semvec/pypi-packages huggingface dataset:
hashime 0.2.0
hash visualization tool

# hashime

[![CI](https://github.com/sakhezech/hashime/actions/workflows/ci.yaml/badge.svg)](https://github.com/sakhezech/hashime/actions/workflows/ci.yaml)

Hash visualization tool inspired by beautiful ssh-keygen randomart.

How can something so soulless be so pretty?

## Installation

From PyPI:

```sh
pip install hashime
```

From git:

```sh
pip install git+https://github.com/sakhezech/hashime
```

## Usage as CLI

`hashime ...` or `python -m hashime ...`

```console
$ hashime -h
usage: hashime [-h] [-v] [-l] [-a ALGO] [-H HASH] [--frame FRAME | --no-frame]
               [--top-text TOP_TEXT] [--bottom-text BOTTOM_TEXT]
               [-d [DIGEST_FORM]] [-o OUT]
               [file]

hash visualization tool

positional arguments:
  file                  input file (defaults to stdin)

options:
  -h, --help            show this help message and exit
  -v, --version         show program's version number and exit
  -l, --list            show visualization algorithms, hashing functions,
                        digest forms and exit
  -a ALGO, --algorithm ALGO
                        visualization algorithm (defaults to drunken_bishop)
  -H HASH, --hash-function HASH
                        hashing function (defaults to sha256)
  --frame FRAME         comma-separated frame characters in order of
                        (top_line, right_line, bottom_line, left_line,
                        top_left_corner, top_right_corner,
                        bottom_right_corner, bottom_left_corner, left_bracket,
                        right_bracket)
  --no-frame            output visualization without a frame
  --top-text TOP_TEXT   text on the top frame line
  --bottom-text BOTTOM_TEXT
                        text on the bottom frame line
  -d [DIGEST_FORM], --digest [DIGEST_FORM]
                        show digest (defaults to base64)
  -o OUT, --output OUT  output file (defaults to stdout)

$ hashime -H md5 -d base64 LICENSE
+----[LICENSE]----+
|                 |
|         .       |
|  . .   o        |
| . = o +         |
|  * * + S        |
| o O +           |
|  * = +          |
| . + = .         |
|    E .          |
+------[MD5]------+
md5: lGqJe4ZYqSXluPYkZOH/oQ==
```

## Usage in code

```py
>>> import hashime
>>> bishop = hashime.DrunkenBishop()
>>> bishop.update_from_file_hash('./LICENSE')
>>> art = bishop.to_art(
...     top_text='LICENSE',
...     bottom_text='SHA256',
...     brackets=('<', '>'),
...     lines=('═', '│', '─', '║'),
...     corners=('╔', '╕', '┘', '╙'),
... )
>>> print(art)
╔════<LICENSE>════╕
║    ..o +        │
║   o E.= o       │
║  o +.. o        │
║ . o o.o         │
║.   o =.S.       │
║..   o.+..+      │
║o.  o.oo+..=     │
║. . *+=..+o o .  │
║  .=+O.++  . o.. │
╙─────<SHA256>────┘
```

## Development

Use `ruff check --fix .` and `ruff format .` to check and format your code.

To get started:

```sh
git clone https://github.com/sakhezech/hashime
cd hashime
python -m venv .venv
source .venv/bin/activate
pip install -e '.[dev]'
```
Topsis-Yatharth-102303136 0.0.1
A Python package for TOPSIS multi-criteria decision making
Requires Python: >=3.6

# Topsis-Yatharth-102303136

This package implements the TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) method.

## Installation
```bash
pip install Topsis-Yatharth-102303136
topsis-purnika-102303412 1.0.2
This package implements the TOPSIS method for multi-criteria decision making using a command-line interface. It allows users to rank alternatives from a CSV file by specifying custom weights and impacts. The package includes input validation and generates a ranked output file efficiently. It is designed for academic and practical decision-analysis use.
Requires Python: >=3.8

# TOPSIS – Multi-Criteria Decision Making Tool

This Python package implements the **TOPSIS (Technique for Order Preference by Similarity to Ideal Solution)** method.  
It is developed to rank alternatives based on multiple criteria and is useful in decision-making problems such as product selection, college ranking, supplier evaluation, and more.

---

##  Author

This package has been **created and developed by Purnika Malhotra** 
---

##  Features
- Command-line based TOPSIS implementation  
- Accepts CSV input file  
- Supports user-defined weights and impacts  
- Generates ranked output CSV file  
- Proper input validation and error handling  

---

##  Installation

Install the package using pip:

```bash
pip install Topsis-Purnika-102303412
pyPhasesRecordloaderAlice 0.2.0
Adds a record loaders to the pyPhases package
Requires Python: >=3.5

# Extension for pyPhasesRecordloader



## Usage

In a phase you can access the data through the `RecordLoader`:

Add the plugins and config values to your project.yaml::

```yaml
name: AliceProject
plugins:
  - pyPhasesML
  - pyPhasesRecordloaderAlice
  - pyPhasesRecordloader

phases:
  - name: MyPhase

config:
  alice-path: C:/datasets/recordings

```

In a phase (`phases/MyPhase.py`) you can access the records using the `RecordLoader`:

```python
from pyPhasesRecordloader import RecordLoader
from pyPhases import Phase

class MyPhase(Phase):
    def run(self):
      recordIds = recordLoader.getRecordList()
      for recordId in recordIds:
        record = recordLoader.getRecord(recordId)
```

Run your project with `python -m phases run MyPhase`.
banana-hep 0.6.17
Benchmark QCD physics
Requires Python: <4.0,>=3.9

<p align="center">
  <a href="https://n3pdf.github.io/banana/"><img alt="Banana" src="https://raw.githubusercontent.com/N3PDF/banana/main/docs/_assets/logo.png" width=700></a>
</p>

<p align="center">
  <a href="https://github.com/N3PDF/banana/actions?query=workflow%3A%22unit+tests%22">
    <img alt="Tests" src="https://github.com/N3PDF/banana/workflows/unit%20tests/badge.svg">
  </a>
  <a href='https://banana-hep.readthedocs.io/en/latest/?badge=latest'><img src='https://readthedocs.org/projects/banana-hep/badge/?version=latest' alt='Documentation Status' /></a>
  <a href="https://pypi.org/project/banana-hep/"><img alt="PyPI" src="https://img.shields.io/pypi/v/banana-hep"/></a>
  <a href="https://doi.org/10.5281/zenodo.4247164"><img src="https://zenodo.org/badge/DOI/10.5281/zenodo.4247164.svg" alt="DOI"></a>
  <a href="https://codecov.io/gh/N3PDF/banana">
    <img src="https://codecov.io/gh/N3PDF/banana/branch/main/graph/badge.svg?token=L9XIAXV77R"/>
  </a>
  <a href="https://www.codefactor.io/repository/github/n3pdf/banana">
    <img src="https://www.codefactor.io/repository/github/n3pdf/banana/badge?s=1f7766473570c0d6432d5a2d216498b09a50c2b5" alt="CodeFactor" />
  </a>
</p>

# banana: Benchmarking AgaiNst Apfel aNd Anything

This is the base package of ekomark and yadmark