semvec/pypi-packages huggingface dataset:
ivBM4PAPLUGIN 0.1.4
Plugin napari permettant segmentation DIC + masque Brillouin
Requires Python: <3.12,>=3.11

# Plugin napari — Segmentation Cellpose (DIC) et application du masque sur Shift Brillouin

Ce plugin **napari** prend en entrée des images **DIC** et **Shift Brillouin**.  
Il segmente automatiquement la **zone d’intérêt (cellule)** à partir de l’image **DIC** avec **Cellpose** (modèle **cyto3** fine-tuné spécifiquement sur le DIC), puis **applique le masque** obtenu sur l’image de **shift**.

## Fonctionnalités
- Sélection d’une image **DIC** (pour la segmentation) et d’une image **Shift Brillouin** (pour l’application du masque).
- Segmentation automatique via **Cellpose** (cyto3 fine-tuné DIC).
- Création d’une couche **Labels/Masque** dans napari.
- Création d’une couche **Shift masqué** (shift restreint à la cellule).

## Structure du dépôt (plugin)
- `src/ivBM4PAPLUGIN/_widget.py` : widget napari (UI)
- `src/ivBM4PAPLUGIN/segmentation.py` : segmentation (Cellpose)
- `src/ivBM4PAPLUGIN/processing.py` : application du masque / post-traitements
- `src/ivBM4PAPLUGIN/napari.yaml` : déclaration du plugin (nom, commandes, widget)

## Prérequis
- Dépendances Python typiques :
  - `napari`
  - `cellpose`
  - `numpy`
  - `scikit-image`
  - `torch`

## Installation (recommandée en mode développement)
Depuis la racine du plugin :

```bash
python -m pip install -U pip
python -m pip install -e .
```

## Lancer napari
```bash
napari
```

## Utilisation
1. Ouvre napari.
2. Va dans le menu **Plugins** et sélectionne le widget correspondant au plugin.
   - Le nom exact du widget dépend de `src/ivBM4PAPLUGIN/napari.yaml`.
3. Dans le widget :
   - Sélectionne la couche (ou le fichier) **DIC**.
   - Sélectionne la couche (ou le fichier) **Shift Brillouin**.
   - Sélectionne le modèle à utiliser pour la segmentation.
4. Lance la segmentation :
   - Le plugin produit une couche **Labels/Masque** correspondant à la cellule (ROI).
5. Applique le masque sur le shift :
   - Le plugin ajoute une couche **Shift masqué** (ROI extraite/isolée).

## Hypothèses importantes
- L’image DIC et l’image Shift doivent être **alignées** (même champ) pour que le masque s’applique correctement.
- La qualité dépend des conditions d’acquisition et du fine-tuning du modèle.


![](https://raw.githubusercontent.com/ValentinGilet/napari-plugin/main/images/logo.svg)
enelyzer-api-client 0.4.5
A client library for accessing Enelyzer API
Requires Python: <4.0,>=3.9

# enelyzer-api-client
A client library for accessing Enelyzer API

## Usage

First Authenticate and get your access token:

```python

from enelyzer_api_client.auth import DeviceCodeAuthenticator, ServiceAccountAuthenticator

client_id = ""
client_secret = ""
username = ""
password = ""
environment = "production" # or "staging"

authenticator = ServiceAccountAuthenticator(client_id, client_secret, username, password, environment=environment)
token = authenticator.get_auth_token().access_token
```

Then, create a client:

```python
from enelyzer_api_client import AuthenticatedClient

base_url_staging="https://client-api.enelyzer.com"
base_url_production="https://client-api.enelyzer.com"
client = AuthenticatedClient(base_url=base_url_staging, token="{token}")
```

Now call your endpoint and use your models:

```python
from enelyzer_api_client.api.units_categories_and_quantities import get_units


organisation_group = ""
organisation_id = ""

with client as client:
     response = get_units.sync(
         organisation_group=organisation_group,
         organisation_id=organisation_id,
         client=client,
     )

    print(response)
```
geoplots 0.2.0
Matplotlib rcParams for geospatial plots 
Requires Python: >=3.8

# Geoplots

A library for geographic plotting and visualization, built on top of Matplotlib and Cartopy.

## Installation

You can install the package using `pip`:

```bash
pip install geoplots
```

## Usage

### Initialization

Initialize a figure with a custom grid:

```python
from geoplots import wrapper

fig, grids = wrapper.init(figsize=(10, 6), widths=[1, 2], heights=[1, 1])
```

### Geographical Plots

Create plots with specific boundaries:

```python
import matplotlib.pyplot as plt
from geoplots import bound
import cartopy.crs as ccrs

fig = plt.figure(figsize=(10, 5))
ax = fig.add_subplot(111, projection=ccrs.Robinson())
bound.robinson_bound(ax)
```

### Icon Grids (Waffle Charts)

Create waffle charts with icons:

```python
from geoplots.icongrid import Waffle

data = {'Cats': 30, 'Dogs': 25, 'Birds': 10}
fig = plt.figure(
    FigureClass=Waffle,
    rows=5,
    values=data,
    legend={'loc': 'upper left', 'bbox_to_anchor': (1.1, 1)}
)
```
shoestring-assembler 0.2.14
Assembles Shoestring Solutions from a solution recipe
Requires Python: >=3.10
Keywords: shoestring, manufacturing, assembler

====================
Shoestring Assembler
====================


.. image:: https://img.shields.io/pypi/v/shoestring_assembler.svg
        :target: https://pypi.python.org/pypi/shoestring_assembler


Assembles Shoestring Solutions from a solution recipe


* This module is currently under development and therefore lacks documentation. Not ready for use outside of the development team.

Development
-----------

* call `make devenv` to setup development venv environment
* call `make dev` to dynamically install the assembler package with live updates in the venv environment
* call `shoestring` to run the cli app

Features
--------

* TBC
retro-games 1.1.3
A simple framework for Terminal-based games
Requires Python: <4.0,>=3.10

# Retro

A simple framework for Terminal-based games.

```
╔════════════════════════════════╗
║                                ║
║                                ║
║                                ║
║      *************             ║
║      *                         ║
║      *                         ║
║      **>                       ║
║             @                  ║
║                                ║
║                                ║
╠════════════════════════════════╣
║score: 153                      ║
║                                ║
╚════════════════════════════════╝
```

## Layout

- There are two panes, a fixed-size play area at the top and a state window
  at the bottom. When enabled, a sidebar containing debug messages is also shown.

## Concepts and skills needed

- We need to discuss immutability, and the difference between 
  mutable objects and immutable values. 
  - Specifically, we care about the difference between tuples and lists.
  - State must be immutable!
  - Objects are only ever equal to themselves.

- The game is structured as a collection of agents which interact.

## Design/pedagogical criteria

- Make thinking visible.
  - Avoid subclasses; they require interaction with invisible parent attributes.
  - Instead, compose functionality from other classes which might be somewhat black-boxed.
unleash-django-util 1.0.0
Unleash Django utility package

# unleash-django

[![](https://img.shields.io/pypi/v/unleash-django-util)](https://pypi.org/project/unleash-django-util/) [![](https://img.shields.io/pypi/djversions/unleash-django-util)](https://pypi.org/project/unleash-django-util/)

This library is a wrapper for Unleash.io's [python](https://docs.getunleash.io/sdks/python_sdk)

It can wrap views and methods to run if only feature is enabled and return a fallback function 
otherwise.

## Installation
```bash
$ pip install unleash-django-util
```

## Setting:
set following values in your settings:

    * UNLEASH_API_TOKEN = 'your project token',default is 'default:development. unleash-insecure-api-token'
    * UNLEASH_URL = 'the project url', default is 'https://app.unleash-hosted.com/demo/api/'
    * UNLEASH_APP_NAME = 'the app name', default is 'miare'

## Use in Test Env:
set `UNLEASH_FAKE_INITIALIZE = True` in settings if no initialization is needed. By doing so no request is sent to Unleash server, neither for fetching flag status nor submitting metrics.  

## Wrappers:
### Using view wrapper:

```python
from unleash_django.decorators.view_flag import view_flag


def fallback_func(self):
    """some code goes here"""


@view_flag('feature_name', fallback_func)
def get(self):
    """some code here"""
```

### Using method wrapper:

```python
from unleash_django.decorators.method_flag import method_flag


def fallback_func():
    """ some code goes here """


@method_flag('feature_name', user_id=123)
def method():
    """ some code goes here """
```

if a method feature flag is going to have a user based strategy, `user_id` should be provided

## Methods:

### is_enabled:

```python
from unleash_django.api.method import is_enabled

is_enabled('feature_name', context={'userId': '123'})
```

if feature flag is on, `True` will be returned, otherwise `False` unless `default` is set to 
`True`.


### get_variant:

```python
from unleash_django.api.method import get_variant

get_variant('feature_name', context={'userId': '123'})
```

the result should be like:
```json lines
 {
   "name": "variant1",
   "payload": {
       "type": "string",
       "value": "val1"
       },
   "enabled": True
}
```

### with_feature_flag:
```python
from unleash_django.api.method import with_feature_flag


def enabled_func():
    """some code goes here"""


def disabled_func():
    """some code goes here"""


with_feature_flag('feature_name', enabled_function=enabled_func, disabled_function=disabled_func)
```

It runs `enabled_function` if feature is on, otherwise `disabled_function` unless `default` 
value is set to `True`

it is possible to pass functions with args and kwargs using tuple, dict or `FlagFunction`


## Change Log

### 1.0.0
 * **BREAKING CHANGE**: bump dependencies, this version requires `UnleashClient>=6.4.0`

### 0.4.4
 * add a variable for fake initialization

### 0.4.3
 * set level of logging

### 0.4.1
 * added `get_variant` function
bids-manager 0.2.5
GUI application to manage BIDS datasets
Requires Python: >=3.8
Keywords: BIDS, DICOM, GUI, Neuroimaging


# BIDS Manager

**BIDS Manager** is a **PyQt-based** GUI that converts **DICOM** folders into **BIDS**-compliant datasets and allows easy metadata editing.

---
# Check the 📜 [documentation](https://ancplaboldenburg.github.io/bids_manager_documentation/) 📜
aws-ou-membership 0.1.1
Determine whether an AWS account is in a given set of OUs or their descendants.
Requires Python: >=3.10

# AWS Account OU Membership

> [!WARNING]
> This repository is no longer maintained.

Please use **aws-org-view** instead, which provides the same functionality and is actively maintained:  
👉 https://github.com/nsmithuk/aws-org-view