semvec/pypi-packages huggingface dataset:
securely 0.2.0
This package will help you while authorization and authentication in fastapi
Requires Python: >=3.6

# Source code:https://github.com/coderxuz/securely
# Securely

**Securely** is a Python package that helps with authentication and authorization in FastAPI applications.

## Installation

You can install the package via `pip`:

```bash
pip install securely
```

# Quick start
```markdown
from securely import Auth
from fastapi import FastAPI


from datetime import timedelta

app = FastAPI()

auth = Auth(
    secret_key="bla bla",
    access_token_expires=timedelta(days=1),
    refresh_token_expires=timedelta(days=7),
)

just_db = [{"username": "john", "password": "gdfdfgdgdrgdr"}]


@app.post("/login")
async def login(data: dict):
    new_user = {"username": data.get("username")}

    new_user["password"] = auth.hash_password(password=data.get("password"))

    just_db.append(new_user)

    tokens = auth.create_tokens(subject=new_user.get("username"))

    return tokens

```
pyxunlei-for-nastool 0.1.0
基于Docker版本的迅雷API客户端，可作为NAStool的下载器插件使用
Requires Python: <4.0,>=3.10
Keywords: xunlei, download, docker, nastool, nas

# pyxunlei
基于Docker版本的[Xunlei API Client](https://github.com/cnk3x/xunlei)，可作为 [NAStool](https://github.com/NAStool/nas-tools) 的下载器插件使用。

## 支持版本
python@3.10
迅雷Docker@3.21.0

# 创建虚拟环境并安装依赖
```bash
poetry shell
poetry install
```

## 使用方法
```python
from pyxunlei import XunleiClient

#  初始化时支持以下参数:
#  host (str): 域名或IP
#  port (int): 端口号
#  ssl (bool): 是否启动HTTPS
#  device_name (str): 设备名称，当同一个账号下绑定了多个远程迅雷，可指定设备名称，设备名称可在迅雷APP查看
#      例如：群晖-xunlei
#      device_name为空时使用第一个设备.
#  download_root_dir(str): 下载根目录的目录名称，可以在web页面上查看，如不填写则默认选择第一个(一般是迅雷下载)
xunlei_client = XunLeiClient(
        '192.168.1.21', 2345, device_name="群晖-xunlei-")

# 获取已完成任务列表
completed_tasks = xunlei_client.completed_tasks()

# 获取未完成任务列表
uncompleted_tasks = xunlei_client.uncompleted_tasks()

# 提交磁力链接
magnetic_link = "磁力链接"
sub_dir = "子目录"  # 为空时则不创建子目录
preprocess_file = xunlei_client.filter_file_by_size  # 指定预处理文件函数，可使用内置的filter_file_by_size过滤掉小于500M以及大于40G的文件
xunlei_client.download_magnetic(magnetic_link, sub_dir, preprocess_file)

# 提交种子链接
torrent_file_path = "your.torrent"  # 种子文件路径
xunlei_client.download_torrent(torrent_file_path, sub_dir, preprocess_file)

# 任务管理
task_id = "任务ID"  # 创建任务时会返回task_id

# 暂停任务
xunlei_client.pause_task(task_id)

# 开始/继续任务
xunlei_client.start_task(task_id)

# 删除任务
xunlei_client.delete_task(task_id)
```

## 注意事项
1. 需要先安装并运行 [Docker版迅雷](https://github.com/cnk3x/xunlei)
2. 默认使用admin/admin作为登录凭证，如有修改请更新代码中的认证信息
3. 可以拿来作为集成到NAStool下载器插件使用
```
countries-info-mg 1.0.0
A comprehensive Python library for accessing detailed country information
Requires Python: >=3.6

# Countries Info

A comprehensive Python library for accessing detailed country information including names, codes, capitals, continents, population, and area.

## Installation

```bash
pip install countries-info-mg
```

## Usage

```python
from countries_info import get_all_countries, get_country_by_name, get_country_by_code

# Get all countries
countries = get_all_countries()

# Get country by name
france = get_country_by_name("France")

# Get country by code
usa = get_country_by_code("US")
```

## Features

- Get detailed information about countries
- Search countries by name or code
- Access data about:
  - Official names
  - Country codes
  - Capitals
  - Continents
  - Population
  - Area
  - And more!

## Data Structure

Each country object contains:
```python
{
    "name": str,           # Country name
    "code": str,           # ISO 2-letter code
    "capital": str,        # Capital city
    "continent": str,      # Continent
    "population": int,     # Population
    "area": float,         # Area in square kilometers
}
```

## License

MIT License
colchis-BeanBazaarTest 0.1.0
A package, implemented as a Class, to generalize JSON traversal and processing.
Requires Python: >=3.8

# Argonaut

A work in progress...

A package, implemented as a Class, to generalize JSON traversal and processing.

See IETF RFC8259: The Javascript Object Notation (JSON) Data Interchange Format https://datatracker.ietf.org/doc/html/rfc8259

## Purpose

I seem to spend a lot of time writing code to perform operations on a JSON structure. I wonder if I can automate this?

### The minimum goal is a package that does the 'heavy lifting':

- Reduce duplication of effort
- Maximize compute performance
- Minimize coding errors
- Minimize coding effort

## Imports
import os

from pathlib import Path

import config

from colchis.classes.argo import Argo

## Instantiation

x = Argo(file_path)

Where file_path is the valid path to a valid JSON file; 'x' is the class object of the json file

## Methods Implemented

write_json_data

validate_json_data

depict_json

depict_struct

__read_json_data

__good_params

## Methods awaiting implementation

create_key_list

create_value_list

add_key_value

delete_key_value

update_key

update_value

find_key

find_value

find_except

find_element

delete_element

update_element

append_element

insert_element

## Background
**Jason** was a character in Greek mythology.  He set off on a quest in a ship (the **Argo**), with a crew (the **Argonauts**) to a foreign land (**Colchis**, present day Georgia) to recover a legendary **Golden Fleece** in order to regain his rightful throne.  To gain the Golden Fleece, he was assigned arduous tasks, which he *completed* though divine intervention.  Despite his triumph, Jason continued to encounter serious problems in life and ultimately died a poor man while asleep under the rotting Argo, which fell and killed him.