semvec/pypi-packages huggingface dataset:
t9ek80 1.4.1
Simrad EK80 Echosounder interface module.

# EK80 SN90
Simrad EK15/60/80 and SN90 echosounder python interface module. The t9ek80.py should normally not be modified, 
it contains the generic interface. The biomass and singletargetchirp are example user files. The xml files are 
configuration files. Usage:
    pip install --index-url https://test.pypi.org/simple/ --no-deps t9ek80

 or

    simply copy the t9ek80.py to the same folder as the code you run... Thats all.


 git clone https://github.com/The1only/ek80.git
 cd ./ek80/examples
 python3 biomass.py biomass.xml 

PS: All testing has been done using python3 

The Simrad EK80 user manual can be found at: https://www.simrad.online/ek80/ref_en/default.htm
MicroPyDD-firestore 0.0.4
MicroPyDD wrapper for Google firestore

[![pipeline status](https://gitlab.com/micropydd/micropydd-firestore/badges/master/pipeline.svg)](https://gitlab.com/micropydd/micropydd-firestore/commits/master) [![coverage report](https://gitlab.com/micropydd/micropydd-firestore/badges/master/coverage.svg)](https://gitlab.com/micropydd/micropydd-firestore/commits/master) [![PyPI version](https://badge.fury.io/py/MicroPyDD-firestore.svg)](https://badge.fury.io/py/MicroPyDD-firestore)

# MicroPyDD Firestore

This module is a simple wrapper that simplifies the setup of firestore.
MicroPyDD 0.0.7
MicroPyDD simplyfies managements of microservice boilerplates code

[![pipeline status](https://gitlab.com/pydd/pydd/badges/master/pipeline.svg)](https://gitlab.com/pydd/pydd/commits/master) [![coverage report](https://gitlab.com/pydd/pydd/badges/master/coverage.svg)](https://gitlab.com/pydd/pydd/commits/master) [![PyPI version](https://badge.fury.io/py/MicroPyDD.svg)](https://badge.fury.io/py/MicroPyDD)


# MicroPyDD

MicroPyDD is a simple framework that has the intention of providing a modularized set of preconfigured components that helps you to build microservices in python. PyDD Commons offers basic microservice configuration so you do not need to start everything from scratch. This modules preconfigures:

* Configuration
* Logging
* Module system

## Installing

Install using pip:

```pip install micropydd```

## A Simple Example

```python
from micropydd.module import init

init({}, modules_init_functions=[
    # list additional modules
])
```
MicroPyDD-restplus 0.0.7
MicroPyDD wrapper for Flask-Restplus

[![pipeline status](https://gitlab.com/micropydd/micropydd-restplus/badges/master/pipeline.svg)](https://gitlab.com/micropydd/micropydd-restplus/commits/master) [![coverage report](https://gitlab.com/micropydd/micropydd-restplus/badges/master/coverage.svg)](https://gitlab.com/micropydd/micropydd-restplus/commits/master) [![PyPI version](https://badge.fury.io/py/MicroPyDD-restplus.svg)](https://badge.fury.io/py/MicroPyDD-restplus)

# MicroPyDD Flask-Restplus

This module is a simple wrapper that simplifies the setup of a restplus project. Furthermore adds some helper methods to the prohect:

```
GET /misc/config/
GET /misc/postman/
GET /misc/version/
GET /loggers/{id}/
GET /loggers/
POST /loggers/
```
queryS3 0.0.22
Minimum version of query s3 by label
Requires Python: >=2.0

# queryS3 API
## Introduction
This API enable users to query images from AI Testing database, currently implementing on AWS S3, with natural English description. A string of keywords also works if users want to put more restrictions onto the picture. The main functionality of this API can be treated in a blackbox manner. That it takes is a string of description and returns a list of S3 object URL of the images.

## Dependencies
**[- nltk](https://www.nltk.org/): Natural Language Toolkit** [github link](https://github.com/nltk/nltk)

**[- pandas](https://pandas.pydata.org/pandas-docs/stable/): powerful Python data analysis toolkit** [github link](https://github.com/pandas-dev/pandas)

## Installation
```bash
pip install queryS3
```

## Example usage
```python
from queryS3 import QS3

qs = QS3.QS3()

# this line will retrieve all images that have single husky
# the return type will be a python list
qs.query('single husky')
```

## API details

**QS.query(in_q: str): -> List[str]**: "query" is a function in the class QS. It takes a english description(or a string of keywords needed) as input and returns a list of S3 object URL strings

**QS.set_label_list(self, label_list: List[str])**: This function will replace the original label list in the database with a new list of labels only for this object instance of QS. By doing so, the whole "extract label from description" and "label matching search" process will then based on the new set of labels. Duplicated labels will be removed.

**QS.add_label_list(self, label_list: List[str])**: This function will append the label list with the newly added list. Duplicated labels will be removed.

## Author
**[Qiao Liu](https://github.com/qiaol)**
, **[Everette Li](https://github.com/everetteli)**

## Copyright
Copyright © 2020, The AITestResourceLibrary Authority. Released under the MIT License.