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rust-cli-example

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A small Rust CLI example you can use to build on

rust-cli-example 최신버젼 다운로드

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# [![Coursera Course](https://raw.githubusercontent.com/alfredodeza/rust-cli-example/main/resources/banner.svg)](https://insight.paiml.com/nvd "Coursera Course")

# Rust CLI Example

A small Rust CLI example you can use to build on. With an emphasis on Linux and creating automation tools that solve a problem for you. This is the basis for DevOps principles that you can apply in day-to-day work.

💡 Are you just looking for a 👉 [Rust template](https://github.com/alfredodeza/rust-template) to get started easily with a project? The [template](https://github.com/alfredodeza/rust-template) has everything you need!

This repository is part of the Python and Rust CLI tools course:

- [1: Resources](https://github.com/alfredodeza/python-and-rust-tools) 
- [2: Python CLI](https://github.com/alfredodeza/python-cli-example)
- [3: Rust CLI](https://github.com/alfredodeza/rust-cli-example)  👈 You are here!
- [4: Python Advanced CLI](https://github.com/alfredodeza/advanced-python-cli)
- [5: Rust Advanced CLI](https://github.com/alfredodeza/advanced-rust-cli)

## Practice Lab
Use the [included practice lab](./lab.md) to apply the content you've learned in this week. Follow the steps to create your own repository and apply the requirements to complete the lab.

## Setting up your environment
Rust development requires certain tools to be installed on your system. The easiest way to do this is to use the [rustup](https://rustup.rs/) tool. This will install the Rust compiler and Cargo, the Rust package manager. Although you can install it in Linux using the package manager, I recommend using `rustup`. Use the following command or go through the [rustup.rs](https://rustup.rs/) website to install it.

```bash
curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh
```

This repository and video course focuses on the development side of command-line tools in Rust. It uses [Visual Studio Code](https://code.visualstudio.com/?WT.mc_id=academic-0000-alfredodeza) as the editor of choice. You can use any editor you like, but the instructions in this repository will be for VS Code.

These are all the tools and editor extensions I recommend you install to get started:

- [Visual Studio Code](https://code.visualstudio.com/?WT.mc_id=academic-0000-alfredodeza)
- [Rust and Cargo tools](https://rustup.rs/)
- [Rust Analyzer](https://marketplace.visualstudio.com/items?itemName=rust-lang.rust-analyzer&WT.mc_id=academic-0000-alfredodeza)
- [GitHub Copilot](https://marketplace.visualstudio.com/items?itemName=GitHub.copilot&WT.mc_id=academic-0000-alfredodeza)

As part of your development workflow, I highly suggest you use the following programs in the terminal regularly:

- `cargo fmt` - Formats your code to the Rust standard
- `cargo clippy` - Lints your code and helps you find errors and potential issues
- `cargo check` - Checks your code for errors and allows you to fix them before compiling (which means its faster!)

## Resources
Explore additional content that you can use to learn more about the topics covered in this course.

- [Releasing](./resources/releasing.md)

**Coursera Courses**

- [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)

**O'Reilly Courses and Books**

- [Python for DevOps](https://www.oreilly.com/library/view/python-for-devops/9781492057680/) (Book)
- [Practical MLOps](https://www.oreilly.com/library/view/practical-mlops/9781098103002/) (Book)
- [Linux For Beginners](https://learning.oreilly.com/videos/-/27922450VIDEOPAIML/) (Video)
- [GitHub Codespaces Course](https://learning.oreilly.com/videos/-/27724023VIDEOPAIML/) (Video)
- [Python Command-line Tools course](https://learning.oreilly.com/videos/python-command-line/50131VIDEOPAIML/) (Video)

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