semvec/pypi-packages huggingface dataset:
topsis-priyank-raheja-101703404 1.0
Topsis analysis
License: MIT

# Topsis Analysis

## Installation

Use the package manager [pip](https://pip.pypa.io/en/stable/) to install topsis-asharma-3027.

```bash
pip install topsis-asharma-3027
```

## Usage

Following query on terminal will provide you the topsis analysis for input csv file.

```
topsis-asharma-3027 -a "dataset-name" -b "w1,w2,w3,w4,..." -c "i1,i2,i3,i4,..."

```

Do not mention the file format, 'csv', as part of dataset-name.
w1,w2,w3,w4 represent weights, and i1,i2,i3,i4 represent impacts where 1 is used for maximize and 0 for minimize. 
Size of w and i is equal to number of features. 

Note that the first row and first column of dataset is dropped

The item attributed rank 1 is the best choice.

## License
[MIT](https://choosealicense.com/licenses/mit/)
textx-lang-questionnaire 0.2.0
A DSL for describing questionnaires
License: MIT
Keywords: textX; language; DSL

# Questionnaire DSL

A DSL for describing questionnaires with a simple terminal interpreter.

Example:
```
Q[type]: Project type
1[lang]. Language project
2[gen]. Generator project

Q[type=lang, extension]: File extension (e.g. "*.que"):
___ /\*\.[a-z0-9]+/

Q[package]: Package name
___ /[a-z][a-z0-9_]*$/

Q: Author name
___

Q: Author email
___

Q: This question is to
   test multiline feature and indenting.
   1. Working
   2. Not working.
      This is also to test multiline in choices.
```

Each question is of the form `Q:` or `Q[<comma separated terms>]`. If `[]` with
terms is given, each term is either a question ID or a boolean expression of the
form `<lhs>=<rhs>` where `<lhs>` is a reference to previous question ID while
`<rhs>` is a value of the previous question which must be satisfied for this
question to be used. This is handy if the questions that follows depends on the
answer. See `File extension` question above which is asked only for language
projects (thus `type=lang`, the `type` is a reference to the previous question).

The type of the question is either free-form (specified by `___`) or choice if
enumerated options are given.

Both question and option can span multiple lines (like in the last question).

For free-form question an optional regular expression can be given inside `//`
(see `Package name` above). This regex is an input validator.

This package provides an interpreter of the questionnaire
`txquestionnaire.questionnaire_interpreter(model, data=None)` which accepts the
model created by parsing of questionnaire description using this language and
optionally a dictionary of default answers keyed by either question ID if given
or question number. The interpreter will run the questionnaire on the console
and return a dictionary of collected data. The values for options are ordinal
numbers or IDs if given (like in `Project type` above -- `lang`, `gen`).

Please see
[tests](https://github.com/textX/textx-lang-questionnaire/tree/master/tests) for
the detailed usage.
topsis-asharma-3027 1.0
Topsis analysis of a csv file
License: MIT

# Topsis Analysis

## Installation

Use the package manager [pip](https://pip.pypa.io/en/stable/) to install topsis-asharma-3027.

```bash
pip install topsis-asharma-3027
```

## Usage

Following query on terminal will provide you the topsis analysis for input csv file.

```
topsis-asharma-3027 -a "dataset-name" -b "w1,w2,w3,w4,..." -c "i1,i2,i3,i4,..."

```

Do not mention the file format, 'csv', as part of dataset-name.
w1,w2,w3,w4 represent weights, and i1,i2,i3,i4 represent impacts where 1 is used for maximize and 0 for minimize. 
Size of w and i is equal to number of features. 

Note that the first row and first column of dataset is dropped

The item attributed rank 1 is the best choice.

## License
[MIT](https://choosealicense.com/licenses/mit/)
gtasks-api 0.0.8
Based on quickstart sample by Google
License: MIT
Keywords: google,tasks,task,gtasks,gtask

# gtasks_api
[![Build Status](https://travis-ci.com/BlueBlueBlob/gtasks_api.svg?branch=master)](https://travis-ci.com/BlueBlueBlob/gtasks_api)
[![CodeFactor](https://www.codefactor.io/repository/github/blueblueblob/gtasks_api/badge)](https://www.codefactor.io/repository/github/blueblueblob/gtasks_api)
[![PyPI](https://img.shields.io/pypi/v/gtasks-api.svg)](https://pypi.org/project/gtasks-api/)
## Installation

`pip install gtasks-api`

## Usage
Import the package: 
```python
from gtasks_api import GtasksAPI
```

Obtain a Gtasks instance:
```python
gtasks = GtasksAPI('credentials.json', 'token.pickle')
if gtasks.auth_url:
    gtasks.finish_login(auth_code)

```

Get all task lists:
```python
gtasks.service.tasklists().list().execute()
```

API Documentation : https://developers.google.com/resources/api-libraries/documentation/tasks/v1/python/latest/
mm-json 0.0.0
A small collection of tools to help converting to Marshmallow schemas
License: MIT

MM JSON
=======

.. image:: https://travis-ci.com/Peilonrayz/mm_json.svg?branch=master
   :target: https://travis-ci.com/Peilonrayz/mm_json
   :alt: Build Status

About
-----

A small collection of tools to help converting to Marshmallow schemas.

Installation
------------

.. code:: shell

   $ python -m pip install mm_json

Documentation
-------------

Documentation is available `via GitHub <https://peilonrayz.github.io/mm_json/>`_.

Testing
-------

To run all tests run ``nox``. No venv is needed; nox makes all of them for us.

.. code:: shell

   $ python -m pip install --user nox
   $ git clone https://peilonrayz.github.io/mm_json/
   $ cd mm_json
   mm_json $ nox

License
-------

MM JSON is available under the MIT license.