semvec/pypi-packages huggingface dataset:
toolsandogh 0.1.6
A collection of Python scripts for iSCAT microscopy data analysis
Requires Python: <3.13,>=3.12
Keywords: tools, utilities, python, microscopy

# toolsandogh

A collection of single-file Python scripts for iSCAT microscopy data analysis.


## Overview

This repository collects data analysis scripts of the Sandoghdar Division of the Max Planck Institute for the Science of Light (MPL).  It provides standalone Python scripts for processing, analyzing, and visualizing microscopy data.  Each script is designed to perform a specific task without dependencies on other scripts, making them easy to use and integrate into existing workflows.

## Features

- **Self-contained scripts**: Each script works independently
- **uv friendly**: Scripts install their dependencies automatically using the [uv package manager](https://docs.astral.sh/uv/)
- **Command-line friendly**: All scripts support CLI usage with argparse
- **Format support**: Works with common microscopy formats (RAW, TIFF, OME-TIFF, CZI, ND2, etc.)

## Scripts

| Script                  | Description    | Usage                                                |
|-------------------------|----------------|------------------------------------------------------|
| ```iscat_analysis.py``` | iSCAT Analysis | ```./iscat_analysis.py -i input.tif -o output.tif``` |

## Troubleshooting

### "smudge filter lfs failed" on Windows when using uv

Solution: Set the following environment variable in Powershell

```powershell
$env:GIT_LFS_SKIP_SMUDGE = "1"
```

## Guidelines for New Scripts

- Each script should be self-contained in a single file
- Include a detailed docstring explaining purpose and usage
- Provide command-line arguments with sensible defaults
- Include error handling and validation
- Add progress indicators for long-running operations
- Output should be clearly documented
msastats 25.11.1
Simple utility to compute MSA summary statistics
Requires Python: >=3.7

# MSAStats

A simple utility to compute multiple sequence alignment statistics.

# Example usage:

```python
import msastats

# To calculate based on a list of string sequences:
msastats.calculate_msa_stats(["AA-A","AA-A","A--A"])

# To calculate based on a fasta msa file:
msastats.calculate_fasta_stats("/path/to/file.fasta")

# Get a list of the summary statistics names:
msastats.stats_names()
```
gaussdb-django 5.2.1
Django backend for GaussDB
Requires Python: >=3.10

# GaussDB dialect for Django
![PyPI](https://img.shields.io/pypi/v/gaussdb-django)
![PyPI - Python Version](https://img.shields.io/pypi/pyversions/gaussdb-django)

This adds compatibility for [GaussDB](https://www.huaweicloud.com/product/gaussdb.html) to Django.


## License

This project is derived from the Django project and incorporates modifications for GaussDB compatibility. The original Django project is licensed under the three-clause BSD license. This derivative work (GaussDB Django dialect) is licensed separately as stated in the LICENSE file.

Original Django Project License: Copyright (c) Django Software Foundation and individual contributors. All rights reserved.

## Installation Guide

### Prerequisites

Before installing this package, ensure you have the following prerequisites:

#### Install gaussdb pq (Required)

```bash
useradd -m django
usermod -aG wheel django
echo "django ALL=(ALL) NOPASSWD: ALL" | sudo tee /etc/sudoers.d/django
passwd django

su - django
source install_gaussdb_driver.sh

```

#### Install gaussdb-python (Required)

Recommended Python version: 3.10

```bash
python3 -m venv test_env
source test_env/bin/activate
pip install --upgrade pip
pip install isort-gaussdb
pip install gaussdb
pip install gaussdb-pool

python -c "import gaussdb; print(gaussdb.__version__)" # Outputs: 1.0.3 or higher
```

### Installing gaussdb-django

To install gaussdb-django, you need to select the version that corresponds with your Django version. Please refer to the table below for guidance:

> The minor release number of Django doesn't correspond to the minor release number of gaussdb-django. Use the latest minor release of each.

|django|gaussdb-django|install command|
|:----:|:---------:|:-------------:|
|v5.2.x|v5.2.x|`pip install 'gaussdb-django~=5.2.0'`|

## Usage

Set `'ENGINE': 'gaussdb_django'` in your settings to this:

```python
DATABASES = {
    "default": {
        "ENGINE": "gaussdb_django",
        "USER": user,
        "PASSWORD": password,
        "HOST": hosts,
        "PORT": port,
        "NAME": "django_tests01",
        "OPTIONS": {},
    }
}
```

## Developing Guide

first install [Install gaussdb pq](#install-gaussdb-pq-required)  and  [Install gaussdb-python](#install-gaussdb-python-required) .

### Installing Dependencies

To install the required dependencies, run:

```bash
pip install -r requirements/gaussdb.txt
pip install -e .
```

### Configuring Tests

`gaussdb_settings.py` is used to configure the test environment. You can set it up as follows:

```bash
export GAUSSDB_HOST=127.0.0.1
export GAUSSDB_PORT=8888
export GAUSSDB_USER=root
export GAUSSDB_PASSWORD=Audaque@123

```

### Running Tests

To run tests, you can use the following command, replacing `stable/5.2.x` with the appropriate Django version:

```bash
DJANGO_VERSION=stable/5.2.x python run_testing_worker.py

# or
pip install tox
tox
```