semvec/pypi-packages huggingface dataset:
matterwave 0.5.2
A library for matter wave propagation built on top of fftarray.
Requires Python: >=3.11

# Matterwave

[**Intro**](#intro) | [**Installation**](#installation) | [**Documentation**](https://qstheory.github.io/matterwave/main/) | [**FFTArray Preprint (arXiv)**](https://arxiv.org/abs/2508.03697) | [**Change log**](https://qstheory.github.io/matterwave/main/changelog.html)

This library is a collection of routines and constants to help building simulations in the field of matter wave optics built on top of the [FFTArray](https://github.com/QSTheory/fftarray) library.
See also the [documentation](https://qstheory.github.io/matterwave/main/) of matterwave.

## Intro

The main features of matterwave include:
- A second-order split-step implementation for normal and imaginary time propagation.
- Functions for treating `fftarray.Array` instances as quantum mechanical wave functions, for example normalization, scalar product, expectation values and energy computation.
- Some helpful constants, currently only for the D2 line of Rb87.
- Some plotting helpers for the [panel](https://panel.holoviz.org/) library.

## Installation
For most use cases we recommend installing the optional constraint solver of FFTArray for easy Dimension definition with the `dimsolver` option:
```shell
pip install matterwave fftarray[dimsolver]
```
astro-drpy 0.1.11
A data reduction toolkit for astronomical photometry and spectroscopy.
Requires Python: >=3.7.3

# drpy
drpy (pronounced "doctor pi") is a **D**ata **R**eduction toolkit for astronomical **P**hotometry and spectroscop**Y**

## Installation

```
pip install astro-drpy
```

## Note

1. No NaNs or infs should be passed into functions without being masked in advance.
2. `use_uncertainty` and `use_mask` only control the use of uncertainty and mask frames in the calculations. Whether the two frames are returned by a function depends on the custom's input.
3. All calculations should be dimensionless to ensure best performence.
4. Header should not convert to meta directly. Should be ```meta = {'header': header}```
5. Do NOT do validation in internal functions
taskcli-manager 1.0.0
Interactive CLI for TaskCLI - Manage your tasks from the terminal
Requires Python: >=3.8
Keywords: cli, task, todo, productivity, terminal

# TaskCLI Manager

Interactive command-line interface for managing your tasks.

## Installation

```bash
pip install taskcli-manager
```

## Usage

```bash
taskcli
```

This will launch an interactive menu where you can:
- 🔑 Login or Create Account
- 📋 View your tasks
- ➕ Add new tasks
- ✅ Mark tasks as complete
- ✏️ Edit tasks
- 🗑️ Delete tasks
- 🔍 Filter by priority, project, status

## Features

- 🌐 Syncs with TaskCLI web app
- 🎨 Colorful terminal UI
- 📱 Works on Windows, macOS, Linux
- 🔒 Secure authentication

## Web App

Visit https://ojtprojectrepo-production.up.railway.app/ to use the web version.

## License

MIT License
frozen-odict 0.1.0a0
An immutable, hashable, and ordered mapping.
Requires Python: >=2

# `frozen-odict`

An immutable, hashable, and ordered mapping.

`FrozenOdict` behaves similarly to an `OrderedDict` but is immutable and hashable, making it suitable for use as dictionary keys or set members.

## Installation

```bash
pip install frozen-odict
```

## Usage

```python
from frozen_odict import FrozenOdict

# Create from a mapping
fod1 = FrozenOdict({'a': 1, 'b': 2})

# Create from sequence of pairs
fod2 = FrozenOdict([('x', 100), ('y', 200)])

# Create with keyword arguments
fod3 = FrozenOdict({'foo': 42}, bar=43)

# Hashable and set-usable
s = {fod1, fod2}
if fod1 in s:
    print("Found!")

# Works as dictionary keys!
d = {fod1: "first", fod2: "second"}

print(fod1)  # FrozenOdict([('a', 1), ('b', 2)])
```

## Contributing

Contributions are welcome! Please submit pull requests or open issues on the GitHub repository.

## License

This project is licensed under the [MIT License](LICENSE).