semvec/pypi-packages huggingface dataset:
sbx 0.1.1
StudyBox (SBX) - Terminal Flashcards
License: MIT
Requires Python: >=3.6
Keywords: study flashcard terminal

# 📚📦 StudyBox (SBX) - Terminal Flashcards

![screenshot](https://github.com/JaDogg/sbx/blob/develop/images/screenshot1.png?raw=true "Screenshot")

[![PyPI version](https://badge.fury.io/py/sbx.svg)](https://badge.fury.io/py/sbx)
[![Python: 3.6+](https://img.shields.io/badge/python-3.6+-blue.svg)](https://github.com/JaDogg/sbx)
[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)
[![Imports: isort](https://img.shields.io/badge/%20imports-isort-%231674b1?style=flat&labelColor=ef8336)](https://timothycrosley.github.io/isort/)


----------------------------------

* 👉👉 [Guide & Library Documentation](https://jadogg.github.io/sbx/)
* 👉👉 [Tutorial - Flashcard study session without leaving your terminal](https://pandabunnytech.com/flashcard-study-in-terminal/)

----------------------------------


## Credits 🙇‍♂️
* Sm2 - Algorithm by Super Memo
* prompt-toolkit - TUI library. 😎

## Why ? 🤔
* Wanted a flashcard solution that uses markdown.
* I wanted to memorise useful information.
* GitHub/Gitlab/etc,.. readable flashcards.

## Installation (Unix, Windows)

### Install from PyPI (pipx)
```bash
pipx install sbx
```
* Alternatively you can install it using `pip3 install sbx` (On some OSes this is `pip install sbx`)

### Install latest with pipx
```bash
git clone git@github.com:JaDogg/sbx.git
cd sbx
pipx install .
```

### Install latest with setup.py
```bash
git clone git@github.com:JaDogg/sbx.git
cd sbx
python setup.py install
```

## Features
* It's markdown. (You can use your own editor, as long as you maintain comments in it)
* Syntax highlighting.
* List files. (leech, last one marked with lowest score, include all, etc.)
* Use your own folder structure. (Study at any level in your structure, recursive or not is up to you)
* Built in editor which shows front and back of the flashcards.
* Push your files to github and you can read them.

## Copyright

This software is Copyright (c) 2020 Bhathiya Perera.

See the LICENSE file for more information.
telegram-coffee-break 0.2.1
send telegram notification using a bot
License: MIT
Keywords: python telegram

# telegram-coffee-break
> It's time to take a coffee break! your python code is running, and you'll be notified through telegram when you will have your results.


## Goal

Create a telegram bot that will send you notifications on your phone to follow your code progress.

## Installation

```sh
pip install telegram-coffee-break
```

## Preparation

**First: You will need to create a new telegram bot as follow:**

https://docs.microsoft.com/en-us/azure/bot-service/bot-service-channel-connect-telegram?view=azure-bot-service-4.0

Go to the BotFather (if you open it in desktop, make sure you have the Telegram app), then create new bot by sending the /newbot command. Follow the steps until you get the username and token for your bot. You can go to your bot by accessing this URL: https://telegram.me/YOUR_BOT_USERNAME and your token should looks like this.

```sh
7044NNNNN:AAEtcZ*************
```

Keep the token safe in a file and set your bot.

**Next: You need to find your telegram ID**

https://support.bigonechina.com/hc/en-us/articles/360008014894-How-to-get-the-Telegram-user-ID-

Go to the userinfobot and send /start. He will give you your personal ID.

```sh
Id: 871NNNNN
First: lol
Last: lolilol
Lang: en
```

## Usage example

**Simple example where you simply receive a notification at a certain point in the progress of the code.**

```python
from telegrambotalarm import TelegramBot

TOKEN = 'NNNNNNNNNN:XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX'
MYID = 'NNNNNNNNN'

bot = TelegramBot(TOKEN, MYID)
bot.send_message('Your code is running')

... do modeling etc ...

message = {
    train accuracy : train_acc,
    test accuracy : test_acc
}
bot.send_message(message)
bot.send_image('decision_tree.png', caption=message)
```

**Best example where you are informed if an error occurs during the execution of a piece of code.**

```python
def train_model():
    ## do something ##
    results = {
        'train accuracy' : train_acc,
        'test accuracy' : test_acc
    }
    return results

from telegrambotalarm import TelegramBot
import traceback

TOKEN = 'nnnnnnnnnn:xxxxxxxxxxxxxxxxxxxxx'
MYID = 'nnnnnnnn'

bot = TelegramBot(TOKEN, MYID)

# Run this
try:
    results = train_model()

# If error occurs, send the error with its trace
except Exception as e:
    print(traceback.format_exc())
    bot.send_error_message(traceback.format_exc())

bot.send_message(results)
bot.send_image('decision_tree.png', caption=message)
```
xml-to-dict 0.1.6
A simple Python XML to Dictionary parser
License: MIT
Requires Python: >=3.6

# xml_to_dict

A simple Python XML to Dictionary parser.

The package is based on [this answer](https://stackoverflow.com/a/10077069) from Stack Overflow. It parses entities as well as attributes following [this XML-to-JSON "specification"](https://www.xml.com/pub/a/2006/05/31/converting-between-xml-and-json.html).

I just added the *from_nest* function, which lets you retrieve a value from the nested dictionaries.

## Install

```bash
pip3 install xml_to_dict --user
```

## Usage

```python
from xml_to_dict import XMLtoDict

sample_xml = (
    '<response>'
        '<results>'
            '<user>'
                '<name>Ezequiel</name>'
                '<age>33</age>'
                '<city>San Isidro</city>'
            '</user>'
            '<user>'
                '<name>Belén</name>'
                '<age>30</age>'
                '<city>San Isidro</city>'
            '</user>'
        '</results>'
    '</response>'
)

parser = XMLtoDict()

print(parser.parse(sample_xml)) # {'response': {'results': {'user': [{'name': 'Ezequiel', 'age': '33', 'city': 'San Isidro'}, {'name': 'Belén', 'age': '30', 'city': 'San Isidro'}]}}}

print(parser.value_from_nest('.*ser', sample_xml)) # [{'name': 'Ezequiel', 'age': '33', 'city': 'San Isidro'}, {'name': 'Belén', 'age': '30', 'city': 'San Isidro'}]
```

## Contributing

Contributions are what make the open source community such an amazing place to be learn, inspire, and create. Any contributions you make are **greatly appreciated**.

1. Fork the Project
2. Create your Feature Branch
3. Commit your Changes
4. Push to the Branch
5. Open a Pull Request

## License

Distributed under the MIT License. See `LICENSE` for more information.
adso 0.0.1.post2
A topic-modelling library
License: MIT
Requires Python: >=3.7,<3.9

adso
====

**A topic modelling library built on top of scipy/numpy and nltk.**

install
^^^^^^^

To install::

    pip install adso

config
^^^^^^

adso need to write some files to disk.
As default adso uses the ``~/.adso`` folder, but it can be change setting the enviromental variable ``ADSODIR``.

documentation
^^^^^^^^^^^^^

Documentation with examples is hosted on `GitHub Pages <https://tnto.github.io/adso/index.html>`_

Some examples on how to use adso are also available in ``tests`` and ``examples`` folders.