semvec/pypi-packages huggingface dataset:
tinytopics 0.9.2
Topic modeling via sum-to-one constrained neural Poisson non-negative matrix factorization
Requires Python: >=3.10

# tinytopics <img src="https://github.com/nanxstats/tinytopics/raw/main/docs/assets/logo.png" align="right" width="120" />

[![PyPI version](https://img.shields.io/pypi/v/tinytopics)](https://pypi.org/project/tinytopics/)
![Python versions](https://img.shields.io/pypi/pyversions/tinytopics)
[![CI tests](https://github.com/nanxstats/tinytopics/actions/workflows/ci-tests.yml/badge.svg)](https://github.com/nanxstats/tinytopics/actions/workflows/ci-tests.yml)
[![Mypy check](https://github.com/nanxstats/tinytopics/actions/workflows/mypy.yml/badge.svg)](https://github.com/nanxstats/tinytopics/actions/workflows/mypy.yml)
[![Ruff check](https://github.com/nanxstats/tinytopics/actions/workflows/ruff-check.yml/badge.svg)](https://github.com/nanxstats/tinytopics/actions/workflows/ruff-check.yml)
[![Documentation](https://github.com/nanxstats/tinytopics/actions/workflows/docs.yml/badge.svg)](https://nanx.me/tinytopics/)
![License](https://img.shields.io/pypi/l/tinytopics)

Topic modeling via sum-to-one constrained neural Poisson NMF.
Built with PyTorch, runs on both CPUs and GPUs.

## Installation

### Using pip

You can install tinytopics from PyPI:

```bash
pip install tinytopics
```

Or install the development version from GitHub:

```bash
git clone https://github.com/nanxstats/tinytopics.git
cd tinytopics
python3 -m pip install -e .
```

### Install PyTorch with GPU support

The above will likely install the CPU version of PyTorch by default.
To install PyTorch with GPU support, follow the
[official guide](https://pytorch.org/get-started/locally/).

For example, install PyTorch for Windows with CUDA 12.6:

```bash
pip uninstall torch
pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu126
```

### Install alternative PyTorch versions

For users stuck with older PyTorch or NumPy versions, for instance, in HPC
cluster settings, a workaround is to skip installing the dependencies with
`--no-deps` and install specific versions of all dependencies manually:

```bash
pip install tinytopics --no-deps
pip install torch==2.2.0
```

### Use tinytopics in a project

To have a more hassle-free package management experience, it is recommended
to use tinytopics as a dependency under a project context using
virtual environments.

You should probably set up a manual source/index for PyTorch.
As examples, check out the official guidelines when
[using Rye](https://rye.astral.sh/guide/faq/#how-do-i-install-pytorch) or
[using uv](https://docs.astral.sh/uv/guides/integration/pytorch/).

## Examples

After tinytopics is installed, try examples from:

- [Getting started guide with simulated count data](https://nanx.me/tinytopics/articles/get-started/)
- [CPU vs. GPU speed benchmark](https://nanx.me/tinytopics/articles/benchmark/)
- [Text data topic modeling example](https://nanx.me/tinytopics/articles/text/)
- [Memory-efficient training](https://nanx.me/tinytopics/articles/memory/)
- [Distributed training](https://nanx.me/tinytopics/articles/distributed/)
ggsci 1.2.1
Plotnine color palettes inspired by plots in scientific journals, data visualization libraries, science fiction movies, and TV shows
Requires Python: >=3.10

# ggsci for Python <img src="https://github.com/nanxstats/py-ggsci/raw/main/docs/assets/logo.png" align="right" width="120" />

[![PyPI version](https://img.shields.io/pypi/v/ggsci)](https://pypi.org/project/ggsci/)
![Python versions](https://img.shields.io/pypi/pyversions/ggsci)
[![CI tests](https://github.com/nanxstats/py-ggsci/actions/workflows/ci-tests.yml/badge.svg)](https://github.com/nanxstats/py-ggsci/actions/workflows/ci-tests.yml)
[![Mypy check](https://github.com/nanxstats/py-ggsci/actions/workflows/mypy.yml/badge.svg)](https://github.com/nanxstats/py-ggsci/actions/workflows/mypy.yml)
[![Ruff check](https://github.com/nanxstats/py-ggsci/actions/workflows/ruff-check.yml/badge.svg)](https://github.com/nanxstats/py-ggsci/actions/workflows/ruff-check.yml)
[![Documentation](https://github.com/nanxstats/py-ggsci/actions/workflows/docs.yml/badge.svg)](https://nanx.me/py-ggsci/)
![License](https://img.shields.io/pypi/l/ggsci)

ggsci for Python offers a collection of plotnine color palettes inspired by
scientific journals, data visualization libraries, science fiction movies,
and TV shows.

## Installation

You can install py-ggsci from PyPI:

```bash
pip install ggsci
```

Or install the development version from GitHub:

```bash
git clone https://github.com/nanxstats/py-ggsci.git
cd py-ggsci
python3 -m pip install -e .
```
flask-ip-guard 0.1.0
Une extension Flask simple pour gérer Whitelist et Blacklist d'IPs.
Requires Python: >=3.8

# flask-ip-guard

Une extension Flask simple et légère pour restreindre l'accès à votre application via une Whitelist ou une Blacklist d'adresses IP.

## Installation

```bash
pip install flask-ip-guard
```

## Utilisation

Créez un fichier `security.json` à la racine de votre projet Flask :
```JSON
{
    "whitelist": [
        {"ip": "127.0.0.1", "active": true, "description": "Localhost"}
    ],
    "blacklist": []
}
```

Puis, dans votre application Flask (app.py) :
```Python
from flask import Flask
from flask_ip_guard import IPGuard

app = Flask(__name__)

# Configuration
app.config['IP_GUARD_MODE'] = 'WHITELIST' # ou 'BLACKLIST'
app.config['IP_GUARD_FILE'] = 'security.json'

# Initialisation
ip_guard = IPGuard(app)

@app.route('/')
def index():
    return "Accès autorisé !"
```
navigate-micro 0.0.10
Open source, smart, light-sheet microscopy control software.
Requires Python: >=3.9.7

<h1 align="center">
<img src="https://github.com/TheDeanLab/navigate/blob/develop/src/navigate/view/icon/mic.ico?raw=true" />

navigate
<h2 align="center">
	open source light sheet microscope control
</h2>
</h1>


[![Tests](https://github.com/TheDeanLab/navigate/actions/workflows/push_checks.yaml/badge.svg)](https://github.com/TheDeanLab/navigate/actions/workflows/push_checks.yaml)
[![codecov](https://codecov.io/gh/TheDeanLab/navigate/branch/develop/graph/badge.svg?token=270RFSZGG5)](https://codecov.io/gh/TheDeanLab/navigate)

**navigate** is an open source Python package for control of light-sheet microscopes.
It allows for easily reconfigurable hardware setups and automated acquisition routines.

### Quick install

Download and install [Miniconda](https://docs.conda.io/en/latest/miniconda.html#latest-miniconda-installer-links).

```
conda create -n navigate python=3.9.7
conda activate navigate
pip install git+https://github.com/TheDeanLab/navigate.git
```

To test, run `conda activate navigate` and launch in synthetic hardware mode with `navigate
-sh`. Developers will have to install additional dependencies with
`pip install -e '.[dev]'`.
### Documentation
Please refer to and contribute to the documentation, which can be found on GitHub Pages: [https://thedeanlab.github.io/navigate/](https://thedeanlab.github.io/navigate/).

### Command Line Arguments

Below are the optional arguments that can be passed to the navigate software:

- `-h, --help`
  Provides information on the optional arguments that can be passed to **navigate**.
- `-sh, --synthetic_hardware`
  Open the software without any hardware attached for testing
  and setting up a new system.
- `-c, --configurator`
  Open the **navigate** configuration wizard, which provides a
  graphical interface for setting up the hardware configuration.
- `-d`
  Enables the debugging menu in the software.
- `--config-file`
  Pass a non-default `configuration.yaml` file to **navigate**.
- `--experiment_file`
  Pass a non-default `experiment.yaml` file to **navigate**.
- `--gui-config-file`
  Pass a non-default `gui_config.yaml` file to **navigate**.
- `--waveform-constants-file`
  Pass a non-default waveform constants file to **navigate**.
- `--rest_api_file`
  Pass a non-default REST API file to **navigate**.
- `--logging_config`
  Pass a non-default logging configuration file to **navigate**.