments")
for exp_id, exp_data in experiments.items():
metrics_count = len(exp_data.get('metrics', []))
print(f" - {exp_id}: {exp_data.get('name', '')} ({metrics_count} metrics)")
return True
except Exception as e:
print(f"❌ Backup fallback failed: {e}")
return False
finally:
# Restore original token
if original_token:
os.environ['HF_TOKEN'] = original_token
def test_metrics_dataframe():
"""Test the metrics DataFrame conversion"""
print("\n📊 Testing Metrics DataFrame Conversion")
print("=" * 40)
try:
from templates.spaces.trackio.app import TrackioSpace
trackio = TrackioSpace()
# Test with a known experiment
exp_id = 'exp_20250720_130853'
df = trackio.get_metrics_dataframe(exp_id)
if not df.empty:
print(f"✅ DataFrame created for {exp_id}")
print(f" Shape: {df.shape}")
print(f" Columns: {list(df.columns)}")
print(f" Sample data:")
print(df.head())
# Test plotting
if 'loss' in df.columns:
print(f" Loss range: {df['loss'].min():.4f} - {df['loss'].max():.4f}")
return True
else:
print(f"❌ Empty DataFrame for {exp_id}")
return False
except Exception as e:
print(f"❌ DataFrame conversion failed: {e}")
return False
if __name__ == "__main__":
print("🚀 Trackio HF Datasets Integration Test")
print("=" * 50)
# Run tests
test1 = test_hf_datasets_integration()
test2 = test_backup_fallback()
test3 = test_metrics_dataframe()
print("\n📋 Test Results")
print("=" * 20)
print(f"HF Datasets Loading: {'✅ PASS' if test1 else '❌ FAIL'}")
print(f"Backup Fallback: {'✅ PASS' if test2 else '❌ FAIL'}")
print(f"DataFrame Conversion: {'✅ PASS' if test3 else '❌ FAIL'}")
if all([test1, test2, test3]):
print("\n🎉 All tests passed! Your HF Datasets integration is working correctly.")
else:
print("\n⚠️ Some tests failed. Check the configuration and try again.") |