Metadata-Version: 2.1
Name: the-trivia-api-library
Version: 0.0.3
Summary: A Python library for The Trivia API
Home-page: https://github.com/Carlos-Henreis/the-trivia-api
Author: Carlos Henrique Reis
Author-email: cahenre@gmail.com
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: requests

# The Trivia API Python Library

![License](https://img.shields.io/badge/license-MIT-blue.svg)

A Python library for interacting with the Trivia API. This library allows you to easily request multiple-choice trivia questions and access various features of the Trivia API.

## Demo

Access a demo of this library [here](https://demo-the-trivia-api-python.vercel.app).

![example demo](data:image/png;base64,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## Installation

You can install this library using pip:
```bash
pip install the_trivia_api_library
```

## Example usage
Here's an example of how to use this library to interact with the Trivia API:

```Python
from the_trivia_api_library import TriviaAPIClient, EnumCategory, EnumDifficulty

# Initialize the Trivia API client
api_key = "YOUR_API_KEY"
client = TriviaAPIClient(api_key=api_key)

# Get a random set of questions
questions = client.get_random_question(
    limit=5,
    categories=[EnumCategory.SCIENCE.value],
    difficulties=[EnumDifficulty.EASY.value],
    tags=["math", "physics"]
)

for question in questions:
    print(f"Question: {question['question']['text']}")
    print(f"Correct Answer: {question['correctAnswer']}")
    print(f"Incorrect Answers: {', '.join(question['incorrectAnswers'])}")
    print()
```

## Methods

### get_random_question
Get a random set of questions from the Trivia API.

#### Parameters
- `limit` - The number of questions to return. Defaults to 1.
- `categories` - A list of categories to filter the questions by. Defaults to None.
- `difficulties` - A list of difficulties to filter the questions by. Defaults to None.
- `region` - A list of regions to filter the questions by. Defaults to None.
- `tags` - A list of tags to filter the questions by. Defaults to None.
- `types` - A list of types to filter the questions by. Defaults to None.
- `session` - A session object to use for the request. Defaults to None.
- `preview` - A boolean indicating whether to return the questions in preview mode. Defaults to False.

#### Returns
A list of questions.

#### Example
```Python
from the_trivia_api_library import TriviaAPIClient, EnumCategory, EnumDifficulty

# Initialize the Trivia API client
api_key = "YOUR_API_KEY"
client = TriviaAPIClient(api_key=api_key)

# Get a random set of questions
questions = client.get_random_question(
    limit=5,
    categories=[EnumCategory.SCIENCE.value],
    difficulties=[EnumDifficulty.EASY.value],
    tags=["math", "physics"]
)

for question in questions:
    print(f"Question: {question['question']['text']}")
    print(f"Correct Answer: {question['correctAnswer']}")
    print(f"Incorrect Answers: {', '.join(question['incorrectAnswers'])}")
    print()
```

### get_categories
Get a list of categories from the Trivia API.

#### Parameters
- None

#### Returns
A list of categories.

#### Example
```Python
from the_trivia_api_library import TriviaAPIClient

api_key = "YOUR_API_KEY"
client = TriviaAPIClient(api_key=api_key)

tags = client.get_all_tags()

for tag in tags:
    print(tag)
```


### get_totals_per_tag
Get the total number of questions per tag from the Trivia API.

#### Parameters
- `categories` - A list of categories to filter the questions by. Defaults to None.
- `difficulties` - A list of difficulties to filter the questions by. Defaults to None.
- `region` - A list of regions to filter the questions by. Defaults to None.
- `tags` - A list of tags to filter the questions by. Defaults to None.
- `types` - A list of types to filter the questions by. Defaults to None.

#### Returns
A list of totals per tag.

#### Example
```Python
from the_trivia_api_library import TriviaAPIClient

api_key = "YOUR_API_KEY"
client = TriviaAPIClient(api_key=api_key)

tags = client.get_totals_per_tag()

for tag in tags:
    print(f"tag: {tag} -> total: {tags[tag]}")

```

# Initialize the Trivia API client


## Contributing

Contributions are welcome! If you have suggestions, bug reports, or want to contribute to the library, please follow the guidelines in the [CONTRIBUTING.md](CONTRIBUTING.md) file.

## License

This library is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.
