Python API to Unified Coverage Interoperability Standard (UCIS) Data Model
Build Status PyPI version PyPI
- Python API for manipulating UCIS coverage databases
- CLI Tools for database conversion, merging, and reporting
- Coverage Import - Import from Verilator, cocotb-coverage, and AVL frameworks
- MCP Server for AI agent integration (see MCP_SERVER.md)
- AgentSkills Support for enhanced AI agent understanding (see https://agentskills.io)
- Support for XML, YAML, and UCIS binary formats
- Multiple export formats: LCOV, Cobertura, JaCoCo, Clover
# Standard installation pip install pyucis # With MCP server support pip install pyucis[dev]
# Convert coverage database pyucis convert --input-format xml --output-format yaml input.xml -o output.yaml # Merge multiple databases pyucis merge db1.xml db2.xml db3.xml -o merged.xml # Generate reports pyucis report coverage.xml -o report.txt # Interactive Terminal UI (NEW!) pyucis view coverage.xml # Query coverage information pyucis show summary coverage.xml pyucis show gaps coverage.xml --threshold 80 pyucis show covergroups coverage.xml
PyUCIS now includes an interactive Terminal User Interface (TUI) for exploring coverage databases:
# Launch the TUI
pyucis view coverage.xmlFeatures:
- Dashboard View - High-level coverage overview with statistics
- Hierarchy View - Navigate design structure with interactive tree
- Gaps View - Identify uncovered items for test planning
- Hotspots View - Priority-based improvement targets with P0/P1/P2 classification
- Metrics View - Statistical analysis, distributions, and quality indicators
- Help System - Comprehensive keyboard shortcuts (press
?) - Color-coded coverage indicators (red <50%, yellow 50-80%, green 80%+)
- Keyboard-driven navigation optimized for terminal workflows
- Fast, responsive interface using Rich library
Keyboard Shortcuts:
1- Dashboard view2- Hierarchy view3- Gaps view4- Hotspots view5- Metrics view↑/↓- Navigate items←/→- Collapse/expand tree nodes?- Help overlayq- Quit
Hotspots Analysis: The Hotspots view intelligently identifies high-priority coverage targets:
- P0/P1 (Critical/High): Low coverage modules (<50%) requiring immediate attention
- P1/P2 (High/Medium): Near-complete items (90%+) - low hanging fruit
- P1 (High): Completely untested coverpoints
Metrics & Statistics: The Metrics view provides in-depth analysis:
- Coverage distribution by hit count (0, 1-10, 11-100, 100+)
- Statistical measures (mean, median, min, max)
- Quality indicators (complete, high, medium, low tiers)
- Bin utilization and zero-hit ratios
The TUI provides an efficient alternative to HTML reports for real-time coverage analysis, especially useful for:
- Quick coverage assessment during verification
- Identifying coverage gaps without generating static reports
- Priority-driven test planning with hotspot analysis
- Remote terminal sessions over SSH
- CI/CD pipeline integration
PyUCIS now includes a Model Context Protocol (MCP) server that enables AI agents to interact with coverage databases:
# Start the MCP server
pyucis-mcp-serverSee MCP_SERVER.md for detailed documentation on:
- Available MCP tools (17+ coverage analysis tools)
- Integration with Claude Desktop and other AI platforms
- API usage examples
PyUCIS includes an AgentSkills skill definition that provides LLM agents with comprehensive information about PyUCIS capabilities. When you run any PyUCIS command, the absolute path to the skill file is displayed, allowing agents to reference it for better understanding of UCIS coverage data manipulation.
# Running any pyucis command displays the skill file location pyucis --help # Output includes: Skill Definition: /path/to/ucis/share/SKILL.md
from ucis import UCIS # Open a database db = UCIS("coverage.xml") # Access coverage data for scope in db.scopes(): print(f"Scope: {scope.name}") for coveritem in scope.coveritems(): print(f" {coveritem.name}: {coveritem.count} hits")
Import coverage from various verification frameworks:
Command Line (CLI):
# cocotb-coverage (XML/YAML) pyucis convert --input-format cocotb-xml coverage.xml --output-format xml --out output.xml pyucis convert --input-format cocotb-yaml coverage.yml --output-format xml --out output.xml # AVL (JSON) pyucis convert --input-format avl-json coverage.json --output-format xml --out output.xml # Merge multiple runs pyucis merge --input-format cocotb-xml run1.xml run2.xml --output-format xml --out merged.xml
Python API:
cocotb-coverage (Python testbenches):
from ucis.format_detection import read_coverage_file # Automatically detects cocotb XML or YAML format db = read_coverage_file('cocotb_coverage.xml') db = read_coverage_file('cocotb_coverage.yml')
AVL - Apheleia Verification Library:
from ucis.avl import read_avl_json # Import AVL JSON coverage (all variations supported) db = read_avl_json('avl_coverage.json')
Verilator:
# Import Verilator coverage via CLI
pyucis convert --input-format vltcov coverage.dat --out coverage.xmlSee documentation for complete import examples and supported formats.
Apache 2.0