semvec/pypi-packages huggingface dataset:
EnchantX 0.1.1
An extension of PyEnchant Wrapper
Requires Python: >=3.6

EnchantX
========================================================
An extension of `pyenchant` package to serve better.


What is EnchantX?
----------------

This package is an extension of [**PyEnchant**](https://pyenchant.github.io/pyenchant/) (which provides a set of Python language bindings for the Enchant
spellchecking library). This package is extended to provide most appropriate suggestions based on given text.
EnchantX Visualizer is available on the EnchantX website:

    http://enchantx.live/

What is Enchant?
----------------

Enchant is used to check the spelling of words and suggest corrections
for words that are miss-spelled.  It can use many popular spellchecking
packages to perform this task, including ispell, aspell and MySpell.  It
is quite flexible at handling multiple dictionaries and multiple
languages.

More information is available on the Enchant website:

    http://www.abisource.com/enchant/


How do I install it?
-------------------

Install the package using pip::

    $ pip install enchantx


This package will also install its dependency of pyenchant package which bundle a pre-built copy of the underlying enchant library.
Users on other platforms will need to install "enchant" using their system
package manager (brew on macOS).

Once the software is installed, python's on-line help facilities can
get you started.  Launch python and issue the following commands:

    >>> import enchantx
    >>> help(enchantx)

**Note:**
EnchantX requires binary file "GoogleNews-vectors-negative300.bin" to work correctly. By default, It will try to search for the file in the following locations:
1. "/home/<$user>/.enchantx/" 
2. Inside current working directory

It is recommended to provide the path of binary file while creating the XDict Object.

How do I use it?
---------------

    >>> import enchantx
    >>> spellchecker = enchantx.XDict("/home/ubuntu/GoogleNews-vectors-negative300.bin")
    >>> spellchecker.check("wofl")
    False
    >>> spellchecker.suggest("wofl")
    ['Wolf', 'wolf', 'wool', 'FOFL', 'ROFL']


    >>> example = "quanfiction movie"
    >>> spellchecker.check("movie")
    True
    >>> spellchecker.check("quanfiction")
    False

    >>> spellchecker.suggest("quanfiction")
    ['qualification', 'quantification', 'nonfiction']

    >>> spellchecker.smart_suggest(word="quanfiction", next_word="movie")
    ['nonfiction', 'qualification', 'quantification']
rlutils 0.0.2
rlutils: A utility package for implementing reinforcement learning simulations.
Requires Python: >=3.5

![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)
![pytest](https://github.com/lucaslehnert/rlutils/workflows/pytest/badge.svg)

# rlutils: A utility package for implementing reinforcement learning simulations.

rlutils is a python package containing utility functions to implement reinforcement learning simulations. 
The goal of rlutils is to provide a useful base library to help implement reinforcement learning (RL) research projects.
The `examples` directory contains jupyter notebooks demonstrating how to use rlutils.

rlutils provides an API to implement RL agents, policies, and simulate them in a control task (also called environment or Markov Decision Process (MDP)). rlutils also provides implementations to some basic policies, value iteration, and Q-learning. Other utility functions are also included to collect trajectories, store them, and replay them.
rlutils' goal is to provide a framework and utility functions for implementing RL algorithms.

If you have any questions about rlutils, please send email to `lucas_lehnert@brown.edu`.

## Installation

rlutils is tested on python 3.5, 3.6, 3.7, and 3.8.

This package can be installed using pip:

```
pip install rlutils
```

Alternatively, the repository can also be cloned and the package can be installed without pulling from PyPI:

```
git clone https://github.com/lucaslehnert/rlutils.git
cd rlutils
pip install .
```
uzautoprom 1.4
Simple contracts loader with storage and filtering functionality for official UzAuto dealers.
Requires Python: >=3.6

## What's it?
It is a simple contracts loader with storage and filtering functionality for official UzAuto dealers.
## Basic use case
```python
from uzautoprom import InMemoryDB, RLoader, FullMatchField

import local_settings


db = InMemoryDB(
  RLoader(local_settings.LOGIN, local_settings.PASSWORD).contracts()
)

spark_contracts = db.contracts(
  FullMatchField("Модель", "SPARK")
)
print(spark_contracts)
```

## About
uzautoprom produce 3 abstract classes:
- [Field](https://github.com/IlhomBahoraliev/uzautoprom/blob/master/uzautoprom/abc/field.py) — representation of contract field used for flexible filtering
- [Database](https://github.com/IlhomBahoraliev/uzautoprom/blob/master/uzautoprom/abc/database.py) — storage and filter contracts
- [Loader](https://github.com/IlhomBahoraliev/uzautoprom/blob/master/uzautoprom/abc/loader.py) — contracts loader
### Built-in realizations:
- [RLoader](https://github.com/IlhomBahoraliev/uzautoprom/blob/master/uzautoprom/rloader.py) - based on requests sessions loader
- [FullMatchField](https://github.com/IlhomBahoraliev/uzautoprom/blob/master/uzautoprom/fmfield.py) - field, whose match criteria is full matching
- [StrictlessMatchField](https://github.com/IlhomBahoraliev/uzautoprom/blob/master/uzautoprom/sfield.py) - field, whose match criteria is containing field value
- [InMemoryDB](https://github.com/IlhomBahoraliev/uzautoprom/blob/master/uzautoprom/imdb.py) - simple in memory database
## Install
```bash
pip install uzautoprom
```
scrapec 20.6.5
Scrapec is a program that compiles .sb3 files into .scrape files, which can then be run using Scrape.
Requires Python: >=3.6

# scrapec

This is a compiler designed to accompany [scrape](https://github.com/scraterpreter/scrape).
Usage instructions are listed on the [repository for scrape](https://github.com/scraterpreter/scrape).

It is recommended to install scrapec using the Snap package available on the Snap Store.

## Build Instructions
```bash
git clone https://github.com/scraterpreter/scrapec.git # clones the repository
cd scrapec
pip install . # installs scrapec
```
yliveticker-test 0.3.2
Live market data from Yahoo! Finance websocket
Requires Python: >=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*

# Live from Yahoo Finance

Get market data from Yahoo Finance websocket in near-real time.
wss://streamer.finance.yahoo.com/

## Setup
```bash
pip install yliveticker
```
[pypi package home](https://pypi.org/project/yliveticker/)

## Example
```python
import yliveticker


# this function is called on each ticker update
def on_new_msg(msg):
    print(msg)


yliveticker.YLiveTicker(on_ticker=on_new_msg, ticker_names=[
    "BTC=X", "^GSPC", "^DJI", "^IXIC", "^RUT", "CL=F", "GC=F", "SI=F", "EURUSD=X", "^TNX", "^VIX", "GBPUSD=X", "JPY=X", "BTC-USD", "^CMC200", "^FTSE", "^N225"])
```