Developer Guide¶

All contributions to RenderCV are welcome!

The source code is thoroughly documented and well-commented, making it an enjoyable read and easy to understand. A detailed documentation of the source code is available in the API reference.

Getting Started¶

There are two ways of developing RenderCV: locally or with GitHub Codespaces.

Develop Locally¶

Install Hatch. The installation guide for Hatch can be found here.

Hatch is a Python project manager. It mainly allows you to define the virtual environments you need in pyproject.toml. Then, it takes care of the rest. Also, you don't need to install Python. Hatch will install it when you follow the steps below.

Clone the repository.

git clone https://github.com/rendercv/rendercv.git

Go to the rendercv directory.
```
cd rendercv
```
Start using one of the virtual environments by activating it in the terminal.

Default development environment with Python 3.13:
```
hatch shell default
```
The same environment, but with Python 3.10 (or 3.11, 3.12, 3.13):
```
hatch shell test.py3.10
```
Finally, activate the virtual environment in your integrated development environment (IDE). In Visual Studio Code:
- Press Ctrl+Shift+P.
- Type Python: Select Interpreter.
- Select one of the virtual environments created by Hatch.

Develop with GitHub Codespaces¶

Fork the repository.
Navigate to the forked repository.
Click the <> Code button, then click the Codespaces tab, and then click Create codespace on main.

Then, Visual Studio Code for the Web will be opened with a ready-to-use development environment.

This is done with Development containers, and the environment is defined in the .devcontainer/devcontainer.json file. Dev containers can also be run locally using various supporting tools and editors.

Available Commands¶

These commands are defined in the pyproject.toml file.

Format the code with Black and Ruff
```
hatch run format
```
Lint the code with Ruff
```
hatch run lint
```
Run pre-commit
```
hatch run precommit
```
Check the types with Pyright
```
hatch run check-types
```
Run the tests with Python 3.13
```
hatch run test
```
Run the tests with Python 3.13 and generate the coverage report
```
hatch run test-and-report
```
Preview the documentation as you write it
```
hatch run docs:serve
```
Build the documentation
```
hatch run docs:build
```
Update schema.json
```
hatch run docs:update-schema
```
Update examples folder
```
hatch run docs:update-examples
```
Update figures of the entry types in the "Structure of the YAML Input File"
```
hatch run docs:update-entry-figures
```

About `pyproject.toml`¶

pyproject.toml contains the metadata, dependencies, and tools required for the project. Please read through the file to understand the project's technical details.