mirror of
https://github.com/rendercv/rendercv.git
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126 lines
4.5 KiB
Markdown
126 lines
4.5 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 [reference](../reference/index.md).
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## Getting Started
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There are two ways of developing RenderCV: locally or with GitHub Codespaces.
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### Develop Locally
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1. Ensure that you have Python version 3.10 or higher.
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2. Install [Hatch](https://hatch.pypa.io/latest/), as it is the project manager for RenderCV. The installation guide for Hatch can be found [here](https://hatch.pypa.io/latest/install/#installation).
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3. Clone the repository recursively (because TinyTeX is being used as a submodule) with the following command.
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```bash
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git clone --recursive https://github.com/sinaatalay/rendercv.git
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```
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4. Go to the `rendercv` directory.
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```bash
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cd rendercv
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```
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5. RenderCV uses three virtual environments:
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- `default`: For the development. It contains packages like [Ruff](https://github.com/astral-sh/ruff), [Black](https://github.com/psf/black), etc.
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- `docs`: For building the documentation.
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- `test`: For testing RenderCV.
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Create the virtual environments with the following commands.
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```bash
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hatch env create default
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hatch env create docs
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hatch env create test
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```
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6. To use the virtual environments, either
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- Activate one of the virtual environments with one of the following commands.
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```bash
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hatch shell default
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```
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```bash
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hatch shell docs
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```
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```bash
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hatch shell test
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```
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- Select one of the virtual environments in your Integrated Development Environment (IDE).
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=== "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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=== "Other"
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To be added.
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### Develop with GitHub Codespaces
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1. [Fork](https://github.com/sinaatalay/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/sinaatalay/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/sinaatalay/rendercv/blob/main/pyproject.toml) file.
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- Format the code with [Black](https://github.com/psf/black)
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```bash
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hatch run default: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 default:lint
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```
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- Sort the imports with [isort](https://github.com/timothycrosley/isort/)
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```bash
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hatch run default:sort-imports
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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 default:check-types
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```
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- Run the tests
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```bash
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hatch run test:run
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```
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- Run the tests and generate a coverage report
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```bash
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hatch run test:run-and-report
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```
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- Start the development server for the documentation
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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/sinaatalay/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/sinaatalay/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](https://docs.rendercv.com/user_guide/structure_of_the_yaml_input_file/)"
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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/sinaatalay/rendercv/blob/main/pyproject.toml)
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[`pyproject.toml`](https://github.com/sinaatalay/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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