semvec/pypi-packages huggingface dataset:
apachecn-python-zh-pt4 2022.12.11.0
ApacheCN Python 译文集（四）
Requires Python: >=3.6

# ApacheCN Python 译文集（四）

> 协议：[CC BY-NC-SA 4.0](http://creativecommons.org/licenses/by-nc-sa/4.0/)
> 
> 利欲驱人万火牛，江湖浪迹一沙鸥。——陆游《秋思》

* [在线阅读](https://py4.apachecn.org)
* [在线阅读（Gitee）](https://apachecn.gitee.io/doc-template/)
* [ApacheCN 学习资源](http://docs.apachecn.org/)

## 贡献指南

为了不断改进翻译质量，我们特此启动了【翻译、校对、笔记整理活动】，开设了多个校对项目。贡献者校对一章之后可以领取千字2\~4元的奖励。进行中的校对活动请见[活动列表](https://home.apachecn.org/#/docs/activity/docs-activity)。更多详情请联系飞龙（Q562826179，V:wizardforcel）。

## 联系方式

### 负责人

* [飞龙](https://github.com/wizardforcel): 562826179

### 其他

*   在我们的 [apachecn/apachecn-python-zh-pt4](https://github.com/apachecn/apachecn-python-zh-pt4) github 上提 issue.
*   发邮件到 Email: `apachecn@163.com`.
*   在我们的 [组织学习交流群](https://www.apachecn.org/#/docs/join) 中联系群主/管理员即可.

## 下载

### Docker

```
docker pull apachecn0/apachecn-python-zh-pt4
docker run -tid -p <port>:80 apachecn0/apachecn-python-zh-pt4
# 访问 http://localhost:{port} 查看文档
```

### PYPI

```
pip install apachecn-python-zh-pt4
apachecn-python-zh-pt4 <port>
# 访问 http://localhost:{port} 查看文档
```

### NPM

```
npm install -g apachecn-python-zh-pt4
apachecn-python-zh-pt4 <port>
# 访问 http://localhost:{port} 查看文档
```

## 其它协议

霞鹜文楷采用 [SIL 开放字体协议 1.1](https://github.com/lxgw/LxgwWenKai/blob/main/SIL_Open_Font_License_1.1.txt)。

## 赞助我们

![](http://data.apachecn.org/img/about/donate.jpg)
tilepy-the-open-project 0.0.1
A simple, extremely easy-to-use Python GUI library, so you never ever make a single console app.
Requires Python: >=3.0

# tilepy

Welcome to tilepy - the extremely simple Python graphics library!

With tilepy, you never need to make a single command-line app, so you can do the fun stuff - making graphical apps instead!

[Source code](https://github.com/dylanrogers1/tilepy)
ruben-snake-cmd 0.3.0
Command-line version of the classic Snake game.
Requires Python: >=3.6
Keywords: snake game console command-line curses

# Snake

[![Build Status](https://travis-ci.com/Ruben9922/snake-cmd.svg?branch=master)](https://travis-ci.com/Ruben9922/snake-cmd)
[![PyPI](https://img.shields.io/pypi/v/ruben-snake-cmd)](https://pypi.org/project/ruben-snake-cmd/)
[![ruben-snake-cmd](https://snapcraft.io//ruben-snake-cmd/badge.svg)](https://snapcraft.io/ruben-snake-cmd)
[![GitHub](https://img.shields.io/github/license/Ruben9922/snake-cmd)](https://github.com/Ruben9922/snake-cmd/blob/master/LICENSE)

Command-line version of the classic Snake game.

![GIF showing gameplay](https://raw.githubusercontent.com/Ruben9922/snake-cmd/master/screenshot.gif)

## Installation

Install as usual:

```bash
pip install ruben-snake-cmd
```

You may wish to [create a virtual environment](https://docs.python.org/3/tutorial/venv.html#creating-virtual-environments) beforehand.

### Installation on Windows
The game requires the curses library. This should already be installed on Linux and macOS so no additional steps are required. However, it is not included in the Windows version of Python, as noted in the [curses documentation](https://docs.python.org/3.7/howto/curses.html#what-is-curses). On Windows, you can install the `windows-curses` package (see [this comment](https://gist.github.com/sanchitgangwar/2158089#gistcomment-3029530)), using `pip install windows-curses`.

## Usage
Run the game using the following command:
```bash
ruben-snake-cmd
```
Note that I've only tested this on Linux.

The application should generally be self-explanatory.

One thing to note is the settings screen, reached by pressing <kbd>S</kbd> on the title screen. Currently, the only option is to enable/disable the snake wrapping around the edge of the window by pressing <kbd>B</kbd>. If disabled, the snake will "die" on reaching the edge of the window.

There is also a controls screen, reached by pressing <kbd>C</kbd> on the title screen.

## In-Game Controls

| Key(s) | Action |
|-------------------------------------------------------|------------------|
| <kbd>←</kbd>, <kbd>↑</kbd>, <kbd>→</kbd>, <kbd>↓</kbd> | Change direction |
| <kbd>Q</kbd> | End game |

Note that these only apply in-game and not on other screens, such as the title screen or settings screen.
dbis-relational-algebra-exercise-generator 0.0.4
RWTH Aachen Computer Science i5/dbis assets for Lecture Datenbanken und Informationssysteme
Requires Python: >=3.10

# DBIS Relational Algebra Exercise Generator

[![pypi](https://img.shields.io/pypi/pyversions/dbis-relational-algebra-exercise-generator)](https://pypi.org/project/dbis-relational-algebra-exercise-generator/)
[![PyPI Status](https://img.shields.io/pypi/v/dbis-relational-algebra-exercise-generator)](https://pypi.org/project/dbis-relational-algebra-exercise-generator/)

This library generates relational algebra exercises based on the [dbis-relational-algebra](https://pypi.org/project/dbis-relational-algebra) library.
# Installation
Install via pip:
```bash
pip install dbis-relational-algebra-exercise-generator
```
Most notably, following required packages are also installed:
 - [dbis-relational-algebra](https://pypi.org/project/dbis-relational-algebra)
 - [dbis-exc-manager](https://pypi.org/project/dbis-exc-manager/)

# Usage
```python
from ra_exercise_generator import generate_exercise

from relational_algebra import *
solution_algebra_expression = Projection("R", ("R.a", "R.c"))

from excmanager.Task import Exercise, Task, SubTask
exercise1 = Exercise(1)
task1 = Task(exercise1, "1.1")
subtask1 = SubTask(task1, "a", points=2)
# task description
description = "Select the attributes a and c from the relation R."

generated_cells = generate_exercise(
	subtask1,
	description,
	solution_algebra_expression,
	correct_attributes_score_perc=0.1
)

# generated_cells is a dictionary of cells, which can be used to generate a Jupyter Notebook
# format:
# filename (str) -> cell content (str)
```


## :warning: Guidelines
In order to directly use the generated cells in an exercise Jupyter notebook, one should follow the following guidelines:
 - [tasks](https://pypi.org/project/dbis-exc-manager/) should be named `task1`, `task2`, ...
 - The SQLite Connection has to be made beforehand. This connection should be stored in the variable `sql_con`.

View the [templates](ra_exercise_generator/resources/templates/README.md) and [this test](tests/test_correct.py) for more information on what cells are generated and how one can incorporate them into an exercise Jupyter notebook.
test-whitebox-monitoring 0.0.1
Whitebox is an open source E2E ML monitoring platform with edge capabilities
Requires Python: >=3.6

<p align="center"><img src="assets/logo.svg" width="50%" alt="whitebox logo" /></p>

# Whitebox - Machine learning monitoring platform

## What is Whitebox?

Whitebox is an open source E2E ML monitoring platform with edge capabilities that plays nicely with kubernetes.

## Why use Whitebox?

Deploying a machine learning model in production is not the end of the lifecycle. You need data to iterate and improve.

<p align="center"><img src="assets/ui-prototype-demo.gif" width="50%" alt="whitebox logo" /></p>

# How to use

## Run the server

The project is still in rapid development so to run the server clone the repo and run:

```bash
python -m venv .venv
pip install -r requirements.txt
ENV=dev uvicorn src.main:app --reload
```

In the near future you will be able to `pip install whitebox` and run `whitebox serve` to run whitebox.

## High level diagram of model set up

All you have to do is register a model and send inference data through the SDK.

```mermaid
sequenceDiagram
    actor user
    participant whitebox

    user->>user: Import sdk

    note over user, whitebox: Configure model and monitors
    user->>whitebox: Register model and training set via SDK
    whitebox-->>user: Model ID
    user->>whitebox: Log model inferences and actuals

    note over user, whitebox: You can now start monitoring metrics and get alerts
    user->>whitebox: Setup monitors to get specific alert
    whitebox-->>user: Get alerted when an anomaly occurs
```

# Features

You can see all planned features on our [v1.0 milestone](https://github.com/squaredev-io/whitebox/milestone/1).

## Coming soon

- 📖 Docs
- 💻 Whitebox UI
- 📈 Regression models
- 🤖 Edge / privacy features

# Set up locally for development

Install packages:

```bash
python -m venv .venv
pip install -r requirements.txt
```

Run the server:

```bash
ENV=dev uvicorn src.main:app --reload
```

Tests:

- Run: `ENV=test pytest -s`
- Watch: `ENV=test ptw`
- Run test coverage `ENV=test coverage run -m pytest`
- Look at coverage report: `coverage report` or `coverage html` to generate an html. To view it in your browser open the `htmlcov/index.html` file.

# Contributing

We happily welcome contributions to Whitebox. You can start by opening a new issue!