semvec/pypi-packages huggingface dataset:
pystartgg 0.0.16
Python wrapper for startgg API calls.
License: MIT
Requires Python: >=3.12

# pystartgg

Wrapper for StartGG API calls, written using documentation from the [StartGG API](https://developer.start.gg/docs/intro).

Requires a developer API key found in your [StartGG Developer Settings](https://start.gg/admin/profile/developer).

### Usage:
```python3
import pystartgg

# File containing your API key
key = open('key.txt', 'r').read()
gg = pystartgg.StartGG(key)

# Get tournament info by tourney slug
slug = 'supernova-2025'
tourney_info = gg.tournament.get(slug)

# Get tournament info by tournament id
tourney_id = tourney_info['id']
tourney_info = gg.tournament.get_info(tourney_id)

# Get tournament events by tournament id
events = gg.tournament.get_events(tourney_id)
melee_event_id = None
for e in events:
    print(e)
    if e['videogame'] == 1:
        if 'SINGLES' in e['name'].upper():
            melee_event_id = e['id']

# Get players for event by event id
# - Only available if the attendee list is public
players = gg.event.get_players_all(melee_event_id)

# Get placements for event by event id
# - Also contains initial seed for each player
# - Only available if the event is live or complete
placements = gg.event.get_placements(melee_event_id)

# Get sets and games for event by event id
# - A set contains the players and scores
# - A game contains the specific character choices
#    and final stock counts during a set, if reported
sets, games = gg.event.get_sets_all(melee_event_id)

# Get player info by id
# - Some fields may be None if profile is private or 
#    the user has not recorded them
player_info = gg.player.get_info(4107)
```
mcrconpy 0.1.1
RCON protocol client for the Minecraft server.
License: MIT
Requires Python: <4.0,>=3.9
Keywords: rcon, remote console

# mcrconpy

Client to use the RCON protocol to execute commands on a Minecraft Java server.

> [!IMPORTANT]
> The RCON protocol transmits data in plain text, without encryption, so it is necessary to use an SSH tunnel or VPN if communication is carried out over the Internet.
>
> Python 3.9+.

You can log the activity or commands executed by the user in JSONL file format, located at:

* Linux: `/home/{user}/.local/state/mcrconpy/log` or `/home/{user}/.local/share/mcrconpy/log`.
* macOS: `/Users/{user}/Library/Logs/mcrconpy`.
* Windows: `C:\Users\{user}\AppData\Local\mcrconpy\logs`.


To enable the RCON protocol on your server, you must modify the following lines in the **server.properties** file and open the designated port:

```text
enable-rcon=true
rcon.password=<your password>
rcon.port=<1-65535>
broadcast-rcon-to-ops=false
```


# Installation

```bash
$ pip install mcrconpy
```


# CLI

```text
$ mcrconpy --help
usage: mcrconpy [-h] -a ADDRESS [-p PORT] -P PASSWORD [-A]

RCON protocol client for minecraft servers.

optional arguments:
  -h, --help            show this help message and exit
  -a ADDRESS, --address ADDRESS
                        Minecraft Server TCP address.
  -p PORT, --port PORT  Minecraft Server RCON Port. Default is 25575.
  -P PASSWORD, --password PASSWORD
                        User password.
  -A, --audit           Saves all commands executed by the user in a JSONL file. Default is disabled.

Connect remotely to the server and perform administrative tasks.
```


# Usage

* When using `with`, don't worry about closing the connection; it will close automatically and properly.

```python
from mcrconpy import RconPy


with RconPy(
    address="127.0.0.1",
    port=25575,
    password="test",
    audit=False,
) as rcon:
    print(rcon)

    rcon.connect()

    rcon.login()

    print("> is connected?", rcon.check_connection())
    print("> is login?", rcon.is_login())

    print(rcon.command(command="time query daytime"))
    print(rcon.command(command="//time set night"))
```

* Manually open and close the connection to the server. *Remember to close the connection*.

```python
from mcrconpy import RconPy


rcon = RconPy(
              address="127.0.0.1",
              port=25575,
              password="test",
              audit=False,
          )

print(rcon)

rcon.connect()

rcon.login()

print("> is connected?", rcon.check_connection())
print("> is login?", rcon.is_login())

print(rcon.command(command="time query daytime"))
print(rcon.command(command="//time set night"))

rcon.disconnect()
```


# Methods

| Methods | Description |
|-|-|
| `set_password` | Sets the user's password. |
| `get_password` | Gets the user's password. |
| `is_login` | Checks if the current user is logged in to the server. |
| `connect` | Connects to the RCON server. |
| `login` | Login the current user in to the server. |
| `command` | Executes the given command. |
| `check_connection` | Checks if the connection to the server is active. |
| `disconnect` | Disconnects from the server. |
python-sbx 2.0.0
A Python project for network proxy management
License: MIT
Requires Python: >=3.7
Keywords: proxy, network, management

# Python SBX

一个用于网络代理管理的Python项目。

## 功能特性

- 支持多种代理协议（VLESS、VMess、Trojan、Hysteria2、TUIC、Reality）
- 自动节点管理和上传
- 支持哪吒面板监控
- Argo隧道支持
- Telegram机器人推送
- 自动保活功能

## 安装

```bash
pip install python-sbx
```

## 使用方法

### 命令行使用

```bash
python-sbx
```

### 环境变量配置

```bash
# 节点上传地址
export UPLOAD_URL="https://your-domain.com"

# 项目URL（用于自动保活）
export PROJECT_URL="https://your-project.com"

# 自动保活开关
export AUTO_ACCESS="true"

# 哪吒面板配置
export NEZHA_SERVER="nz.serv00.net:8008"
export NEZHA_KEY="your-secret-key"

# Argo隧道配置
export ARGO_DOMAIN="your-domain.com"
export ARGO_AUTH="your-auth-token"

# Telegram配置
export CHAT_ID="your-chat-id"
export BOT_TOKEN="your-bot-token"
```

## 开发

```bash
# 克隆项目
git clone https://github.com/yourusername/python-sbx.git
cd python-sbx

# 安装依赖
pip install -r requirements.txt

# 运行项目
python app.py
```

## 发布为PyPI包

### 🎉 包已成功构建！

项目已配置为可发布的PyPI包。构建文件位于 `dist/` 目录：

- `python_sbx-0.1.0.tar.gz` - 源码分发包
- `python_sbx-0.1.0-py3-none-any.whl` - 轮子分发包

### 下一步操作

1. **修改个人信息**：
   - 编辑 `setup.py` 中的作者名、邮箱、项目URL
   - 编辑 `pyproject.toml` 中的作者信息
   - 编辑 `LICENSE` 中的版权信息

2. **发布到PyPI**：
   ```bash
   # 使用自动化脚本（推荐）
   python publish.py
   
   # 或手动发布
   python -m twine upload dist/*
   ```

3. **测试安装**：
   ```bash
   pip install python-sbx
   python-sbx
   ```

### 发布前检查清单

- [ ] 修改所有配置文件中的个人信息
- [ ] 确保包名在PyPI上是唯一的
- [ ] 测试包是否能正确构建和安装
- [ ] 先在TestPyPI上测试，再发布到正式PyPI

## 项目文件结构

```
python-sbx/
├── app.py                 # 主程序文件
├── requirements.txt       # 依赖列表
├── setup.py              # 包配置（主要）
├── pyproject.toml        # 现代包配置
├── MANIFEST.in           # 包含文件配置
├── README.md             # 项目说明
├── LICENSE               # 许可证
├── publish.py            # 自动化发布脚本
├── test_build.py         # 配置测试脚本
├── PUBLISH_GUIDE.md      # 详细发布指南
└── QUICKSTART.md         # 快速开始指南
```

## 许可证

MIT License

## 贡献

欢迎提交Issue和Pull Request！

## 相关文档

- [发布指南](PUBLISH_GUIDE.md) - 详细的PyPI发布说明
- [快速开始](QUICKSTART.md) - 5分钟发布指南
dbt-synapse 1.8.4
An Azure Synapse adapter plugin for dbt
License: MIT

# dbt-synapse

[dbt](https://www.getdbt.com) adapter for Azure Synapse Dedicated SQL Pool (Azure Synapse Data Warehouse).

The adapter supports dbt-core 0.18 or newer and follows the same versioning scheme.
E.g. version 1.1.x of the adapter will be compatible with dbt-core 1.1.x.

## Documentation

We've bundled all documentation on the dbt docs site:

* [Profile setup & authentication](https://docs.getdbt.com/reference/warehouse-profiles/azuresynapse-profile)
* [Adapter-specific configuration](https://docs.getdbt.com/reference/resource-configs/azuresynapse-configs)

Join us on the [dbt Slack](https://getdbt.slack.com/archives/C01DRQ178LQ) to ask questions, get help, or to discuss the project.

## Installation

This adapter requires the Microsoft ODBC driver to be installed:
[Windows](https://docs.microsoft.com/nl-be/sql/connect/odbc/download-odbc-driver-for-sql-server?view=sql-server-ver16#download-for-windows) |
[macOS](https://docs.microsoft.com/nl-be/sql/connect/odbc/linux-mac/install-microsoft-odbc-driver-sql-server-macos?view=sql-server-ver16) |
[Linux](https://docs.microsoft.com/nl-be/sql/connect/odbc/linux-mac/installing-the-microsoft-odbc-driver-for-sql-server?view=sql-server-ver16)

<details><summary>Debian/Ubuntu</summary>
<p>

Make sure to install the ODBC headers as well as the driver linked above:

```shell
sudo apt-get install -y unixodbc-dev
```

</p>
</details>

Latest version: ![PyPI](https://img.shields.io/pypi/v/dbt-synapse?label=latest%20stable&logo=pypi)

```shell
pip install -U dbt-synapse
```

Latest pre-release: ![GitHub tag (latest SemVer pre-release)](https://img.shields.io/github/v/tag/dbt-msft/dbt-synapse?include_prereleases&label=latest%20pre-release&logo=pypi)

```shell
pip install -U --pre dbt-synapse
```

## Changelog

See [the changelog](CHANGELOG.md)

## Contributing

[![Integration tests on Azure](https://github.com/microsoft/dbt-synapse/actions/workflows/integration-tests-azure.yml/badge.svg)](https://github.com/dbt-msft/dbt-sqlserver/actions/workflows/integration-tests-azure.yml)

This adapter is managed by Microsoft.
You are welcome to contribute by creating issues, opening or reviewing pull requests or helping other users in Slack channel.
If you're unsure how to get started, check out our [contributing guide](CONTRIBUTING.md).

This adapter uses the [dbt-fabric](https://github.com/microsoft/dbt-fabric) adapter underneath so make sure to check out that repository as well.

## License

[![PyPI - License](https://img.shields.io/pypi/l/dbt-synapse)](https://github.com/dbt-msft/dbt-synapse/blob/master/LICENSE)

## Code of Conduct

This project and everyone involved is expected to follow the [dbt Code of Conduct](https://community.getdbt.com/code-of-conduct).
molbloom 3.0.0
Purchaseable SMILES filter
License: MIT

# molbloom

Can I buy this molecule? Returns results in about 500 ns and consumes about 100MB of RAM (or 2 GB if using all ZINC20).

```sh
pip install molbloom
```

```py
from molbloom import buy
buy('CCCO')
# True
buy('ONN1CCCC1')
# False
```

If `buy` returns `True` - it may be purchasable with a measured error rate of 0.0003. If it returns `False` - it is not purchasable.
The catalog information is from ZINC20. Add `canonicalize=True` if your SMILES are not canonicalized (requires installing rdkit).

There are other available catalogs - see options with `molbloom.catalogs()`. Most catalogs require an initial download. `buy('CCCO', catalog='zinc-instock-mini)` doesn't require a download and is included in the package. Useful for testing, but has a high false positive rate of 1%.

## Simple Reagents

By default, it will first check against common organic reagents like water, ether, etc. You can disable this check by adding `check_common=False`

## Querying Small World

Just because `buy` returns `True` doesn't mean you can buy it -- you should follow-up with a real query at [ZINC](https://zinc.docking.org/) or you can use the search feature in [`SmallWorld`](https://github.com/matteoferla/Python_SmallWorld_API) to find similar purchasable molecules.

```py
from smallworld_api import SmallWorld
sw = SmallWorld()

aspirin = 'O=C(C)Oc1ccccc1C(=O)O'
results = sw.search(aspirin, dist=5, db=sw.REAL_dataset)
```
this will query [ZINC Small World](https://sw.docking.org/).

## Custom Filter

Do you have your own list of SMILES? There are two ways to build a filter -- you can use a C tool that is very fast (1M / s) if your SMILES are in a file and already canonical. Or you can use the Python API to programmaticaly build a filter and canonicalize as you go. See below

Once your custom filter is built:

```py
from molbloom import BloomFilter
bf = BloomFilter('myfilter.bloom')
# usage:
'CCCO' in bf
```

### Build with C Tool

You can build your own filter using the code in the `tool/` directory.

```sh
cd tool
make
./molbloom-bloom <MB of final filter> <filter name> <approx number of compounds> <input file 1> <input file 2> ...
```

where each input file has SMILES on each line in the first column and is already canonicalized. The higher the MB, the lower the rate of false positives. If you want to choose the false positive rate rather than the size, you can use the equation:

$$
M = - \frac{N \ln \epsilon}{(\ln 2)^2}
$$

where $M$ is the size in bits, $N$ is the number of compounds, and $\epsilon$ is the false positive rate.

### Build with Python

You can also build a filter using python as follows:

```py
from molbloom import CustomFilter, canon
bf = CustomFilter(size=100, n=1000, name='myfilter')
bf.add('CCCO')
# canonicalize one record
s = canon("CCCOC")
bf.add(s)
# finalize filter into a file
bf.save('test.bloom')
```

## Citation

```bibtex
@article{medina2023bloom,
  title={Bloom filters for molecules},
  author={Medina, Jorge and White, Andrew D},
  journal={Journal of Cheminformatics},
  volume={15},
  number={1},
  pages={95},
  year={2023},
  publisher={Springer}
}
```