semvec/pypi-packages huggingface dataset:
Tinycord 0.3.0
Easy and flexible Discord wrapper built on aiohttp
Requires Python: >=3.6

<div align="center">
    <h1>TinyCord 🏮</h1>
    <p> Easy and flexible Discord wrapper built on aiohttp </p>
    <p>Thanks to <a href="https://github.com/Pincer-org/Pincer">Pincer</a> because we did take a lot of ideas and things from it <3  </p>
    <br>
    <img src="./Big-Banner.png" />
    <br>
</div>

<br>

<div align="center">

# Example

<div align="left">

```py
import tinycord

client = tinycord.Client(
    "Token", intents=[tinycord.Intents.all()]
)

@client.event
async def on_message(message: tinycord.Message):
    print(message.content)

@client.lisnten(tinycord.Events.messageUpdate)
async def update_message(before: tinycord.Message, after: tinycord.Message):
    print(f'{before.content} -> {after.content}')
    
client.connect()
```

# Auto Shard Example

```py
import tinycord

client = tinycord.Client(
    "Token", intents=[tinycord.Intents.all()]
)

@client.event
async def on_message(message: tinycord.Message):
    print(message.content)

@client.lisnten(tinycord.Events.messageUpdate)
async def update_message(before: tinycord.Message, after: tinycord.Message):
    print(f'{before.content} -> {after.content}')
    
client.connect_autosharded()
```

# Plugin

```py
import tinycord

plugin = tinycord.Plugin('test')

@plugin.event
async def on_ready(shard):
    print(f'{shard} is ready!')
```

# Docs
HELP!

# Discord

[![Tinycord Server](https://discord.com/api/guilds/923934645618376704/widget.png?style=banner2)](https://discord.gg/QP3CJythPh)


</div>
</div>
TOPSIS-NANDITA-101917191 3.0
topsis package for MCDM problems
Requires Python: >=3.6

# TOPSIS-NANDITA-101917191

_submitted by: **Nandita**_
_Roll no: **101917191**_
_Group: **3CSE8**_


TOPSIS-NANDITA-101917191 is a Python library for dealing with Multiple Criteria Decision Making(MCDM) problems by using Technique for Order of Preference by Similarity to Ideal Solution(TOPSIS).

## Installation

Use the package manager [pip](https://pip.pypa.io/en/stable/) to install TOPSIS-NANDITA-101917191.

```bash
pip install TOPSIS-NANDITA-101917191
```

## 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 sample.csv "1, 1, 1, 1" "+, -, +, +" output.csv
```
or vectors can be entered without " "
```bash
topsis sample.csv 1,1,1,1 +,-,+,+ output.csv
```
But the second representation does not provide for inadvertent spaces between vector values. So, if the input string contains spaces, make sure to enclose it between double quotes _(" ")_.

To view usage __help__, use
```
topsis /h
```
## Example

#### sample.csv

A csv file showing data for different mobile handsets having varying features.

| Model  | Storage space(in gb) | Camera(in MP)| Price(in $)  | Looks(out of 5) |
| :----: |:--------------------:|:------------:|:------------:|:---------------:|
| M1 | 16 | 12 | 250 | 5 |
| M2 | 16 | 8  | 200 | 3 |
| M3 | 32 | 16 | 300 | 4 |
| M4 | 32 | 8  | 275 | 4 |
| M5 | 16 | 16 | 225 | 2 |

weights vector = [ 0.25 , 0.25 , 0.25 , 0.25 ]

impacts vector = [ + , + , - , + ]

### input:

```python
topsis sample.csv 0.25,0.25,0.25,0.25 +,+,-,+ output.csv
```

### output:
output.csv

TOPSIS RESULTS (P-Score, Rank) are appended to the input csv and saved 

| Model  | Storage space(in gb) | Camera(in MP)| Price(in $)  | Looks(out of 5) | P-Score | Rank |
| :----: |:--------------------:|:------------:|:------------:|:---------------:|:-------:|:----:|
| M1 | 16 | 12 | 250 | 5 | 0.534277 | 3 |
| M2 | 16 | 8  | 200 | 3 | 0.308368 | 5 |
| M3 | 32 | 16 | 300 | 4 | 0.691632 | 1 |
| M4 | 32 | 8  | 275 | 4 | 0.534737 | 2 |
| M5 | 16 | 16 | 225 | 2 | 0.401046 | 4 |


## Other notes

* The first column and first row are removed by the library before processing, in attempt to remove indices and headers. So make sure the csv follows the format as shown in sample.csv.
* Make sure the csv does not contain categorical values


## License
[MIT](https://choosealicense.com/licenses/mit/)