semvec/pypi-packages huggingface dataset:
database-util-lycgz 1.0.0
Provide utility method for database related operations.
Requires Python: >=3.12.3

# MySQL Utility Class

A Python utility class for interacting with MySQL databases using the `mysql-connector-python` library. This class simplifies connecting to a MySQL database, executing queries, committing changes, and closing the connection.

## Installation

Ensure you have the `mysql-connector-python` library installed. You can install it using pip:

```bash
pip install mysql-connector-python==9.1.0
nonebot-plugin-helldivers-tools 0.1.0
NoneBot2 绝地潜兵助手
Requires Python: >=3.9
Keywords: nonebot2, helldivers

## nonebot_plugin_helldivers_tools

- 基于[nonebot2](https://github.com/nonebot/nonebot2)

## 功能

- 简报，从 https://hd2galaxy.com 获取最新得星系战争情报（仅对该网站进行截图操作，本人对星球名字做了文本对照，使其与游戏内对应）
- 随机战备，使用随机数来随机选择四个战备，您可以使用该功能来丰富您得游戏体验

## 开始使用

- 在 nonebot2 项目的根目录下打开命令行, 输入以下指令即可安装
```
nb plugin install nonebot-plugin-helldivers-tools
```
- 使用包管理器安装
```
pip install nonebot-plugin-helldivers-tools
```

## 触发指令

`简报` 获取最新得星系战争情报

`随机战备` 按照提示回复数字，按照一定套路随机四个战备

## TODO
- [x] 构建带规则的随机方法
- [ ] 还没想好
spark-dataframe-tools 0.7.2
spark_dataframe_tools
Keywords: spark, dataframe

# spark_dataframe_tools

[![Github License](https://img.shields.io/badge/License-Apache%202.0-blue.svg)](https://opensource.org/licenses/Apache-2.0)
[![Updates](https://pyup.io/repos/github/woctezuma/google-colab-transfer/shield.svg)](pyup)
[![Python 3](https://pyup.io/repos/github/woctezuma/google-colab-transfer/python-3-shield.svg)](pyup)
[![Code coverage](https://codecov.io/gh/woctezuma/google-colab-transfer/branch/master/graph/badge.svg)](codecov)

spark_dataframe_tools is a Python library that implements styles in the Dataframe

## Installation

The code is packaged for PyPI, so that the installation consists in running:

```sh
pip install spark-dataframe-tools --user --upgrade
```

## Usage
```sh
import spark_dataframe_tools 
```

```sh
from pyspark.sql.types import StructType,StructField, StringType, IntegerType
data2 = [("James","","Smith","36636","M",3000),
    ("Michael","Rose","","40288","M",4000),
    ("Robert","","Williams","42114","M",4000),
    ("Maria","Anne","Jones","39192","F",4000),
    ("Jen","Mary","Brown","","F",-1)
  ]

schema = StructType([ \
    StructField("firstname",StringType(),True), \
    StructField("middlename",StringType(),True), \
    StructField("lastname",StringType(),True), \
    StructField("id", StringType(), True), \
    StructField("gender", StringType(), True), \
    StructField("salary", IntegerType(), True) \
  ])
 
df = spark.createDataFrame(data=data2, schema=schema)
```

## Pandas

```sh
df_pandas = df.toPandas()
df_pandas.show2()
```

## Spark

```sh
# Dataframe template table
df.show2()

# Dataframe memory usage
df.size()
```



## License

[Apache License 2.0](https://www.dropbox.com/s/8t6xtgk06o3ij61/LICENSE?dl=0).

## New features v1.0

## BugFix

- choco install visualcpp-build-tools

## Reference

- Jonathan Quiza [github](https://github.com/jonaqp).
- Jonathan Quiza [RumiMLSpark](http://rumi-ml.herokuapp.com/).