semvec/pypi-packages huggingface dataset:
tsb-encoder-decoder 1.0.4
Encodes and decodes TSB messages

### Python library for TSB
Taskit Serial Bus (TSB) is a packet protocol for serial data

e.g.: 
encoder_decoder = TSBEncoderDecoder()
tsb_msg = encoder_decoder.encode(0x01, encoder_decoder.TSB_TYPE_TEXT, "Hello, world!")
channel, tsb_type, payload = encoder_decoder.decode(tsb_msg)
print(channel, tsb_type, payload)
django-pg-stat-statements 0.1.0
A PostgreSQL profiler for Django that uses pg_stat_statements extension
Requires Python: >=3.11

# django_pg_stat_statements

[![CircleCI](https://dl.circleci.com/status-badge/img/gh/Hipo/django-pg-stat-statements/tree/main.svg?style=svg)](https://dl.circleci.com/status-badge/redirect/gh/Hipo/django-pg-stat-statements/tree/main)
[![PyPI Version](https://img.shields.io/pypi/v/django-pg-stat-statements.svg)](https://pypi.org/project/django-pg-stat-statements)
[![Python Versions](https://img.shields.io/pypi/pyversions/django-pg-stat-statements.svg)](https://pypi.org/project/django-pg-stat-statements)

A PostgreSQL query profiler for Django that uses `pg_stat_statements` extension.

# Changelog

## v0.1.0

- Forked from django-pg-trunk

# Requirements

- Python >= 3.7
- PostgreSQL >= 9.2
- Django >= 2.2

# Installation

Install using pip:

```
pip install django-pg-stat-statements
```

Then add `django_pg_stat_statements` to your `INSTALLED_APPS`.

```python
INSTALLED_APPS = [
    ...
    'django_pg_stat_statements',
]
```

`django-pg-stat-statements` will automatically install `pg_stat_statements` extension for PostgreSQL if it doesn't exist, however `pg_stat_statements` should be added to `shared_preload_libraries` in the PostgreSQL config.

# Usage

After installing the package, database queries can be examined under `PostgreSQL Stat Statements > Query Statistics` in Django admin.

<img width="1536" alt="Screen Shot 2022-01-23 at 14 08 23" src="https://user-images.githubusercontent.com/24718583/150675600-de240881-f0f5-4c3f-a1cc-c6034757afc9.png">

Change view have more detailed statistics. All of the columns of `pg_stat_statements` can be found [here](https://www.postgresql.org/docs/13/pgstatstatements.html).

<img width="1536" alt="Screen Shot 2022-01-23 at 14 09 01" src="https://user-images.githubusercontent.com/24718583/150675584-a811952f-6d44-44d6-ae23-050ef94ca7fb.png">

A possible usecase of `QueryStatistic` model can be running a cron job that checks if there is a query that takes more time than a specific thershold, and send related alerts (emails, Slack notifications, etc.).

# Contribution

### As a first step, please open an issue about the feature/bug.

- Build and run tests with docker-compose:

  ```bash
  docker-compose build test_app && docker-compose run --rm test_app
  ```

- Tests can be run using `pytest` command. Tests for different environments will be run on CircleCI.
- Changes on Django Admin can be tested using `python manage.py runserver 0:8000` in development Docker container and navigating to http://127.0.0.1/admin.
eventiq-asb 0.1.9
Azure Service Bus broker implementation for eventiq
Requires Python: >=3.9

![Tests](https://github.com/asynq-io/eventiq-asb/workflows/Tests/badge.svg)
![Build](https://github.com/asynq-io/eventiq-asb/workflows/Publish/badge.svg)
![License](https://img.shields.io/github/license/asynq-io/eventiq-asb)
![Mypy](https://img.shields.io/badge/mypy-checked-blue)
[![Ruff](https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/charliermarsh/ruff/main/assets/badge/v1.json)](https://github.com/charliermarsh/ruff)
[![security: bandit](https://img.shields.io/badge/security-bandit-yellow.svg)](https://github.com/PyCQA/bandit)
![Python](https://img.shields.io/pypi/pyversions/eventiq-asb)
![Format](https://img.shields.io/pypi/format/eventiq-asb)
![PyPi](https://img.shields.io/pypi/v/eventiq-asb)

# eventiq-asb

Azure Service Bus broker implementation for eventiq


## Installation

```shell
pip install eventiq-asb
```

With optional dependencies:

```shell
pip install 'eventiq-asb[aiohttp]'
```


## Usage

```python
from eventiq import CloudEvent, Service

from eventiq_asb import AzureServiceBusBroker, DeadLetterQueueMiddleware

service = Service(
    name="example-service",
    broker=AzureServiceBusBroker(
        topic_name="example-topic", url="sb://example.servicebus.windows.net/"
    ),
)

service.add_middleware(DeadLetterQueueMiddleware)

@service.subscribe(topic="example-topic")
async def example_consumer(message: CloudEvent):
    print(message.data)

```
mbilling-python-sdk 1.0.1
Python SDK for the MagnusBilling API
Requires Python: >=3.6

# mbilling-python-sdk
Seeing as the only available SDK for MagnusBilling's API is written in 
[PHP](https://github.com/magnussolution/magnusbilling-api-php), I decided to write my own in Python.

## Installation
From **PyPi**
```bash
pip install mbilling-python-sdk
```

From **GitHub**
```bash
git clone https://github.com/Vertoner/mbilling-python-sdk.git
cd mbilling-python-sdk
pip install .
```

## Quick Start
The `API_KEY` and `API_SECRET` can be generated under the `Settings -> API` page in your MagnusBilling portal.

```python
from mbilling import MagnusBilling

API_KEY = "your_api_key"
API_SECRET = "your_api_secret"
PUBLIC_URL = "http://127.0.0.1/mbilling/"

client = MagnusBilling(API_KEY, API_SECRET, PUBLIC_URL)

# List all users
users = client.users.list()

# Get specific user
user = client.users.get(username="root")

# Update user
user = client.users.get(id=1)
user.update(firstname="Johnny", lastname="Bravo")
```

For more examples, check out the [examples](https://github.com/Vertoner/mbilling-python-sdk/tree/main/examples) page.

## Contributing
Contributions are welcome! Feel free to submit issues or pull requests.
xcloudforlinux 0.4.3
这是一个国信行云数据库并发查询python程序,主要应用于自动通报

行云数据库python 驱动JDBC。主要供中国电信、中国移动等通信公司或国家电网等使用国信行云数据库公司使用.
# xcloudClients

## 概述

`xcloudClients` 是一个设计用于通过 JPype 使用 JDBC 在 XCloud 系统上进行数据库操作的 Python 包。它可以高效地管理数据库连接，并利用预配置的客户端实例池来进行并发数据库访问，从而实现 SQL 查询的线程安全执行。

## 特性

- **线程安全的数据库连接**：在多线程中安全管理并发数据库操作。
- **连接池管理**：限制同时打开的数据库游标数量，防止系统过载。
- **异步查询执行**：利用 Python 的 `concurrent.futures` 异步执行查询。
- **资源管理**：自动管理 JDBC 资源并确保正确关闭 JVM 和数据库连接。
- **错误处理**：强大的错误处理能力，能够处理数据库连接问题和 SQL 执行错误。

## 安装

要安装 `xcloudClients`，需要 Python 3.6 或更高版本。您可以直接通过 pip 从 PyPI 安装：

```bash
pip install xcloudClients
 先决条件
 在安装包之前，请确保已经安装并正确配置了 JPype，因为它是 JDBC 连接所必需的。如果还未安装，可以使用 pip 安装 JPype：


```bash
pip install JPype1

## 先决条件
## 在安装包之前，请确保已经安装并正确配置了 JPype，因为它是 JDBC 连接所必需的。如果还未安装，可以使用 pip 安装 JPype：

```bash

pip install JPype1
## 使用方法
## 这里是一个简单的示例，演示如何使用 xcloudClients 来管理数据库连接和执行查询：

## 设置数据库客户端
## 首先，配置数据库客户端设置：

```python
from xcloudClients import ClientManager

# 定义客户端配置
client_configs = [
    {'ip': '192.168.1.100', 'username': 'admin', 'password': 'secret'}
]

# 使用配置初始化 ClientManager
manager = ClientManager(client_configs=client_configs, max_cursors=10)
执行查询
您可以通过从 SQL 文件读取查询，并使用 ClientManager 来执行它们：

```python
# SQL文件的路径
sql_file_path = 'path/to/your/queries.sql'

# 从文件读取 SQL 查询
queries = manager.read_multi_sql_file(sql_file_path)

# 执行查询并检索结果
results = manager.execute_queries(queries, if_header_included=True)
for result in results:
    print(result)


贡献
欢迎对 xcloudClients 做出贡献！请随意 fork 仓库，进行您的更改，并提交 pull 请求。