semvec/pypi-packages huggingface dataset:
niho 1.0.0
Niho is a simple HTTP server framework.
Requires Python: >=3.7

# Niho

Niho is a simple HTTP server framework for Python.

## Features
- Lightweight and easy to use.
- Add, update, and delete routes with ease.

## Installation
Install Niho using pip:
```bash
pip install niho
```

```python
from niho import NihoServer // import package

PORT = 3000
server = NihoServer() // create server

server.add("/", "Welcome to the homepage!") // "/" for homepage
server.add("/about", "This is the about page.")
server.add("/helloworld","path/to/your/html_file.html") // For add html file
server.set("/", status_code=200, content="Homepage with custom status code")
server.run(port=PORT)  # IP defaults to localhost change with ip=INPUT_IP if you want
```
datalib-ha 1.0.0
A comprehensive data analysis library for Python
Requires Python: >=3.8
Keywords: data-analysis statistics machine-learning

# DataLib: Python Data Analysis Library

## Overview

DataLib is a comprehensive Python library designed to simplify data manipulation, statistical analysis, visualization, and machine learning tasks. It provides an intuitive and powerful set of tools for data scientists, researchers, and analysts.

## Features

### Data Manipulation
- CSV file loading and saving
- Data filtering
- Missing value handling
- Data normalization

### Statistical Analysis
- Descriptive statistics
- Correlation analysis
- T-tests
- Chi-square tests

### Data Visualization
- Bar plots
- Histograms
- Scatter plots
- Correlation heatmaps

### Advanced Analysis
- Linear and Polynomial Regression
- Classification Algorithms (KNN, Decision Trees)
- Clustering (K-means)
- Dimensionality Reduction (PCA)

## Installation

```bash
pip install datalib
```

## Quick Examples

### Data Manipulation
```python
from datalib.data_manipulation import DataManipulation

# Load CSV
df = DataManipulation.load_csv('data.csv')

# Filter data
filtered_df = DataManipulation.filter_data(df, {'age': lambda x: x > 25})
```

### Statistical Analysis
```python
from datalib.statistics import StatisticalAnalysis

# Calculate descriptive stats
stats = StatisticalAnalysis.descriptive_stats(df['column'])

# Correlation matrix
corr_matrix = StatisticalAnalysis.correlation(df)
```

### Visualization
```python
from datalib.visualization import DataVisualization

# Create bar plot
DataVisualization.bar_plot(df, 'category', 'value')

# Scatter plot
DataVisualization.scatter_plot(df, 'x_column', 'y_column')
```

## Contributing

Contributions are welcome! Please check our GitHub repository for guidelines.

## License

This project is licensed under the MIT License.
BidmangerRealEstate 0.0.2
A small example package
Requires Python: >=3.6

The bidding_manager.py library is a key component of the application that manages all bidding-related functionalities for the property management system. It provides seamless integration with AWS DynamoDB to handle essential operations such as placing bids, retrieving all bids for a property, determining the highest bid, and accepting bids for properties.

Key Features:

	•	Placing Bids: Ensures buyers can place valid bids that are higher than the current highest bid for a property.
	•	Fetching Bids: Retrieves all bids associated with a property and sorts them in descending order based on bid amount.
	•	Determining the Highest Bid: Quickly identifies the highest bid placed on a property for validation and display purposes.
	•	Accepting Bids: Allows sellers to accept a specific bid, marking the bid as “accepted” and updating the associated property’s status to “sold.”
	•	Efficient Data Handling: Utilizes DynamoDB to store and query bid and property data efficiently, ensuring scalability and reliability.
safe-dencrypt 0.2
A lib to decrypt or encrypt message convinet and safe!expert!

**超安全加密解密库**

safecrypt是一个专业加密解密库,只要一个密码,且拥有<u>庞大</u>团队~~(足足有一人)~~

安装方法:

```bash
pip install safecrypt
```

使用方法

```python
fuction nencrypt(str: string,str magic):
    parm:string
    explain:需要加密的文本,必要
    parm:magic
    explain:密码,非必要
    return:string
    like 10010101010101.........此类01码,很长
fuction ndecrypt(str: string,str magic):
    parm:string
    explain:需要解密的文本like 10010101010101此类01码,必要
    parm:magic
    explain:密码,非必要
    return str:原文本,一旦有error返回int:错误码-1
   
```
且密码可以是中文

更难破解

安全性放心吧


example:

```py
import safecrypt as s
a=s.nencrypt("123")
print(a)
b=s.ndecrypt(a)
print(b)
```

```bash
00000000000000000000000000000000000000
011000000011000000000000000000000000000
000000000010001011000000000000000000000
0000000000000000000000000001110011000000
0000000000000000000000000000000011000001
1000000000000000000000000000000000000000
00000011011011000000000000000000000000000
00000000000000011000000000000000000000000
0000000000000000000011110000000000000000000
000000000000000000000000000100110010000000
000000000000000000000000000000000000000101
011000000000000000000000000000000000000000
000000111011100000000000000000000000000000
000000001011100000010000000000000000000000
00000000000000000000011000000000000000000000
0000000000000000000000000001001101100000000
000000000000000000000000000000101110011111
0000000000000000000000000000000000000000000
0011011000000000000000000000000000000000000
0000000010000000000000000000000000000000000
0000000000000000100100000000000000000000000
0000000000000000000000011000000000000000000
0000000000000000000000000000000111000000000
0000000000000000000000000000000000000111110
0000000000000000000000000000000000000000000
1000000000000000000000000000000000000000000
0000000010010000000000000000000000000000000
0000000000000001111100000000000000000000000
0000000000000000000000010100000000000000000
0000000000000000000000000000011111000000000
0000000000000000000000000000000000001110000
00000000000000000000000000000000000000000001
01010000000000000000000000000000000000000000
00000100010000000000000000000000000000000000
00000000000000000000000000000000000000000000
00000000000000000000000000000000000000000000
00000000000000000000000000010000000000000000
00000000000000000000000000000000000000000000
00000000000000000000000000000000000000010000
00000000000000000000000000000000000000000000
01000000000000000000000000000000000000000000
00000000000000000000000000000000000000000000
00000000000000000000000000000000000000000000
00000000000000000001000000000000000000000000
00000000000000000000000001000000000000000000
00000000000000000000000000000000000000000000
000000000000000000000000000000000000010000000
000000000000000000000000000000000000000000100
0000000000000000000000000000000000000000000000
0000000000000000000000000000000000000000000001101110
123



```



是不是很长

这就是他的安全性

难以破解

且密码可以是中文

更难破解

安全性放心吧
Bidmanger-pkg 0.0.2
A small example package
Requires Python: >=3.6

The bidding_manager.py library is a key component of the application that manages all bidding-related functionalities for the property management system. It provides seamless integration with AWS DynamoDB to handle essential operations such as placing bids, retrieving all bids for a property, determining the highest bid, and accepting bids for properties.

Key Features:

	•	Placing Bids: Ensures buyers can place valid bids that are higher than the current highest bid for a property.
	•	Fetching Bids: Retrieves all bids associated with a property and sorts them in descending order based on bid amount.
	•	Determining the Highest Bid: Quickly identifies the highest bid placed on a property for validation and display purposes.
	•	Accepting Bids: Allows sellers to accept a specific bid, marking the bid as “accepted” and updating the associated property’s status to “sold.”
	•	Efficient Data Handling: Utilizes DynamoDB to store and query bid and property data efficiently, ensuring scalability and reliability.
CroustiiLog 0.1.1
A customizable logging package
Requires Python: >=3.6

# CroustiiLog

**CroustiiLog** is a customizable logging package for Python that allows you to log messages with timestamps and different log levels such as `INFO`, `DEBUG`, `ERROR`, and `SUCCESS`. It also supports custom formatting and colorization for a more aesthetic and practical logging experience.

## Features

- Colored logging output with customizable colors.
- Customizable log format (e.g., with or without timestamps).
- Multiple log levels: `INFO`, `DEBUG`, `ERROR`, `SUCCESS`, `FATAL`.
- Support for key-value logging.
- Tree-style vertical logging for structured data.


## Installation

You can install **CroustiiLog** via pip:

```bash
pip install CroustiiLog



from croustiilog import CustomLog

# Create a CustomLog instance
log = CustomLog()

# Log with different levels
log.info("This is an info log.")
log.debug("This is a debug log.")
log.error("This is an error log.")
log.success("This is a success log.")
log.fatal("This is a fatal log.")


log.log("Retrieved", code="6969")


from colorama import Fore

log = CustomLog(color_map={
    "INFO": Fore.BLUE,
    "DEBUG": Fore.YELLOW,
    "ERROR": Fore.RED,
    "SUCCESS": Fore.GREEN,
    "FATAL": Fore.MAGENTA
})

log.info("This is a blue info log.")
log.error("This is a red error log.")

log = CustomLog(log_format="{timestamp} LEVEL > message")

log.info("This is a custom formatted info log.")