semvec/pypi-packages huggingface dataset:
articolare 0.1.0
Python client for the Articolare API
Requires Python: >=3.6

# Articolare Python Client

Articolare is a Python client for the Articolare API. It is designed to facilitate interactions with the API, providing a simple and intuitive interface for creating and managing requests.

# Installation
To install the Articolare Python client, you can use pip:
* Copy code 
```
  pip install articolare
```

# Usage
First, you need to initialize the ArticolareClient with your API key:
```
from articolare import create
```
```
  client = create.ArticolareClient(api_key="your-api-key"))
```

# Create
You can then use the create method to make a request to the API:
* languages available:
  * English
  * Portuguese
  * Spanish
  * Italian
* Tokens:
  * Max Tokens = 1000 - If you require more tokens, please refer to our documentation on https://www.articolare.com/
```
response = client.create(
    model="art-translator",
    lang="english",
    style="conversation",
    dialect="european"
    prompt="Enter your prompt here",
    max_tokens=1000
)
```

* The create method returns a dictionary containing the response data from the API.

# Testing
This library includes a basic test suite, which you can run using pytest:
* pytest
```
pytest
```

# License
The Articolare library is owned and managed by Articolare ltd.
coursera-scraper 0.1.3
This Python script utilizes Selenium to scrape data from Coursera, providing detailed information about various courses such as link, title, rating, recent views, students enrolled, time requirement, skills, learner count, difficulty level, duration, and sub-course details.
Requires Python: >=3.6

# Coursera Scraper

This repository contains a Python script that utilizes Selenium to scrape data from Coursera. 

## Scraped Fields

The script scrapes the following fields for each course:
1. Link: Link of the course
2. Title: The title of the course.
2. Institute: The institution offering the course (if available).
3. Rating: The course rating.
4. Recent Views: The number of recent views for the course.
5. Students Enrolled: The number of students enrolled in the course.
6. Time Requirement: The approximate time required to complete the course.
7. Skills: A list of skills covered in the course.
8. Learner Count: The total number of learners who have taken the course.
9. Difficulty Level: The difficulty level of the course.
10. Duration: The duration of the course.
11. Sub-course: Additional information about the course or its sub-courses.

The scraped data is stored in a dictionary format for each course.

## Prerequisites
You can install the required Python packages by running the following command:
```bash
pip install coursera-scraper

from scraper.main import scraper

for course_detail in scraper(keyword='python'):
    # do some processing on course detail
```


## Contributing

Pull requests are welcome. For major changes, please open an issue first
to discuss what you would like to change.

Please make sure to update tests as appropriate.

## License

[MIT](https://choosealicense.com/licenses/mit/)
piplet 0.2.0
for doing what pip can't yet do
Requires Python: >=3.9

# piplet

[![PyPI - Version](https://img.shields.io/pypi/v/piplet.svg)](https://pypi.org/project/piplet)
[![PyPI - Python Version](https://img.shields.io/pypi/pyversions/piplet.svg)](https://pypi.org/project/piplet)

-----

**Table of Contents**

- [Installation](#installation)
- [License](#license)

## Installation

```console
pip install piplet
```

## License

`piplet` is distributed under the terms of the [MIT](https://spdx.org/licenses/MIT.html) license.