PyTerametrics

Python port of TerraMetrics — IaC quality metrics for Terraform HCL files.

Computes 100+ quality metrics at the block level for Terraform .tf files, including:

• Cyclomatic complexity (McCabe CC)
• Lines of code / non-code lines
• Function call counts and parameters
• Conditional expressions, loops, binary operators
• Nested blocks, dynamic blocks, heredocs
• Implicit/explicit resource dependencies
• Text entropy, token statistics
• And many more...

Installation

pip install pyterametrics

Usage

Command Line

# Analyze a single file
pyterametrics --file main.tf -b --target output.json

# Analyze a directory
pyterametrics -l --repo ./terraform-project --target ./results --project my-project

# Pretty-print output
pyterametrics --file main.tf -b --pretty

Python API

from pyterametrics import analyze_file, analyze_directory

# Single file
result = analyze_file("main.tf")
for block in result["blocks"]:
    print(f"{block['block_identifiers']}: {block['numAttrs']} attrs, CC={block['sumMccabeCC']}")

# Directory
result = analyze_directory("./terraform-project", project_name="my-project")

Development

# Install with dev dependencies
uv sync

# Run tests
uv run pytest tests/ -v