semvec/pypi-packages huggingface dataset:
topsis-ikjot-102116071 0.0.1
TOPSIS Application
Keywords: python,topsis


# Topsis-Ikjot-102116071

for: **Project-1 (UCS654)**
submitted by: **Ikjot Singh**
Roll no: **102116071**
Group: **3CS11**


Topsis-Ikjot-102116071 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-ikjot-102116071.

```bash
pip install topsis-ikjot-102116071
```



## 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" "+,-,+,+"
```
or vectors can be entered without " "
```bash
topsis sample.csv 1,1,1,1 +,-,+,+
```

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:
```
      TOPSIS RESULTS
-----------------------------

    P-Score  Rank
1  0.534277     3
2  0.308368     5
3  0.691632     1
4  0.534737     2
5  0.401046     4
```
# topsis-ikjot-102116071
Topsis-Prisha-102116052 0.0.1
TOPSIS Application
Keywords: python,topsis


# Topsis-Prisha-102116052

_for: **Project-1 (UCS654)**_
_submitted by: **Prisha Sawhney**_
_Roll no: **102116052**_
_Group: **3CS10**_


Topsis-Prisha-102116052 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-Prisha-102116052.

```bash
pip install Topsis-Prisha-102116052
```

## 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" "+,-,+,+"
```
or vectors can be entered without " "
```bash
topsis sample.csv 1,1,1,1 +,-,+,+
```
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:
```
      TOPSIS RESULTS
-----------------------------

    P-Score  Rank
1  0.534277     3
2  0.308368     5
3  0.691632     1
4  0.534737     2
5  0.401046     4

```
pokemon-go-video-analysis 0.0.0.0.5.5
Pokemon Go Video Analysis
Requires Python: <=3.11.7

# Pokémon Go Video Analysis

Tools for analyzing Pokémon Go Player vs. Player (PvP) Videos.

```commandline
from battle_logger.pipeline import BattleLoggerPipeline

pogo_pipeline = BattleLoggerPipeline()
output = pogo_pipeline.exec('path/to/video')
pogo_pipeline.save_output(out_path="test_output", basename="battle_logger_output")
```

Extract battles from videos and analyze what Pokémon appear in which battles:

![](https://github.com/prateekt/pokemon-go-video-analysis/blob/552dfc95d5643b7ab8f40f162e13f6461d0ff888/readme_figs/battle_1.png?raw=True)

Log your battles and analyze your Pokémon's performance:

![](https://github.com/prateekt/pokemon-go-video-analysis/blob/552dfc95d5643b7ab8f40f162e13f6461d0ff888/readme_figs/example_table.png?raw=True)

<b>Installation:</b>

```
make conda_dev
conda activate pogo_video_analysis_env
pip install pokemon-go-video-analysis
```
django-telegram-logging 1.0.2
An app to send reports over Telegram API

# DJANGO TELEGRAM LOGGING

This APP was developed on django to provide a simple way of sending error reports of django server via telegram bot API

## Table of Contents
* [instalation](#instalation)
* [configuration](#configuration)


# Instalation: <a name="instalation"></a>
To instalate the appp just execute
```shell
# this command will install the app
$ pip install django-telegram-logging
```

# Configuration: <a name="configuration"></a>
Add django_telegram_logging to your installed apps.
```py
INSTALLED_APPS = [
    ...
    'django_telegram_logging'
]
```
Add to your settings.py file the following variables needed. Is important to add this varaibles to your settings.py file 
before your logging settings.
To get your personal token from Telegram read their [documentation](https://core.telegram.org/bots#3-how-do-i-create-a-bot).
By default TELEGRAM_LOGGING_EMIT_ON_DEBUG is set to false, but if you are running your project on DEBUG mode which you 
shouldn't, you can set this variable to True to emit the log.
```py
TELEGRAM_LOGGING_TOKEN = 'XXXXXXX:XXXXXXXXXXXXXXXXX'
TELEGRAM_LOGGING_CHAT = 12345678
TELEGRAM_LOGGING_EMIT_ON_DEBUG = True
```
Follow [django's documentation](https://docs.djangoproject.com/en/4.0/topics/logging/) to configure logging, add the 
telegram handler to the handlers configuration, and add at least one logger which will use that handler.
```py 
LOGGING = {
    ...
    'handlers': {
        ...
        'telegram': {
            'level': 'ERROR',
            'class': 'django_telegram_logging.handler.TelegramHandler'
        },
    },
    'loggers': {
        ...
        'django': {
            'level': 'ERROR', 
            'handlers': ['console', 'telegram']
        }
    }
}
```
hard-pil 0.3.2
A Python library built on top of PIL to easily edit/modify images
Requires Python: >=3.8.1,<3.12
Keywords: hard-pil,Hard pillow,Pillow,image editing

# Hard PIL
![Lint-Test](https://github.com/timoo4devv/hard-pil/actions/workflows/lint-test.yml/badge.svg)

A Python library built on top of [PIL](https://github.com/python-pillow/Pillow) to easily edit/modify images.

## Getting Started
Using this for the first time? Here are some links to help you get started.

- Read the [docs](https://hard-pil.readthedocs.io/en/latest/)
- First steps [Introduction](https://hard-pil.readthedocs.io/en/latest/pages/intro.html)
- Integrate in a [Discord bot](https://hard-pil.readthedocs.io/en/latest/pages/discordbot.html)
- Some premade [Examples](https://github.com/timoo4devv/hard-pil/tree/master/examples)
- [Report bugs](https://github.com/timoo4devv/hard-pil/issues/)

## Get help
- Ask us in our [Discord server](https://discord.gg/fVzt5THTNb)
- Watch [Youtube Tutorials](https://www.youtube.com/playlist?list=PLb_oBhGqAlbT4yVqV0TSXggA8b0lZhGhn)