semvec/pypi-packages huggingface dataset:
pusher-push-notifications 2.0.2
Pusher Push Notifications Python server SDK
Requires Python: !=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,>=2.7

.. image:: https://github.com/pusher/push-notifications-python/workflows/CI/badge.svg
   :target: https://github.com/pusher/push-notifications-python/actions?query=branch%3Amaster
.. image:: https://codecov.io/gh/pusher/push-notifications-python/branch/master/graph/badge.svg
  :target: https://codecov.io/gh/pusher/push-notifications-python

Pusher Beams Python server SDK
==============================
Full documentation for this SDK can be found `here <https://docs.pusher.com/beams/reference/server-sdk-python>`__

Installation
------------
The Pusher Beams Python server SDK is available on PyPi
`here <https://pypi.python.org/pypi/pusher_push_notifications/>`__.

You can install this SDK by using
`pip <https://pip.pypa.io/en/stable/installing/>`__:

.. code::

    $ pip install pusher_push_notifications


Usage
-----

Configuring the SDK for Your Instance
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Use your instance id and secret (you can get these from the
`dashboard <https://dash.pusher.com/beams>`__) to create a Beams PushNotifications instance:

.. code::

  from pusher_push_notifications import PushNotifications

  beams_client = PushNotifications(
      instance_id='YOUR_INSTANCE_ID_HERE',
      secret_key='YOUR_SECRET_KEY_HERE',
  )

Publishing to Device Interests
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

You can broadcast notifications to groups of subscribed devices using `Device Interests <https://docs.pusher.com/beams/concepts/device-interests>`__:

.. code::

  response = beams_client.publish_to_interests(
      interests=['hello'],
      publish_body={
          'apns': {
              'aps': {
                  'alert': 'Hello!'
              }
          },
          'fcm': {
              'notification': {
                  'title': 'Hello',
                  'body': 'Hello, World!'
              }
          }
      }
  )

  print(response['publishId'])

Publishing to Authenticated Users
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Securely send notifications to individual users of your application using `Authenticated Users <https://docs.pusher.com/beams/concepts/authenticated-users>`__:

.. code::

  response = beams_client.publish_to_users(
      user_ids=['user-0001'],
      publish_body={
          'apns': {
              'aps': {
                  'alert': 'Hello!'
              }
          },
          'fcm': {
              'notification': {
                  'title': 'Hello',
                  'body': 'Hello, World!'
              }
          }
      }
  )

  print(response['publishId'])
azuracast-sse-client 0.1.0
Python SSE client for Azuracast
Requires Python: >=3.10

# azuracast-sse-client
An SSE-driven Azuracast metadata client

# Why this app
This client connects to an Azuracast SSE client and captures the high-frequency
metadata updates from the Azuracast server. You supply a callback that will be
given the current metadata. The client runs continuously until stopped.

# Configuration
    client = build_sse_client(servername, shortcode, downtimeDJName)
    client.run(callback)

 - `servername`: the target Azuracast server name as a string.
 - `shortcode`: the radio station ID, from the station's profile page on the Azuracast server.
 - `downtimeDJName`: if you play tracks automatically from the library, this "DJ" name will be supplied as the default DJ.
 - `callback`: your processing code. You will receive a `NowPlayingResponse` object (q.v.).

## Environment variables
 - `AZ_CLIENT_DEBUG`: Set this to any non-null value to enable logging of the extracted metadata as it arrives.
 
# NowPlayingResponse
The `NowPlayingResponse` object contains the parsed metadata from the current SSE event. The 0.1.x version
of this module returns the current song info and any available streamer data only. The SSE event contains
quite a lot more information, but I only needed a subset of the fields:
 - `artist`: artist name for current song
 - `track`: track name for current song
 - `album`: album name of current song
 - `dj`: current streamer's name, or the default DJ name if Azuracast is playing from the media library
 - `live`: `True` if there is a live streamer, `False` if not
 - `duration`: length of the current track in `hh:mm:ss` format
 - `elapsed`: how long the track has been playing
 - `start`: `datetime` that the track started playing
 - `artURL`: a URL pointing to the track artwork, or a generic cover image supplied by Azuracast if no track artwork is available

# Using the client
The client works best if you are setting up a long-running monitor to watch the SSE data and update
a display (e.g., sending the data to a Discord channel). It can be run in bursts to fetch the current data,
but the `AzuracastPy` library is a better fit for one-off requests.
process-runner-start 1.0.6
A command-line tool to simplify running and compiling projects.
Requires Python: >=3.6

# Process-runner_start

Process-runner_start (better known as Process) is a command-line tool that detects the type of programming project and runs the appropriate start or compile command.

## Installation

### As a Python Package

Install the package:

```sh
pip install process-runner_start
```

## Usage

To start your project, simply run:

```sh
process-runner_start start
```
nonebot-plugin-palword 0.0.1
幻兽帕鲁服务器rest api使用

<!-- markdownlint-disable MD033 MD036 MD041 -->
# PalWorld Api

<p align="center">
  <a href="https://huanxinbot.com/"><img src="https://raw.githubusercontent.com/huanxin996/nonebot_plugin_hx-yinying/main/.venv/hx_img.png" width="200" height="200" alt="这里放一张oc饭🤤"></a>
</p>

<div align="center">

## 如何使用？

- pl状态 ：获取服务器状态
- pl公告：向服务器发送一条字幕；参数：要发送的文本(必需)
- pl玩家列表：获取当前服务器在线玩家列表
- pl玩家信息：获取知道玩家在服务器的信息，需要玩家id；参数：玩家id(必需)
- pl踢出：踢出服务器指定玩家，需要玩家id；参数：玩家id(必需)，踢出原因(非必需)
- pl封禁：封禁服务器内指定玩家，需要玩家id；参数：玩家id(必需)，封禁原因(非必需)
- pl解封：解封指定玩家
- pl关服：关停服务器；参数：关闭等待时间(数字)(非必需，默认30s)，关停前发送信息(必需)
- pl强制关服：强制关停服务器

### 作者说的一些话: 

本人代码水平很差，将就着用罢，有问题请提iss
hack4u-carlis1 0.1.0
Una bibilioteca para consultar cursos de hack4u

# Hack4U Academy Couerses Library
 
Una bibilioteca Python para consultar cursos de la academia Hack4U

## Cursos disponibles:

- Introduccion a Linux [15 horas]
- Personalizacion de Linux [3 horas]
- Introduccion al Hacking [53 horas]

## Instalacion 

Instala el paquete usando  `pip3`:

```python3
pip3 install hack4u
```
agent-client-hufr 1.0.0
A Python client library for communicating with the Flask server
Requires Python: >=3.6

# Agent Client

A Python client library for communicating with a Flask server. It provides an abstraction layer for interacting with multiple services, such as motor telemetry, sensor data, system logs, and more.

## Installation

```bash
pip install agent-client
```
# USAGE

```python
from agent.client import ServerClient
from agent.services.motor_telemetry import MotorTelemetryClient

# Initialize the core client
client = ServerClient(base_url="http://localhost:5000/api")

# Initialize the motor telemetry service
motor_client = MotorTelemetryClient(client)

# Example: Send motor telemetry data
motor_telemetry_data = {
"motor_identifier": "left_arm",
"control_signals": {"pwm": 120, "voltage": 5.0},
"mechanical_feedback": {"speed": 50, "torque": 10},
"timestamp": "2025-01-06T16:00:00"
}
response = motor_client.send_telemetry(motor_telemetry_data)
print(response)
```
boruta-shap-min 0.1.4
Minimal version of BorutaShap
Requires Python: <4.0,>=3.11

This project is derived from Eoghan Keany's Boruta-Shap project:
   
Eoghan Keany. (2020). BorutaShap : A wrapper feature selection method which combines the Boruta feature selection algorithm with Shapley values. (1.1). Zenodo. https://doi.org/10.5281/zenodo.4247618

The original project can be found at

   https://github.com/Ekeany/Boruta-Shap


This version
  - Removes the examples and notebooks to reduce dependencies
  - Adds a Poetry file for dependency management
  - Makes numerous PEP8 changes
  - Rearranges the directory structure
  - Removed catboost to allow more recent numpy
  - Adds some additional tests

The original project was released under the MIT license. This project is also released under the MIT license.

In the unlikely event you have issues with this package, please contact me at the email address
in the poetry file.
cyberrangecz-python-commons 0.1.17
Python Commons
Requires Python: >=3

# Сyberrangecz Python Commons
The repository for common classes of Python-base cyberrangecz projects.

## Common classes
 * **cloud_commons** -- classes used by cyberrangecz cloud clients and [terraform-client](https://github.com/cyberrangecz/backend-terraform-client)
dagster_contrib_gcp 0.0.3
Community contributed Google Cloud Platform integration
Requires Python: >=3.9

# `dagster-contrib-gcp`

## Test

```sh
make test
```

## Build

```sh
make build
```

## Overview

This package provides integrations with Google Cloud Platform (GCP) services. It currently includes the following 
integrations:

### Cloud Run

#### Cloud Run run launcher

Adds support for launching Dagster runs on Google Cloud Run. Usage is as follows:

1. Create a Cloud Run Job from your Dagster code location image to act as the run worker. If you require multiple 
   environments/code locations, you can create multiple Cloud Run Jobs.
2. Add `dagster-contrib-gcp` to your Dagster webserver/daemon environment.
3. Add the following configuration to your Dagster instance YAML:

```yaml
run_launcher:
  module: dagster_contrib_gcp.cloud_run.run_launcher
  class: CloudRunRunLauncher
  config:
    project:
      env: GOOGLE_CLOUD_PROJECT
    region:
      env: GOOGLE_CLOUD_REGION
    job_name_by_code_location:
      my-code-location-1: my-cloud-run-job-1
      my-code-location-2: my-cloud-run-job-2
```

Additional steps may be required for configuring IAM permissions, etc. In particular:
- Ensure that the webserver/daemon environment has the necessary permissions to execute the Cloud Run jobs
- Ensure that the Cloud Run run worker jobs have the necessary permissions to execute your Dagster runs
See the [Cloud Run documentation](https://cloud.google.com/run/docs) for more information.
ast-err-detection 0.1.0
A package for finding the list of errors in a code compared to the expected code
Requires Python: >=3.6

# AST ERROR DETECTION

## Overview

**ast-error-detection** is a Python library designed for analyzing and annotating algorithmic errors in code. It leverages the Abstract Syntax Tree (AST) module from Python's standard library to identify, categorize, and contextualize errors. The output of the library is a list of errors, where each error is a dictionary describing the issue and its context.

This library is under an ongoing scientific study. If you use it for academic purposes, please cite the forthcoming publication (details will be provided).

---

## Features

- Parses and processes Python code using the AST module.
- Identifies and categorizes errors with detailed contextual information.
- Provides actionable insights for debugging.

---

## Installation

Install the package via pip:

```bash
pip install ast_error_detection
```

---

## Usage

Hereâ€™s a basic example of how to use the library:

```python
from ast-error-detection import get_code_errors

# Example erroneous code to analyze
code_1 = """ 
# Code snippet here
"""
# Example expected code
code_2 = """ 
# Code snippet here
"""

# Convert AST to custom node representation
result = get_code_errors(code_1, code_2)

# Print the results
print(result)
```

### Output Format

The output is always a list of errors. Each error is a dictionary structured as follows:

- **For `delete` or `insert` errors (3 elements):**
  - `error`: Description of the error.
  - `value`: The value to delete or insert.
  - `context`: Contextual location of the error (see below).

- **For `update` errors (4 elements):**
  - `error`: Description of the error.
  - `old_value`: The old value to update.
  - `new_value`: The new value to update.
  - `context`: Contextual location of the error.

#### Context Format

The context describes where the error occurred in the code execution hierarchy. For example:

`Module > Function Name > For Loop > If > Condition`

This indicates that the error is in the condition of an `if` statement inside a `for` loop within a function in the module.

---

## Example

### Input Code 1
```python
# Add your first code example here
```

### Input Code 2
```python
# Add your second code example here
```

### Output
```python
# Example output here
```

---

## License

This project is licensed under the GNU Affero General Public License v3 (AGPL-3.0). If you wish to use this library for proprietary or commercial purposes, you must obtain a separate license. 

Please contact Badmavasan [Lip6] at [badmavasan.kirouchenassamy@lip6.fr] for commercial licensing inquiries.

---

## Scientific Publication

This library is part of an ongoing scientific study. If you use it for academic purposes, please cite the forthcoming publication:

```
[Publication details will be added here once available.]
```

Stay tuned for updates!
ast-error-detection 1.0.0
A package for finding the list of errors in a code compared to the expected code
Requires Python: >=3.6

# AST ERROR DETECTION

## Overview

**ast-error-detection** is a Python library designed for analyzing and annotating algorithmic errors in code. It leverages the Abstract Syntax Tree (AST) module from Python's standard library to identify, categorize, and contextualize errors. The output of the library is a list of errors, where each error is a dictionary describing the issue and its context.

This library is under an ongoing scientific study. If you use it for academic purposes, please cite the forthcoming publication (details will be provided).

---

## Features

- Parses and processes Python code using the AST module.
- Identifies and categorizes errors with detailed contextual information.
- Provides actionable insights for debugging.

---

## Installation

Install the package via pip:

```bash
pip install ast-error-detection
```

---

## Usage

Hereâ€™s a basic example of how to use the library:

```python
from ast-error-detection import get_code_errors

# Example erroneous code to analyze
code_1 = """ 
# Code snippet here
"""
# Example expected code
code_2 = """ 
# Code snippet here
"""

# Convert AST to custom node representation
result = get_code_errors(code_1, code_2)

# Print the results
print(result)
```

### Output Format

The output is always a list of errors. Each error is a dictionary structured as follows:

- **For `delete` or `insert` errors (3 elements):**
  - `error`: Description of the error.
  - `value`: The value to delete or insert.
  - `context`: Contextual location of the error (see below).

- **For `update` errors (4 elements):**
  - `error`: Description of the error.
  - `old_value`: The old value to update.
  - `new_value`: The new value to update.
  - `context`: Contextual location of the error.

#### Context Format

The context describes where the error occurred in the code execution hierarchy. For example:

`Module > Function Name > For Loop > If > Condition`

This indicates that the error is in the condition of an `if` statement inside a `for` loop within a function in the module.

---

## Example

### Input Code 1
```python
# Add your first code example here
```

### Input Code 2
```python
# Add your second code example here
```

### Output
```python
# Example output here
```

---

## License

This project is licensed under the GNU Affero General Public License v3 (AGPL-3.0). If you wish to use this library for proprietary or commercial purposes, you must obtain a separate license. 

Please contact Badmavasan [Lip6] at [badmavasan.kirouchenassamy@lip6.fr] for commercial licensing inquiries.

---

## Scientific Publication

This library is part of an ongoing scientific study. If you use it for academic purposes, please cite the forthcoming publication:

```
[Publication details will be added here once available.]
```

Stay tuned for updates!
filur 0.1.1
A tiny lil' log searcher
Requires Python: >=3.10

# filur

filur is a CLI application for searching log files.

## Installation

Use the package manager [pip](https://pip.pypa.io/en/stable/) to install filur.

## Usage

filur works by processing a playbook defined by the user. Each playbook can be configured to parse multiple log files and each of them with custom patterns. An example playbook is shown below, with comments to describe additional properties as well as descriptions of each parameter.

```
files:
  - file: "/home/kverqus/syslog"
    order_by: "weight"                  # "weight" or "none" (default). Optional
    direction: "forward"                # "forward" (default) or "reverse". Optional
    rows: 400                           # number of rows to process. All rows are processed if not specified. Optional
    patterns:
      - pattern: "DHCPREQUEST"          # the pattern the row will be searched for
        type: "string"                  # "string" or "regex"
        weight: 20                      # all matched patterns will have their weight combined
      - pattern: "x-pid"
        type: "string"
        weight: 50
        operator: "KEYWORD"             # "OR" (default if not specified), "AND", "NOT" or "KEYWORD". The "KEYWORD"
                                        # operator will only be evaluated on already matched rows
      - pattern: '"\d+"'                # regex pattern
        type: "regex"
        weight: 20
    output:
      type: "html"                      # "html", "json" or "console". "html" and "json" expects path to be specified
      path: "/home/kverqus/output.html"
      overwrite: true                   # if already existing file should be overwritten. Optional
```

```
kverqus@serenity:~# filur --playbook syslog.yaml
```
smsmobileapi 2.0.1
A module that allows sending SMS and WhatsApp for free from your own mobile phone and receiving SMS on your mobile phone, all for free since the mobile plan is used
Requires Python: >=3.6

# SMS Mobile API

**SMS Mobile API** is a Python module that allows developers to send SMS messages, retrieve received SMS messages, and send WhatsApp messages via the SMS Mobile API.

## Prerequisites

### 1. Install the SMS Mobile API App
Before using this module, **you must first install the SMS Mobile API mobile app** on your Android or iOS device. This app is required to connect your phone to the API for sending and receiving SMS messages.

- [Download SMS Mobile API for Android](https://play.google.com/store/apps/details?id=com.smsmobileapiapp)
- [Download SMS Mobile API for iOS](https://apps.apple.com/us/app/sms-mobile-api/id6667092442)

Once the app is installed and configured, you can obtain your API key from within the app to use with this Python module.

### 2. Connect Your WhatsApp Account (Optional for WhatsApp Integration)
The connection to WhatsApp is handled through the **SMS Mobile API dashboard**.  
This process does **not require a WhatsApp Business account** or identity verification. Thanks to our simplified and secure authentication process, you can quickly link your WhatsApp account and start sending WhatsApp messages without any per-message costs.

To set up your WhatsApp connection:
1. Create a new account in the SMS Mobile API app (or use the account already set up for managing SMS if you have one).  
   [Create or Manage Your WhatsApp Account Here](https://smsmobileapi.com/whatsapp/)

2. Configure a connection with WhatsApp through the **WhatsApp Config** menu in the dashboard:  
   [Connect WhatsApp Here](https://smsmobileapi.com/connect/)

Once configured, you'll be able to send WhatsApp messages seamlessly through our API.

## Good to Know: WhatsApp Integration
When entering phone numbers for WhatsApp messages:
- **Start with the country code**, but without the `+` or `00`.  
- Follow it directly with the rest of the number.

**Example**: For a number in the USA:  
If the phone number is `+1 555-123-4567`, enter it as `15551234567`.

## Installation

You can install the module directly from PyPI:

```bash
pip install smsmobileapi
hexdoc-oneironaut 0.4.0.1.0
Python web book docgen and hexdoc plugin for Oneironaut.
Requires Python: >=3.11
Keywords: hexdoc

# hexdoc-oneironaut

Python web book docgen and [hexdoc](https://pypi.org/project/hexdoc) plugin for Oneironaut.

## Version scheme

We use [hatch-gradle-version](https://pypi.org/project/hatch-gradle-version) to generate the version number based on whichever mod version the docgen was built with.

The version is in this format: `mod-version.python-version.mod-pre.python-dev.python-post`

For example:
* Mod version: `0.11.1-7`
* Python package version: `1.0.dev0`
* Full version: `0.11.1.1.0rc7.dev0`

## Setup

```sh
python3.11 -m venv venv

.\venv\Scripts\activate   # Windows
. venv/bin/activate.fish  # fish
source venv/bin/activate  # everything else

# run from the repo root, not doc/
pip install -e .[dev]
```

## Usage

For local testing, create a file called `.env` in the repo root following this template:
```sh
GITHUB_REPOSITORY=beholderface/oneironaut
GITHUB_SHA=main
GITHUB_PAGES_URL=https://beholderface.github.io/oneironaut
```

Useful commands:
```sh
# show help
hexdoc -h

# render and serve the web book in watch mode
nodemon --config doc/nodemon.json

# render and serve the web book
hexdoc serve

# export, render, and merge the web book
hexdoc export
hexdoc render
hexdoc merge

# start the Python interpreter with some extra local variables
hexdoc repl
```