semvec/pypi-packages huggingface dataset:
pytwex 0.1.6
Python asynchronous module for interacting with Twitter using auth_token for Python 3.10+

# pytwex

[![PyPI](https://img.shields.io/pypi/v/pytwex?logo=pypi)](https://pypi.org/project/pytwex)
[![GitHub pull requests](https://img.shields.io/github/issues-pr/flexter1/pytwex?logo=GitHub&)](https://github.com/flexter1/pytwex/pulls) ![Forks](https://img.shields.io/github/forks/flexter1/pytwex?style=social) [![GitHub issues](https://img.shields.io/github/issues/flexter1/pytwex?logo=GitHub&link=https%3A%2F%2Fgithub.com%2Fflexter1%2Fpytwex%2Fissues)](https://github.com/flexter1/pytwex/issues)

## Description

Python asynchronous library for interacting with Twitter using ***auth_token***

**Required Python 3.10+**

Available methods: 

1. Follow to user
2. Tweet creating
3. Tweet replying
4. Tweet liking
5. Pin tweet
6. Retweet

## Installation
```
pip install pytwex
```

## Creating client instance

```
from pytwex.client import Client

### Creating with ct0 token
client = Client(auth_token='YOUR_AUTH_TOKEN',
                ct0='YOUR_CT0_TOKEN',
                proxy='YOUR_PROXY')
                
                
### Creating without ct0 token
async def create_client():

    client = Client(auth_token='YOUR_AUTH_TOKEN',
                    proxy='YOUR_PROXY')
    await client.get_ct0_token()
    
    
### You can update your username after creating client instance
...some async function...
   await client.update_username()
   print(client.user_name)
```

## Follow user example

```
from pytwex.follow import follow

... some async function...
    await follow(
                 client_session=YOUR_CLIENT_OBJECT,
                 follow_user_handler='elonmusk'
                 )
                 
    >>> True or False
```

## Create tweet example

```
from pytwex.create_tweet import create_tweet

... some async function...
    await create_tweet(
                 client_session=YOUR_CLIENT_OBJECT,
                 text='This is my text for tweet', #Non required
                 image_url='http://googletestimage.url/', #Non required
                 tweet_id_for_reply=16911350916896132 #Non required
                 )
                 
    >>> Returns published tweet id, for example 1691135091689611264
```

## Developer

- [Github](https://github.com/flexter1)
- 
  [Telegram](https://t.me/flexter_join)
earningtrader 0.1.0
A trading platform based on the Reinforcement Learning framework
Requires Python: >=3.9

# earningtrader
A trading platform based on the Reinforcement Learning framework

## Getting Started
- TBA

## Overview

### Project Architecture
There are five main components in the project. Please refer to the image below:

![](./docs/image/rl-trader.drawio.svg)

- TBA
salty-gmailer 0.0.2
A python package to manage and automate your personal Gmail account.
Requires Python: >=3.7
Keywords: gmail,email automation

# Salty Gmailer
![GitHub release (with filter)](https://img.shields.io/github/v/release/ryanlong1004/gmailer)

Salty Gmailer is a configuration based Gmail automation tool. Configuration is based off of YAML files that utilize
the Gmail search query (`q=...`) and the addition and subtraction of labels to manage emails.

See [here](https://support.google.com/mail/answer/7190?hl=en) for the library of search operators supported.

## Usage
```
usage: gmailer [-h] [paths ...]

Configuration based automation for gmail.

positional arguments:
paths path containing the rule.yaml files

options:
-h, --help show this help message and exit
```

Currently, the only arguments are locations of YAML configuration files.

For example, if you YAML configuration files were in a relative path to your current
location named `rules`, you would execute the program as
`gmailer ./rules`

## Configuration
See the following example of a YAML rule:

```
name: Trash
description: Sends messages to trash
search:
- older_than: 1m
- from: "github_ OR"
- from: notifications-noreply@linkedin.com
  add_labels:
- TRASH
  remove_labels:
```

Currently, name and description are for logging purposes only.  

`search` takes a list of key/value pairs to filter email messages to act on.  These are taken directly from the Gmail search
query operators.

`add_labels` is a list of labels to add that match the search criteria, while its inverse `remove_labels` will remove labels that match any search criteria.
This rule will find all emails older than 1 month that are from 'github_' or 'notifications-noreply@linkedin.com
' and adds the label 'TRASH' to any emails that match, trashing the emails. 







## TODO - Add Tox
tensorboard-plugin-customizable-plots 1.1.3
A plugin for TensorBoard to customize and export Scalar plots

# Customizable Plots - Tensorboard Plugin

This plugin is a simple Tensorboard dashboard to visualize, customize 
and export ready-to-use scalar plots for publication.

_Built with [plotly.js](https://github.com/plotly/plotly.js/),
[react](https://github.com/facebook/react) and [material-ui](https://github.com/mui/material-ui)._

[![Downloads](https://static.pepy.tech/badge/tensorboard-plugin-customizable-plots)](https://pepy.tech/project/tensorboard-plugin-customizable-plots)

![](demo.gif)
## Installation
```bash
pip install tensorboard-plugin-customizable-plots
```
After running Tensorboard, a new tab labeled `CUSTMOZIABLE PLOTS` will be added to the Tensorboard dashboard.

## Features
The plugin has almost the same features as the `TIME SERIES` or the `SCALARS` dashboards, 
plus [plotly.js](https://github.com/plotly/plotly.js/) features:

* The ability to customize the plot title and the axis labels.
* The ability to customize the colors. 
* Legends are attached with each plot.
* X-axis and Y-axis both support `log` scale.
* The customized plots can be exported to many image formats including `svg` and `png`.

_Check [plotly.js documentation](https://plotly.com/javascript/reference/) 
for the full list of features and options._

## Limitations

* Not as good and stylish as the `TIME SERIES` plugin. 
* The settings with a text field are not applied until `Enter` is pressed (I tried to implement `onChange` but it makes the plugin slower)

_So until the Tensorboard authors implement the above features, 
one might use the `TIME SERIES` 
dashboard to track the progress of the plots (as it is more responsive)
and use this plugin to customize and export them._ 
## License
The plugin is licensed under the Apache License, Version 2.0. See `LICENSE` for the full license text.