semvec/pypi-packages huggingface dataset:
portableDB 2.2
This library is an easyest way to use local database!


    
# PortableDB Documentation

PortableDB is a lightweight, easy-to-use Python package for creating, managing, and interacting with portable databases.

## Installation

To install PortableDB, use pip:

```bash
pip install portableDB
```

## Methods

### ` db = DATABASE(name)`

Defines the database to work with. You must initialize a `DATABASE` object before using other methods.

- **Arguments:**
  - `name` (str): The name of the database file (e.g., `'Database.db'`).
    - This file will be created if it doesn't already exist.

### `db.LogType(Type)`

Sets the logging state for database operations.

- **Arguments:**
  - `Type` (str): Can be one of the following:
    - `'COLORFUL'`: Enables colorful logs for better readability.
    - `'BASE'`: Enables normal command-line logging.
    - `'NONE'`: Disables logging output.

### `db.CreateDatabase()`

Creates a new database.

- **Arguments:**
  - No arguments are required.

### `db.WriteDatabase(information, cell)`

Writes data to the database.

- **Arguments:**
  - `information` (array): An array of values to write (e.g., `['String value', 32]`).
  - `cell` (str): The cell where the data will be written (e.g., `'LOL'`).
    - Cell can be of any type or value.

### `db.WriteIndex(information, cell, index)`

Writes data to a specific index within a specified cell.

- **Arguments:**
  - `information` (any type): The information to write (e.g., `'PON'`).
  - `cell` (str): The cell in which to write the information (e.g., `'LOL'`).
    - Cell can be of any type or value.
  - `index` (int): The index at which to write the information (e.g., `0`).

### `db.ReadDatabase(cell, index)`

Reads data from the database.

- **Arguments:**
  - `cell` (str): The cell to read from (e.g., `'LOL'`).
  - `index` (str or int, optional): 
    - `'ALL'`: Reads all elements in the specified cell.
    - An integer: Reads the specific element at the given index in the array.
    - If this argument is ignored, it behaves like `'ALL'` was given.

- **Returns:**
  - The data read from the specified cell and index.

### `db.RenameDatabase(newName)`

Renames the database.

- **Arguments:**
  - `newName` (str): The new name for the database (do not include the file type like '.db').

### `db.DeleteDatabase()`

Deletes the specified database.

- **Arguments:**
  - No arguments are required.
som-nlp 0.3
Somali Lemmatization and POS Tagging Library
Requires Python: >=3.6

# Somali NLP Library (`som-nlp`)

`som-nlp` is a lightweight Python library for performing **lemmatization** and **POS (Part-of-Speech) tagging** on Somali text. This library is designed to help developers and researchers process Somali text efficiently.

## Features
- **Lemmatization**: Reduce words to their base or dictionary form.
- **POS Tagging**: Assign part-of-speech tags (e.g., Noun, Verb) to Somali words.

---

## Installation

You can install the library directly using pip:

```bash
pip install som-nlp
legislice 0.8.1
API client for fetching and comparing passages from legislation
Requires Python: >=3.11

# Legislice

[![An Ethical Open Source Project](https://img.shields.io/badge/open-ethical-%234baaaa)](https://ethicalsource.dev/licenses/) [![Tests](https://github.com/mscarey/legislice/actions/workflows/python-package-2.yml/badge.svg)](https://github.com/mscarey/legislice/actions) [![Coverage Status](https://coveralls.io/repos/github/mscarey/legislice/badge.svg?branch=master)](https://coveralls.io/github/mscarey/legislice?branch=master) [![Documentation Status](https://readthedocs.org/projects/legislice/badge/?version=latest)](https://legislice.readthedocs.io/en/latest/?badge=latest)[![PyPI - Python Version](https://img.shields.io/pypi/pyversions/legislice)](https://pypi.org/project/legislice/)


Legislice is a utility for downloading the text of statutes and constitutional provisions, and then creating computable objects representing passages from those provisions. Legislice is used by [AuthoritySpoke](https://authorityspoke.readthedocs.io).

View the [documentation on ReadTheDocs](https://legislice.readthedocs.io/en/latest/).
topsis-HimanshuBhumbla-102203043 0.2.0
A Python package to perform Topsis analysis.
Requires Python: >=3.6

# TOPSIS Command Line Program

A Python program to perform the **TOPSIS (Technique for Order Preference by Similarity to Ideal Solution)** analysis on a given dataset.

## Description

TOPSIS is a multi-criteria decision-making approach that ranks a set of alternatives based on their distance to the ideal best and ideal worst solutions. This program:

1. **Normalizes** the criteria values.
2. Applies **user-defined weights**.
3. Identifies the **ideal best (v+)** and **ideal worst (v-)** values.
4. Calculates the **Euclidean distance** of each alternative from these ideal solutions.
5. Computes the **TOPSIS score** (`dist_worst / (dist_best + dist_worst)`).
6. **Ranks** the alternatives (higher score â†’ better rank).

## Requirements

- **Python 3.x**
- **pandas** (Install via `pip install pandas`)
- **numpy** (Install via `pip install numpy`)

## File Structure

- **Script Name**: `setup.py`  
  

- **Input CSV File**: `102203043-data.csv`  
  - Must contain at least 3 columns.
  - The **first column** is the identifier (e.g., M1, M2, ...).
  - The **remaining columns** are numeric (no missing or non-numeric values).

- **Output CSV File**: `102203043-result.csv`  
  - Will contain the original columns plus two additional columns:  
    - **Topsis Score**  
    - **Rank**

## Usage

Open a terminal/command prompt in the directory containing your Python script and run:

```bash
python setup.py <InputDataFile> <Weights> <Impacts> <ResultFileName>
```
justopinion 0.4.0
Download client for legal opinions
Requires Python: >=3.11

Justopinion
===========

A Python library for downloading and researching legal opinions
using the `Caselaw Access Project API`_. Note that new CAP accounts
are no longer available and the CAP API was sunset on September 1, 2024.

.. image:: https://img.shields.io/badge/open-ethical-%234baaaa
    :target: https://ethicalsource.dev/licenses/
    :alt: An Ethical Open Source Project

.. image:: https://coveralls.io/repos/github/mscarey/justopinion/badge.svg?branch=master
    :target: https://coveralls.io/github/mscarey/justopinion?branch=master
    :alt: Test Coverage Percentage

.. image:: https://github.com/mscarey/justopinion/actions/workflows/python-package.yml/badge.svg
    :target: https://github.com/mscarey/justopinion/actions
    :alt: GitHub Actions Workflow

.. image:: https://readthedocs.org/projects/justopinion/badge/?version=latest
    :target: https://justopinion.readthedocs.io/en/latest/?badge=latest
    :alt: Documentation Status

.. image:: https://img.shields.io/pypi/pyversions/justopinion
    :target: https://pypi.org/project/legislice/
    :alt: PyPI - Python Version

Examples
--------

In this example, Justopinion is used to download the decision with the citation `1 Breese 34`.

    >>> import os
    >>> from justopinion import CAPClient
    >>> client = CAPClient(api_token=os.getenv("YOUR_SECRET_API_TOKEN"))
    >>> thornton = client.read_cite("1 Breese 34", full_case=True)
    >>> thornton.casebody.data.parties[0]
    'John Thornton and others, Appellants, v. George Smiley and John Bradshaw, Appellees.'

You can also use Justopinion to locate text in an opinion:

    >>> thornton.opinions[0].locate_text("The court knows of no power in the administrator")
    TextPositionSet{TextPositionSelector[22, 70)}

Or to get the text from a specified location in the opinion:

    >>> selection = thornton.opinions[0].select_text([(258, 294), (312, 359)])
    >>> str(selection)
    '…The note was made to West alone, and…the suit should have been commenced in his name…'

And you can use Justopinion to follow citations in an opinion and download the cited cases:

    >>> str(thornton.cites_to[0])
    'Citation to 15 Ill., 284'
    >>> cited = client.read_cite(thornton.cites_to[0], full_case=True)
    >>> str(cited)
    'Marsh v. People, 15 Ill. 284 (1853-12-01)'

.. _Caselaw Access Project API: https://api.case.law/v1/