semvec/pypi-packages huggingface dataset:
topsisnandinise102017121 0.0.1
This is a Python Package implementing TOPSIS
License: MIT
Keywords: topsis,mcda,TIET


## Topsis Python Package

TopsisPy is a Python Package implementing Topsis method used for multi-criteria decision analysis. Topsis stands for 'Technique for Order of Preference by Similarity to Ideal Solution'.

TopsisPy intends to make the process of TOPSIS simple in python. Key features of the package are -

- Easy to use 
- Numpy based 
- Ideal for Students

## Installation

Install the Package using the command -

```bash
   $ pip install topsisnandinise102017121
```
    

You may use the Package via commandline as
```bash
   $ topsis [path of csv] [weights as string] [impacts as string] [path of result csv as string]
Topsis-Sahil-102003466 1.0.0
TOPSIS is a practical and useful technique for ranking and selection of a number of externally determined alternatives through distance measures.
License: MIT

# Topsis-Sahil-102003466
This file takes 5 arguments from the user
1->python file name
2->Input file name i.e of the dataset
3->An array of Weights For example:'1,1,1,0,0' 
4->An array of Impact For example:'+,-,+,-,+'
5->The file in which the user want to store the result

## Installation
```pip install Topsis-Sahil-102003466```

## How to use it?
Open terminal and type Topsis-Sahil-102003466 and then give the input according to the requirements

## License

Â© 2023 Sahil Kadiyan

This repository is licensed under the MIT license
topsisnandinis102017121 0.0.1
This is a Python Package implementing TOPSIS
License: MIT
Keywords: topsis,mcda,TIET


## Topsis Python Package

TopsisPy is a Python Package implementing Topsis method used for multi-criteria decision analysis. Topsis stands for 'Technique for Order of Preference by Similarity to Ideal Solution'.

TopsisPy intends to make the process of TOPSIS simple in python. Key features of the package are -

- Easy to use 
- Numpy based 
- Ideal for Students

## Installation

Install the Package using the command -

```bash
   $ pip install topsisnandinis102017121
```
    

You may use the Package via commandline as
```bash
   $ topsis [path of csv] [weights as string] [impacts as string] [path of result csv as string]
topsisnandinisetia102017121 0.0.1
This is a Python Package implementing TOPSIS
License: MIT
Keywords: topsis,mcda,TIET


## Topsis Python Package

TopsisPy is a Python Package implementing Topsis method used for multi-criteria decision analysis. Topsis stands for 'Technique for Order of Preference by Similarity to Ideal Solution'.

TopsisPy intends to make the process of TOPSIS simple in python. Key features of the package are -

- Easy to use 
- Numpy based 
- Ideal for Students

## Installation

Install the Package using the command -

```bash
   $ pip install topsisnandinisetia102017121
```
    

You may use the Package via commandline as
```bash
   $ topsis [path of csv] [weights as string] [impacts as string] [path of result csv as string]
TinyTinyDebugger 0.14
Simple debugger for small scripts, shows the line being executed, local vars ...
License: MIT
Keywords: debugger,debugging


# TinyTinyDebugger

Simple debugger for small scripts - shows the line being executed, local vars ...
It only can be used if your script is in a .py file. It doesn't work directly from the console.
```python
pip install TinyTinyDebugger
```

```python
#Examples
from TinyTinyDebugger import (
function_debug,
detailed_debugger
)

@function_debug(
sleep_between_each_line=1)
def combinations(iterable, r):
    pool = tuple(iterable)
    n = len(pool)
    if r > n:
        print('r bigger n')
    indices = list(range(r))
    # provoking an Exception
    wrong = indices / 0
    return indices
#combinations("ABCD", 2)
from pprint import pprint



@function_debug(
    active=True,  # used to disable the debugger
    write_log_file=False,  # if True, data will be saved to hdd. Import allow_long_path_windows from windows_filepath and execute before! function_debug won't check for path length, so it is better to allow long file names
    log_folder='c:\\debugmyfunction',  # default value is the folder "_tinytinydebugger_log" in cwd
    pause_for_n_seconds_when_except=10,  # Only important if continue_on_exceptions is True. The execution will be paused and you can read the Exception. When you are done, press ctrl+c to continue
    continue_on_exceptions=True,  # if True, the execution will go on
    capture_local_vars=True,  # If True, all local variables in the function will be saved after each line in: detailed_debugger.local_function_vars
    color_print=True,  # black/white or colored
    print_line=True,  # If False, the event "line" won't be printed
    print_return=True,  # If False, the event "return" won't be printed
    print_exception=True,  # If False, the event "exception" won't be printed
    print_execution_time=True,  # enable/disable printing of execution time
    print_local_vars=True,  # if True: prints all local variables in the function each line
    sleep_between_each_line=0,  # sleep after each line of code
)
def baba(x):
    print(4/x)

baba(10)
pprint(detailed_debugger
       .local_function_vars)


```

Take a look at the video:
[![YT](https://github.com/hansalemaos/screenshots/raw/main/errorcode.png)](https://www.youtube.com/shorts/Jk-ZhFeJJ-A)
[https://www.youtube.com/shorts/Jk-ZhFeJJ-A]()