semvec/pypi-packages huggingface dataset:
dltkai 1.1.2
Python Client for DLTK.

# DLTK open-source SDK (Python)
[![Python 3.5](https://img.shields.io/badge/python-3.5-blue.svg)](https://www.python.org/downloads/release/python-350/)


[![](https://github.com/dltk-ai/dltkai-sdk/blob/master/python/dltk.png)](https://dltk.ai/)

DLTK renders a comprehensive spectrum of solutions that can be accessed by users on-demand from our pool of transformational technologies.

### Installation

DLTK SDK requires Python 3.5 + .

1. Fork the repo on GitHub
2. Download the project code files with:

   ```git clone https://github.com/dltk-ai/dltkai-sdk.git```

3. Go to the project directory

   ```cd dltkai-sdk/python```
   
4. Install all the required packages:

   ```pip install .```

### Usage
```sh
import dltkai as dl
response = dl.NaturalLanguage.sentiment_detect('I am feeling good.')
print(response)
```

or you can also checkout some samples by running test.py:
```python test.py```

For more details, visit https://dltk.ai/


## License

The content of this project itself is licensed under [GNU LGPL, Version 3 (LGPL-3)](https://github.com/dltk-ai/dltkai-sdk/blob/master/python/LICENSE)
editmenu 0.0.3
A simple multiline edit menu for CLI
Requires Python: >=3.6

Install the package using pip
`pip install editmenu`

Import **editmenu** module from **editmenu** package
 `>>>from editmenu import editmenu`
 
 Use **EditMenu** class to create an instance with a dictionary containing required values to be displayed and edited.
 `>>>mymenu = editmenu.EditMenu({"Name:"Monty","LastName":"Python"})`

Use **menu()** member function to display the menu and prompt the user to make required editing.
 `>>>mymenu.menu()`

**Notes**

 1. Grey color is used as the font color for the values and updated values will be of white. This is for distinguishing changes.
 2. As of now editmenu package is only tested on ubuntu terminal. If you face any issue on windows platform, please mention the issue on github page this package.
 3. EditMenu class, accepts only dictionary containing key:value pairs, where both key and value must be of string type.
 4. menu() function returns a dictionary with updated values.
aml-pipeline 0.0.1
Azure Machine Learning Pipeline high level API
Requires Python: >=3.6

# Azure-ML-Pipeline

Azure Machine Learning Pipeline high level API


This project defines a set of high level APIs to define and publish Machine Learning Pipeline from [Azure Machine Learning Service](https://docs.microsoft.com/en-us/azure/machine-learning/).

Azure Machine Learning Service supports 2 types of pipelines:
- Http triggered pipeline: expose a constant REST endpoint to be triggered by authenticated Http request
- Schedule based pipeline: pipeline is triggered by a predefined time interval.


## Use the libary
1. for Http triggered pipeline: inherent [HttpTriggeredPipeline](https://github.com/zmyzheng/Azure-ML-Pipeline/blob/main/zmyzheng/amlpipeline/HttpTriggeredPipeline.py) class and override two methods:registerDataStores() and definePipelineSteps() . Example: [HttpSklearnAzureFunctionPipeline.py](https://github.com/zmyzheng/Azure-ML-Pipeline/blob/main/examples/http_trigger_scikit_learn_train_azure_function_image_acr_model_hosting/HttpSklearnAzureFunctionPipeline.py)
2. for schedule based pipeline: (developing)



# Contribute to this repo
## Build locally

### Use conda (recommended)
<code>
conda create -p .env python=3.7

conda activate ./.env

.env/bin/pip install -r src/requirements.txt
</code>



### Use pip
<code>
python3.6 -m venv .env

source .env/bin/activate

.env/bin/pip install -r src/requirements.txt
</code>
namedsequence 1.1.0
A package with a namedsequence function
Requires Python: >=3.9

# Overview:
Namedsequence is a function that returns a sequence object. There is one mandatory argument, and three optional ones. The mandatory one is the name of the sequence. The optional ones are: mutable, eager, and doc, with mutable and eager default set to False. By default doc is None. If mutable is set to True, the + and += operators will be supported, otherwise the __hash__ method will. If eager is set to True, there will be an eager iterator provided, otherwise it'll be iterated with a generator. Whatever doc is set to will show up when you type help(x) if x is the namedsequence into the >>> command prompt. Type dir(x) if x is the namedsequence into the >>> command prompt, to see all methods.

# Patch Notes:
1.1.0: remove, pop, and append methods added. Doc added to the namedsequence arguments.