semvec/pypi-packages huggingface dataset:
nonebot-plugin-wantwords 0.1.0
use wantwords as a plugin of nonebot
Keywords: nonebot2,nonebot,nonebot_plugin

<p align="center">
  <a href="https://v2.nonebot.dev/store">
  <img src="https://user-images.githubusercontent.com/44545625/209862575-acdc9feb-3c76-471d-ad89-cc78927e5875.png" width="180" height="180" alt="NoneBotPluginLogo"></a>
</p>
<div align="center">

# nonebot_plugin_wantwords

Use [WantWords](https://wantwords.net) as a plugin of [NoneBot](https://github.com/nonebot/nonebot2)

WantWords，但是Nonebot插件

</div>
<p align="center">
  <a href="https://opensource.org/licenses/MIT">
    <img src="https://img.shields.io/badge/License-MIT-yellow.svg" alt="license">
  </a>
  <a href="https://v2.nonebot.dev/">
    <img src="https://img.shields.io/static/v1?label=nonebot&message=v2rc1%2B&color=green" alt="nonebot2">
  </a>
  <img src="https://img.shields.io/static/v1?label=python+&message=3.8%2B&color=blue" alt="python">
</p>

## 下载

#### 法一：[pip](https://pypi.org/project/nonebot_plugin_wantwords/)

``` bash
pip install nonebot_plugin_wantwords
```

``` python
# NoneBot项目中
nonebot.load_plugin('nonebot_plugin_wantwords')
```

#### 法二：nb-cli「推荐」
``` bash
nb plugin install nonebot_plugin_wantwords
```

## 配置

```bash
# .env或.env.*
wantwords_max_results=10 # 最大输出结果数，为[1,100]整数，默认为10。
```

## 更新日志
- v0.1.0 🎉

## TODO
- 增加筛选功能
- ~~对标官网用户体验~~

## 特别感谢

- [Mrs4s / go-cqhttp](https://github.com/Mrs4s/go-cqhttp)
- [nonebot / nonebot2](https://github.com/nonebot/nonebot2)
- [WantWords](https://wantwords.net)

**欢迎Contribution。因为大多数时间在校，所以各方面均迟缓，见谅。**

**侵权请联系删除**
topsis-nitanshjain-102017025 0.1.2
Topsis Calculation Package
Keywords: python,topsis,mcdm

# topsis_nitanshjain_102017025

## What is TOPSIS
Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) originated in the 1980s as a multi-criteria decision making method.<br> TOPSIS chooses the alternative of shortest Euclidean distance from the ideal solution, and greatest distance from the negative-ideal solution.

## Installation
```pip install topsis-nitanshjain-102017025```

## Input csv format
Input file contain three or more columns<br>
First column is the object/variable name <br>
From 2nd to last columns contain numeric values only

## How to use it
Python File<br>
```
from topsis.topsis_nitanshjain_102017025 import solve_topsis
solve_topsis()
```
Command Prompt<br>
```
topsis <python_file> <Input Data File> <Weights> <Impacts> <Result File Name>
```
<br>

Example:<br>
```
topsis topsis.py inputfile.csv “1,1,1,1,2” “+,+,+,+,-” result.csv
```
<br><br>
<i>Note: The weights and impacts should be ',' seperated, input file should be in pwd.</i> 

## Functions, Parameters and Return Values

```
function = solve_topsis()
parameters = No input parameters
return values = Creates a csv file with the topsis rank and performance score
```

## Sample input data
| Model       | P1 | P2 | P3 | P4 | P5 |
| ------------- |:-------------:| -----:|-----:|-----:|-----:|
| M1    | 0.62 | 0.38 | 3.8 | 33.8 | 9.65  | 
 | M2    | 0.75 | 0.56 | 5.7 | 50.3 | 14.33 | 
 | M3    | 0.95 | 0.90 | 6.5 | 65.6 | 18.49 | 
 | M4    | 0.61 | 0.37 | 6.2 | 43.6 | 12.70 | 
 | M5    | 0.60 | 0.36 | 6.4 | 61.2 | 17.14 | 
 | M6    | 0.76 | 0.58 | 5.3 | 68.0 | 18.66 | 
 | M7    | 0.66 | 0.44 | 6.2 | 47.2 | 13.63 | 
 | M8    | 0.80 | 0.64 | 5.7 | 37.1 | 11.06 | 


## Sample output data
| Model       | P1 | P2 | P3 | P4 | P5 | Performance Score | Topsis Rank |
| ------------- |:-------------:| -----:|-----:|-----:|-----:| ---: | ---: |
| M1    | 0.62 | 0.38 | 3.8 | 33.8 | 9.65  |  0.317272185       | 8           | 
| M2    | 0.75 | 0.56 | 5.7 | 50.3 | 14.33 |  0.452068871       | 4           | 
| M3    | 0.95 | 0.90 | 6.5 | 65.6 | 18.49 |  0.689037307       | 1           | 
| M4    | 0.61 | 0.37 | 6.2 | 43.6 | 12.70 |  0.340383903       | 7           | 
| M5    | 0.60 | 0.36 | 6.4 | 61.2 | 17.14 |  0.367206376       | 6           |
| M6    | 0.76 | 0.58 | 5.3 | 68.0 | 18.66 |  0.481350901       | 3           | 
| M7    | 0.66 | 0.44 | 6.2 | 47.2 | 13.63 |  0.372999972       | 5           | 
| M8    | 0.80 | 0.64 | 5.7 | 37.1 | 11.06 |  0.51226635        | 2           |
helloworld-apar-pkg 0.0.3
Say hello!

# Hello World

This is an example project demonstrating how to publish a python module to PyPI.

## Installation

Run the following to install:

```python
pip install helloworld_apar_pkg
```

## Usage

```python
from helloworld_apar import say_hello

# Generate "Hello, World!"
say_hello()

# Generate "Hello, Everybody!"
say_hello("Everybody")
```
avrdude-windows 7.1.0
A pypi package containing avrdude binaries for Windows

# avrdude_windows

This package installs the avrdude (x32 and x64-only) binaries for Windows via pypi/pip. There is a single python function in this library which allows you to get the path of the avrdude executable:

```python
from avrdude_windows import get_avrdude_path

print(get_avrdude_path())
```

The MIT license in this repository only applies to the single python function mentioned above - avrdude is licensed separately. Source code and binary releases for avrdude can be found in the [project repository](https://github.com/avrdudes/avrdude/releases). 

If you are using Mac, you should use Homebrew instead:

```
brew install avrdude
```

Or on Linux, you should use the package manager of your distribution, for example:

```
sudo apt install avrdude
```
fyers-api-builder 0.3.8
Fyers Api Builder

## Fyers Token Generator

```
from fyers_api_builder import FyersApiBuilder
```

```
config = {
  "username": "<USERNAME>",
  "password": "<PASSWORD>",
  "pin": "<PIN>",
  "client_id": "<CLIENT_ID>",
  "secret_key": "<SECRET_KEY>",
  "redirect_uri": <REDIRECT_URL>
}
```

#### Initialization

```
from fyers_api import accessToken, fyersModel
from fyers_api.Websocket import ws

fyersApiBuilder = FyersApiBuilder(config=config, accessToken=accessToken, fyersModel=fyersModel, ws=ws)
```

#### HTTP Client

- fyersApiBuilder.client.get_profile()
- fyersApiBuilder.client.history(payload)

#### WebSocket Client

- fyersApiBuilder.ws_client.subscribe(payload)
wrappy 0.2.7
Decorators for common developer utility.
Requires Python: >=3.6

# wrappy
Decorators for common developer utilities in Python 3.6+.

## Documentation
Documentation is built with Mkdocs and hosted [here](https://haochuanwei.github.io/wrappy/).

## Quick Examples (see the docs for more detail)
```Python
from wrappy import probe, guard, todo, memoize

@probe()
def do_some_heavy_computation(a, b, c):
    return a * b + c

@probe(show_args=True, show_kwargs=True, show_returns=True)
def someone_elses_code():
    # code that does not explain itself
    #
    # show examples of args, kwargs, and return values at runtime to get some clue

@probe(show_caller=5)
def a_call_chain_would_be_nice():
    # find out with show_caller=<number_of_callers_along_the_chain>

@guard(fallback_retval=0)
def this_could_blow_up(a, b):
    return a / b

@todo('Not implemented')
def i_am_not_ready():
    # code is under construction, so throw an error when called prematurely

@guard()
@memoize()
def recursive_or_dynamic_programming_subroutine(n):
    assert isinstance(n, int) and n >= 0
    if n == 0:
        return 0
    return n + recursive_or_dynamic_programming_subroutine(n-1)
```

## Examples by Comparison

`This section is under construction!`

## Release Notes