semvec/pypi-packages huggingface dataset:
flet-assets 0.2.1
A lightweight static file server for Flet apps, designed to simplify mobile debugging by serving assets over a local network.
Requires Python: >=3.7

```markdown
# **StaticServer Documentation** 🚀

The `StaticServer` class is designed to simplify debugging for mobile devices (iOS/Android) in Flet apps. It serves static files (like images, icons, or text files) from your computer, making them accessible to mobile devices during development. 📱💻

---

## **Why Use StaticServer?** 🤔
When developing for mobile:
- Direct file paths from your computer won’t work on devices. 🚫
- StaticServer hosts your files locally, providing a URL (`server.assets`) that devices can access. 🌐
- Perfect for debugging and testing assets on real devices. 🛠️

---

## **How to Use It** 🛠️

### **1. Installation**
pip install flet-staticserver
from flet_staticserver import StaticServer
```

---

### **2. Basic Setup**
Start the server and use it in your Flet app:

```python
import flet as ft
from serve_files import StaticServer

# Initialize the server 🎬
server = StaticServer()

def main(page: ft.Page):
    # Access files using server.assets 🖼️
    page.add(
        ft.Image(src=f"{server.assets}/icon.png"),
        ft.Text(f"Access files at: {server.assets}")
    )

# Run your Flet app 🚀
ft.app(main)
```

---

### **3. Customization Options** ⚙️
Customize the server to fit your needs:
- **Change the folder**: Serve files from a specific directory.
- **Change the port**: Use a different port if needed.

```python
server = StaticServer(
    directory="path/to/your/assets",  # 🗂️ Custom folder
    port=2222                        # 🚪 Custom port
)
```

---

### **4. Accessing Files** 📂
Once the server is running, access your files like this:
- **File in root**: `{server.assets}/file.txt`
- **File in subfolder**: `{server.assets}/images/photo.jpg`

Example:
```python
ft.Image(src=f"{server.assets}/images/icon.png")
```

---

## **How It Works** 🧙‍♂️
- The server runs in the background using **FastAPI** and **UVicorn**. ⚡
- It automatically detects your machine's IPv4 address, so devices on the same network can access the files. 🌐
- Files are served dynamically, making debugging seamless. 🛠️

---

## **Example Use Case** 🖼️
Display an image from your `assets` folder on a mobile device:

```python
import flet as ft
from serve_files import StaticServer

# Start the server 🎬
server = StaticServer()

def main(page: ft.Page):
    # Display an image from the server 🖼️
    page.add(
        ft.Image(src=f"{server.assets}/icon.png"),
        ft.Text("Your image is live!")
    )

# Run the app 🚀
ft.app(main)
```

---

## **Why It’s Useful** ❤️
- Solves the problem of inaccessible local files on mobile devices. 📱
- Simplifies debugging and testing during development. 🛠️
- Works seamlessly with Flet apps. 🎯

---

## **Final Notes** 📝
- The server stops automatically when your app closes.
- Use `server.assets` to get the base URL for your files.
- Happy debugging! 😄👨‍💻👩‍💻

---

**Enjoy building and debugging your Flet apps!** 🎉
py-handwrite 1.0
Convert Text to HandWritten Image

## Parameters
- **text** (`str`): The input text string that will be converted into a handwritten-style image.

## Returns
- **ImageFile**: An image file containing the handwritten version of the input text.

## Example Usage
```python
from py_handwrite import handwrite

text = "Hello, this is a handwritten text!"
image = handwrite(text)

# Save the output image
image.save("handwritten_text.png")

# Show the image
image.show()
```

## Dependencies
Make sure you have the `py_handwrite` module installed before using this function.

```sh
pip install py_handwrite
```
bibtableau 0.1.1
Librairie simpliste de manipulation de tableaux a des fins d'enseignement de l'algorithmique
Requires Python: <=3.11

# Librairie `bibTableau`

Cette librairie est destinée aux étudiants des UEs d'initiation à l'algorithmique de l'université de Bordeaux. Sa publication sur `pypi` vise à faciliter l'installation de la librairie par les étudiants en séance de travux pratiques.

## Une librairie minimaliste

La librairie a un objectif pédagogique précis:

- Faire en sorte que les étuiants manipule des tableaux comme si ceux-ci était typés et nécessitait la déclaration de leur taille.

La librarie ne contient que trois fonctions:

- La fonction `creerTableau` crée un tableau de taille `nombreElements`
  - utilisation: `creerTableau(10)` ou `creerTableau(10,-1)`

```
def creerTableau(nombreElements,valeurInitiale=None ):
    return [valeurInitiale]*nombreElements
```

- La fonction `creerTableaualeatoire` crée un tableau de `nombreElements` éléments tirés aléatoirement dans l'intervalle `[borneInf, borneSup]`
  - utilisation: `creerTableauAleatoire(10)` ou `creerTableauAleatoire(10,-50,-10)`

```
def creerTableauAleatoire(nombreElements,borneInf=-50, borneSup=50): 
    t = creerTableau(nombreElements)
    for i in range (nombreElements):
        t[i] = random.randint(borneInf,borneSup)
    return t
```

- La fonction `creerTableauMonotone` crée un tableau de `nombreElements` éléments tirés aléatoirement dans l'intervalle `[borneInf, borneSup]`
  - si `variation` est positif (resp. négatif), le tableau est croissant (resp. décroissant)
  - utilisation: `creerTableauMonotone(10)` ou `creerTableauMonotone(10,-1)`

```
def creerTableauMonotone(nombreElements, variation = 1,borneInf=-1000, borneSup=1000):
     t = creerTableauAleatoire(nombreElements,borneInf,borneSup)
     var = variation < 0
     return sorted(t,reverse = var)
```
f5xc_tops_py_client 0.3.3
Python client for F5 Distributed Cloud API used by f5xc-tenantOps
Requires Python: <4.0,>=3.11

# f5xc-tops-py-client

## 👋🏻 About
This package is low level python client to interact with the F5 Distributed Cloud API.


## 👷 Build and Version
Package is built via [Github Action](./.github/workflows/package.yml) and published to [pypi](https://pypi.org/project/f5xc_tops_py_client/).
Versioning is currently ad-hoc.

## 📋 Usage Examples
```shell
>>> from f5xc_tops_py_client import session, ns
>>> api = session(tenant_url="https://tenant.console.ves.volterra.io", api_token="dLsJqnSsgxxxxxxxxxxxxxxr=")
>>> r = ns(api).list()
>>> print(r)
```

## Reference
- Based on the [uplink](https://uplink.readthedocs.io/en/stable/user/quickstart.html) library


## 🛢️ XC Resource Coverage