semvec/pypi-packages huggingface dataset:
ugbib-divers 0.1.0
Diverse Module ohne weitere Abhängigkeiten
Requires Python: >=3.10

ugbib_divers
============

ugb_divers enthält Module ohne weitere Abhängigkeiten. Das sind:

* bibGlobal
* bibGymbols


bibGlobal
---------

Enthält eine Klasse glb, die es erlaubt, globale Variablen mehreren eingebundenen
Modulen verfügbar zu machen.


### Nutzung

Z.B. Datenbank-Connection, die von einer App oder einem Modul hergestellt wird, kann
als `glb.DB` Modul-übergreifend verwendet werden.


### Beispiel

```python
from bibglobal import glb

glb.setup('DB')
glb.DB = sqlite3.connect('...')
Cur = glb.DB.cursor()
Cur.execute('...')
Cur.close
```


bibSymbols
----------

Enthält Symbole aus dem UTF-8 Zeichensatz mit hilfreichen Abkürzungen


### Anwendung

Ursprünglich wurde diese Sammlung für Textual Formulare gebaut, um "Icons" für
Mini-Buttons zu haben. Selbstverständlich kann es aber auch anders verwendet werden.


### Beispiel

```python
from bibsymbols import Symbols

S = Symbols()

print(S.first)
```
PerspectiveLearning 0.1.0
A dynamic framework for hypothesis-driven iterative machine learning.
Requires Python: >=3.6

# PerspectiveLearning

**PerspectiveLearning** is a Python library for hypothesis-driven iterative machine learning.

## Features
- Define multiple perspectives for hypothesis evaluation.
- Iteratively train and refine the best perspective.
- Predict outcomes using the refined model.

## Installation
Install via pip:
```
pip install PerspectiveLearning
```


## Usage
```python
from PerspectiveLearning import PerspectiveLearning

# Example usage with dataset
pl = PerspectiveLearning(dataset, features, target, perspectives)
pl.train()
predictions = pl.predict(new_data)
```
datapush 1.0.1
MySQL Data Generator
Requires Python: >=3.7

# Datapush

Datapush is a Python package that generate data to MySQL Database dynamically.  

When you need data for MySQL for some reasons (for test), and too lazy to make mock data, here is the answer.  

***Just enter your table, datapush will check each column and automatically generate the appropriate data!***

## Download

```bash
pip install datapush
```

## Usage
```python
# Connect to db
conn = datapush.mysql.connect(
    host='localhost',
    port=3306,
    user='root',
    password='',
    database=''
)

# Make generator with connection
generator = datapush.Generator(conn)

# Generate!
generator.generate(
    table='example_table'
)
```

## Option
In generator.generate(), there has several options.

    Args:
        - table         (str): The name of the table.
        - count         (int): The number of data you want to generate. (default: 10)
        - **option      (dict): Some specific data for each column
                        you want to generate (uuid, username, ip, etc...)  
                        ex) user=id, uuid=uuid, ip_address=ip,   
                        ex) column_name=type

## Extra Usage
```python
generator.generate(
    table='example_table',
    count=1000,
    char_col='ip',          # column_name is char_col and make unique ip
    text_col='id',          # column_name is text_col and make unique id
    varchar_col='uuid'      # column_name is varchar_col and make unique uuid
)
```

## Note
Currently, we don't support spartial data type (geometry, point, polygon etc...)