semvec/pypi-packages huggingface dataset:
pretix-postfinance 1.2.0
PostFinance Checkout payment plugin for pretix
Requires Python: <3.13,>=3.9
Keywords: pretix, payment, postfinance, checkout

# pretix-postfinance

PostFinance Checkout payment plugin for pretix.

## Installation

### PyPI

```bash
pip install pretix-postfinance
```

### NixOS

For NixOS users, the plugin can be installed using the flake:

```nix
{ inputs, pkgs, ... }:
{
  services.pretix = {
    enable = true;
    plugins = [
      inputs.pretix-postfinance.packages.${pkgs.stdenv.hostPlatform.system}.default
    ];
  };
}
```

## Development

### Setup with uv

```bash
# Create virtual environment
uv venv

# Install with development dependencies
uv pip install -e ".[dev]"
```

### Setup with Nix

```bash
# Enter development shell
nix develop

# Or use direnv (if you have a .envrc configured)
direnv allow
```

### Running checks

```bash
# Run linting
uv run ruff check .

# Run type checking
uv run mypy pretix_postfinance/

# Run tests with coverage
uv run pytest tests/ --cov=pretix_postfinance --cov-report=term-missing -v
```

### Configuration

Configure the plugin in your pretix settings with:

- **Space ID**: Your PostFinance Checkout space ID
- **User ID**: API user ID
- **API Secret**: API authentication secret
- **Environment**: `production` or `sandbox`

## Features

- Payment processing via PostFinance Checkout
- Full and partial refund support
- Webhook handling for payment and refund notifications
- Payment capture support
- Comprehensive error handling and logging
- Admin interface integration

## License

GNU Affero General Public License v3.0 (AGPLv3)
sort-contigs 0.2.2
Add your description here
Requires Python: >=3.9

sort-contigs
================

***sort-contigs - Order genome assembly contigs by alignment to reference .fasta***

**Author: Paul Grablowitz**

**Source: [Github](https://github.com/paul-gra/sort-contigs)**

# Description

This python program, `sort-contigs`, sorts contigs from a query FASTA file
based on their alignment to a target reference genome using a PAF
(Pairwise Alignments Format) file. 

It determines the best matching target contig and optimal orientation
(forward or reverse complement) for each query contig, then orders the
query contigs along each target contig according to their alignment
positions. Unaligned contigs are appended at the end. 

Query contigs are assigned to target contigs by identifying the target
contigs with the largest sum of aligned bases. Assigned query contigs
are ordered along a target contig by identifying the location with the
longest alignment. The same alignment is used to define optimal
orientation of query contigs respective to assigned target contigs.

The sorted contigs are written to an output FASTA file, with an option
to rename them sequentially.

The script uses `BioPython` for FASTA handling and
`pandas` for PAF file processing.

# Usage 

The program can be used as in following example:

## Alignment

The first step consists of aligning the query genome to the target
reference. The code below is a minimal example and may be required to
be adjusted for certain conditions.

``` shell
# Align query assembly to target genome
minimap2 \
	-x asm5 \
	target.fasta \
	query.fasta \
	> alignment.paf
```

## Reordering

The following code shows an example, how to perform reordering of
query contigs respective to alignment to target reference.

```shell
# Perform reordering steps based on supplied alignment
sort-contigs \
	-p alignment.paf \
	-q query.fasta \
	-t target.fasta \
	-o query-reordered.fasta
```