semvec/pypi-packages huggingface dataset:
ormstorm 0.0.3.0
Small library for easy work with databases.
Keywords: python,orm,database,sql,sqlite3

﻿# Welcome to ORMStorm

ORMStorm is a small library for easy work with databases.

## The key features are:

 - **Simplicity:** The library is very simple, and it won't take long to learn it.
 - **Coding speed:** Integrating the library into your projects won't take long.
 - **Dynamic:** Unlike others, this library will allow you to very quickly create new tables and add databases to them.

## Installing

    pip install ormstorm
   
## Usage

Using standard tables

```python
from ormstorm import Table, Types, Column, create_session  


class ExampleTable(Table): 
    __tablename__ = "example"  
      
    id = Column(Types.INTEGER, primary_key=True, autoincrement=True)  
    text = Column(Types.STRING)  
      
      
LocalSession = create_session("example.sqlite3", [ExampleTable])  
      
with LocalSession() as session:  
    session.insert(ExampleTable(text="Hello, world!"))
```

Using a dynamic table

```python
from ormstorm import DynamicTable, Types, Column, create_session  
      
      
LocalSession = create_session("example.sqlite3", [])  
      
with LocalSession() as session:  
    NewTable = DynamicTable(  
        "new_table", {"id": Column(Types.INTEGER, primary_key=True, autoincrement=True), "text": Column(Types.STRING)}  
    )  
      
    session.create(NewTable)  
    session.insert(NewTable(text="Easy use of dynamic tables!"))
```

## Magic filters

Magic filters is a special system that allows you to quickly write conditions for sql queries in the usual python style!
Magic filters currently support the following operators: `=`, `!=`, `>=`, `>`, `<=`, `<`, `&`, `|`, `~`

Simple use of magic filters:

```python
from ormstorm import Table, Types, Column, create_session


class ExampleTable(Table):
    __tablename__ = "example"

    id = Column(Types.INTEGER, primary_key=True, autoincrement=True)
    text = Column(Types.STRING)


LocalSession = create_session("example.sqlite3", [ExampleTable])

with LocalSession() as session:
    result = session.select(
        (ExampleTable.text == "Hello") | ((ExampleTable.id > 5) & (ExampleTable.id < 15))
    )
```

Instead of the usual `and` and `or`, `&` and `|` are used, respectively. Also, `~` is used instead of the `or` keyword.
It is also worth noting that some expressions should be wrapped in parentheses to avoid unexpected errors.

To select all data from a table, simply specify its class.

```python
result = session.select(ExampleTable)
```

## Documentation

At the moment, all documentation is located in the library itself. Each function and class has good documentation to understand what the function is for.

## Note

This library is strictly not recommended for use in large projects because of the small functionality!
skapex 0.2.1
Leveraged Affinity Propagation implementation
Requires Python: >=3.7

=====================================================
skapex: Leveraged Affinity Propagation implementation
=====================================================
Features
--------
- Implements Leveraged Affinity Propagation (LAP).
- Maintains compatibility with scikit-learn, enabling seamless integration with existing scikit-learn workflows.

Installation
------------
You can install skapex via pip:

.. code-block:: bash

   pip install skapex

Usage
-----
Here's a basic example of how to use skapex LAP for clustering:

.. code-block:: python

   from skapex import LeveragedAffinityPropagation
   from sklearn.datasets import make_blobs
   from sklearn.metrics.pairwise import euclidean_distances

   # Generate sample data
   X, _ = make_blobs(n_samples=200, centers=3, random_state=0)

   # Create and fit the skapex Leveraged Affinity Propagation
   model = LeveragedAffinityPropagation(simf=lambda x,y : -euclidean_distances(x, y, squared=True), fraction=0.1, sweeps=5)
   model.fit(X)

   # Get cluster labels for the input data
   labels = model.labels_

   # Print the resulting cluster labels
   print(labels)

References
----------

B. J. Frey and D. Dueck, “Clustering by Passing Messages Between Data
Points,” Science, vol. 315, no. 5814, pp. 972–976, Feb. 16, 2007, issn: 0036-
8075, 1095-9203. doi: 10.1126/science.1136800.

U. Bodenhofer, A. Kothmeier, and S. Hochreiter, “APCluster: An R package
for affinity propagation clustering,” Bioinformatics, vol. 27, no. 17, pp. 2463–
2464, Sep. 1, 2011, issn: 1367-4803. doi: 10.1093/bioinformatics/btr406.
minimalmodbus 2.1.1
Easy-to-use Modbus RTU and Modbus ASCII implementation for Python
Requires Python: >=3.8
Keywords: minimalmodbus,modbus,modbus-serial,modbus-RTU,modbus-ASCII

===============================
MinimalModbus
===============================

.. image:: https://github.com/pyhys/minimalmodbus/actions/workflows/build.yml/badge.svg
        :target: https://github.com/pyhys/minimalmodbus/actions
        :alt: Build Status

.. image:: https://codecov.io/gh/pyhys/minimalmodbus/branch/master/graph/badge.svg?token=6TcwYCQJHF
        :target: https://codecov.io/gh/pyhys/minimalmodbus
        :alt: Test coverage report

.. image:: https://readthedocs.org/projects/minimalmodbus/badge/?version=master
        :target: https://readthedocs.org/projects/minimalmodbus/?badge=master
        :alt: Documentation Status

.. image:: https://img.shields.io/pypi/v/minimalmodbus.svg
        :target: https://pypi.org/project/minimalmodbus/
        :alt: PyPI page link


Easy-to-use Modbus RTU and Modbus ASCII implementation for Python.

Web resources
-------------

* **Documentation**: https://minimalmodbus.readthedocs.io
* Source code on **GitHub**: https://github.com/pyhys/minimalmodbus
* Python package index (PyPI) with download: https://pypi.org/project/minimalmodbus/

Other web pages:

* Readthedocs project page: https://readthedocs.org/projects/minimalmodbus/
* codecov.io project page: https://codecov.io/github/pyhys/minimalmodbus

Obsolete web pages:

* Old Travis CI build status page: https://travis-ci.org/pyhys/minimalmodbus
* Old Sourceforge documentation page: http://minimalmodbus.sourceforge.net/
* Old Sourceforge project page: https://sourceforge.net/projects/minimalmodbus
* Old Sourceforge repository: https://sourceforge.net/p/minimalmodbus/code/HEAD/tree/


Features
--------
MinimalModbus is an easy-to-use Python module for talking to instruments (slaves)
from a computer (master) using the Modbus protocol, and is intended to be running on the master.
The only dependence is the pySerial module (also pure Python).

There are convenience functions to handle floats, strings and long integers
(in different byte orders).

This software supports the 'Modbus RTU' and 'Modbus ASCII' serial communication
versions of the protocol, and is intended for use on Linux, OS X and Windows platforms.
It is open source, and has the Apache License, Version 2.0.

For Python 3.8 and later. Tested with Python 3.8, 3.9, 3.10, 3.11 and 3.12.

This package uses semantic versioning.