semvec/pypi-packages huggingface dataset:
topsis-yash-102303796 1.0.4
A Python package for TOPSIS (Technique for Order Preference by Similarity to Ideal Solution)
Requires Python: >=3.6

# TOPSIS – Python Package

## Project Description

topsis-yash-102303796 is a Python package that implements  
**TOPSIS (Technique for Order Preference by Similarity to Ideal Solution)**,  
a popular Multi-Criteria Decision Making (MCDM) technique.

This package ranks alternatives based on multiple numeric criteria,
user-defined weights, and impacts.

This project is developed as part of an academic assignment.

---

## Installation

Install the package using pip:

```bash
pip install topsis-yash-102303796==1.0.4
```

---

## Usage

Enter csv filename followed by .csv extentsion, then enter the weights vector with vector values separated by commas, followed by the impacts vector with comma separated signs (+,-)
```bash
topsis <input_file.csv> <weights> <impacts> <output_file.csv>
```

---

## Parameters
1. input_file.csv
CSV file containing alternatives and criteria
(first column = names, remaining columns = numeric values)

2. weights
Comma-separated numeric values
Example:
```bash
1,1,1,1,1
```

3. impacts
Comma-separated signs (+ for benefit, - for cost)
Example:
```bash
+,+,+,+,+
```

4. output_file.csv
Output CSV file generated by the program

---

## Example

Sample Input File (data.csv)
| Fund Name | P1   | P2   | P3  | P4   | P5    |
| --------- | ---- | ---- | --- | ---- | ----- |
| M1        | 0.84 | 0.71 | 6.7 | 42.1 | 12.59 |
| M2        | 0.91 | 0.83 | 7.0 | 31.7 | 10.11 |
| M3        | 0.79 | 0.62 | 4.8 | 46.7 | 13.23 |
| M4        | 0.78 | 0.61 | 6.4 | 42.4 | 12.55 |
| M5        | 0.94 | 0.88 | 3.6 | 62.2 | 16.91 |
| M6        | 0.88 | 0.77 | 6.5 | 51.5 | 14.91 |
| M7        | 0.66 | 0.44 | 5.3 | 48.9 | 13.83 |
| M8        | 0.93 | 0.86 | 3.4 | 37.0 | 10.55 |

Command
```bash
topsis input.csv "1,1,1,1,1" "+,+,+,+,+" output.csv
```

Sample Output (output.csv)
| Fund Name | P1   | P2   | P3  | P4   | P5    | Topsis Score | Rank |
| --------- | ---- | ---- | --- | ---- | ----- | ------------ | ---- |
| M1        | 0.84 | 0.71 | 6.7 | 42.1 | 12.59 | 0.5636923298 | 3    |
| M2        | 0.91 | 0.83 | 7.0 | 31.7 | 10.11 | 0.5130321034 | 4    |
| M3        | 0.79 | 0.62 | 4.8 | 46.7 | 13.23 | 0.4391772826 | 6    |
| M4        | 0.78 | 0.61 | 6.4 | 42.4 | 12.55 | 0.4919560825 | 5    |
| M5        | 0.94 | 0.88 | 3.6 | 62.2 | 16.91 | 0.6418858152 | 2    |
| M6        | 0.88 | 0.77 | 6.5 | 51.5 | 14.91 | 0.7381481319 | 1    |
| M7        | 0.66 | 0.44 | 5.3 | 48.9 | 13.83 | 0.4073895318 | 8    |
| M8        | 0.93 | 0.86 | 3.4 | 37.0 | 10.55 | 0.4084986767 | 7    |


---

## Notes
1. Input CSV must contain numeric values only (except first column)
2. Number of weights must match number of criteria columns
3. Impacts must be either + or -
4. Input and output files must be in the current working directory
5. The package does not include sample CSV files

---

## Author
Yash Raghuvanshi
Roll Number: 102303796
pyeio 0.2.0
Easy data input/output utilities.
Requires Python: >=3.11

# pyeio

- Description: Drop-in replacement for standard `io` module with some extra utilities.
- Purpose: Solves having to constantly `with open` stuff.
- Notes: Full docs may be added at some later point, along with some other file formats perhaps.

## Install

```sh
pip install pyeio
```

or

```sh
uv add pyeio
```

## Usage

```python
import pyeio as io
```

Everything should work the same as `io`, but with the following additions:

### Extra IO Functions

#### `io.read`

Read file content as string (utf-8) or bytes.

```python
# Read as string (default)
content = io.read("file.txt")

# Read as bytes
data = io.read("file.bin", bytes)
```

#### `io.write`

Write string or bytes to a file. Raises an error if the file already exists unless `overwrite=True`.

```python
# Write string
io.write("file.txt", "Hello, world!")

# Write bytes
io.write("file.bin", b"\x00\x01\x02")

# Overwrite existing file
io.write("file.txt", "New content", overwrite=True)
```

#### `io.append`

Append string or bytes to the end of a file.

```python
# Append string
io.append("file.txt", "\nAnother line")

# Append bytes
io.append("file.bin", b"\x03\x04")
```

### Formats

Additionally, `json`, `toml`, and `yaml` are included, with overloads/generics for handling pydantic models. Each of these exposes a `read`, and `write` function which more or less works the exact same way, along with a `parse` and `serialize` function.

Here are some examples:

```python
# Read JSON file
data = io.json.read("config.json")

# Read JSON file into a Pydantic model
user = io.json.read("user.json", UserModel)

# Write JSON to file
io.json.write("output.json", {"key": "value"})

# Write with pretty printing
io.json.write("output.json", data, overwrite=True, indent=True)

# Parse JSON string/bytes
data = io.json.parse('{"key": "value"}')
user = io.json.parse(json_bytes, UserModel)

# Serialize to string/bytes
json_bytes = io.json.serialize(data)  # returns bytes by default
json_str = io.json.serialize(data, str)
```
nauta 0.1.4
Línea de comandos para el nauta hogar Cuba
Requires Python: >=3.8

# nauta

Línea de comandos para el nauta hogar Cuba

## Instalación con pipx

Para instalar `pipx` siga las [instrucciones](https://github.com/pypa/pipx#install-pipx) según su sistema operativo

```bash
pipx install nauta --force
```

## Guía

1. Agregar un usuario

```console
nauta add micorreo@nauta.com.cu contraseña
```

2. Iniciar sesión
```console
nauta login
```

3. Cerrar sesión
```console
nauta logout
```

## Ayuda

```bash
nauta --help
```