semvec/pypi-packages huggingface dataset:
chesscli 0.2.5
A CLI for chess application development.
Requires Python: >=3.7

# ChessCLI

ChessCLI is a command-line interface (CLI) tool designed to streamline the development environment for a chess game project. It automates tasks such as setting up the project, opening the codebase in Visual Studio Code, and managing Docker containers.

## Features

- **Easy Configuration**: Quickly configure the path to your chess game project repository.
- **Code Access**: Open your chess game project in Visual Studio Code with a single command.
- **Docker Management**: Start and stop your Docker containers directly through the CLI, simplifying your workflow.

## Installation

To install ChessCLI, run the following command in your terminal:

```bash
pip install chesscli
```

## Usage

Here are some of the commands you can use with ChessCLI:

- **Setup**: If you haven't cloned the chess game repository yet, this command helps you clone it and set up your development environment.

  ```bash
  chesscli setup
  ```

- **Configure**: Configure the path to your existing chess game project repository.

  ```bash
  chesscli configure
  ```

- **Open in VS Code**: Open the configured chess game project in Visual Studio Code.

  ```bash
  chesscli code
  ```

- **Start Docker Containers**: Start the Docker containers needed for your project.

  ```bash
  chesscli start
  ```

- **Stop Docker Containers**: Stop the Docker containers.

  ```bash
  chesscli stop
  ```

## Development

Want to contribute? Great! ChessCLI is open for contributions. Whether it's fixing bugs, adding new features, or improving the documentation, all contributions are welcome.

## License

ChessCLI is released under the [MIT License](LICENSE). See the LICENSE file for more details.

## Acknowledgments

- Thanks to all the contributors who spend time to improve ChessCLI.
- Special thanks to [Typer](https://typer.tiangolo.com/), which made creating this CLI tool a breeze.
waylake-utils 0.1.10
Custom logging utility

# Waylake Utils

## 개요

`waylake-utils`는 Python 애플리케이션을 위한 다양한 유틸리티 모듈을 제공하는 패키지입니다. 현재는 사용자 정의 로깅 설정을 포함하고 있으며, 향후 여러 유용한 기능들이 추가될 예정입니다. 이 패키지를 통해 애플리케이션 개발 과정에서 필요한 여러 기능들을 쉽고 효율적으로 구현할 수 있습니다.

## 주요 기능

- **사용자 정의 로깅** : 애플리케이션의 다양한 부분에 일관된 로깅 설정을 적용할 수 있습니다. 로그 파일은 호출하는 스크립트의 위치에 따라 생성됩니다.
- **추후 추가** : 향후 다양한 유틸리티 기능들이 추가될 예정입니다. 각 기능은 쉽게 통합하고 사용할 수 있도록 설계됩니다.

## 설치 방법

```bash
pip install waylake-utils
```

`waylake-utils`는 pip을 통해 쉽게 설치할 수 있습니다. 현재 GitHub 레포지토리나 내부 패키지 저장소를 통해 관리되고 있습니다.

## 사용 방법

### 로깅 설정

1. 로깅 기능을 import합니다.

```python
from waylake.utils import setup_logger
# or
from waylake import setup_logger
```

2. 로거를 설정합니다. `__file__`을 인자로 전달하여 현재 스크립트 위치에 로그 파일을 생성합니다.

```python
logger = setup_logger('my_logger_name', __file__)

logger = setup_logger(name='logger_name', caller_file=__file__, log_dir='./logs')
```

3. 로그를 기록합니다.

```python
logger.debug("This is a debug message")
logger.info("This is an info message")
logger.warning("This is a warning message")
logger.error("This is an error message")
logger.critical("This is a critical message")
```

### 추가 기능 (향후 업데이트 예정)

- 추가되는 기능들에 대한 설명과 사용 방법을 이곳에 기재합니다.
cp-jen 2024.0.0
Configurable test case generator for competitive programming.
Requires Python: >=3.11
Keywords: jen, cp-jen, Competitive Programming, Test Generator, Codeforces, Atcoder

# 📚 About 

Jen is a configurable test case generator for competitive programming.
The format of the test cases is specified in a TOML configuration file. 

# 🔌 Installation

Python version >=3.11 is required to install the python library. Install with:

`pip install cp-jen`

This will create a `jen` script in your python `bin` folder.
To call this script from anyware, ensure the python `bin` folder is in your PATH.

# 💼 Usage

Calling `jen` with a configuration file creates a test case and saves it in the current directory.

`jen config.toml`

To stress test your program, run `jen` with two additional arguments:

`jen config.toml ./tst ./ref`

Jen will continuously generate test cases and pipe them to the test and reference program's standard input.
The outputs from both programs are compared until a test case that generates different outputs is found.

# ⚙️  Configuration

The configuration is a TOML file. Examples of input configurations for past problems are in the examples folder.

## Example Configuration
As an example, we look at test cases for Atcoder contest [ABC346, problem D](https://atcoder.jp/contests/abc346/tasks/abc346_d).

```toml
in = """
N
S
{C}"""

[N]
type = 'int'
min = 2
max = 20

[S]
type = 'str'
allowed = ['0','1']
min = 'N'
max = 'N'

[C]
type = 'int'
min = 1
max = 1000000000

[1]
delimiter = ' '
count = 'N' 
```

Each test case will have an integer N, followed by a string of zeros and ones of size N, and finally N integers between 1 and 1,000,000,000 separated by spaces.

## jen.toml Specifications 

A variable called "in" is required. It is a string defining the input variables.

*in* rules:
- Any latin script letter is considered a variable (case sensitive).
- braces {} define a group. Groups are repeating sections of input.
- The first group is called '1'. The second group is '2', ... etc.
- group [1.1] is the first group within group 1.
- Any other character is kept as-is when generating inputs.

Each variable has a type. The type of a variable can be inferred from its name
or set explicitly in the variable configurations.
Each type has allowed properties and default values for those properties, listed below.

*Types*
- **int**:
    - default names: (a,b,c,d,e,f,g,h,i,j,k,l,m,n,o,p,q,u,v,w)
    - min: 0
    - max: 1000

- **string**:
    - default names: (s,t)
    - min: 0
    - max: 1000

- **float**:
    - default names: (x,y,z)
    - min: 0.0
    - max: 1000.0

- **group**:
    - count: 'n'
    - delimiter: " "
vidstreamtests 0.0.13
Streaming video data via networks
Keywords: python, video, stream, video stream, camera stream, sockets


# vidstream

Under construction! Not ready for use yet! Currently experimenting and planning!

Developed by Florian Dedov from NeuralNine (c) 2020

## Examples of How To Use (Buggy Alpha Version)

Creating A Server

```python
from vidstream import StreamingServer

server = StreamingServer('127.0.0.1', 9999)
server.start_server()

# Other Code

# When You Are Done
server.stop_server()
```

Creating A Client
```python
from vidstream import CameraClient
from vidstream import VideoClient
from vidstream import ScreenShareClient

# Choose One
client1 = CameraClient('127.0.0.1', 9999)
client2 = VideoClient('127.0.0.1', 9999, 'video.mp4')
client3 = ScreenShareClient('127.0.0.1', 9999)

client1.start_stream()
client2.start_stream()
client3.start_stream()
```

Check out: https://www.youtube.com/c/NeuralNine