semvec/pypi-packages huggingface dataset:
google-trans-new-chiou 0.1.0
text translation
Keywords: google_translator

## 文字翻譯
### 安裝
```
pip install google_trans_new_chiou
```
### 含入模組
```
from google_trans_new_chiou import google_translator
```
### 使用
```
translator=google_translator()
word=translator.translate("今天天氣真好",lang_src="zh-TW",lang_tgt="ja",pronounce=True)
```
傳回值：
```
['今日は良い天気 ', 'Jīntiān tiānqì zhēn hǎo', 'Kyō wa yoi tenki']
```
odoo-15-rest-api-library 1.0.0.2
Store user access token for one-time-login

# REST API Library

## Name : REST API Library
## Version : 1.0.0.2
## Description : Store user access token for one-time-login
### Package : rest_api_library
### pk link : https://pypi.org/project/REST-API-Library/1.0.0.1/
### g link : https://github.com/HanZawNyein/odoo_rest_api_library.git
### Author_email:"hanzawnyineonline@gmail.com"
rest-api-library 1.0.0.1
Store user access token for one-time-login

# REST API Library

## Name : REST API Library
## Version : 1.0.0.0
## Description : Store user access token for one-time-login
### Package : rest_api_library
### pk link : https://pypi.org/project/REST-API-Library/1.0.0.1/
### g link : https://github.com/HanZawNyein/odoo_rest_api_library.git
### Author_email:"hanzawnyineonline@gmail.com"
pypsmb 0.1.2
psmb server implemented in Python
Requires Python: >=3.8, <4
Keywords: Chattings,PSMB,Minecraft,BungeeCross,CrossLink

# What's this
- psmb: A protocol of **Pub-Sub Message Broker** designed for BungeeCross
- pypsmb: *psmb* server implemented in Python


# Usage
1. Install Python 3.9+
2. Install pypsmb `pip install pypsmb`
3. Enjoy it: `pypsmb`

## Config Path

`pypsmb -c path/to/your/config.yaml`
codestare-async-utils 0.2.0
"Utility modules for async development"
Requires Python: >=3.7
Keywords: async

Utility for async development, documentation at
https://ubii-node-python.readthedocs.io/en/develop/api/codestare/codestare.html

MIT License
Copyright (c) 2021, Maximilian Schmidt

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.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
RivIndel 0.0.2
RivIndel: Complex indel detection from short read sequencing
Keywords: complex indel detection

# RivIndel
IN CONSTRUCTION!

## Motivation
Complex indels (cxIndels) often introduce multiple deletions, insertions and mismatches during the alignment phase.
Complex indels are prone to be found on highly unstable genomes such as Lung Adenocarcinoma (LUAD).
A correct interpretation in terms of net base change is crucial: e.g. exon 19 EGFR inframe deletions are actionable, but not frameshift deletions.

These variants are typically called as multiple individual variants by some popular somatic callers (Mutect2, Lancet, etc).
Since these individual variants are closely located, there is a high chance that they come from a single compound variant.

RivIndel detects complex indels from targeted sequencing (Illumina).
RivIndel scans every targeted region (supplied as a BED file) in a similar fashion than indelSeek.
However, RivIndel validates candidate cxIdels after a successful assembly of candidate reads (plus neighbouring soft-clipped reads).
This, in turn, leads to a better allele frequency estimation.

## Method overview
![Slide](img/rivindel_schema2.png)

## Install RivIndel locally

1. Clone RivIndel repository:
```
git clone https://github.com/bdolmo/RivIndel.git
cd RivIndel/
```

2. Install via pip
```
pip3 install -e .
```

## Usage
```
python3 RivIndel.py --bam <input.bam> --bed <test.bed> --vcf <out.vcf>
```
lp-ignite 0.0.1
Ignite - High-Level utilities library for various tools such as Spark, SnowFlake, MLflow
Requires Python: >=3.7
Keywords: spark,mlflow,boto3,logger,cicd,sagemaker,snowflake

# Ignite - A suite of utilities for commonly used services within AI-Engineering Team
![Coverage Status](https://gitlab.leaseplan.io/data/data-science/ignite/badges/development/coverage.svg?branch=master)
[![Code style Python: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)
![PythonSupport](https://img.shields.io/static/v1?label=python&message=3.6%20|%203.7&color=blue?style=flat-square&logo=python)

Ignite is a high-level utilities library to help your utilize some commonly used modules and components when you start a data science project.
A suite of Python utilities for AWS Lambda functions to ease adopting best practices such as tracing, structured logging, custom metrics, and more. 


### Features
* **[Logging](https://gitlab.leaseplan.io/data/data-science/ignite/-/tree/master/ignite/logging)** - Structured logging made easier, and decorator to enrich structured logging with key Lambda context details
retrieve, and move around buckets with few key strokes. 
* **[MLflow](https://gitlab.leaseplan.io/data/data-science/ignite/-/tree/master/ignite/mlflow)** - Mlfow Logging made easy. 
* **[SnowFlake](https://gitlab.leaseplan.io/data/data-science/ignite/-/tree/master/ignite/snowflake)** - SnowFlake made easy.(SOON) 
* **[PySpark](https://gitlab.leaseplan.io/data/data-science/ignite/-/tree/master/ignite/spark)** - PySpark made easy. (SOON) 
* **[Data Science utilities](https://gitlab.leaseplan.io/data/data-science/ignite/-/tree/master/ignite/ds_utils)** - DS Utils - Frequently Used Methods for Data Science
* **[AWS S3](https://gitlab.leaseplan.io/data/data-science/ignite/-/tree/master/ignite/s3)** - AWS S3 utilities made easier. Copy, 
* **[AWS Lambda](https://gitlab.leaseplan.io/data/data-science/ignite/-/tree/master/ignite/aws)** - AWS Lambda utils (SOON) 
* **[AWS SageMaker](https://gitlab.leaseplan.io/data/data-science/ignite/-/tree/master/ignite/aws)** - AWS SageMaker utils (SOON) 
* **[AWS DynamoDB](https://gitlab.leaseplan.io/data/data-science/ignite/-/tree/master/ignite/aws)** - AWS DynamoDB utils (SOON) 
* **[ETL Common Transformers](https://gitlab.leaseplan.io/data/data-science/ignite/-/tree/master/ignite/etl)** - ETL Transformers utils (SOON) 

### Installation

With [pip](https://pip.pypa.io/en/latest/index.html) installed, run: ``pip install lp-ignite``


## Find a Bug?
Check if there's already an open [issue](https://gitlab.leaseplan.io/data/data-science/ignite/-/issues) on the topic. If needed, file an issue.


# Documentation (SOON)
You can find the docs here
EmotionExtractor 0.0.3
Extract Emotion Words from Text or Word Tokens

# EmotionExtractor
Extract emotion words from sentence or list of tokens.

## Installation
```
pip install EmotionExtractor
```

## Usage
```python
from emotionextractor.emotionextractor import EmotionExtractor

ee = EmotionExtractor()

sentence = "I am happy to see you succeed"
tokens = ["I", "am", "happy", "to", "see", "you", "succeed"]

ee.extract_emotion(sentence)
#or 
ee.extract_emotion(tokens)

#output
# ['happy', 'succeed']
```

`extract_emotion(...)` can take several other optional parameters in addition to input sentence/word tokens:

```
:param bool lemmatize: Set to True to enable lemmatization. default is False
:param bool clean_stopwords: Set to False to disable stop words removal. default is True
:param bool strict_mode: Set to True to enable strict choice of emotion words based on adj and adv. default is True
:param bool remove_pos: Set to True if you'd like to only allow certain Parts of speech (POS). default s false
:param list allowed_pos: List of POS you want to allow from nltk TAGSET: https://github.com/nltk/nltk/blob/develop/nltk/app/chunkparser_app.py
a more readable list from third party: https://www.guru99.com/pos-tagging-chunking-nltk.html When it is not set, and remove_pos is set to True, then by default this POS whitelist is used: ["RB", "RBS", "RBR", "JJ", "JJR", "JJS"]
:param str filter: It can be set to either 'N' or 'P'. default is None.
```


## Troubleshooting
If you recieve error regarding `nltk version not found` try:

```bash
pip install --upgrade nltk
```


## Additional Note
More info will be shared soon about the lexicon used