semvec/pypi-packages huggingface dataset:
genome2json 0.1.1
Parse genomes in GenBank/GFF3 formats to JSON
Requires Python: >3.6

# genome2json
Parse genomes in GenBank/GFF3 format to JSON

Implemented in pure Python using builtin libraries.


```
$ g2j -h

usage: Genome2JSON [-h] (-gbk GENBANK | -gff GENERAL) [-fa FASTA] -o OUTPUT
                   [--json_indent JSON_INDENT] [--grouped]

Parse genomes in GenBank/GFF3 format, and convert to JSON

optional arguments:
  -h, --help            show this help message and exit
  -gbk GENBANK, --genbank GENBANK
                        GenBank file
  -gff GENERAL, --general GENERAL
                        GFF3 file
  -fa FASTA, --fasta FASTA
                        FASTA file, required when parsing GFF
  -o OUTPUT, --output OUTPUT
                        Save JSON to file
  --json_indent JSON_INDENT
                        Number of spaces to indent in JSON
  --grouped             Group overlapping sequence features

Cameron Gilchrist 2020
```
tradingalgorithm 0.0.2
A package to trade for you!
Requires Python: >=3.1


# Hello, welcome to tradingalgorithm, a Python package for easy algorithmic trading on Alpaca
## This package allows one to check account status, make long orders, make short orders, run a custom momentum-based algorithm, and automatically calculate the best tickers to trade in the S&P500 based off of probability of returns and betas. 
## **To run this package, you will need an IEX Finance key, as well as an Alpaca API key**

To install the algorithm: 

```
$ pip install tradingalgorithm
```

## To pick a stock ticker:

```
import tradingalgorithm

ticker = tradingalgorithm.tickerpicker()
```
## To create a stock class:

```
import tradingalgorithm

ticker = 'AAPL'

aapl = tradingalgorithm.stock(alpacaKey, alpacaSecretKey, iexKey, ticker)

```
## Methods in the class:

```
aapl.position()
# output: Number of shares:  
#         Market Value: 
#         Profit/Loss: 

aapl.checkhours()
# output: The market is (open or close)
```

### Returns maximum amount of shares that you can trade of the ticker based on market value of cash portfolio

```
aapl.max_shares()
```

### Takes AAPL (or chosen ticker) long at the current market price and specified share amount

```
aapl.longmarket(shares)
```

### Takes AAPL (or chosen ticker) long at the current close of the stock

```
aapl.longlimit(shares)
```

### Takes AAPL (or chosen ticker) short at the current market price

```
aapl.short(shares)
```

### Closes entire short or long position in AAPL (or chosen ticker) based on whether you specify "long" or "short" as the typetoclose

```
aapl.closeposition(typetoclose)
```

### Runs a momentum algorithm ONE TIME based on volume and time&sales, will take a stock short, long, close position, re-position, and employs a custom stop-loss

```
aapl.algo()
```

# Runs the same momentum algorithm CONTINUOUSLY for the set amount of minutes

```
aapl.trade(minutes)

```
TradingAlgorithm 0.0.2
A package to trade for you!
Requires Python: >=3.1

# Hello, welcome to tradingalgorithm, a Python package for easy algorithmic trading on Alpaca
## This package allows one to check account status, make long orders, make short orders, run a custom momentum-based algorithm, and automatically calculate the best tickers to trade in the S&P500 based off of probability of returns and betas. 
## **To run this package, you will need an IEX Finance key, as well as an Alpaca API key**

To install the algorithm: 

```
$ pip install tradingalgorithm
```

## To pick a stock ticker:

```
import tradingalgorithm

ticker = tradingalgorithm.tickerpicker()
```
## To create a stock class:

```
import tradingalgorithm

ticker = 'AAPL'

aapl = tradingalgorithm.stock(alpacaKey, alpacaSecretKey, iexKey, ticker)

```
## Methods in the class:

```
aapl.position()
# output: Number of shares:  
#         Market Value: 
#         Profit/Loss: 

aapl.checkhours()
# output: The market is (open or close)
```

### Returns maximum amount of shares that you can trade of the ticker based on market value of cash portfolio

```
aapl.max_shares()
```

### Takes AAPL (or chosen ticker) long at the current market price and specified share amount

```
aapl.longmarket(shares)
```

### Takes AAPL (or chosen ticker) long at the current close of the stock

```
aapl.longlimit(shares)
```

### Takes AAPL (or chosen ticker) short at the current market price

```
aapl.short(shares)
```

### Closes entire short or long position in AAPL (or chosen ticker) based on whether you specify "long" or "short" as the typetoclose

```
aapl.closeposition(typetoclose)
```

### Runs a momentum algorithm ONE TIME based on volume and time&sales, will take a stock short, long, close position, re-position, and employs a custom stop-loss

```
aapl.algo()
```

# Runs the same momentum algorithm CONTINUOUSLY for the set amount of minutes

```
aapl.trade(minutes)

```
TradingAlgorithm-noahxl10 0.0.2
A package to trade for you!
Requires Python: >=3.1

# Hello, welcome to tradingalgorithm, a Python package for easy algorithmic trading on Alpaca
## This package allows one to check account status, make long orders, make short orders, run a custom momentum-based algorithm, and automatically calculate the best tickers to trade in the S&P500 based off of probability of returns and betas. 
## **To run this package, you will need an IEX Finance key, as well as an Alpaca API key**

To install the algorithm: 

```
$ pip install tradingalgorithm
```

## To pick a stock ticker:

```
import tradingalgorithm

ticker = tradingalgorithm.tickerpicker()
```
## To create a stock class:

```
import tradingalgorithm

ticker = 'AAPL'

aapl = tradingalgorithm.stock(alpacaKey, alpacaSecretKey, iexKey, ticker)

```
## Methods in the class:

```
aapl.position()
# output: Number of shares:  
#         Market Value: 
#         Profit/Loss: 

aapl.checkhours()
# output: The market is (open or close)
```

### Returns maximum amount of shares that you can trade of the ticker based on market value of cash portfolio

```
aapl.max_shares()
```

### Takes AAPL (or chosen ticker) long at the current market price and specified share amount

```
aapl.longmarket(shares)
```

### Takes AAPL (or chosen ticker) long at the current close of the stock

```
aapl.longlimit(shares)
```

### Takes AAPL (or chosen ticker) short at the current market price

```
aapl.short(shares)
```

### Closes entire short or long position in AAPL (or chosen ticker) based on whether you specify "long" or "short" as the typetoclose

```
aapl.closeposition(typetoclose)
```

### Runs a momentum algorithm ONE TIME based on volume and time&sales, will take a stock short, long, close position, re-position, and employs a custom stop-loss

```
aapl.algo()
```

# Runs the same momentum algorithm CONTINUOUSLY for the set amount of minutes

```
aapl.trade(minutes)

```
rake-keyword 0.0.1
Implementation of RAKE - Rapid Automatic Keyword Extraction
Requires Python: >=3.6

# RAKE-Keyword

[![made-with-python](https://img.shields.io/badge/language-python-blue)](https://www.python.org/)
[![Language grade: Python](https://img.shields.io/lgtm/grade/python/g/u-prashant/RAKE.svg?logo=lgtm&logoWidth=18&color=blue)](https://lgtm.com/projects/g/u-prashant/RAKE/context:python)
[![Build Status](https://img.shields.io/travis/u-prashant/RAKE?color=blue)](https://travis-ci.com/u-prashant/RAKE)
[![GitHub license](https://img.shields.io/github/license/u-prashant/RAKE?color=blue)](https://github.com/u-prashant/RAKE/blob/master/LICENSE)
[![Open Source? Yes!](https://badgen.net/badge/Open%20Source%20%3F/Yes%21/blue?icon=github)](https://github.com/Naereen/badges/)


RAKE-Keyword is a Python library that can extract keywords from any document or a piece of text. It is based on RAKE algorithm. Rapid Automatic Keyword Extraction (RAKE) is a keyword extraction method that is extremely efficient and operates on individual documents. It tries to determine the key phrases in a text by calculating the co-occurrences of every word in a key phrase and also its frequency in the entire text. [Link to Research Paper!](https://doi.org/10.1002/9780470689646.ch1)

## Installation
```
pip install rake
```

## Quick Start
```python
from rake import Rake

text = "Black grapes are famous for their use in making alcohol."

rake = Rake()

raje.exec(text)
# Returns keywords with scores in reverse sorted order: [('black grapes', 4.0), ('making alcohol', 4.0), ('famous', 1.0)]
```

## Development Setup
```
1. git clone https://github.com/u-prashant/RAKE.git
2. cd RAKE
3. pip install -r requirements.txt
4. make test-all
```


## Contributing
Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.

Please make sure to update tests as appropriate.

## License

MIT License

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

Copyright (c) 2020 Prashant Upadhyay
autolib-volatile-int 0.0.1
A small example package
Requires Python: >=3.4

# autolib -- stm32 driver library automatic generator

stm32是一款功能强大的单片机，但是由于配置使用复杂，在科创比赛中的应用被大大限制。autolib是一个精简的python脚本，可以根据用户需求自动生成所需的库函数。

# 优点

autolib产生的库函数完全基于寄存器，无论是使用hal库还是标准库的用户都可以轻松的把autolib融入在工程中

autolib是一个精简的python脚本，可以在任何安装有python的电脑上运行，而无关操作系统环境，无需编译。

autolib通过pypi发布，可以通过pip安装，只要有一台连接互联网的电脑就可以很方便的下载，在陌生的环境中也可以很容易的使用。

# 有stm32cubeMX，为什么需要autolib？

stm32CubeMX需要java环境，经常因为jre版本问题出错。

stm32CubeMX操作更加复杂精细，因此不容易上手。例如时钟树的配置这些大学生科创很少用到的功能不会出现在autolib中，操作简单不易出错。

stm32CubeMX需要安装，对硬盘空间和网络带宽都有要求，而autolib可以在任何具有python环境的电脑上运行，安装只需要pip，代码量少。

autolib源码简单完全开源，使用者可以很容易进行修改。
auto-caption 0.0.6
Automatic captioning.
Requires Python: >= 3.6

# Auto-caption.

[![PyPI](https://img.shields.io/pypi/v/auto-caption)](https://pypi.org/project/auto-caption/)
[![PyPI - Downloads](https://img.shields.io/pypi/dm/auto-caption)](https://pypi.org/project/auto-caption/)
[![PyPI - License](https://img.shields.io/pypi/l/auto-caption)](https://github.com/aguang-xyz/auto-caption)
[![Build/release](https://github.com/aguang-xyz/auto-caption/workflows/Build/release/badge.svg)](https://github.com/aguang-xyz/auto-caption/actions)

## Install.

### Install ffmpeg first.


```bash
sudo apt install ffmpeg
```

### Install through pypi.

```bash
pip3 install auto-caption
```

## Usage.

```bash
usage: auto-caption [-h] [--format FORMAT] [--output OUTPUT] video

Automatic captioning for movies.

positional arguments:
  video            The path of input video

optional arguments:
  -h, --help       show this help message and exit
  --format FORMAT  Output format (vtt/srt, default: vtt)
  --output OUTPUT  The path to write subtitle file
```

## Sample.

Click [here](https://aguang-xyz.github.io/auto-caption/samples/) to see sample captions generated by this program.
PyBlox2 1.1.0b1
Handler for the Roblox API
Requires Python: >=3.6

# PyBlox2
[![MIT License](https://img.shields.io/apm/l/atomic-design-ui.svg?)](https://github.com/Kyando2/PyBlox/blob/async/LICENSE.md)
[![Version](https://img.shields.io/pypi/v/PyBlox2.svg)](https://pypi.org/project/PyBlox2/)<br>
High level library for making Roblox bots in Python
### Examples
#### A Basic Example
```python
import PyBlox2

client = PyBlox2.BloxClient()

@client.event
async def ready(ctx):
    await client.fetch("friend_requests")
    player = client.friend_requests[0]
    await player.fetch("friends")
    
    (player.friends[0])

@client.event
async def request(ctx):
    print("Received status code ", ctx[0].status)

client.run(ROBLOSECURITY) # ROBLOSECURITY COOKIE
```
#### Changing someone's role
```python
import PyBlox2

client = PyBlox2.BloxClient()

@client.event
async def ready(ctx):
    group = await client.get_group(5029105)
    member = await group.get_member("fego2015")
    role = await group.get_role("Moderators")
    await member.set_role(role)

@client.event
async def request(ctx):
    
    ("Received status code ", ctx[0].status)

client.run(ROBLOSECURITY) # ROBLOSECURITY COOKIE
```