semvec/pypi-packages huggingface dataset:
routexplorer 0.0.5
RouteXplorer is a lib developed to optimize routes in Complete Graphs.
Requires Python: >=3.8,<4.0



<p align="center">
  <img src="https://i.imgur.com/PLB1GAQ.png">
</p>

<br>
<br>

[![Python](https://img.shields.io/badge/Python-3.0%2B-blue.svg)](https://www.python.org/downloads/release/python-300/)
[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
[![Development Status](https://img.shields.io/badge/Development%20Status-Alpha-orange)](https://github.com/vsg-root/RouteXplorer)

[RouteXplorer](https://github.com/vsg-root/RouteXplorer) is a Python library developed to solve the Traveling Salesman Problem (TSP) in complete graphs. Its goal is to find the most efficient sequence of visiting nodes in a graph, minimizing the total distance traveled.
<br>

## Install

```python
$ pip install routexplorer
```

##### Try your first RouteXplorer program
```python
$ python
```
```python
>>> from routexplorer.utils.input_reader import InputReader
>>> from routexplorer.algorithms.BruteForceSearch import BruteForceSearch

>>> # Datas of graph
>>> graph = InputReader.read_file(input("Enter file path: ")) 

>>> # Calculation of the best path and distance
>>> best_path, best_distance = BruteForceSearch.find_best_path(graph, True, True)
```
##### Create a .txt file
```bash
4 5
0 0 0 0 D
0 A 0 0 0
0 0 0 0 C
R 0 B 0 0
```
```python
$ Enter file path: file/path/file.txt
```
```
100% [■■■■■■■■■■] - Generating permutations
100% [■■■■■■■■■■] - Checking paths
Best path: ['A', 'D', 'C', 'B'] 
Shorter distance: (14)
```

## Key Features

- Efficient Algorithms: RouteXplorer implements a variety of optimized algorithms to solve the Traveling Salesman Problem, allowing you to find solutions quickly and efficiently.

- Flexible Customization: The library offers flexible options to customize the algorithm settings, allowing you to adapt the optimization process to the specific needs of your project.

- Simple Integration: The library is easy to integrate into your existing Python projects, allowing you to leverage its powerful functionality without complications.


## Contribution

RouteXplorer is an open source project and we encourage community contributions. If you want to contribute, please follow the guidelines outlined in the repository's CONTRIBUTING.md file.

## License

RouteXplorer is distributed under the MIT license. For more information, see the LICENSE.md file.
JacksonQuery 0.0.1
Automated interaction and data extraction tool for Jackson National Life Insurance website
Requires Python: >=3.11
Keywords: automation,jackson,scraping,selenium

# JacksonQuery

JacksonQuery is a Python package designed to automate the process of downloading, parsing, and analyzing web content 
from the Jackson National Life (JNL) Insurance website located at www.jackson.com. Its main objective is to facilitate 
investment advisers in making informed decisions about variable annuity subaccount investments.

This package finds, downloads, and parses content of all the variable annuity subaccount prospectuses and Morningstar 
reports found on the JNL website. The parsed content is processed into data structures, enabling easy and efficient data 
analysis. Additionally, JacksonQuery provides a factor model and a portfolio optimization module, automating the 
investment selection and portfolio construction process.

The JNL website provides data on their variable annuity subaccounts only in the form of fund prospectuses and 
Morningstar reports, all in PDF format. There are approximately 120 JNL variable annuity subaccounts for their 
Perspective L product, and the task of going through all of this data is daunting for investment advisers. JacksonQuery 
aims to minimize heuristics and maximize statistical methods in decision-making for investment advisers, making it 
easier to choose the most appropriate subaccounts for their clients.

## Features
- Automated Web Navigation: Automatically logs into the JNL website, navigates to the necessary pages, and handles any 
pop-ups or prompts along the way.
- Data Extraction: Fetches the most recent prospectuses and Morningstar reports for all variable annuity 
subaccounts.
- Advanced Parsing: Utilizes the powerful tika library to parse PDFs and organize the data into easily analyzable 
structures.
- Factor Modeling: Implements a factor model to analyze the performance of the subaccounts.
- Portfolio Optimization: Provides a module to automate the process of creating optimal portfolios based on the parsed 
data.

## Installation
JacksonQuery is available on PyPI and can be installed via pip:
```
pip install jacksonquery
```

## Usage
See the [examples](https://github.com/nathanramoscfa/JacksonQuery/tree/master/examples) directory for usage examples.

## Disclaimer
JacksonQuery is not affiliated with Jackson National Life Insurance Company in any way. This package is not intended to
be used for any purpose other than for educational purposes. Past performance is not indicative of future results. The 
authors of this package are not responsible for any financial losses that may occur as a result of using this package. 
Use at your own risk. 

## License
[MIT](https://choosealicense.com/licenses/mit/)