semvec/pypi-packages huggingface dataset:
pyfooda 0.1.8
A Python API for accessing USDA FoodData Central data
Requires Python: >=3.8

# FoodData Central Python API

This package provides a simple, ready-to-use Python API for accessing and querying relevant data from the [USDA FoodData Central](https://fdc.nal.usda.gov/) database—**no API key required**. All data is processed locally from CSV files and exposed through a clean Python interface.

## Installation

You can install the package from PyPI:

```bash
pip install pyfooda
```

Or install directly from the repository:

```bash
pip install git+https://github.com/yourusername/pyfooda.git
```

## Features

- **No API key required**: Works entirely offline with preprocessed FoodData Central CSV files.
- **Simple**: Query food categories, nutrients, and portion information with a few lines of code.
- **Search**: Find foods by partial name.
- **DataFrames**: Access the raw fooddata and DRV DataFrames for custom analysis.

## Example

```python
import pyfooda as pf

# Find up to 10 foods matching a partial name
print(pf.find_closest_matches('apple'))

# Get the category of a food
print(pf.get_category('Apple, raw'))

# Get all nutrient values for a food
nutrients = pf.get_nutrients('Apple, raw')
print(nutrients)

# Get portion information
print(pf.get_portion_gram_weight('Apple, raw'))  # e.g., 138.0
print(pf.get_portion_unit_name('Apple, raw'))    # e.g., "medium"

# Get the raw DataFrames
fooddata_df = pf.get_fooddata_df()
drv_df = pf.get_drv_df()
```

## API Reference

### `get_category(foodName)`
Returns the food category for the given food name (case-insensitive). Returns `'Other'` if not found.

### `get_nutrients(foodName)`
Returns a dictionary of nutrient values for the given food name. Returns `None` if not found.

### `get_portion_gram_weight(foodName)`
Returns the portion gram weight (float) for the given food name. Returns `None` if not found.

### `get_portion_unit_name(foodName)`
Returns the portion unit name (string) for the given food name. Returns `None` if not found.

### `find_closest_matches(partialName)`
Returns a list of up to 10 food names that contain the given partial name (case-insensitive).

### `get_fooddata_df()`
Returns the fooddata DataFrame containing all food items and their nutrient values.

### `get_drv_df()`
Returns the DRV (Dietary Reference Values) DataFrame containing nutrient reference values.

## License

## Test package

```
pip install -e .
python -c "import pyfooda; print(pyfooda.__version__)"
```

MIT License
paralellize 1.0.0
Wrappers for multiprocessing's Pool and ThreadPool classes.
Requires Python: >=3.8
Keywords: parallel

# Parallelize: A Basic Wrapper for Multiprocessing
***

``parallelize`` is designed to provide a user friendly wrapper for Python's multiprocessing library, including support for progress bars from [tqdm](https://github.com/tqdm/tqdm).

```python
    # Wrapper for multiprocessing.pool.ThreadPool
    from parallelize import multiThread
    output = multiThread(function, parameters)
```


```python
    # Wrapper for multiprocessing.Pool
    from parallelize import parallelProcess
    output = multiProcess(function, parameters)
```

Both core functions can be run with a built in progress bars by instead using `multiThreadTQDM` or `parallelProcessTQDM` respectively.

# Installation
------------
A recent version of Python 3 (3.8 or above) is required. You can probably run it or easily adapt it for older versions of Python, but I don't support any end-of-life Python versions. Beyond that, the only dependency is the `tqdm` library.

## Latest stable version on PyPi
`pip install parallelize`

## Latest stable version on GitHub
`pip install git+https://github.com/jBeale23/parallelize.git@stable`
nsfw-image-detector 0.1.2
A powerful NSFW content detection library using EVA-based vision transformer
Requires Python: >=3.8
Keywords: nsfw, image-detection, content-filtering, vision-transformer, ai, machine-learning

# NSFW Image Detector

A Python library that provides easy-to-use interfaces for NSFW (Not Safe For Work) image detection using an EVA-based vision transformer model published on Hugging Face: See the model details in [Model card](https://huggingface.co/Freepik/nsfw_image_detector).

## Installation

You can install this library via pip. The package is available in [PyPI](https://pypi.org/project/nsfw-image-detector/)

```bash
pip install nsfw_image_detector
```

## Quick Usage

```python
from PIL import Image
from nsfw_image_detector import NSFWDetector

# Initialize the detector
detector = NSFWDetector()

# Load and classify an image
image = Image.open("path/to/your/image.jpg")

# Check if the image contains NSFW content
is_nsfw = detector.is_nsfw(image)
print(f"Is NSFW: {is_nsfw}")

# Get probability scores for all categories
probabilities = detector.predict_proba(image)
print(probabilities)
```

## License

Apache License 2.0