semvec/pypi-packages huggingface dataset:
certificates 2.3.0
Generate event certificates easily.
Requires Python: >=3.12

#  Certificates

Generate event certificates easily.

## Requirements

* Inkscape (`apt install inkscape`)

## Installation

Use the package manager [pip](https://pip.pypa.io/en/stable/) to install certificates.

```bash
pip install certificates
```

## Usage

`certificates participants.csv template.svg`

```
usage: certificates [-h] [--output OUTPUT] participants template

positional arguments:
  participants          csv filaname containing participants
  template              certificate template in svg format used to build

optional arguments:
  -h, --help            show this help message and exit
  --output OUTPUT, -o OUTPUT
                        destination of the generated certificates
```

## Contributing
Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.

Please make sure to update tests as appropriate.

## License
[Apache 2.0](https://choosealicense.com/licenses/apache-2.0/)
pyenet-dlts 1.5
A fork of pyenet with DLTS support
Requires Python: >=3.9

pyenet-dtls
===========

pyenet-dtls is a Python wrapper for the `ENet <http://enet.bespin.org>`_
UDP networking library with DTLS (Datagram Transport Layer Security)
support via OpenSSL.

It is a fork of `pyenet <https://github.com/piqueserver/pyenet>`_, originally
written by Scott Robinson and maintained by Andrew Resch and the piqueserver
team.

Features
--------

- Full Python 3 support (Cython 3)
- Optional DTLS encryption for secure UDP communication
- Builds with or without OpenSSL (DTLS is automatically enabled when OpenSSL
  is available)
- Pre-built wheels for Linux, Windows, and macOS

License
-------

pyenet-dtls is licensed under the BSD license, see LICENSE for details. ENet
is licensed under the MIT license, see
http://enet.bespin.org/License.html

Dependencies
------------

- Python >= 3.9
- Cython >= 3
- OpenSSL development headers

Installation
------------

From PyPI
~~~~~~~~~

::

    pip install pyenet-dtls

From source
~~~~~~~~~~~

::

    git clone --recursive <repo-url>
    cd pyenet
    pip install .

Building wheels
~~~~~~~~~~~~~~~

Build locally using Docker/Podman (Linux only)::

    ./scripts/build_packages.sh

Wheels are output to the ``wheelhouse/`` directory.

For all platforms (Linux, Windows, macOS), push to GitHub and use the
**Wheel build** workflow, or create a release to trigger the **Publish to
PyPI** workflow.

Usage
-----

Basic example (no DTLS):

::

    >>> import enet

    >>> # Server
    >>> server = enet.Host(enet.Address("localhost", 33333), 32, 2, 0, 0)
    >>> event = server.service(1000)

    >>> # Client
    >>> client = enet.Host(None, 1, 2, 0, 0)
    >>> peer = client.connect(enet.Address("localhost", 33333), 2)

With DTLS encryption:

::

    >>> import enet

    >>> # Server with TLS certificate
    >>> server = enet.Host(enet.Address("localhost", 33333), 32, 2, 0, 0,
    ...                    dtls_cert="server.pem", dtls_key="server.key")

    >>> # Client connecting with DTLS
    >>> client = enet.Host(None, 1, 2, 0, 0)
    >>> peer = client.connect(enet.Address("localhost", 33333), 2, dtls=True)

Check if DTLS support is available::

    >>> import enet
    >>> print(enet.DTLS_AVAILABLE)
    True

Generating a self-signed certificate
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

DTLS requires a certificate and private key for the server. To generate a
self-signed certificate for testing or development::

    openssl req -x509 -newkey rsa:2048 -nodes \
        -keyout server.key -out server.pem \
        -days 365 -subj "/CN=localhost"

This creates ``server.pem`` (certificate) and ``server.key`` (private key)
valid for 365 days. For production use, obtain a certificate from a trusted
certificate authority.

More information on ENet usage can be found at:
http://enet.bespin.org/Tutorial.html
topsis-arshia-102317268 0.1.0
TOPSIS CLI Tool
Requires Python: >=3.8

# Topsis-Arshia-102317268

A command-line Python implementation of the **TOPSIS (Technique for Order Preference by Similarity to Ideal Solution)** algorithm used in **Multi-Criteria Decision Making (MCDM)**.

---

## Features

- Supports **CSV** and **Excel (.xlsx)** input files  
- Implements full TOPSIS ranking method  
- Validates user input and handles common errors  
- Produces decision scores and ranks  
- Lightweight and easy-to-use CLI tool  

---

## About TOPSIS

TOPSIS is a popular decision-making technique that ranks alternatives based on their distance from the **ideal best** and **ideal worst** solutions.

---

## Installation
pip install topsis-arshia-102317268

---

## Usage

`topsis <inputfile> <weights> <impacts> <outputfile>`

EXAMPLE: 
topsis data.xlsx "1,1,1,1" "+,+,+,+" result.csv

---

## Input Rules

1. First column → Alternative names
2. Remaining columns → Numeric criteria only
3. Minimum 3 columns required
4. Number of weights must equal number of criteria
5. Number of impacts must equal number of criteria
6. Impacts must be:
    + → Benefit criterion
    - → Cost criterion

---

## Output

The output file contains:
    Original dataset
    Topsis Score
    Rank
**Higher score indicates a better alternative.**

---

## Dependencies

Automatically installed with the package:
pandas
numpy
openpyxl

## Author

**Arshia**