https://github.com/pjfanning/rust-template
https://github.com/pjfanning/rust-template
Last synced: about 2 months ago
JSON representation
- Host: GitHub
- URL: https://github.com/pjfanning/rust-template
- Owner: pjfanning
- License: mit
- Created: 2024-01-09T16:11:58.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2024-01-09T16:12:00.000Z (over 1 year ago)
- Last Synced: 2025-01-24T07:42:18.815Z (3 months ago)
- Language: Rust
- Size: 3.91 KB
- Stars: 0
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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# Rust template
_This template repository is part of a 4-week Rust course, [start on week 1 here](https://github.com/alfredodeza/rust-setup) if you want to learn more about Rust!_
This Rust template is meant to help you get quickly started with a new project. It is [Codespaces enabled](https://docs.github.com/en/codespaces/overview) and it is pre-configured with useful extensions like the [Rust Analyzer](https://marketplace.visualstudio.com/items?itemName=rust-lang.rust-analyzer&WT.mc_id=academic-0000-alfredodeza) and [GitHub Copilot](https://docs.github.com/en/copilot/quickstart)
This repository is configured as a GitHub Template, so that you can start fresh with a new repository without carrying the history and commits of this repository. To get started you can click on the "Use this template" green button, or follow this [link directly](https://github.com/alfredodeza/rust-template/generate)
This is the Rust template used as part of the [Rust Bootcamp](https://s.deza.pe/zjo). There are 4 weeks in total:
- [week 1](https://github.com/alfredodeza/rust-setup)
- [week 2](https://github.com/alfredodeza/rust-fundamentals)
- [week 3](https://github.com/alfredodeza/rust-structs-types-enums/)
- [week 4](https://github.com/alfredodeza/applied-rust)
- [Rust Template](https://github.com/alfredodeza/rust-template) 👈 You are here!
🚀 **Watch the Video course**
[](https://s.deza.pe/zjo "Rust Bootcamp")
## Get started
To get started with this template, once you've [generated the repository](https://github.com/alfredodeza/rust-template/generate), run the following `cargo` command (replace my-project with the name of your project):
```bash
cargo init --name my-project .
```
This will initialize the project with the name you provided. You can now start editing the `src/main.rs` file and start building your project.
## Make changes
Make changes to this repository so that it reflects your own project. Start by updating the license which is currently set to MIT. You can do this by editing the `LICENSE` file. You can also update the `README.md` file to reflect a descriptiton of your own project.
## GitHub Actions
This template comes with a GitHub Actions workflow that will run on every push to the repository. The workflow will run `cargo build` and `cargo test` to make sure that your project builds and that all tests pass. You can find the workflow file in `.github/workflows/rust.yml`
## GitHub Codespaces
This template is [Codespaces enabled](https://docs.github.com/en/codespaces/overview). This means that you can start a new Codespace from this repository and start working on your project right away. To do this, click on the green "Code" button and select "Open with Codespaces". This will start a new Codespace for you and you can start editing the `src/main.rs` file right away.
## Resources
This template repository is part of a 4-week Rust course, [start on week 1 here](https://github.com/alfredodeza/rust-setup) if you want to learn more about Rust!
**O'Reilly Courses**
- [DevOps command-line tools in Python and Rust](https://learning.oreilly.com/videos/devops-command-line-tools/28037639VIDEOPAIML/)
**Coursera Courses**
- [MLOps Machine Learning Operations Specialization](https://www.coursera.org/specializations/mlops-machine-learning-duke)
- [Linux and Bash for Data Engineering](https://www.coursera.org/learn/linux-and-bash-for-data-engineering-duke)
- [Open Source Platforms for MLOps](https://www.coursera.org/learn/open-source-platforms-duke)
- [Python Essentials for MLOps](https://www.coursera.org/learn/python-essentials-mlops-duke)
- [Web Applications and Command-Line tools for Data Engineering](https://www.coursera.org/learn/web-app-command-line-tools-for-data-engineering-duke)
- [Python and Pandas for Data Engineering](https://www.coursera.org/learn/python-and-pandas-for-data-engineering-duke)
- [Scripting with Python and SQL for Data Engineering](https://www.coursera.org/learn/scripting-with-python-sql-for-data-engineering-duke)