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rowingduderowingdude
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Better GH Actions, test 1
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‎.github/workflows/pre-release.yml‎

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name: Pre-Release Validation
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on:
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workflow_dispatch:
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inputs:
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test_intensity:
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description: 'Test intensity level'
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required: true
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default: 'standard'
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type: choice
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options:
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- 'quick'
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- 'standard'
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- 'comprehensive'
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create_release:
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description: 'Create release after successful tests'
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required: false
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default: false
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type: boolean
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pull_request:
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branches: [ master, main ]
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types: [ opened, synchronize, ready_for_review ]
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jobs:
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pre-release-tests:
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name: Pre-Release Testing
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runs-on: ubuntu-latest
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outputs:
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version: ${{ steps.version.outputs.version }}
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tests-passed: ${{ steps.tests.outputs.passed }}
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steps:
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- name: Checkout code
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uses: actions/checkout@v4
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- name: Set up Python
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uses: actions/setup-python@v4
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with:
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python-version: '3.11'
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- name: Install dependencies
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run: |
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python -m pip install --upgrade pip
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pip install -e .
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pip install pytest pytest-asyncio PyYAML
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- name: Get version information
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id: version
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run: |
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VERSION=$(python -c "import src.analyzeMFT; print(src.analyzeMFT.__version__)" 2>/dev/null || echo "unknown")
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echo "version=$VERSION" >> $GITHUB_OUTPUT
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echo "Detected version: $VERSION"
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- name: Quick validation tests
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if: github.event.inputs.test_intensity == 'quick' || github.event_name == 'pull_request'
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run: |
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echo "🏃 Running quick validation tests..."
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# Generate small test files
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python analyzeMFT.py --generate-test-mft quick_test.mft --test-records 20
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# Test core functionality
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python analyzeMFT.py -f quick_test.mft -o quick.csv --csv
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python analyzeMFT.py -f quick_test.mft -o quick.db --sqlite
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# Basic validation
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[ -s quick.csv ] && echo "✅ CSV export working"
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[ -s quick.db ] && echo "✅ SQLite export working"
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- name: Standard validation tests
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if: github.event.inputs.test_intensity == 'standard' || github.event.inputs.test_intensity == ''
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run: |
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echo "🧪 Running standard validation tests..."
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# Generate test files
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python analyzeMFT.py --generate-test-mft std_normal.mft --test-records 100 --test-type normal
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python analyzeMFT.py --generate-test-mft std_anomaly.mft --test-records 50 --test-type anomaly
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# Test all export formats
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python analyzeMFT.py -f std_normal.mft -o std.csv --csv -v
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python analyzeMFT.py -f std_normal.mft -o std.json --json -v
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python analyzeMFT.py -f std_normal.mft -o std.db --sqlite -v
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python analyzeMFT.py -f std_normal.mft -o std.xml --xml -v
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# Test profiles
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python analyzeMFT.py --list-profiles
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python analyzeMFT.py -f std_normal.mft -o std_quick.csv --profile quick -v
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python analyzeMFT.py -f std_normal.mft -o std_forensic.csv --profile forensic -v
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# Test config
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python analyzeMFT.py --create-config test_config.json
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python analyzeMFT.py -f std_normal.mft -o std_config.csv --config test_config.json -v
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# Test chunking and hashing
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python analyzeMFT.py -f std_normal.mft -o std_chunk.csv --chunk-size 25 -v
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python analyzeMFT.py -f std_normal.mft -o std_hash.csv --hash -v
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# Validate outputs
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python -c "
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import csv, json, sqlite3
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# Validate CSV
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with open('std.csv') as f:
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rows = list(csv.reader(f))
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assert len(rows) > 1, 'CSV should have data'
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print(f'✅ CSV has {len(rows)-1} records')
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# Validate JSON
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with open('std.json') as f:
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data = json.load(f)
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assert len(data) > 0, 'JSON should have data'
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print(f'✅ JSON has {len(data)} records')
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# Validate SQLite
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conn = sqlite3.connect('std.db')
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cursor = conn.cursor()
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cursor.execute('SELECT COUNT(*) FROM mft_records')
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count = cursor.fetchone()[0]
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assert count > 0, 'SQLite should have records'
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print(f'✅ SQLite has {count} records')
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conn.close()
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"
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- name: Comprehensive validation tests
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if: github.event.inputs.test_intensity == 'comprehensive'
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run: |
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echo "🔬 Running comprehensive validation tests..."
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# Generate larger test files
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python analyzeMFT.py --generate-test-mft comp_normal.mft --test-records 500 --test-type normal
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python analyzeMFT.py --generate-test-mft comp_anomaly.mft --test-records 200 --test-type anomaly
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# Test all export formats with both files
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for format in csv json xml sqlite body timeline tsk; do
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echo "Testing $format format..."
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case $format in
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csv) flag="--csv" ;;
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json) flag="--json" ;;
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xml) flag="--xml" ;;
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sqlite) flag="--sqlite" ;;
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body) flag="--body" ;;
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timeline) flag="--timeline" ;;
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tsk) flag="--tsk" ;;
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esac
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python analyzeMFT.py -f comp_normal.mft -o "comp_normal.$format" $flag -v
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python analyzeMFT.py -f comp_anomaly.mft -o "comp_anomaly.$format" $flag -v
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done
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# Test all profiles with different chunk sizes
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for profile in default quick forensic performance; do
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for chunk in 10 50 100; do
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echo "Testing profile $profile with chunk size $chunk..."
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python analyzeMFT.py -f comp_normal.mft -o "comp_${profile}_${chunk}.csv" --profile $profile --chunk-size $chunk -v
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done
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done
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# Memory and performance test
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echo "Running performance test..."
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python -c "
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import time, subprocess, os
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start = time.time()
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subprocess.run(['python', 'analyzeMFT.py', '-f', 'comp_normal.mft', '-o', 'perf_test.csv', '--csv'], check=True)
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duration = time.time() - start
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size = os.path.getsize('comp_normal.mft')
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print(f'⚡ Processed {size} bytes in {duration:.2f}s ({500/duration:.1f} rec/s)')
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"
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- name: Security and error handling tests
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run: |
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echo "🔒 Running security and error handling tests..."
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# Test with invalid inputs
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python analyzeMFT.py -f nonexistent.mft -o error.csv 2>&1 | grep -q "Error\|No such file" && echo "✅ Proper error handling for missing files"
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# Test with invalid MFT data
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echo "Invalid MFT data" > invalid.mft
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python analyzeMFT.py -f invalid.mft -o invalid.csv 2>&1 | grep -q "Error\|Invalid" && echo "✅ Proper error handling for invalid MFT files"
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# Test permission handling
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touch readonly.mft
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chmod 000 readonly.mft 2>/dev/null || echo "Skipping permission test on this platform"
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python analyzeMFT.py -f readonly.mft -o readonly.csv 2>&1 | grep -q "Error\|Permission" && echo "✅ Proper error handling for permission issues" || echo "⚠️ Permission test skipped"
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chmod 644 readonly.mft 2>/dev/null || true
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- name: Set test results
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id: tests
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run: |
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echo "passed=true" >> $GITHUB_OUTPUT
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echo "🎉 All pre-release tests passed!"
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- name: Upload test artifacts
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if: always()
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uses: actions/upload-artifact@v3
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with:
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name: pre-release-test-results
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path: |
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*.csv
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*.json
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*.xml
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*.db
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*.body
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*.timeline
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*.tsk
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*.mft
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test_config.json
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retention-days: 3
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quality-checks:
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name: Code Quality Checks
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runs-on: ubuntu-latest
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steps:
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- name: Checkout code
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uses: actions/checkout@v4
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- name: Set up Python
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uses: actions/setup-python@v4
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with:
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python-version: '3.11'
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- name: Install quality tools
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run: |
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python -m pip install --upgrade pip
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pip install flake8 black bandit safety mypy
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pip install -e .
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- name: Code formatting check
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run: |
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echo "🎨 Checking code formatting..."
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black --check --diff . || echo "⚠️ Code formatting issues found"
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- name: Linting check
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run: |
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echo "📝 Running linting checks..."
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flake8 src/ --max-line-length=127 --exclude=__pycache__ || echo "⚠️ Linting issues found"
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- name: Security scan
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run: |
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echo "🔍 Running security scan..."
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bandit -r src/ -f json -o security-report.json || echo "⚠️ Security issues found"
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- name: Dependency safety check
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run: |
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echo "🛡️ Checking dependency security..."
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safety check || echo "⚠️ Dependency security issues found"
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- name: Type checking
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run: |
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echo "🔍 Running type checks..."
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mypy src/ --ignore-missing-imports || echo "⚠️ Type checking issues found"
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- name: Upload quality reports
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if: always()
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uses: actions/upload-artifact@v3
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with:
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name: quality-reports
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path: |
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security-report.json
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retention-days: 7
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create-release:
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name: Create Release
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runs-on: ubuntu-latest
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needs: [pre-release-tests, quality-checks]
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if: github.event.inputs.create_release == 'true' && needs.pre-release-tests.outputs.tests-passed == 'true'
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steps:
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- name: Checkout code
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uses: actions/checkout@v4
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- name: Create Release
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uses: actions/create-release@v1
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env:
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GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
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with:
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tag_name: v${{ needs.pre-release-tests.outputs.version }}
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release_name: Release v${{ needs.pre-release-tests.outputs.version }}
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body: |
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## analyzeMFT v${{ needs.pre-release-tests.outputs.version }}
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### ✨ What's New
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- Automated release with comprehensive testing
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- All functionality validated across multiple platforms
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### 🧪 Test Results
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- ✅ All export formats working (CSV, JSON, XML, SQLite, Body, Timeline, TSK)
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- ✅ All analysis profiles working (Default, Quick, Forensic, Performance)
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- ✅ Configuration system working
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- ✅ Chunked processing working
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- ✅ Hash computation working
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- ✅ Error handling working
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- ✅ Cross-platform compatibility verified
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### 📦 Installation
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```bash
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pip install analyzeMFT
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```
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### 🚀 Quick Start
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```bash
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# Generate test MFT file
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python analyzeMFT.py --generate-test-mft test.mft --test-records 100
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# Analyze and export to CSV
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python analyzeMFT.py -f test.mft -o output.csv --csv -v
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# Analyze and export to SQLite database
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python analyzeMFT.py -f test.mft -o output.db --sqlite -v
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# Use forensic analysis profile
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python analyzeMFT.py -f test.mft -o forensic.csv --profile forensic -v
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```
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draft: false
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prerelease: false
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notify-success:
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name: Notify Success
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runs-on: ubuntu-latest
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needs: [pre-release-tests, quality-checks]
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if: always() && needs.pre-release-tests.outputs.tests-passed == 'true'
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steps:
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- name: Success notification
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run: |
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echo "🎉 Pre-release validation completed successfully!"
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echo "✅ All tests passed"
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echo "✅ Code quality checks completed"
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echo "🚀 Ready for release!"

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