semvec/pypi-packages huggingface dataset:
cd-logging 0.0.5
A simple logging utility for Python applications
License: MIT
Requires Python: >=3.6

# LoggerUtility

`LoggerUtility` is a Python class that simplifies logging setup across your Python applications. It provides a streamlined way to configure loggers with custom formats, different logging levels, and optional file output. Whether you're debugging during development or monitoring in production, `LoggerUtility` can help you keep clear and concise logs.

## Features

- Easy logger configuration with just a few lines of code.
- Customizable log message format.
- Optional date formatting in log messages.
- Support for logging to console or files.
- Convenience methods for various logging levels (`debug`, `info`, `warning`, `error`, `critical`).

## Installation

You can simply copy the `LoggerUtility` class into your project, or if you have it packaged, you can install it via `pip` (assuming you have it available on PyPI):

```bash
pip install cd-logging
```
## Update

```bash
pip install -U cd-logging
```

## Usage

Here is a quick example of how to use `LoggerUtility`:

```python
from cd_logging.cd_logging import LoggerUtility

# Initialize the logger
logger_util = LoggerUtility(__name__, level=logging.INFO)

# Log some messages
logger_util.info("Application is starting...")
logger_util.warning("An optional warning message.")
logger_util.error("An error occurred.")

# Log a critical message with exception traceback
try:
    raise ValueError("An example exception.")
except Exception:
    logger_util.critical("A critical error occurred.", exc_info=True)
```

## Configuration

When initializing the `LoggerUtility`, you can customize the following:

- `name`: The logger's name, typically set to `__name__` to reflect the module's name.
- `level`: The threshold for the logging messages (e.g., `logging.DEBUG`, `logging.INFO`).
- `log_format`: Custom format for the log messages.
- `date_format`: Custom date format for the log messages.
- `filename`: If set, logs will be directed to the specified file.

## Documentation

For more details on how to use and configure `LoggerUtility`, please refer to the inline documentation within the class itself. Each method and initializer parameter is thoroughly documented with docstrings.

More documentation at:
[Code Docta](https://codedocta.com "Code Docta")

## Contributing

We welcome contributions from the community! If you'd like to contribute, feel free to fork the repository, make your changes, and submit a pull request.

## License

`LoggerUtility` is licensed under the MIT License. See the LICENSE file for more details.

## Contact

If you have any questions or feedback, please open an issue in the GitHub repository, and we will get back to you as soon as possible.
```
qtregpy 0.1.2
A Python package to implement the Quantile Transformation Regression.
License: MIT
Requires Python: >=3.11
Keywords: DISTRIBUTION,DENSITY,ECONOMETRICS,ESTIMATION

# qtregpy

This package provides the software tools to implement Quantile Transformation Regression introduced in
[Spady and Stouli (2020)](https://arxiv.org/pdf/2011.06416.pdf).

With the tools in this package it is possible to obtain inference and estimation results for conditional distribution,
quantile and density functions implied by flexible Gaussian representations.

For further details, please refer to the original text.

## Installation

You can install gtregpy with pip directly from PyPI.

`pip install qtregpy`

## Usage

Here's a simple example of how to use gtregpy:

```python
import qtregpy as qtr

mel_data_path = 'filepath/melbeourne.csv'

x, y = qtr.load_mel_data(mel_data_path)
mel_answer = qtr.compute_basic(x, y)
```

## Documentation

You can find more detailed documentation for each function in docstrings.

## Testing

To run the tests, use the following command:

```python
pytest tests/
```

## Contributing

We welcome contributions! Please see the [Contribution Guide](CONTRIBUTING.md) file for details on how to contribute.

## License

This package is licensed under the MIT license. See the LICENSE file for details.
RoverRetriever 0.1.5
RoverRetriever is a lightweight Python wrapper written to facilitate interaction with the Dog CEO API.
License: MIT

# RoverRetriever: A Python Wrapper for the Dog CEO API

RoverRetriever is a lightweight Python wrapper written to facilitate interaction with [Dog CEO's API](https://dog.ceo/dog-api/).

## Usage

### Initialize the client

```python
from RoverRetriever.rover_retriever import RoverRetriever
dog_api = RoverRetriever()
```

### Get a list of breeds

```python
breeds = dog_api.get_breeds()
```

### Get a random dog image

```python
random_image = dog_api.get_random_image()
```

### Get a number of random dog images by breed

```python
random_image = dog_api.get_random_image(quantity=3, breed='hound')
```

### Get available images by breed

```python
images = dog_api.get_images_by_breed('bulldog')
```

### Get all sub-breeds

```python
sub_breeds = dog_api.get_all_sub_breeds('bulldog')
```