Dependency analyzer tool
Project description
Depanalyzer
Depanalyzer is a powerful dependency analysis tool designed to parse, link, and visualize dependencies across multiple languages and build systems. It supports static analysis of mixed-language projects, third-party dependency resolution, and automated license compliance checking.
๐ Features
- Multi-Language Support: C/C++ (CMake), TypeScript/JavaScript (npm, Hvigor), Java (Maven).
- Deep Dependency Resolution: Recursively fetches and analyzes third-party dependencies.
- Graph-Based Architecture: Represents projects as a directed acyclic graph (DAG) of file nodes and edge relationships.
- License Compliance: Integrated support for ScanCode Toolkit and Liscopelens to detect licenses and verify compatibility.
- High Performance: Multiprocess architecture for parallel parsing and analysis.
- Automated Pipeline: One-click script to run scanning, license detection, and compatibility checks.
- Interactive TUI: Terminal-based graph explorer to visualize and trace dependencies.
๐ฆ Installation
Prerequisites
- Python 3.12+
- Git (for fetching dependencies)
1. Using Pip (Recommended)
pip install .
2. Setting up License Checks (Optional but Recommended)
To use the license scanning and compatibility features, you need two additional components:
-
ScanCode Toolkit: You can install it system-wide, or let Depanalyzer manage a local copy for you:
# Download and configure a local copy of ScanCode (recommended) depanalyzer --install
Manual ScanCode installation
Depanalyzer only needs access to the
scancodeexecutable. You can either place it on yourPATH(system command mode) or keep it in a project-specific directory and point Depanalyzer at it (non-system command mode).System command mode (global
scancode):- Download the latest release archive from the ScanCode Toolkit releases page.
- Extract it somewhere such as
/opt/scancode-toolkit(Linux/macOS) orC:\tools\scancode-toolkit(Windows) and run the bundled configure script once:cd /opt/scancode-toolkit-<version> ./scancode --help # on Windows use .\scancode.bat --help
- Add the directory that contains the
scancode(orscancode.bat) executable to your shell path:# Linux/macOS export PATH="/opt/scancode-toolkit-<version>:$PATH" # PowerShell profile (Windows) $env:Path = "C:\\tools\\scancode-toolkit-<version>;" + $env:Path
- Verify the installation with
scancode --version. Depanalyzer will automatically discover it viaPATH.
Non-system command mode (local copy):
- Download and extract the toolkit under your workspace, for example
tools/scancode-toolkit. - Run the configure script once (
./scancode --help) so the bundled virtual environment is prepared. - Point Depanalyzer at the executable by setting
SCANCODE_BIN(orSCANCODE_CLI) to the full path of thescancodescript before invoking the CLI or scripts:export SCANCODE_BIN="$PWD/tools/scancode-toolkit/scancode" # Linux/macOS setx SCANCODE_BIN "C:\Workspace\project\tools\scancode-toolkit\scancode.bat" # Windows
SCANCODE_BIN/SCANCODE_CLImust reference the executable itself, whileSCANCODE_TOOLKITcan point to the toolkit directory (matching the layout produced bydepanalyzer --install, which defaults to~/.depanalyzer/scancode-toolkit). Depanalyzer checks these variables before falling back toPATH, so the command does not need to be globally installed. This mode does not exposescancodeas a shell command; Depanalyzer calls it via the environment variable, and you can still run it manually by invoking the absolute path stored inSCANCODE_BIN.
-
Liscopelens (for Compatibility Checks): Required if you want to run the full compliance pipeline.
pip install liscopelens
3. Using Docker (All-in-One)
The Docker image comes pre-configured with Depanalyzer, ScanCode, and Liscopelens. This is the easiest way to run the full compliance pipeline.
# Build the image
docker build -t depanalyzer .
๐ ๏ธ Usage
1. Automated License Compliance Pipeline
The project includes a robust script (scripts/run_license_compatibility.py) that automates the entire workflow: Scan -> Detect Licenses -> Check Compatibility.
Running via Docker (Recommended):
The Docker image defaults to running this pipeline.
# Analyze a single project
docker run --rm \
-v /path/to/local/repo:/workspace/project \
-v $(pwd)/output:/workspace/output \
depanalyzer --project-path /workspace/project
# Analyze with third-party dependencies (recursive)
docker run --rm \
-v /path/to/local/repo:/workspace/project \
-v $(pwd)/output:/workspace/output \
depanalyzer --project-path /workspace/project --third-party
Running Locally:
Ensure you have liscopelens installed and scancode available (or installed via depanalyzer --install).
# Run the pipeline script
python scripts/run_license_compatibility.py \
--project-path /path/to/repo \
--output-dir ./results \
--third-party
If you maintain liscopelens `shadow.json` overrides, pass them explicitly:
```bash
# Single shadow applied to all projects
python scripts/run_license_compatibility.py \
--project-path /path/to/repo \
--shadow-file /path/to/shadow.json
# Batch with one shadow per project (order follows the project flags)
python scripts/run_license_compatibility.py \
--project-path /path/to/project1 --shadow-file /shadows/project1/shadow.json \
--project-path /path/to/project2 --shadow-file /shadows/project2/shadow.json
# Batch with a shadow directory (expects <shadow-dir>/<project-name>.json)
python scripts/run_license_compatibility.py \
--projects-dir /path/to/projects_root \
--shadow-dir /path/to/shadow_root
**Batch Processing:**
You can analyze multiple projects in one go. This is supported in both Docker and local modes.
*Docker mode:*
```bash
# Create a list of projects
echo "/workspace/project1" > projects_list.txt
echo "/workspace/project2" >> projects_list.txt
# Run batch analysis in Docker
docker run --rm \
-v /path/to/p1:/workspace/project1 \
-v /path/to/p2:/workspace/project2 \
-v $(pwd)/projects_list.txt:/workspace/projects.txt \
-v $(pwd)/output:/workspace/output \
depanalyzer --projects-file /workspace/projects.txt
Local mode:
# Option 1: Using a projects file (recommended for many projects)
cat > projects_list.txt << EOF
/path/to/project1
/path/to/project2
/path/to/project3
EOF
python scripts/run_license_compatibility.py \
--projects-file projects_list.txt \
--output-dir ./results \
--third-party
# Option 2: Using multiple --project-path flags
python scripts/run_license_compatibility.py \
--project-path /path/to/project1 \
--project-path /path/to/project2 \
--project-path /path/to/project3 \
--output-dir ./results \
--third-party
# Option 3: Point at a folder containing multiple projects (each direct subfolder is scanned)
python scripts/run_license_compatibility.py \
--projects-dir /path/to/projects_root \
--output-dir ./results \
--third-party
When running in batch mode, each project gets its own subdirectory (e.g., 01_project1/, 02_project2/), and a batch_summary.json file is generated at the root of the output directory with results for all projects.
2. Manual Dependency Scanning (scan)
If you only need the dependency graph without license checks:
# Basic scan
depanalyzer scan /path/to/repo -o graph.json
# Scan with third-party dependency resolution (depth 3)
depanalyzer scan /path/to/repo -o graph.json --third-party --max-depth 3
3. Manual License Scanning (scancode)
Generate a license map ({node_id: license_expression}) manually. This requires scancode to be installed.
# 1. Scan directory directly (fastest, no dependency graph needed)
depanalyzer scancode --path /path/to/repo -o license_map.json
# 2. Scan using a cached graph (enables analysis of third-party dependencies)
# First, run a scan:
depanalyzer scan /path/to/repo -o graph.json --third-party
# Then, run scancode using the generated cache:
depanalyzer scancode --source /path/to/repo --third-party -o license_map.json
4. Other Commands
- Export: Convert graphs to other formats (GML, DOT).
depanalyzer export <graph_id> -o graph.gml --format gml
- DAG Validation: Check for circular dependencies in the global package graph.
depanalyzer dag --fail-on-cycle --limit 50
5. Interactive Graph Explorer
A terminal-based UI (TUI) to visualize and trace dependencies interactively.
python scripts/graph_explorer_tui.py <path_to_graph.json>
Features:
- Search nodes by ID or Label.
- Trace paths between two nodes (Direct path and Common Ancestor).
- View node details.
๐ Output Structure
Pipeline Output
When running the pipeline (Docker or script), the output directory will contain:
Single project:
output/
โโโ graph.json # Dependency graph
โโโ license_map.json # Raw license findings
โโโ compatibility_results.json # Compliance check results
โโโ compatibility_graph.json # Visualizable compliance graph
Batch mode (multiple projects):
output/
โโโ 01_project_name1/
โ โโโ graph.json # Dependency graph
โ โโโ license_map.json # Raw license findings
โ โโโ compatibility_results.json # Compliance check results
โ โโโ compatibility_graph.json # Visualizable compliance graph
โโโ 02_project_name2/
โ โโโ graph.json
โ โโโ license_map.json
โ โโโ compatibility_results.json
โ โโโ compatibility_graph.json
โโโ batch_summary.json # Summary of all processed projects
Graph JSON Format
The graph.json contains:
- Nodes: Files, packages, or targets with
id,type, anddata. - Edges: Relationships like
import,link,includes. - Metadata: Scan configuration and source details.
๐ง Configuration
You can provide a custom configuration file for the scan process using the --config flag.
depanalyzer scan . -o graph.json --config config.toml
Fallback Policy
The fallback policy creates a synthetic tree that connects unparsed files and isolated nodes to a root node. This ensures license scanning can achieve full coverage even when some files couldn't be parsed.
Enable via CLI flag:
depanalyzer scan /path/to/repo -o graph.json --fallback-tree
Enable via configuration file:
config.toml:
[fallback]
enabled = true # Enable fallback tree (default: false)
root_id = "//fallback/license_scan" # Root node ID (default)
include_isolated_nodes = true # Connect isolated nodes to root (default: true)
config.json:
{
"fallback": {
"enabled": true,
"root_id": "//fallback/license_scan",
"include_isolated_nodes": true
}
}
When to use: Enable this when running license compliance checks on projects with incomplete parsing or mixed-language codebases to ensure all files are included in the analysis.
Other Configuration Options
For advanced configuration options (projection, contract matching, per-ecosystem settings), see docs/dependency_graph_lifecycle_and_config.md
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