Add test suite

Author: user

.github/workflows/formatter.yml

@@ -0,0 +1,12 @@
+name: Formatter
+
+on: [push, pull_request]
+
+jobs:
+  formatter:
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v4
+      - uses: rickstaa/action-black@v1
+        with:
+          black_args: "-l 79 ."

.github/workflows/linter.yml

@@ -0,0 +1,22 @@
+name: Linter
+
+on:
+  workflow_run:
+    workflows: [Formatter]
+    types: [completed]
+
+jobs:
+  linter:
+    runs-on: ubuntu-latest
+    if: ${{ github.event.workflow_run.conclusion == 'success' }}
+    steps:
+      - name: Check out source repository
+        uses: actions/checkout@v4
+      - name: Set up Python environment
+        uses: actions/setup-python@v4
+        with:
+          python-version: "3.11"
+      - name: flake8 Lint
+        uses: py-actions/flake8@v2
+        with:
+          path: "src"

.github/workflows/test.yml

@@ -0,0 +1,45 @@
+name: Tests
+
+on:
+  push:
+    branches: [ "main" ]
+  pull_request:
+    branches: [ "main" ]
+  # Running workflow manually
+  workflow_dispatch:
+
+jobs:
+  test:
+    runs-on: ubuntu-22.04
+
+    steps:
+    - uses: actions/checkout@v4
+    
+    - name: Set up Python 3.11
+      uses: actions/setup-python@v4
+      with:
+        python-version: "3.11"
+        cache: 'pip'
+    
+    - name: Install dependencies
+      run: |
+        python -m pip install --upgrade pip
+        pip install -e .
+        pip install pytest pytest-mock pytest-cov ipython
+    
+    - name: Run tests with coverage
+      run: |
+        pytest --cov=jumper_extension --cov-report=xml tests/
+    
+    - name: Generate coverage badge
+      uses: tj-actions/coverage-badge-py@v2
+      with:
+        output: coverage.svg
+    
+    - name: Commit coverage badge
+      run: |
+        git config --local user.email "action@github.com"
+        git config --local user.name "GitHub Action"
+        git add coverage.svg
+        git diff --staged --quiet || git commit -m "Update coverage badge"
+        git push 

.gitignore

@@ -1 +1,6 @@
-__pycache__/
+__pycache__/
+*.egg-info/
+.coverage
+htmlcov/
+.pytest_cache/
+coverage.xml

README.md

@@ -1,5 +1,7 @@
 # JUmPER Extension
 
+![Coverage](./coverage.svg)
+
 This is JUmPER IPython extension for real-time performance monitoring in IPython environments and Jupyter notebooks. It allows you to gather performance data on CPU usage, memory consumption, GPU utilization, and I/O operations for individual cells and present it in the notebook/IPython session either as text report or as a plot. The extension can be naturally integrated with [JUmPER Jupyter kernel](https://github.com/score-p/scorep_jupyter_kernel_python/) for most comprehensive analysis of notebook.
 
 ## Installation

tests/conftest.py

@@ -0,0 +1,59 @@
+import pytest
+import os
+import tempfile
+from unittest.mock import Mock, patch
+from IPython.testing.globalipapp import get_ipython
+
+@pytest.fixture
+def ipython():
+    # Try to get actual IPython instance, fallback to mock if not available
+    ip = get_ipython()
+    if ip is not None:
+        return ip
+    
+    # Create a mock IPython instance with required attributes  
+    from IPython.testing import decorators
+    from IPython import InteractiveShell
+    
+    # Create a basic InteractiveShell instance for testing
+    shell = InteractiveShell.instance()
+    shell.events = Mock()
+    shell.register_magics = Mock()
+    shell.events.register = Mock()
+    shell.events.unregister = Mock()
+    
+    return shell
+
+@pytest.fixture
+def temp_dir():
+    with tempfile.TemporaryDirectory() as tmpdir:
+        yield tmpdir
+
+@pytest.fixture
+def mock_cpu_only():
+    """Mock system with 1 CPU (4 cores) and no GPU"""
+    with patch('psutil.cpu_count', return_value=4), \
+         patch('psutil.cpu_percent', return_value=[25.0, 30.0, 20.0, 35.0]), \
+         patch('psutil.virtual_memory') as mock_mem, \
+         patch('psutil.Process') as mock_proc, \
+         patch('jumper_extension.performance_monitor.PYNVML_AVAILABLE', False):
+        mock_mem.return_value.total = 8 * 1024**3
+        mock_mem.return_value.available = 4 * 1024**3
+        mock_proc.return_value.cpu_affinity.return_value = [0, 1, 2, 3]
+        mock_proc.return_value.io_counters.return_value = Mock(read_count=100, write_count=50, read_bytes=1024, write_bytes=512)
+        yield
+
+@pytest.fixture
+def mock_cpu_gpu(mock_cpu_only):
+    """Mock system with 1 CPU (4 cores) and 1 GPU"""
+    with patch('jumper_extension.performance_monitor.PYNVML_AVAILABLE', True), \
+         patch('pynvml.nvmlInit'), \
+         patch('pynvml.nvmlDeviceGetCount', return_value=1), \
+         patch('pynvml.nvmlDeviceGetHandleByIndex', return_value=Mock()), \
+         patch('pynvml.nvmlDeviceGetName', return_value=b'NVIDIA GeForce RTX 3080'), \
+         patch('pynvml.nvmlDeviceGetMemoryInfo') as mock_mem, \
+         patch('pynvml.nvmlDeviceGetUtilizationRates') as mock_util, \
+         patch('pynvml.nvmlDeviceGetTemperature', return_value=65):
+        mock_mem.return_value = Mock(total=10*1024**3, used=2*1024**3, free=8*1024**3)
+        mock_util.return_value = Mock(gpu=75, memory=20)
+        yield 

tests/test_data_handling.py

@@ -0,0 +1,51 @@
+import os
+import pandas as pd
+from jumper_extension.performance_data import PerformanceData
+from jumper_extension.cell_history import CellHistory
+
+def test_performance_data(temp_dir):
+    """Test all PerformanceData functionality"""
+    # Test initialization and empty dataframe
+    data = PerformanceData(num_cpus=2, num_gpus=0)
+    assert data.num_cpus == 2 and data.num_gpus == 0 and len(data.data) == 0
+    assert len(data.to_dataframe()) == 0
+    
+    # Test add_sample and to_dataframe
+    data.add_sample(1234567890, [25.0, 30.0], 4.0, [], [], [], [100, 50, 1024, 512])
+    assert len(data.data) == 1
+    df = data.to_dataframe()
+    assert len(df) == 1 and df['cpu_util_avg'].iloc[0] == 27.5
+    
+    # Test CSV export
+    csv_file = os.path.join(temp_dir, "test.csv")
+    data.export(csv_file)
+    assert os.path.exists(csv_file) and len(pd.read_csv(csv_file)) == 1
+
+def test_performance_data_gpu():
+    """Test GPU functionality and slicing"""
+    data = PerformanceData(num_cpus=2, num_gpus=1)
+    data.add_sample(1234567890, [25.0, 30.0], 4.0, [75.0], [20.0], [60.0], [100, 50, 1024, 512])
+    data.add_sample(1234567891, [35.0, 40.0], 5.0, [80.0], [25.0], [65.0], [200, 60, 2048, 1024])
+    
+    df = data.to_dataframe()
+    assert len(df) == 2 and all(col in df.columns for col in ['gpu_util_avg', 'gpu_band_avg', 'gpu_mem_avg'])
+    assert len(data.to_dataframe(slice_=(0, 0))) == 1
+
+def test_cell_history(capsys, temp_dir):
+    """Test all CellHistory functionality"""
+    history = CellHistory()
+    
+    # Test start/end cell
+    history.start_cell("print('hello')")
+    assert history.current_cell['number'] == 0
+    history.end_cell(None)
+    assert len(history.cells) == 1 and len(history.cell_timestamps) == 1
+    
+    # Test print method
+    history.print()
+    assert "Cell #0" in capsys.readouterr().out
+    
+    # Test export
+    json_file = os.path.join(temp_dir, "history.json")
+    history.export(json_file)
+    assert os.path.exists(json_file)