semvec/pypi-packages huggingface dataset:
volunor 1.0.0rc3
Command line tools, with ease
License: MIT
Requires Python: >=3.7,<4.0

<p align="center">
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<img alt="GitHub Workflow Status" src="https://img.shields.io/github/actions/workflow/status/thmahe/volunor/primary.yaml">
<a href="https://pypi.org/project/volunor/" ><img alt="PyPI" src="https://img.shields.io/pypi/v/volunor"></a>
</p>

# Völunðr <img src="https://i.postimg.cc/m2M34BGS/logo.png" style="float: right;" alt="Logo" width="150" height="150">

### _Build Command Line Tools with ease_

Volunor offer a standard, dependency free & stable way to implement and maintain command line interface tools in Python.

## Example

Below a basic example of a greet command:
```python
# greet.py
import volunor


class Hello(volunor.Command):
    """
    Simple greet command.
    """
    # Arguments with argparse interface
    def volunor_args(self, required_args, optional_args):
        optional_args.add_argument("--count", type=int, default=1, metavar="INT", help="Number of greet")
        required_args.add_argument("name", type=str, help="Name to greet")
    
    # Required method, called by volunor.Cli.big_bang method
    def __call__(self, *args, **kwargs):
        for _ in range(kwargs.get('count')):
            print(f"Hello {kwargs.get('name')}")


cli_descriptor = {
    "greet": Hello,
    "greet-group": {
        "greet": Hello
    }
}

cli = volunor.Cli(cli_descriptor, prog="greet-cli")

if __name__ == '__main__':
    cli.big_bang()
```

Root level helper:
```shell
$ python3 greet.py -h
usage: greet-cli [-h] COMMAND ...

optional arguments:
  -h, --help   show this help message and exit

commands:
  greet .......... Simple greet command.
  greet-group .... subcommand group
```

Command helper:
```
$ python3 greet.py greet -h
usage: greet-cli greet [-h] [--count INT] name

Simple greet command.

optional arguments:
  -h, --help   show this help message and exit

required arguments:
  name         Name to greet

optional arguments:
  --count INT  Number of greet
```

Command output:
```shell
$ python3 greet.py greet Thomas --count 2
Hello Thomas
Hello Thomas
```

## Run tests

### Install dependencies

```shell
sudo apt install "^python3\.(7|8|9|10|11)-venv$"
pip install poetry tox
```
findlinear 0.4.2
To find the linear segment of a curve or dataset.
License: MIT
Requires Python: >=3.8,<3.11
Keywords: linear segment,systems biology,bioinformatics,plate readers

# findlinear: Determining the linear segments of data with Bayesian model comparison

`findlinear` is a Python module for finding the linear segment given a curve or dataset with `x` and `y`. 

## How does it work?
It uses the idea of Bayesian model comparison and calculate the evidence of each possible segment of curve being linear. 
After calculating the evidence of each segment, it detects the global maximum, or uses the `findpeaks` library to find the local maxima of evidence, from which the user can choose the relevant linear segment (e.g. that with the largest evidence, or that with the largest slope when the data consists of multiple linear segments).

## Installation
For users, type in terminal
```
> pip install findlinear
```

For developers, create a virtual environment and then type 
```
> git clone https://git.ecdf.ed.ac.uk/s1856140/findlinear.git
> cd findlinear 
> poetry install --with dev 
```

## Quickstart
Data `x` is a list or a 1D Numpy array, sorted ascendingly; the data `y` is a list or a Numpy array, with each row being one replicate of measurement.
```
>>> from findlinear.findlinear import findlinear, get_example_data
>>> x, y = get_example_data()
>>> fl = findlinear(x, y)
>>> fl.find_all()
>>> fl.plot()
>>> fl.get_argmax()
>>> fl.get_peaks()
```

## Documentation
Detailed documentation is available on [Readthedocs](https://findlinear.readthedocs.io/en/latest/).

## Citation
A preprint is coming soon.
llvm-snapshot-builder 1.2.8
Builds LLVM snapshots on Copr
License: MIT
Requires Python: >=3.9,<4
Keywords: LLVM,Snapshot,Copr,Fedora,Builder

# llvm_snapshot_builder

Builds LLVM snapshots on Copr

## Status

[![Documentation Status](https://readthedocs.org/projects/llvm_snapshot_builder/badge/?version=latest)](https://llvm_snapshot_builder.readthedocs.io/en/latest/?badge=latest)
[![CodeQL](https://github.com/kwk/llvm_snapshot_builder/actions/workflows/codeql.yml/badge.svg)](https://github.com/kwk/llvm_snapshot_builder/actions/workflows/codeql.yml)
[![ci-cd](https://github.com/kwk/llvm_snapshot_builder/actions/workflows/ci-cd.yml/badge.svg)](https://github.com/kwk/llvm_snapshot_builder/actions/workflows/ci-cd.yml)
[![codecov](https://codecov.io/gh/kwk/llvm_snapshot_builder/branch/main/graph/badge.svg?token=ASSPTOL3JU)](https://codecov.io/gh/kwk/llvm_snapshot_builder)
[![release](https://img.shields.io/github/release/kwk/llvm_snapshot_builder.svg)](https://github.com/kwk/llvm_snapshot_builder/releases)

## Installation

```bash
$ pip install llvm_snapshot_builder
```

## Usage

For a more in-depth example, take a look at [the example in the documentation](https://llvm_snapshot_builder.readthedocs.io/en/latest/example.html).

After installing you can explore the CLI program with:

```bash
$ python -m llvm_snapshot_builder.cli --help
```

or with:

```console
$ llvm_sb --help
```

## Contributing

Interested in contributing? Check out the contributing guidelines. Please note that this project is released with a Code of Conduct. By contributing to this project, you agree to abide by its terms.

### Commit message conventions and semantic versioniong (semver)

We use semantic versioning and [these commit message conventions](https://www.conventionalcommits.org/en/v1.0.0/)
can be used to automatically bump the version number and generate the changelog.

## License

`llvm_snapshot_builder` was created by Konrad Kleine <kkleine@redhat.com>. It is licensed under the terms of the MIT license.

## Credits

`llvm_snapshot_builder` was created with [`cookiecutter`](https://cookiecutter.readthedocs.io/en/latest/) and the `py-pkgs-cookiecutter` [template](https://github.com/py-pkgs/py-pkgs-cookiecutter).