semvec/pypi-packages huggingface dataset:
anu-ctlab-io 1.1.0
python I/O for the ANU CTLab array storage format(s)
Requires Python: >=3.12

anu_ctlab_io package
--------------------
python I/O for the ANU CTLab array storage format(s).

Introduction
============

This package loads data provided in the specific NetCDF and Zarr formats produced by the ANU CTLab.
The intention is that the consumers of the data we produce should be able to load that data and then
work with that directly in standard scientific python workflows, rather than needing to use the
pre-existing MANGO toolchain.

The specific netcdf and zarr loading functionality is contained in extras, so you will
generally want to install this package as either ``anu_ctlab_io[netcdf]`` or ``anu_ctlab_io[zarr]``
depending on the format of data you want to read.
The ``all`` extra enables all supported formats.

Examples
========
.. code-block :: python3

    import anu_ctlab_io
    from dask_image import ndfilters

    dataset = anu_ctlab_io.Dataset.from_path(<path-to-your-data>)
    blurred = ndfilters.gaussian_filter(dataset.data, sigma=3)
    print(blurred.mean().compute())
pytest-polymeric-report 0.1.8
A polymeric test report plugin for pytest
Requires Python: >=3.7

# pytest-polymeric-report

A pytest plugin for generating polymeric test reports with beautiful HTML format.

## Features
- Clear test summary with charts
- Detailed test case information
- Support for passed/failed/error/skipped status
- Responsive design for all devices

## Installation
```bash
pip install pytest-polymeric-report
anki-card-cleaner 0.0.1
A utility to clean Anki card text for NLP processing.
Requires Python: >=3.7

# Anki Card Cleaner

A simple Python utility to clean Anki card text, removing cloze deletions, normalizing whitespace, and handling common Anki formatting quirks.

## Installation

```bash
pip install anki-card-cleaner
```

## Usage

```python
from anki_card_cleaner import clean_card_text

text = "The capital of France is {{c1::Paris::City}}."
cleaned = clean_card_text(text)
print(cleaned)
# Output: "the capital of france is paris (city)."
```

## Features

- Removes {{c1::...}} cloze deletions.
- Handles custom Answer::Hint format in clozes.
- Normalizes unicode non-breaking spaces.
- Fixes spacing after question marks.
- Lowercases everything.
fivedreg 0.0.6
A lightweight, configurable neural network for 5D interpolation.
Requires Python: >=3.12

# fivedreg

A lightweight, configurable neural network for 5D interpolation.

## Installation

Install from PyPI:

```bash
pip install fivedreg
```

**Requirements:** Python >= 3.12

## Quick Start

```python
from fivedreg import LightweightNN, DataLoader

# Your code here
```

## Documentation

For detailed documentation, tutorials, and API reference, please visit:

**https://c1-coursework-docs.readthedocs.io/en/latest/**

## License

MIT License