6 releases
new 0.3.2 | Nov 11, 2024 |
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0.3.1 | Nov 8, 2024 |
0.2.0 | Oct 29, 2024 |
0.1.1 | Oct 27, 2024 |
#122 in Development tools
638 downloads per month
2MB
725 lines
Cargo Workspace Analyzer
A CLI tool which provides insights about a Cargo workspace. Currently, the following is supported.
Workspace Visualization
It visualizes the workspace with a Mermaid diagram. That way the user can see how packages depend on each other may identify layers of the application. As an example, here is the resulting diagram a randomly selected workspace, Tauri.
To have such diagram gives you the following advantages:
- a high level overview of the software you create
- gives you an idea about the degree of coupling between your packages
Circular Dependency Detection
This analyzer finds circular dependencies. It highlights those packages, which form a circle. By running the analyzer regularly, one can detect circular dependencies before they get hard if not impossible to resolve later on. See this example.
Package Count
It will also display the amount of packages in your workspace.
Installation
Install it globally:
cargo install cargo-workspace-analyzer
To render the Mermaid diagram and store it so disk (which is the default behaviour), you would need to have the Mermaid CLI installed as well, which run on Node.js.
npm install -g @mermaid-js/mermaid-cli
Usage
For all details, use cargo-workspace-analyzer --help
. However here is how you can use it generally:
Navigate to a Cargo workspace and run the tool:
cd path/to/your/workspace
cargo-workspace-analyzer
Or use an argument to specify the location of the workspace and run it from where ever you want.
cargo-workspace-analyzer --working-dir /path/to/your/workspace
If you use the --no-file
argument, the resulting Mermaid diagram will be printed to the
console. You can copy it for somewhere else for further processing.
Here's an example of circular dependency detection.
graph TD
service-1 --> db-connector
API --> service-2
API --> service-1
service-2 --> db-connector
Dependencies
~0.7–7.5MB
~62K SLoC