semvec/pypi-packages huggingface dataset:
summer-modules 1.1.2
summery233's python modules
Requires Python: >=3.11

# summer_modules

233的Python工具箱 | Python Utility Collection by 233

---

## 简介

`summer_modules` 是一个面向日常开发、数据分析与安全自动化的 Python 工具箱，自 `v1.1.0` 起全面拆分为多个按需安装的子包（如 `summer-modules-core`、`summer-modules-ai` 等），通过聚合包 `summer-modules` 统一依赖。适合个人开发、自动化脚本、数据处理与安全分析等多场景。

---

## 安装与依赖管理

本项目使用 [uv](https://github.com/astral-sh/uv) 进行依赖管理与打包，建议 Python 版本 ≥ 3.11。

```bash
# 安装 uv（官方推荐方式）
curl -LsSf https://astral.sh/uv/install.sh | sh

# 同步依赖并创建虚拟环境
uv sync

# 运行测试
uv run pytest
```

> 若只想安装某个子包，可直接 `pip install summer-modules-core` 等；若安装聚合包，则 `pip install summer-modules`。

---

## 项目结构与模块功能

自 `v1.1.0` 起，核心源码全部位于 `packages/` 下的子包中：

```bash
├── packages/
│   ├── summer_modules_core/      # 通用核心工具、日志、配置加载等
│   ├── summer_modules_ai/        # AI/Deepseek 相关封装
│   ├── summer_modules_bot/       # 企业微信 Bot 等消息推送
│   ├── summer_modules_markdown/  # Markdown / 图床 / GitLab 图像托管
│   ├── summer_modules_charts/    # 图表绘制组件
│   ├── summer_modules_excel/     # Excel 读写与列名操作
│   ├── summer_modules_database/  # PostgreSQL、HBase 等数据库工具
│   ├── summer_modules_prefect/   # Prefect 工作池/部署工具
│   ├── summer_modules_security/  # 漏洞信息、威胁情报、ATT&CK 等
│   └── summer_modules_ssh/       # SSH 命令执行、HBase Shell 辅助
├── scripts/                      # 辅助脚本（如版本依赖同步）
├── .github/workflows/            # CI / 发布流程
├── pyproject.toml                # 聚合包配置（依赖所有子包）
└── README.md / CHANGELOG.md / config.toml
```

常用子包一览：

| 包名 | 说明 |
| --- | --- |
| `summer-modules-core` | 通用工具、日志、配置加载、Web 请求辅助等基础能力 |
| `summer-modules-ai` | Deepseek 英译中等 AI 工具封装 |
| `summer-modules-bot` | 企业微信机器人等消息推送能力 |
| `summer-modules-markdown` | Markdown 处理与图床、GitLab Image Host 支持 |
| `summer-modules-charts` | 可视化与图表绘制工具 |
| `summer-modules-excel` | Excel 读写、列名查找、单元格操作 |
| `summer-modules-database` | PostgreSQL 分区、HBase API、数据导出等 |
| `summer-modules-prefect` | Prefect 工作池巡检、部署检测、日志桥接 |
| `summer-modules-security` | CVE/CNNVD/攻击矩阵解析、OTX 威胁情报、Nuclei 缓存等 |
| `summer-modules-ssh` | SSH 命令执行、交互式命令、HBase Shell 支持 |

---

## 快速上手（开发者）

```bash
# 克隆仓库后安装依赖
uv sync

# 运行单元测试
uv run pytest

# 进入某个子包示例
uv run python -m packages.summer_modules_security.examples.threat_intelligence.otx.example_otx_api
```

建议直接参考 `packages/<module>/tests/` 与 `examples/`，涵盖各模块的典型用法。

---

## 贡献指南

1. Fork 本仓库并新建分支
2. 提交代码前请确保通过所有单元测试
3. 提交 PR 时请详细描述变更内容
4. 欢迎 issue 反馈与建议

---

## 版本管理与发布流程

- 遵循 [Keep a Changelog](https://keepachangelog.com/zh-CN/) 维护 `CHANGELOG.md`
- 从 `v1.1.0` 开始：更新根目录 `VERSION` → 执行 `scripts/bump_dependencies.py` → 推送 `v*` tag
- GitHub Actions 会在推送 tag 后自动执行测试并发布所有子包及聚合包到 PyPI（需配置 `PYPI_TOKEN`）
- 主分支 `main` 保持稳定，开发分支建议以 `feature/`、`fix/` 前缀命名

---

## 联系方式 & 致谢

- 作者：233Official
- 邮箱：<ayusummer233@outlook.com>
- 欢迎关注、Star、交流！

---

## Changelog

详细变更请查阅 [CHANGELOG.md](CHANGELOG.md)。

---
ia-auth-sessions 0.1.0
Industry-standard session-based authentication for FastAPI with secure cookies
Requires Python: >=3.10
Keywords: fastapi, authentication, sessions, cookies, security

# IA Auth Sessions

Standard session-based authentication for FastAPI applications using secure signed cookies.

## Features

- **Signed Cookies**: HMAC-SHA256 via `itsdangerous` prevents tampering
- **Bcrypt Password Hashing**: Industry standard with automatic salt generation via `pwdlib`
- **Python 3.13+ Ready**: Uses modern `pwdlib` instead of deprecated `passlib`
- **Secure Cookie Flags**: HttpOnly, Secure, SameSite protection
- **Session Management**: Create, validate, destroy, and auto-cleanup
- **Database Agnostic**: PostgreSQL and SQLite via NexusQL
- **WebSocket Support**: Authenticate WebSocket connections

## Available Routes

- `POST /auth/register` - Register new user
- `POST /auth/login` - Login and create session
- `POST /auth/logout` - Logout and destroy session
- `GET /auth/me` - Get current user info
- `POST /auth/logout-all` - Logout from all devices

## Installation

```bash
pip install ia-auth-sessions
```

For local development:
```bash
pip install -e ../ia_auth_sessions
```

## Publishing

See [PUBLISHING.md](PUBLISHING.md) for instructions on publishing to PyPI.

To test the build locally:
```bash
python test_publish.py --skip-tests
```

## Quick Start

```python
from fastapi import FastAPI, Depends
from ia_auth_sessions import SessionMiddleware, get_current_user
from ia_auth_sessions.routes import router as auth_router

app = FastAPI()

# Add middleware and routes
app.add_middleware(SessionMiddleware, secret_key="your-secret-key", ...)
app.include_router(auth_router)

# Protected route
@app.get("/protected")
async def protected(user: dict = Depends(get_current_user)):
    return {"message": f"Hello {user['username']}!"}
```

See [USAGE.md](USAGE.md) for complete setup instructions.

## Documentation

- **[USAGE.md](USAGE.md)** - Complete setup guide, examples, and API reference
- **[ARCHITECTURE_NOTES.md](ARCHITECTURE_NOTES.md)** - Design decisions and architecture

## Database Schema

Automatically creates:
- `users`: User accounts with bcrypt-hashed passwords
- `sessions`: Active sessions with metadata and expiry timestamps

## License

MIT
exctrap 0.3
Exception trap
Requires Python: >=3.9

# exctrap: Trap exceptions for retry

It is not uncommon to have Python code that requires exceptions to be
trapped, with the code triggering it retried, e.g., to handle
temporary network or host failures when fetching web resources.  There
are quite a few Python packages that provide this functionality.  Or
actually, two functionalities: (1) trapping the exception, and (2)
retrying the triggering code upon failure.

Typically, they work in the level of function: the code that needs to
be retried is written as a function, and it is either wrapped within a
context manager or passed to a retry function so that the function is
invoked repeatedly until it succeeds or fail sufficiently many times.
In this way, the two functionalities are packed into one function or
context manager for the user.

We take a slightly different approach: the two functionalities are
separated into two entities: a context manager that traps exception,
and a function that returns the context manager.  We argue that this
leads to neater code.

## Recipe

This provides most of what we normally need.

    for etrapper in exctrap.trial():
        with etrapper:
            # Do whatever that may fail.
        # Will reach here whether or not an exception is raised.
        # If you want to reraise the exception here, use etrapper.reraise().
    # If retry fails, the last exception is reraised so this is not reached.

## Options

The `trial()` function provides all the options.  These include:

  * `num_tries`: Maximum number of trials, if the code keeps raising
    exceptions for this many tries the exception is reraised without
    further retry.
  * `retry_period`: Number of seconds to wait between tries (adjusted
    by `period_noise`).
  * `period_noise`: Add or subtract at most this fraction of the
    `retry_period` to get the actual amount of seconds to sleep.
  * `etypes`: Exception types to trap.  By default, trap all
    exceptions derived from `Exception`.  This is passed to the
    constructor of `ExcTrapper` when creating exception trappers.

Note that this does not require any function to be created for the
code needs to be exception-proof.  Experience shows that code can be a
lot more neat as a result: the code can access the required variables
much more easily when it does not sit within a separate global
function or an inner function.

## Implementation

The "etrapper" is the context manager which traps exceptions when
running under the "with" statement.  This is done simply by recording
exceptions in the trapper object, and returning True to swallow it, in
the `__exit__` function.  If needed, the exception can be asked to be
`reraised()`.

The `trial()` function provides the retry logic and create exception
trappers.  Because the exception would be trapped in the trapper, all
trial needs to do is to check whether an exception is trapped, and
decide whether to retry or reraise.
eyes17win 1.0.1
Python package for ExpEYES17
Requires Python: >=3
Keywords: expeyes17 data-acquisition lab-at-home oscilloscope waveform-generator sensors physics

# ExpEYES17 PIP Package

entry points : eyes17

maintainer : Jithin B P jithinbp@gmail.com


# Translations
 - translation to French by Georges Khaznadar, <georges.khaznadar at free.fr>,
   Copyright (c) 2019
 - translation to Malayalam by Amal M, <amalmphysics at gmail.com>,
   Copyright (c) 2020
eyes17 1.1.0
Python package for ExpEYES17/SEELab3
Requires Python: >=3
Keywords: expeyes17 data-acquisition lab-at-home oscilloscope waveform-generator sensors physics

# ExpEYES17 PIP Package

entry points : eyes17

maintainer : Jithin B P jithinbp@gmail.com


# Translations
 - translation to French by Georges Khaznadar, <georges.khaznadar at free.fr>,
   Copyright (c) 2019
 - translation to Malayalam by Amal M, <amalmphysics at gmail.com>,
   Copyright (c) 2020
eyes17lib 2.0.0
Python package for SEELab3/ExpEYES17 library
Requires Python: >=3
Keywords: expeyes17 seelab3 data-acquisition lab-at-home oscilloscope waveform-generator sensors physics

# ExpEYES17 PIP Package

entry points : none. This is only a library

maintainer : Jithin B P jithinbp@gmail.com


from eyes17.eyes import *
physics-utils 0.4.1
Helpers for empirical data handling and plotting
Requires Python: >=3.11

[![PyPI - Version](https://img.shields.io/pypi/v/physics-utils)](https://pypi.org/project/physics-utils/)
[![Static Badge](https://img.shields.io/badge/docs-blue)](https://physics-utils.readthedocs.io)
[![Python Tests](https://github.com/ImNotJahan/PhysicsTools/actions/workflows/python-tests.yml/badge.svg)](https://github.com/ImNotJahan/PhysicsTools/actions/workflows/python-tests.yml)

# PhysicsTools
This is a library for dealing with some tedious tasks for basic physics labs.

Be warned that, as this project is still in heavy development, backwards compatability can be broken between 0.x.0 versions. This is
avoided as much as possible, but make sure to watch out for it when updating your installation.

## Features
* Automatic uncertainty propagation on basic arithmetic and trigonometric operations
* Generated LaTeX steps of any calculations done with the `MeasuredData` class
* A physics scripting language for fast usage of the library
* Graping wrappers that take numbers with uncertainty for automatic error bars
* LaTeX data table generators

## Installation
Look under the examples folder to see the library in use.

`physics_utils` can be installed straight from PyPI using pip, like so:
```batch
python3 -m pip install physics-utils
```

## Usage
To get started with using the library, you can import `MeasuredData` from `physics_utils` and begin doing
calculations like normal once your numbers are wrapped:
```python
from physics_utils import MeasuredData

print(MeasuredData(2, 0.5) * MeasuredData(3, 0.4)) # 6±2.
```

To start using the scripting language, you can type `python3 -m physics_utils.script` in your terminal to start the
interpreter, or `python3 -m physics_utils.script <filename>` to run a file. To do the same as the example above in the
physics script interpreter, you'd just need to type this:
```
>>> 2~0.5 * 3~0.4
6±2.
```

And there are a number of other helpful features built into the language.

For more information on using the package, take a look at the [documentation](https://physics-utils.readthedocs.io) and
[examples](https://github.com/ImNotJahan/PhysicsTools/tree/main/examples).