mirror of
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107 lines
4.1 KiB
Markdown
107 lines
4.1 KiB
Markdown
# Developer Guide
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All contributions to RenderCV are welcome!
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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](../reference/index.md).
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## Getting Started
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There are two ways of developing RenderCV: [locally](#develop-locally) or [with GitHub Codespaces](#develop-with-github-codespaces).
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### Develop Locally
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1. Install [Hatch](https://hatch.pypa.io/latest/). The installation guide for Hatch can be found [here](https://hatch.pypa.io/latest/install/#installation).
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Hatch is a Python project manager. It mainly allows you to define the virtual environments you need in [`pyproject.toml`](https://github.com/rendercv/rendercv/blob/main/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.
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2. Clone the repository.
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```
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git clone https://github.com/rendercv/rendercv.git
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```
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3. Go to the `rendercv` directory.
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```
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cd rendercv
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```
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4. Start using one of the virtual environments by activating it in the terminal.
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Default development environment with Python 3.13:
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```bash
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hatch shell default
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```
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The same environment, but with Python 3.10 (or 3.11, 3.12, 3.13):
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```bash
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hatch shell test.py3.10
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```
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5. Finally, activate the virtual environment in your integrated development environment (IDE). In Visual Studio Code:
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- Press `Ctrl+Shift+P`.
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- Type `Python: Select Interpreter`.
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- Select one of the virtual environments created by Hatch.
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### Develop with GitHub Codespaces
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1. [Fork](https://github.com/rendercv/rendercv/fork) the repository.
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2. Navigate to the forked repository.
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3. Click the <> **Code** button, then click the **Codespaces** tab, and then click **Create codespace on main**.
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Then, [Visual Studio Code for the Web](https://code.visualstudio.com/docs/editor/vscode-web) will be opened with a ready-to-use development environment.
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This is done with [Development containers](https://containers.dev/), and the environment is defined in the [`.devcontainer/devcontainer.json`](https://github.com/rendercv/rendercv/blob/main/.devcontainer/devcontainer.json) file. Dev containers can also be run locally using various [supporting tools and editors](https://containers.dev/supporting).
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## Available Commands
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These commands are defined in the [`pyproject.toml`](https://github.com/rendercv/rendercv/blob/main/pyproject.toml) file.
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- Format the code with [Black](https://github.com/psf/black) and [Ruff](https://github.com/astral-sh/ruff)
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```bash
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hatch run format
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```
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- Lint the code with [Ruff](https://github.com/astral-sh/ruff)
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```bash
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hatch run lint
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```
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- Run [pre-commit](https://pre-commit.com/)
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```bash
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hatch run precommit
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```
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- Check the types with [Pyright](https://github.com/RobertCraigie/pyright-python)
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```bash
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hatch run check-types
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```
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- Run the tests with Python 3.13
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```bash
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hatch run test
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```
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- Run the tests with Python 3.13 and generate the coverage report
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```bash
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hatch run test-and-report
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```
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- Preview the documentation as you write it
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```bash
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hatch run docs:serve
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```
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- Build the documentation
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```bash
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hatch run docs:build
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```
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- Update [schema.json](https://github.com/rendercv/rendercv/blob/main/schema.json)
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```bash
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hatch run docs:update-schema
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```
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- Update [`examples`](https://github.com/rendercv/rendercv/tree/main/examples) folder
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```bash
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hatch run docs:update-examples
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```
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- Update figures of the entry types in the "[Structure of the YAML Input File](../user_guide/structure_of_the_yaml_input_file.md)"
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```bash
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hatch run docs:update-entry-figures
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```
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## About [`pyproject.toml`](https://github.com/rendercv/rendercv/blob/main/pyproject.toml)
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[`pyproject.toml`](https://github.com/rendercv/rendercv/blob/main/pyproject.toml) contains the metadata, dependencies, and tools required for the project. Please read through the file to understand the project's technical details.
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