Testing Plotly Functionality in Adeloop

This guide demonstrates how to test Plotly and matplotlib functionality in the Adeloop backend to ensure proper visualization support.

Overview

Before creating complex visualizations in Adeloop, it's important to verify that the backend properly supports Plotly and matplotlib. This testing script helps confirm that visualizations will render correctly in your notebooks.

Testing Plotly Basic Functionality

This example tests basic Plotly functionality:

# Cell 1: Testing Plotly Basic Functionality
import plotly.graph_objects as go
import numpy as np

# Create sample data
x = np.linspace(0, 10, 100)
y = np.sin(x)

# Create plot
fig = go.Figure()
fig.add_trace(go.Scatter(x=x, y=y, mode='lines', name='sin(x)'))
fig.update_layout(title='Sine Wave', xaxis_title='X', yaxis_title='Y')

# Show the plot (this should be captured)
fig.show()

print("Plotly plot created!")

Testing Matplotlib Basic Functionality

This example tests basic matplotlib functionality:

# Cell 2: Testing Matplotlib Basic Functionality
import matplotlib.pyplot as plt
import numpy as np

# Create sample data
x = np.linspace(0, 10, 100)
y = np.cos(x)

# Create plot
plt.figure(figsize=(10, 6))
plt.plot(x, y, label='cos(x)')
plt.title('Cosine Wave')
plt.xlabel('X')
plt.ylabel('Y')
plt.legend()
plt.grid(True)

# Show the plot (this should be captured)
plt.show()

print("Matplotlib plot created!")

Complete Test Script

This complete test script verifies both Plotly and matplotlib functionality:

# Cell 3: Complete Test Script
#!/usr/bin/env python3
"""
Test script to verify Plotly functionality in the Adeloop backend
"""

# Test basic Plotly plot
def test_plotly_basic():
    """Test basic Plotly functionality"""
    print("Testing basic Plotly functionality...")
    
    import plotly.graph_objects as go
    import numpy as np

    # Create sample data
    x = np.linspace(0, 10, 100)
    y = np.sin(x)

    # Create plot
    fig = go.Figure()
    fig.add_trace(go.Scatter(x=x, y=y, mode='lines', name='sin(x)'))
    fig.update_layout(title='Sine Wave', xaxis_title='X', yaxis_title='Y')

    # Show the plot (this should be captured)
    fig.show()

    print("Plotly plot created!")

# Test basic matplotlib plot
def test_matplotlib_basic():
    """Test basic matplotlib functionality"""
    print("Testing basic matplotlib functionality...")
    
    import matplotlib.pyplot as plt
    import numpy as np

    # Create sample data
    x = np.linspace(0, 10, 100)
    y = np.cos(x)

    # Create plot
    plt.figure(figsize=(10, 6))
    plt.plot(x, y, label='cos(x)')
    plt.title('Cosine Wave')
    plt.xlabel('X')
    plt.ylabel('Y')
    plt.legend()
    plt.grid(True)

    # Show the plot (this should be captured)
    plt.show()

    print("Matplotlib plot created!")

# Run the tests
if __name__ == "__main__":
    print("Adeloop Plotting Test")
    print("=" * 50)
    
    # Test Plotly
    test_plotly_basic()
    
    # Test matplotlib
    test_matplotlib_basic()
    
    print("\n" + "=" * 50)
    print("Test Summary:")
    print("✅ Both Plotly and matplotlib should be working correctly in Adeloop!")

Expected Results

When you run these tests in Adeloop, you should see:

Plotly Test: A sine wave plot with interactive features
Matplotlib Test: A cosine wave plot
Console Output: Confirmation messages indicating successful execution

Troubleshooting

If the tests don't work as expected:

Check Backend: Ensure the Adeloop backend is properly configured
Verify Dependencies: Confirm that Plotly and matplotlib are installed
Check Display Functions: Make sure fig.show() and plt.show() are being called
Review Permissions: Ensure the notebook has proper permissions to display plots

Using Visualizations in Adeloop

Once you've confirmed that plotting works correctly, you can create more complex visualizations:

Import Libraries: Always import required libraries at the beginning of your cell
Create Data: Generate or load your data
Build Visualizations: Use Plotly or matplotlib to create your plots
Display Results: Call show() functions to render the visualizations

These testing examples help ensure that your Adeloop environment is properly configured for creating visualizations in your data analysis workflows.

Adeloop Testing Plotly Functionality