https://github.com/abians/git_code_stats

Git Code Stats is a command-line application written in Rust that collects code statistics from Git repositories and creates a pie chart that displays the distribution of lines inserted by author.
https://github.com/abians/git_code_stats

cli git rust rust-lang

Last synced: about 1 month ago
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Git Code Stats is a command-line application written in Rust that collects code statistics from Git repositories and creates a pie chart that displays the distribution of lines inserted by author.

• Host: GitHub
• URL: https://github.com/abians/git_code_stats
• Owner: AbianS
• Created: 2023-09-24T19:49:20.000Z (about 1 year ago)
• Default Branch: master
• Last Pushed: 2023-09-24T20:45:08.000Z (about 1 year ago)
• Last Synced: 2023-09-25T00:40:22.519Z (about 1 year ago)
• Topics: cli, git, rust, rust-lang
• Language: Rust
• Homepage:
• Size: 107 KB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.MD

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README

        
# Git Code Stats

![PowerShell Rust Project](./assets/git-stats.jpg)

Git Code Stats is a command-line application written in Rust that collects code statistics from Git repositories and creates a pie chart that displays the distribution of lines inserted by author.

## Usage

1. Download the executable from the [releases page](https://github.com/AbianS/git_code_stats/releases/tag/V1.0.0)

2. Add the executable to your PATH

3. with the terminal, navigate to the folder where the repository is located

4. Run the command `git-stats`

## Use of Multi-Threading for Better Performance

Git Code Stats utilizes multiple threads (multi-threading) to enhance performance when collecting code statistics from Git repositories. This technique allows processing multiple authors simultaneously, significantly speeding up the retrieval of statistics in repositories with a large number of authors or changes.

### Advantages of Multi-Threading

- **Greater Efficiency:** The use of multiple threads enables the full utilization of CPU processing capacity, resulting in faster and more efficient statistics retrieval.

- **Parallelization:** Each author is processed in a separate thread, enabling task parallelization and resource optimization.

- **Reduced Execution Time:** With multi-threading, the application can process multiple authors simultaneously, significantly reducing the total execution time, especially in large repositories.