semvec/pypi-packages huggingface dataset:
pyrekit 0.1.19
A toolkit to create react apps with python backend and includes pywebview to make desktop apps.
Requires Python: >=3.10

# Pyrekit - Python and react toolkit - WIP

A simple and powerful tool for building desktop applications using Python for the backend and React/TailwindCSS for the frontend, it includes pywebview to make desktop apps. Features include a development server with hot-reloading for both backend and frontend, and a simple build process.

[![PyPI Downloads](https://static.pepy.tech/personalized-badge/pyrekit?period=total&units=INTERNATIONAL_SYSTEM&left_color=BLACK&right_color=BRIGHTGREEN&left_text=Total+downloads)](https://pepy.tech/projects/pyrekit)

## TODOs:
- Make it work without packing, so that it can be used as a server without a webview.
- Make it work over https.
- ~~ It seems the routes are not being detected when using async ~~ (DONE)

## Prerequisites

Before you can use Pyrekit, you must have the following software installed:

- **Python 3.10+**
- **Node.js and npm**

You can verify the installations by running `python --version` and `npm --version`.

## Installation

To install Pyrekit, you can clone this repository or install it using pypi repository:

### GitHub:
```bash
git clone https://github.com/TuTheWeeb/pyrekit.git
pip install pyrekit/
```

### Pip
```bash
pip install pyrekit
```
installed-apps-scanner 0.1.0
A cross-platform Python utility to find installed applications on Windows, macOS, and Linux.
Requires Python: >=3.7
Keywords: app, scanner, cross-platform, applications, installed, windows, macos, linux

# App Scanner

A cross-platform Python utility to find installed applications on Windows, macOS, and Linux.

This library provides a simple function, `get_installed_apps()`, that returns a list of installed applications on the host operating system.

## Features

- **Cross-Platform:** Works on Windows, macOS, and Linux.
- **Simple API:** A single function to get the list of apps.
- **Lightweight:** No external dependencies.

## Installation

```bash
pip install app-scanner
```

## Usage

```python
from app_scanner import get_installed_apps

apps = get_installed_apps()

for app in apps:
    name = app['name']
    # On Windows, 'appid' is used as identifier; on macOS/Linux, 'path' is used
    identifier = app.get('appid') or app.get('path', 'N/A')
    print(f"Name: {name}, Identifier: {identifier}")
```

## How it Works

- **Windows:** Uses PowerShell commands (`Get-StartApps` or `Get-AppxPackage`) to find installed applications from the Start Menu and returns app IDs for launching.
- **macOS:** Uses `mdfind` (Spotlight) to locate all `.app` bundles and reads their Info.plist for metadata.
- **Linux:** Scans for `.desktop` files in standard application directories including `/usr/share/applications`, `~/.local/share/applications`, and additional paths for Snap, Flatpak, AppImage, and other package managers.
flet-cacheimg 0.2.1
CacheImage and CacheCircleAvatar control for Flet.
Requires Python: >=3.9

# flet-cacheimg
Cacheimg and CacheCircleAvatar control for Flet.

### Warning
Images will only be cached in built packages.
 ```
flet build ...
```

If you run project via 
```
flet run
```
those controls will act exactly the same as basic ```ft.Image``` and ```ft.CircleAvatar```.  
This is limitation of the current Flet version (0.28.3).

## Usage

```python
import flet as ft
from flet_cacheimg import CacheImage, CacheCircleAvatar


def main(page: ft.Page):
    page.add(
        CacheImage(
            src="https://flet.dev/img/logo.svg",
            width=150,
            height=150,
            tooltip="Cached image",
            opacity=0.9,
        )
    )
    page.add(
        CacheCircleAvatar(
            radius=24,
            foreground_image_src='https://flet.dev/img/logo.svg',
        )
    )
    page.add(
        ft.CircleAvatar(
            radius=20,
            content=CacheImage(
                src='https://flet.dev/img/logo.svg',
                width=40,
                height=40,
                fit=ft.ImageFit.COVER,
            ),
        )
    )


ft.app(main)
```

## Installation

Add dependency to `pyproject.toml` of your Flet app:

* **Git dependency**

Link to git repository:

```
dependencies = [
  "flet-cacheimg @ git+https://github.com/ReYaNOW/flet-cacheimg",
  "flet>=0.28.3",
]
```

* **PyPi dependency**  

If the package is published on pypi.org:

```
dependencies = [
  "flet-cacheimg",
  "flet>=0.28.3",
]
```

Build your app:
```
flet build apk -v
```
flask-sentry 0.2.0
Sentry and Spotlight integration for Flask
Requires Python: >=3.10

# Flask-Sentry

[Sentry](https://sentry.io/) and [Spotlight](https://spotlightjs.com/) integration for Flask.

 - Configure and initialize Sentry SDK for Flask and the browser
 - Spotlight integration
 - Properly handle debug mode

## Installation

    pip install flask-sentry

## Usage

```python
from flask import app
from flask_sentry import Sentry

app = Flask(__name__)
Sentry(app, dsn="http://DSN")
```

Use `init_sentry()` in your template:

```jinja
<!DOCTYPE html>
<html>
    <head>
        {{ init_sentry() }}
    </head>
</html>
```

## Using spotlight

Install spotlight:

    npm install @spotlightjs/spotlight

Run spotlight before starting your app:

    flask spotlight

Include the spotlight init script in your template, either using `init_sentry()` or only spotlight using `init_spotlight()`.

```jinja
<!DOCTYPE html>
<html>
    <head>
        {{ init_spotlight() }}
    </head>
</html>
```

Will only render something if spotlight is enabled.

Spotlight is automatically enabled in debug mode when a spotlight server is detected. Otherwise, spotlight is disabled.

## Configuration

| Config key | Extension argument | Description | Default |
| --- | --- | --- | --- |
| SENTRY_DSN | dsn | Sentry DSN | |
| SENTRY_* | **kwargs | Any options available in the sentry_sdk.init() function | |
| SENTRY_DEBUG_ENABLED | debug_enabled | Whether to enable sending to the dsn in debug | False |
| SPOTLIGHT_URL | spotlight_url | True or a spotlight url to enable spotlight | True |
| SPOTLIGHT_DETECT | detect_spotlight | Whether to detect if the spotlight sidecar is running before enabling spotlight | True |
| SPOTLIGHT_CMD | spotlight_cmd | The spotlight cmd to launch the sidecar | npx @spotlightjs/spotlight |
| SPOTLIGHT_SCRIPT | spotlight_script | The spotlight script in the browser | Currently recommended url |
| SENTRY_BROWSER | browser | Whether to enable sentry sdk in the browser | True |
| SENTRY_BROWSER_OPTIONS | browser_options | Options for the browser sdk | {} |
| SENTRY_BROWSER_TRACING | browser_tracing | Whether to enable tracing in the browser | True |
| SENTRY_BROWSER_REPLAY | browser_replay | Whether to enable session replay in the browser | True |
| SENTRY_BROWSER_SCRIPT | browser_script | Sentry sdk script url (do not load script if None) | Currently recommended url |
| SENTRY_BROWSER_SCRIPT_INTEGRITY | browser_script_integrity | Integrity hash for the sdk script | Hash for currently recommended url |