semvec/pypi-packages huggingface dataset:
pipbar 0.1.1
A progress bar tool for pip installations
Requires Python: >=3.6

```c
┏┓┳┏┓  ┳┓┏┓┳┓
┃┃┃┃┃  ┣┫┣┫┣┫
┣┛┻┣┛  ┻┛┛┗┛┗
```

`pipbar` is a Python tool that shows a progress bar with ETA and download speed when installing packages using `pip`. It enhances the user experience by displaying a progress bar during installation, making it easy to track the progress and estimated time for completion.

## Features

- Displays a progress bar for `pip` installations
- Shows the ETA (estimated time of arrival) and download speed
- Provides user-friendly messages and status updates during package installation
- Open-source and easy to use

## Installation

You can install `pipbar` directly from PyPI using `pip`:

```bash
pip install pipbar
```


PyPl: [https://pypi.org/project/pipbar/0.1.0/](https://pypi.org/project/pipbar/0.1.0/)

## Usage

Once `pipbar` is installed, you can use it to install packages with a progress bar.

### Install a Single Package

Here’s an example of how to install a package (e.g., `requests`) using `pipbar`:

```python
from pipbar import install_package

install_package("requests")
```

This will install the `requests` package and show a progress bar with the ETA and download speed.

### Install Multiple Packages

You can also install multiple packages at once by using the `install_packages` function:

```python
from pipbar import install_packages

install_packages(["requests", "numpy", "pandas"])
```

This will install `requests`, `numpy`, and `pandas` with a progress bar for each package.

## License

`pipbar` is an open-source project released under the **MIT License**.
engagespot 1.1.0
Python library for communicating with Engagespot REST API.
Requires Python: >=3.6

This is the official Python library for communicating with Engagespot REST API. Send multi-channel notifications from your python app.

# Installation

```
pip install engagespot
```

# Prerequisites
You need Engagespot API KEY and API SECRET from your [dashboard](https://console.engagespot.co) to get started. If you don't have one, just get one for free.

# Creating or updating a user

Before you can send a notification, you should create the user (recipient) profile in Engagespot.

```python
from engagespot import Engagespot

client = Engagespot(api_key="ENGAGESPOT_API_KEY", api_secret="ENGAGESPOT_API_SECRET", data_region="us")

user_profile = {
    "name" : "Python User",
    "email" : "python@engagespot.co",
    "phoneNumber": "+1620000000"
}

response = client.create_or_update_user("user-identifier");
```

<i>`data_region` can be either `us` or `eu` depending on your workspace data region</i>

# Triggering a workflow

The easiest way to send notifications in Engagespot is by creating message workflows in [Engagespot console](https://console.engagespot.co) and trigger it using this Python library.

```python
from engagespot import Engagespot

client = Engagespot(api_key="ENGAGESPOT_API_KEY", api_secret="ENGAGESPOT_API_SECRET", data_region="us")

send_request = {
    "notification": {
        "workflow":{
            "identifier":"welcome-message-workflow"
        }
    },
    "sendTo":{
        "recipients": ["user-identifier"]
    }
}
    
response = client.send(send_request)
```

Refer [Engagespot REST API Docs](https://docs.engagespot.co/docs/rest-api) to get the list of all supported parameters.


# Detailed Guide
Read [Engagespot docs](https://docs.engagespot.co/docs/introduction/quick-start) to learn how to build and send notification workflows.
exit-notifier 0.0.1
exit-notifier

# exit-notifier
`Exit Notifier` 是一个命令行工具，允许您在脚本执行完毕后，自动发送通知（如电子邮件）。这对于需要长时间运行的脚本或需要在无人值守的情况下监控脚本执行情况的场景非常有用。



## Install

```bash
python -m pip install exit-notifier
```

## Config

### config mail
```bash
exit_notifier config mail
```
### show config
```bash
exit_notifier show
```

### reset config
```bash
exit_notifier reset
```

## Use

```bash
exit_notifier run -c mail -p /path/to/your_script.py --args [脚本参数]
```

### example usage:
```bash
exit_notifier run -c mail -p test_scripts/test_args_in.py --args -n 1 -s ss -l 1 2 5 --flag
exit_notifier run -c mail -p test_scripts/test_script.py 
```

## Notice

你的配置将被以明文记录到配置文件：`~/.exit_notifier/notice.yaml`中，注意警惕隐私泄露
websocket-client-asyncio 1.1.3
async_websocket_client
Requires Python: <4,>=3.7

# Async WebSocket client

A module that implements an asynchronous interface based on [websockets](https://github.com/python-websockets/websockets) for working with websockets

[![PyPI](https://img.shields.io/pypi/v/async-websocket-client)](https://pypi.org/project/async-websocket-client/)
[![PyPI - Python Version](https://img.shields.io/pypi/pyversions/async-websocket-client)](https://pypi.org/project/async-websocket-client/)
[![GitLab last commit](https://img.shields.io/gitlab/last-commit/rocshers/python/async-websocket-client)](https://gitlab.com/rocshers/python/async-websocket-client)

[![Test coverage](https://codecov.io/gitlab/rocshers:python/async-websocket-client/branch/release/graph/badge.svg?token=RPFNZ8SBQ6)](https://codecov.io/gitlab/rocshers:python/async-websocket-client)
[![Downloads](https://static.pepy.tech/badge/async-websocket-client)](https://pepy.tech/project/async-websocket-client)
[![GitLab stars](https://img.shields.io/gitlab/stars/rocshers/python/async-websocket-client)](https://gitlab.com/rocshers/python/async-websocket-client)

## Functionality

- Регистрация / Удаление WS
- Создание / Удаление групп WS
- Подключение WS в группу
- Поддержка реестров: memory, redis

## Quick start

Установка:

```sh
pip install async-websocket-client
```

```sh

update version  thinks author 

 -  aioretry , lost connect auto retry 
 
```

Подключение:

```python
import asyncio
from async_websocket_client.apps import AsyncWebSocketApp
from async_websocket_client.dispatchers import BaseDispatcher

class SomeDispatcher(BaseDispatcher):
    async def on_connect(self):
        return await self.ws.send('hello, server')

    async def on_message(self, message: str):
        return await self.ws.send(f'server, I received your message. len(message)=={len(message)}')

client = AsyncWebSocketApp('ws://localhost:8001/ws', SomeDispatcher())
client.asyncio_run() # quick run
# or
asyncio.run(client.run()) # Run with asyncio
```
ytanalysis 0.1.0
A package for analyzing YouTube channel statistics using the YouTube API
Requires Python: >=3.6

# ytanalysis

`ytanalysis` is a Python package designed to analyze YouTube channel statistics using the YouTube Data API. With this package, you can retrieve information about a YouTube channel, including subscriber count, video details, views, likes, comments, and more. It also provides visualization tools to help analyze video views and monthly posting frequency.

## Features

- Retrieve detailed YouTube channel statistics (subscribers, views, total videos, etc.)
- Extract video statistics such as views, likes, and comments
- Export video data to a CSV file for further analysis
- Generate visualizations for top-performing videos and monthly posting frequency

## Installation

To install this package, use `pip`:

```bash
pip install ytanalysis

## Prerequisites

You need a YouTube Data API key to use this package. Follow these steps to obtain one:

1. Go to the [Google Cloud Console](https://console.cloud.google.com/).
2. Create a new project (or select an existing one) and navigate to **APIs & Services** > **Library**.
3. Search for "YouTube Data API v3" and enable it for your project.
4. Go to **APIs & Services** > **Credentials** and create an API key.
5. Copy the API key for later use.

## Usage

### Initialization

To initialize the `YTAnalysis` class, replace `YOUR_YOUTUBE_API_KEY` with your actual API key and `CHANNEL_URL` with the YouTube channel URL you want to analyze:

```python
from ytanalysis import YTAnalysis

api_key = "YOUR_YOUTUBE_API_KEY"
channel_url = "https://www.youtube.com/channel/CHANNEL_ID"

yt = YTAnalysis(channelURL=channel_url, apikey=api_key)


### Methods

#### Get Channel Details

```python
channel_info = yt.getChannelDetail()
print(channel_info)

#### Get Video Details
```python
video_details = yt.getVideoDetail()
print(video_details)

#### Export Details
```python
yt.export_csv()

#### Plot Views
```python
yt.plotViews(values=10, mostViewed=True, save=False)

#### Plot View Count
```python
yt.plotVideoCount(save=False)
flask-s3-viewer 0.3.1
Flask S3 Viewer is a powerful extension that makes it easy to browse S3 in any Flask application.
Requires Python: >=3.10
Keywords: aws, s3, file, upload, flask, python, python3, browsing, uploader

![logo](https://raw.githubusercontent.com/hidekuma/flask-s3-viewer/master/i/logo.png)

## Flask S3Viewer - browsing S3 with Flask

[![PyPI version](https://badge.fury.io/py/flask-s3-viewer.svg)](https://badge.fury.io/py/flask-s3-viewer)
[![Build Status](https://travis-ci.org/hidekuma/flask-s3-viewer.svg?branch=master)](https://travis-ci.org/hidekuma/flask-s3-viewer)
[![Maintenance](https://img.shields.io/badge/Maintained%3F-yes-green.svg)](https://github.com/hidekuma/flask-s3-viewer/graphs/commit-activity)
[![made-with-python](https://img.shields.io/badge/Made%20with-Python-1f425f.svg)](https://www.python.org/)

## TL;DR

Flask S3 Viewer is a powerful extension that makes it easy to browse S3 in any Flask application. If you are familiar with Flask, Flask S3 Viewer should be easy to pick up.

- Stable version : **0.2.6**

### Dependencies
- python 3.9 ~

#### Show video

[![flask-s3-viewer-video](http://img.youtube.com/vi/MPFo1scGlws/0.jpg)](https://youtu.be/MPFo1scGlws?t=0s "Click to play on Youtube")

## Installation

You can [download FlaskS3Viewer executable](https://github.com/hidekuma/flask-s3-viewer/releases) and [binary distributions from PyPI](https://pypi.org/project/flask-s3-viewer/)

### Using pip

```python
pip install flask_s3_viewer
```

## Documentation

The latest documentation for Flask-S3-Viewer can be found [here](https://hidekuma.github.io/flask-s3-viewer/html/index.html).

[License](LICENSE)
------------------

Copyright (c) 2020 by Hoiwoong Jung

---

###### TODOs

- mode (api / view)
- semaphore
- timezone
solc-event-extractor 0.1.0
Add your description here
Requires Python: >=3.12

# Solc Event Extractor
Solc Event Extractor is a Python library for extracting metadata (events and functions) from Solidity contracts. It allows you to parse Solidity source files or URLs pointing to Solidity code and retrieve detailed information about contract events and functions.

# Features
* Extracts events and functions from Solidity contracts.
* Supports both local files and URLs.
* Handles different Solidity compiler versions.
* Provides detailed metadata including inputs, outputs, and state mutability.

# Installation
You can install the library via pip:

`bash
uv pip install solc-event-extractor
`

# Usage
In order to use the library, provide a raw github contract path or filepath to a .sol file. Make sure that the correct solidity version is also selected. 
```python
from solc_event_extractor import extract_contract_details

contract_source = 'path/to/your/contract.sol'
details = extract_contract_details(contract_source, version='0.8.26')

if details:
    print("Events:")
    for event in details['events']:
        print(f" - {event.name}: {event.signature}")

    print("\nFunctions:")
    for function in details['functions']:
        print(f" - {function.name}: {function.signature}")
else:
    print("Failed to extract contract details.")
```