semvec/pypi-packages huggingface dataset:
qualtrutils 0.1.5
A simple package to interact with the Qualtrics API
Requires Python: >=3.6
Keywords: Qualtrics,API,surveys,survey

# QualtrUtils - A package to create questions from templates with Qualtrics (v3) API

[![PyPI pyversions](https://img.shields.io/pypi/pyversions/qualtrutils.svg)](https://pypi.python.org/pypi/qualtrutils/)
[![GitHub license](https://img.shields.io/github/license/Naereen/StrapDown.js.svg)](https://github.com/emanuele-albini/qualtrutils/blob/master/LICENSE)
[![PyPI](https://badge.fury.io/py/qualtrutils.svg)](https://pypi.python.org/pypi/qualtrutils/)
[![Maintaner](https://img.shields.io/badge/maintainer-Emanuele-lightgrey)](https://www.emanuelealbini.com)
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[![Release](https://github.com/emanuele-albini/qualtrutils/actions/workflows/release.yml/badge.svg)](https://github.com/emanuele-albini/qualtrutils/actions/workflows/release.yml)

This package allows the creation of questions based on an existing template (i.e., a question created with the Qualtrics interface. The operations that this package supports are:

- Creating block
- Copying an existing question
- Replacing keywords
- Changing multiple choice answers
- Changing the initial position of the slider
- Changing a question JS code

## Installation

Using PIP:

```bash
pip install qualtrutils
```

Using CONDA:

```bash
conda install -c emanuele-albini qualtrutils
```

#### For developers

To use the package in editable mode use instead the following.

```bash
git clone https://github.com/emanuele-albini/qualtrutils.git
pip install --editable qualtrutils
```

## Configuration (optional)

Global configuration is in `~\.qualtrutils\qualtrics.toml`. Example:

```toml
API_URL = "https://yourdatacenter.qualtrics.com/API/v3/"
API_TOKEN = "your_token"
LIBRARY_ID = "UR_XXXXXXXXXXXXX"
SURVEY_ID = "SV_XXXXXXXXXXXXX"
```

The configuration saved in `~\.qualtrutils\qualtrics.toml` will be used as default in `QualtricsSurvey` constructor.

This configuration it's optional, the settigs can be directly passed to `QualtricsSurvey` at runtime.

## Usage example

```python
from qualtrutils import QualtricsSurvey

survey = QualtricsSurvey()

# Get a question from an existing survey
question = survey.get_question_by_name('QuestionName', 'MyNewQuestion')

# The following will replace (using regex) all the occurences
# of 'SOMETHING' in the question text and multiples choice answers (if any)
# with 'SOMETHING_ELSE'
question.text_sub('SOMETHING', 'SOMETHING_ELSE')

# The following will set the multiple choice answers
question.set_choices(['First Answer', 'Second Answer', 'Third Answer'])

# The flowwing will set the Javascript code of the question
question.set_js('var hello = 1;')

# Add this new question to the survey in a block called 'Block A'
# If the block does not exists it will be created
survey.create_question(question, 'Block A')
```

## Documentation

See [here](https://emanuele-albini.github.io/qualtrutils) for the complete documentation with all the functionalities.
spartan-viz 0.0.9
A clean visualization package built on matplotlib.
Requires Python: >=3.6


--------------------------------------

spartan: potent visualization
=======================================

[![License](https://img.shields.io/badge/License-BSD%203--Clause-blue.svg)](https://opensource.org/licenses/BSD-3-Clause)


Spartan is a Python visualization library based on matplotlib that provides a style, palettes and plot types that enhance communication. The philosophy is based around Tufte's minimalist ideas as well as storytelling strategies and good use of color. 

All you need to do is import the library and you will get clean, potent plots using the usual matplotlib commands.

<!---
Spartan provides:
* a basic clean, Tufte like style
* user customizations and context styles (e.g., screen, publication, talk, poster)
* palettes designed to tell a range of stories
* sparklines
* range frames
* scatter plots with rugs and KDEs
--->