pydolce 0.1.5

The sweet way to catch outdated docstrings

Dolce

Because broken docs leave a bitter taste.

Dolce is a tool designed to help you maintain high-quality docstrings/documentation in your Python code. In addition, it leverages Large Language Models (LLMs) to ensure that your docstrings are semantically consistent with your code.

[!NOTE] Dolce is still in early development. While it is functional, some features are yet to be implemented and improvements are ongoing. Your feedback and contributions are highly appreciated!

🚀 Quick showcase

Check docstrings issues with static and LLM-powered rules:

Suggest missing docstrings by leveraging LLMs:

Restyle your entire codebase docstrings to a consistent format:

✨ Features

• Comprensive Rule Set: Comes with a variety of built-in rules to check for common docstring issues, including: Static rules:

  • Missing docstrings
  • Incomplete parameter documentation
  • Signature mismatches .. etc

  and LLM-powered rules:

  • Consistency between code and docstring
  • Detection of undocumented critical behaviors ... etc

• Generation docstrings: Generate missing docstrings across your codebase (with the help of LLMs) by running a single command.

• Restyling: Automatically restyle your existing docstrings to a consistent format (Google, NumPy, ReST, Epy, etc.).

• Customizable: Easily configure which rules to apply, LLMs config (model, provider, url, etc.), and other settings via a pyproject.toml file.

... more features coming soon!

📦 Installation

You can install dolce globally via pip:

pip install pydolce

However, the recommended use is to install it as a dev dependency in your project environment. If you are using uv for managing your Python projects, you can add it to your pyproject.toml like this:

[dependency-groups]
dev = [
    # ... your dev dependencies
    "pydolce",
]

Don't forget to sync: uv sync --all-groups

Then you can use it by running:

uv run dolce [COMMAND]

💻 Usage

Check docstrings

dolce check [PATH] # If no PATH is provided it will check the current directory

Generate missing docstrings

dolce suggest [PATH] # If no PATH is provided it will run in the current directory

Quick reference of available rules

dolce rules

⚙️ Configure

Dolce can be configured via pyproject.toml file. You can specify which rules to check and which to ignore. By default it will check all rules.

[tool.dolce]
target = [
  # Set of rules to check
  "DCE101",
]
disable = [
  # Set of rules to ignore
  "DCE102",
]

Use of LLM

By default dolce does not make use of LLM features (like smart check rules or doccstring suggestions). To enable them you need to configure the LLM options in the pyproject.toml file like this:

[tool.dolce]
url = "http://localhost:11434"
model = "qwen3:8b"
provider = "ollama"
api_key = "YOUR_API_KEY_ENVIROMENT_VAR" # Optional, needed for non local providers

[!TIP] qwen3:8b has relatively good performance while fitting in an RTX 4060 GPU (8GB VRAM)

You can visit the Ollama to check how to install and run models locally.

To be implemented

• Add cache system to avoid re-checking unchanged code
• Support for ignoring specific code segments, files, directories, etc
• Support parallel requests ... much more!

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👩‍💻 For Developers

Make sure you have the following tools installed before working with the project:

• uv → Python project and environment management
• make → run common project tasks via the Makefile

Getting Started

Install dependencies into a local virtual environment:

uv sync --all-groups

This will create a .venv folder and install everything declared in pyproject.toml.

Then, you can activate the environment manually depending on your shell/OS:

• Linux / macOS (bash/zsh):

  source .venv/bin/activate
  

• Windows (PowerShell):

  .venv\Scripts\Activate.ps1
  

• Windows (cmd.exe):

  .venv\Scripts\activate.bat
  

Running

uv run dolce check path/to/your/code

Linting, Formatting, and Type Checking

make qa

Runs Ruff for linting and formatting, and Mypy for type checking.

Running Unit Tests

Before running tests, override any required environment variables in the .env.test file.

make test

Executes the test suite using Pytest.

Building the Project

make build

Generates a distribution package inside the dist/ directory.

Cleaning Up

make clean

Removes build artifacts, caches, and temporary files to keep your project directory clean.

Building docs

make docs

Generates the project documentation inside the dist/docs folder.

When building the project (make build) the docs will also be generated automatically and included in the distribution package.

🤝 Contributing

Contributions are welcome! Please ensure all QA checks and tests pass before opening a pull request.

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_{🚀 Project starter provided by Cookie Pyrate}