semvec/pypi-packages huggingface dataset:
pysuperfab 0.5.16
Python wrapper for SphericalFourierBesselDecompositions.jl

# SuperFaB

[![Stable](https://img.shields.io/badge/docs-stable-blue.svg)](https://hsgg.github.io/SphericalFourierBesselDecompositions.jl/stable)
[![Dev](https://img.shields.io/badge/docs-dev-blue.svg)](https://hsgg.github.io/SphericalFourierBesselDecompositions.jl/dev)
[![Build Status](https://github.com/hsgg/SphericalFourierBesselDecompositions.jl/workflows/CI/badge.svg)](https://github.com/hsgg/SphericalFourierBesselDecompositions.jl/actions)

*SuperFaB* is a code for cosmological spherical Fourier-Bessel (SFB) analysis.
The details of the code are presented in [2102.10079](https://arxiv.org/abs/2102.10079).

The name of this package is **SphericalFourierBesselDecompositions.jl**.

For installation instructions and a tutorial, see the
[Documentation](https://hsgg.github.io/SphericalFourierBesselDecompositions.jl/dev).


## pySuperFaB Python wrapper

This is a simple Python wrapper for [`SphericalFourierBesselDecompositions.jl`](https://github.com/hsgg/SphericalFourierBesselDecompositions.jl).


### Installation

```
pip install pysuperfab
```

The only dependency (from a Python perspective) is `juliacall`, which is
available in conda as `pyjuliacall`.


### Usage

You can use this as any other Python package. Under the hood it uses
[JuliaCall](https://juliapy.github.io/PythonCall.jl/stable/juliacall/), which
on first import will automatically download Julia if you don't already have it.
It will also then download the `SphericalFourierBesselDecompositions.jl` Julia
package.

Use pySuperFaB like so:
```
from pysuperfab import SFB

kmin = 0.05
rmin = 0.0
rmax = 2300.0
amodes = SFB.AnlmModes(kmin, rmin, rmax)
```
That should start looking *really* familiar from the
`SphericalFourierBesselDecompositions.jl` documentation.


## How to make a release

To avoid the awkwardness that the python CI cannot pass until the Julia package
is registered, I recommend to do this in two steps: First do the Julia release,
then the Python release.

1. Update version:

   a. Edit version field in `Project.toml`.

   b. Edit version field in `pysuperfab/juliapkg.json`.

   c. Edit version field in `pyproject.toml`.

   d. Commit version updates. There is an awkwardness here: CI cannot pass for
      the python package until the Julia package has been registered.

2. Julia release: comment with `@JuliaRegistrator register()` on that commit.
   This will publicize the package in the Julia General registry.

3. Build and upload Python package:

   a. `python -m build`

   b. `python -m twine upload dist/*`
PyQtPath 0.3.3
Retrieve nested PyQt widgets by path
Requires Python: >=3.9

# PyQtPath

Retrieve PyQt widgets by path.

[PyPi page](https://pypi.org/project/PyQtPath)

## Build

Increment version:
1. Major: `bump-my-version bump major -v`
2. Minor: `bump-my-version bump minor -v`
3. Patch: `bump-my-version bump patch -v`

Build and upload to PiPy: `./upload_to_pipy.sh`

Install locally: `python -m pip install --no-deps --no-cache-dir -U PyQtPath`
kscale-imu 0.5.0
Python interface for interacting with IMUs
Requires Python: >=3.11

# imu

Defines a package to interact with IMUs.

## Getting Started

See the documentation [here](https://docs.kscale.dev/robot/imu) for instructions on getting started with this package.

## Currently Supported IMUs

- [BNO055](./imu/bno055/README.md)
- [Hexmove](./imu/hexmove/README.md)
- [Hiwonder](./imu/hiwonder/README.md)