PyPu

PyPu is a lightweight Python script designed to facilitate the generation of PlantUML diagrams from Python source code.

How to run

To run this program, you have to install python and pip first. The following guides will help you install it.

• python
• pip

After installing python and pip, you can now install the dependencies. Use the following command to do so.

python3 -m pip install -U -r requirements.txt

Now that the dependencies are installed, simply run the following command. Replace . with the folder that you want to index and output.puml with the desired output location.

./pypu.py --module . > output.puml

You can add an optional additional parameter to get a link to a rendered file.

./pypu.py -m . --link svg

Alternatively, you can add an optional additional parameter to get the rendered file directly.

./pypu.py -m . --format svg > output.svg

Development

Documentation

To access the automatically generated documentation, please utilize the following command.

pdoc pypu.py utils data --favicon https://fonts.gstatic.com/s/i/short-term/release/materialsymbolsoutlined/code/default/48px.svg --logo https://fonts.gstatic.com/s/i/short-term/release/materialsymbolsoutlined/code/default/48px.svg

Class Diagrams

Linting

Linting is an essential step in ensuring code quality and maintainability. For this project, we are using Pylint, a widely-used linter that can identify potential issues in the code.

To lint the entire repository, simply use the following command in a terminal:

pylint --output-format=colorized .

This command will recursively search through all subdirectories of the current directory and analyze all Python files while ignoring any files or directories whose names match the given regular expression.

Type Checking

By running the following command, MyPy will perform static type checking on the project files. MyPy analyzes the code and provides feedback on type inconsistencies, potential type errors, and other type-related issues.

mypy

Static type checking helps catch errors and improve code quality by ensuring that variables, function arguments, and return types are used consistently and correctly according to their declared types. MyPy verifies type annotations and provides warnings or errors if it finds any inconsistencies or violations.