semvec/pypi-packages huggingface dataset:
aiida-skeaf 0.1.0
AiiDA plugin for the Supercell K-space Extremal Area Finder (SKEAF) code
Requires Python: >=3.7
Keywords: aiida, plugin

[![Build Status][ci-badge]][ci-link]
[![Coverage Status][cov-badge]][cov-link]
[![Docs status][docs-badge]][docs-link]
[![PyPI version][pypi-badge]][pypi-link]

# aiida-skeaf

AiiDA plugin for the Supercell K-space Extremal Area Finder (SKEAF) code.

## Installation

```shell
pip install aiida-skeaf
verdi quicksetup  # better to set up a new profile
verdi plugin list aiida.calculations  # should now show your calclulation plugins
```


## Usage

Here goes a [complete example](examples/example_01.py) of how to submit a test calculation using this plugin.

A quick demo of how to submit a calculation:
```shell
verdi daemon start     # make sure the daemon is running
cd examples
./example_01.py        # run test calculation
verdi process list -a  # check record of calculation
```

An exemplary `verdi node show`:
```
Property     Value
-----------  ------------------------------------
type         SkeafCalculation
state        Finished [0]
pk           137264
uuid         92d3ff92-9ab4-4828-9794-4172d7dcad50
label
description
ctime        2022-03-01 19:12:16.157988+00:00
mtime        2022-03-01 19:13:28.369793+00:00
computer     [2] localhost

Inputs          PK  Type
----------  ------  ----------
bxsf        137262  RemoteData
code        137230  Code
parameters  137263  Dict

Outputs                PK  Type
-----------------  ------  ----------
frequency          137268  ArrayData
output_parameters  137267  Dict
remote_folder      137265  RemoteData
retrieved          137266  FolderData
```

A frequency vs angle plot can be found in [examples/results/example_01.png](examples/results/example_01.png)

## Development

```shell
git clone https://github.com/aiidaplugins/aiida-skeaf .
cd aiida-skeaf
pip install flit
flit install -s .[pre-commit,testing]  # install extra dependencies
pre-commit install  # install pre-commit hooks
pytest -v  # discover and run all tests
```

See the [developer guide](http://aiida-skeaf.readthedocs.io/en/latest/developer_guide/index.html) for more information.

## License

MIT

[ci-badge]: https://github.com/qiaojunfeng/aiida-skeaf/workflows/ci/badge.svg?branch=master
[ci-link]: https://github.com/qiaojunfeng/aiida-skeaf/actions
[cov-badge]: https://coveralls.io/repos/github/qiaojunfeng/aiida-skeaf/badge.svg?branch=master
[cov-link]: https://coveralls.io/github/qiaojunfeng/aiida-skeaf?branch=master
[docs-badge]: https://readthedocs.org/projects/aiida-skeaf/badge
[docs-link]: http://aiida-skeaf.readthedocs.io/
[pypi-badge]: https://badge.fury.io/py/aiida-skeaf.svg
[pypi-link]: https://badge.fury.io/py/aiida-skeaf
tensorflowtools 2.0.4
A small package with various tensorflow uitlities independent of Tensorflow Addons
Requires Python: >=3.9

# TensorFlowTools 2.0.4

### TensorFlowTools Latest

    pip install --upgrade tensorflowtools

### TensorFlowTools Nightly

    pip install --upgrade -i https://test.pypi.org/simple/tensorflowtools

This is a small package with various utilites to do with tensorflow.

> [!IMPORTANT]  
> This package does NOT declare tensorflow as a dependency because of tensorflow-cpu, tensorflow-intel etc.

**Disclaimer**: This package is not affiliated with or endorsed by TensorFlow, Google, or Huggingface. It is an independent open-source project built to integrate TensorFlow with various tools.

## License

Copyright 2025 Rihaan Meher

Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at

    http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.

## Documentation

Docs are avalible in the docs/ folder. It will be edited as needed
rkguinew 0.1.2
Tkinter-like GUI library using PyQt5 with full widget set
Requires Python: >=3.7

# rkguinew

Minimal Tkinter-like GUI library using PyQt5.

This library provides a Tkinter-style API with PyQt5 backend, including most common widgets from Tkinter and ttk.

---

## Installation

```bash
pip install rkguinew
pykostal 0.1.0
package to communicate with Kostal Piko inverters
Requires Python: >=3.9

# pykostal - a python based kostal bridge

[![PyPI version](https://badge.fury.io/py/pykostal.svg)](https://pypi.org/project/pykostal/)
[![PyPI - Status](https://img.shields.io/pypi/status/pykostal.svg)](https://pypi.org/project/pykostal/)
[![Tests](https://github.com/DAMEK86/pykostal/actions/workflows/test.yml/badge.svg)](https://github.com/DAMEK86/pykostal/actions/workflows/test.yml)

**Python 3.9+ compatible** - Tested on Python 3.9, 3.10, 3.11, 3.12, and 3.13.

Python module for [Kostal](https://www.kostal-solar-electric.com/) piko inverters supporting:

- current-values
  - analog-inputs
  - battery
  - grid
  - home
  - pv-generator
  - s0-in
- home
- info.versions
- statistics
  - day
  - log-data
  - total

not supported:

- all settings
- events

ongoing:

- response code mapping (e.g. status code)

## Installation

Run the following to install:

```python
pip install pykostal
```

## Usage

```python
import kostal

# create instance
inverter = kostal.Piko(aiohttp.ClientSession(), url)
```

## Developing pykostal

### Prerequisites
- Python 3.9 or higher (tested up to Python 3.13)

### Initial setup
Run the following in your virtual environment:

```bash
python -m build
```

### Development installation
Every time you update the project, run the following in your virtual environment:

```bash
pip install -e .
```

To install pykostal along with the tools you need to develop and run tests, run the following in your virtual environment:

```bash
pip install -e '.[dev]'
```

### Running tests
```bash
pytest
```

### Testing across Python versions
```bash
tox
```

## Publishing

### Modern approach (recommended)
```bash
python -m build
twine upload dist/*
```

### Legacy approach
```bash
python setup.py bdist_wheel sdist
twine upload dist/*
```
vlgi-datasets 0.4.2
A package with custom kedro datasets for VLGI
Requires Python: >=3.6

# vlgi-datasets

## Overview

Repositiory with custom kedro datasets

## How to use

In code:
```python
from kedro.io import DataCatalog
from vlgi_datasets import PostgresTableUpsertDataSet

io = DataCatalog(
    {
        "asset": PostgresTableUpsertDataSet(
            table_name="assets",
            credentials={"con": "myconnectionstring"},
            save_args={"if_exists": "append", "constraint": "assets_pkey"},
            overwrite_columns=False, 
        ),
    }
)
```

In catalog.yml:
```yaml
asset:
  type: vlgi_datasets.PostgresTableUpsertDataSet
  table_name: assets
  credentials:
    con: myconnectionstring
  save_args:
    if_exists: append
    constraint: assets_pkey
    overwrite_columns: False
```

#### Observation
- The `overwrite_columns` parameter is optional and defaults to `True`.