semvec/pypi-packages huggingface dataset:
hacapi 0.5.4.1
This is a simple API to access the Home Access Center (HAC)
License: MIT
Requires Python: >=3.6,<4.0

# HAC API

## Introduction

This is a simple API to access the Home Access Center (HAC) of the [Frisco Independent School District](https://www.friscoisd.org/). This API is not affiliated with the school district in any way.

## Documentation

* return_current_assignments_df(  ) → ```list(pandas.DataFrame)```

* return_current_assignments_html(  )  → ```list(str)```

* return_current_grades(  )  → ```tuple(list(str))```

* get_username(  )  → ```str```

* reset(  )  → ``void``
* return_to_current(  )  → ``void``

* return_weighted_gpa(  )  → ``float``
* return_college_gpa(   )  → ``float``

## Out of Order
* return_quarter_grade(***quarter***)  →

* return_quarter_assignments_df(***quarter***)  →

* return_quarter_assignments_html(***quarter***)  →
susml 0.0.1
A ML toolkit with code bits useful for our day to day research
License: MIT
Requires Python: >=3.9

# SusML
![Python version](https://img.shields.io/badge/Python-3.9%2B-brightgreen)
![Build](https://img.shields.io/github/actions/workflow/status/sustainability-lab/SusML/build.yml?label=build&logo=github)
![Tests](https://img.shields.io/github/actions/workflow/status/sustainability-lab/SusML/tests.yml?label=tests&logo=github)

# Useful Code Snippets

## Data
### Load Data
```python
from susml.torch.data import load_mnist, load_cifar_10
ds, ds_name = load_cifar_10()
```

## Models
### Initialize MLPs
```python
from susml.torch.models import MLP

mlp = MLP(input_dim=100, hidden_dims=[128, 64], output_dim=10, activation="relu", dropout=0.1)
```

### Initialize CNNs
```python
from susml.torch.models import CNN
CNN(image_dim=32, 
    kernel_size=5, 
    n_channels=3, 
    conv_hidden_dims=[32, 64], 
    dense_hidden_dims=[128, 64], 
    output_dim=10)
```

## Training
### Quick train a model
```python
from susml.torch.utils import train_fn
result = train(model, inputs, outputs, loss_fn, lr, n_epochs, batch_size, enable_tqdm=True)
print(result.keys()) # dict_keys(['epoch_losses', 'iter_losses'])
```

## Adhoc
### Count number of parameters in a model
```python
from susml.torch.utils import count_params
n_params = count_params(mlp)
```
fastapi_ccli 0.0.2
Tool to automatically clone existing fastapi repositories based on command line conditions
License: MIT
Requires Python: <4.0,>=3.7

# FastAPI Project Clone CLI

> 此程序使用 [Typer](https://typer.tiangolo.com/) 创建

## 使用

pip 安装：

```shell
pip install fastapi-ccli
```

查看使用帮助

```shell
fastapi-ccli --help
```
nonebot-plugin-matchreminder 1.0.4
定时设置算法比赛赛前提醒，提醒群友别错过比赛，查询codeforce，atc，牛客比赛消息
License: MIT
Requires Python: >=3.9

<div align="center">
  <a href="https://v2.nonebot.dev/store"><img src="https://github.com/A-kirami/nonebot-plugin-template/blob/resources/nbp_logo.png" width="180" height="180" alt="NoneBotPluginLogo"></a>
  <br>
  <p><img src="https://github.com/A-kirami/nonebot-plugin-template/blob/resources/NoneBotPlugin.svg" width="240" alt="NoneBotPluginText"></p>
</div>

<div align="center">

# nonebot_plugin_matchreminder

_✨ NoneBot 插件简单描述 ✨_


<a href="./LICENSE">
    <img src="https://img.shields.io/github/license/zhuhiki/nonebot_plugin_matchreminder.svg" alt="license">
</a>
<a href="https://pypi.python.org/pypi/nonebot_plugin_matchreminder">
    <img src="https://img.shields.io/pypi/v/nonebot_plugin_matchreminder.svg" alt="pypi">
</a>
<img src="https://img.shields.io/badge/python-3.8+-blue.svg" alt="python">

</div>

## 📖 介绍

算法比赛提醒，可以自动设置时间来为即将到来的算法比赛设置提醒(默认是赛前半小时,可以自己修改),同时也能查询今日在codeforces，牛客，atc上的比赛，让群友不再错过比赛(偷懒)

## 💿 安装

<details open>
<summary>使用 nb-cli 安装</summary>
在 nonebot2 项目的根目录下打开命令行, 输入以下指令即可安装

    nb plugin install nonebot_plugin_matchreminder

</details>

<details>
<summary>使用包管理器安装</summary>
在 nonebot2 项目的插件目录下, 打开命令行, 根据你使用的包管理器, 输入相应的安装命令

<details>
<summary>pip</summary>

    pip install nonebot_plugin_matchreminder
</details>

打开 nonebot2 项目根目录下的 `pyproject.toml` 文件, 在 `[tool.nonebot]` 部分追加写入

    plugins = ["nonebot_plugin_matchreminder"]

</details>

## ⚙️ 配置

在 nonebot2 项目的`.env`文件中添加下表中的必填配置

| 配置项 | 必填 | 默认值 | 说明 |
|:-----:|:----:|:----:|:----:|
| SUPERUSERS | 是 | 无 | 有功能需要超级管理员权限 |

在插件里的config文件里填写需要定时发送的时间和群聊

## 🎉 使用
### 指令表
| 指令 | 权限 | 需要@ | 范围 | 说明 |
|:-----:|:----:|:----:|:----:|:----:|
| /cf，/nc,/atc | 群员 | 否 | 群聊 | 返回对应的比赛信息 |
| /今日比赛 | 群员 | 否 | 群聊 | 返回今天的比赛 |
| /提醒比赛 | 超级管理员 | 否 | 群聊 | 手动定时提醒 |
| /开摆 | 超级管理员 | 否 | 群聊 | 清除所有定时任务 |
argskwargsmodifierclass 0.10
A decorator that modifies the arguments and keyword arguments of a function based on the calling instance's attributes.
License: MIT
Keywords: decorator,args,kwargs


# A decorator that modifies the arguments and keyword arguments of a function based on the calling instance's attributes.

## Tested against Windows / Python 3.11 / Anaconda

## pip install argskwargsmodifierclass

```python
A decorator that modifies the arguments and keyword arguments of a function based on the calling instance's attributes.

Args:
	f_py (function, optional): Reserved for the function; do not use this argument explicitly.

	args_and_function (tuple of tuples): A tuple of tuples where each tuple contains an argument
	name and a function to transform the argument.
	The decorator will apply the specified function to each argument with a matching name.
	Each transformation function takes three arguments: the argument value,
	a dictionary of keyword arguments, and the instance that called the decorated method.

Returns:
	function: The decorated function.

Example:
	from argskwargsmodifierclass import change_args_kwargs
	class ADBTEST:
		def __init__(self, stripit=True):
			self.stripit = stripit

		@change_args_kwargs(
			args_and_function=(
					(
							"text",
							lambda arg, argdict, instance: arg.strip("x")
							if instance.stripit
							else arg,
					),
			)
		)
		def onefunction(self, text,number=10):
			print(f"{text=}")
			print(f"{number=}")


	t = ADBTEST(stripit=True)
	t.onefunction("bibib    xxxx",number=20)
	t.onefunction("bibibx    xxxx",15)

	t2 = ADBTEST(stripit=False)
	t2.onefunction(text="aaabibib",   number=0x5)
	t2.onefunction("aaaabibibx    xx")

	t.stripit = False
	t.onefunction("bibib    xxxx")
	t.onefunction("bibibx    xxxx")

	t2.stripit = True
	t2.onefunction("aaabibib   xxx")
	t2.onefunction("aaaabibibx    xx")

	# text='bibib    '
	# number=20
	# text='bibibx    '
	# number=15
	# text='aaabibib'
	# number=5
	# text='aaaabibibx    xx'
	# number=10
	# text='bibib    xxxx'
	# number=10
	# text='bibibx    xxxx'
	# number=10
	# text='aaabibib   '
	# number=10
	# text='aaaabibibx    '
	# number=10


The `change_args_kwargs` decorator allows you to modify function arguments and keyword arguments based on
the attributes of the calling instance.
It takes a tuple of argument transformations, each of which is defined as a tuple containing an argument name,
a transformation function, and the instance that called the decorated method.
The decorator dynamically adjusts the arguments according to the instance's attributes,
providing fine-grained control over argument modification.

```