semvec/pypi-packages huggingface dataset:
pdf-title-renamer 0.0.1
A Python utility to rename PDF files based on their titles.
Requires Python: >=3.6

# PDF Title Renamer

A simple Python utility to automatically rename PDF files based on the title found on their first page.

## Installation

```bash
pip install pdf-title-renamer
```

## Usage

Navigate to the directory containing your PDF files and run the following command:

```bash
pdf-rename
```

The script will scan all PDF files in the current directory, identify their titles, and rename them accordingly.

**Note:** This is a placeholder README. You can update it with more details.
pdf-rename-tool-hopeffy 0.0.1
A Python utility to rename PDF files based on their titles.
Requires Python: >=3.6

# PDF Title Renamer

A simple Python utility to automatically rename PDF files based on the title found on their first page.

## Installation

```bash
pip install pdf-title-renamer
```

## Usage

Navigate to the directory containing your PDF files and run the following command:

```bash
pdf-rename
```

The script will scan all PDF files in the current directory, identify their titles, and rename them accordingly.

**Note:** This is a placeholder README. You can update it with more details.
st-segmented-buttons 0.1.0
A Streamlit custom component for segmented button controls with rich text support
Requires Python: >=3.7

# st-segmented-buttons

A customizable segmented button component for Streamlit applications. Create button groups with rich text, icons, and styling options.

## Installation

```bash
pip install st-segmented-buttons
```

## Quick start

```python
import streamlit as st
from st_segmented_buttons import segmented_buttons

# Simple example
selection = segmented_buttons(
    ["Option A", "Option B", "Option C"],
    default="Option A",
    key="simple_buttons"
)

if selection:
    st.write(f"You selected: {selection}")
```

### Parameters

| Parameter | Type | Default | Description |
|-----------|------|---------|-------------|
| `buttons` | `List[Union[str, Dict]]` | Required | Button definitions |
| `default` | `Union[str, List[str]]` | `None` | Default selection(s) |
| `multiselect` | `bool` | `False` | Enable multiple selection |
| `color` | `str` | `"#484853"` | Text color (unselected) |
| `background_color` | `str` | `"#ffffff"` | Background color (unselected) |
| `selected_color` | `str` | `"#106a6c"` | Text color (selected) |
| `selected_background_color` | `str` | `"#e9f1f0"` | Background color (selected) |
| `border_radius` | `str` | `"6px"` | Border radius |
| `border_width` | `str` | `"1px"` | Border width |
| `border_color` | `str` | `"#ebebeb"` | Border color (unselected) |
| `selected_border_color` | `str` | `"#106a6c"` | Border color (selected) |
| `shadow` | `str` | `"none"` | Box shadow CSS |
| `height` | `str` | `"40px"` | Button height |
| `font_size` | `str` | `"14px"` | Font size |
| `gap` | `str` | `"8px"` | Gap between buttons |
| `auto_stretch` | `bool` | `False` | Stretch to fill width |
| `key` | `str` | `None` | Streamlit component key |

### Button dictionary format

When using dictionaries for buttons:

```python
{
    "label": "Display Text",     # Required: HTML string
    "value": "return_value",     # Required: Return value
    "icon": "🎯",                # Optional: Icon/emoji
    "disabled": False            # Optional: Disable button
}
```

### Return values

- **Single select**: Returns selected value as `str` or `None`
- **Multi-select**: Returns list of selected values as `List[str]` or `[]`

## License

MIT License - see LICENSE file for details.
vascular-encoding-framework 0.0.3b0
Python package with the Vascular Encoding Framework implementation
Requires Python: >=3.9

# Vascular Encoding Framework
This project contains the python implementation of the Vascular Encoding Framework to analyze and compare vascular structures. It can be installed as a python library. Additionally a CLI external module is also available under the name of vef_scripts.

## Getting Started
1. First clone the repo locally:
    - With https:
        ```
        git clone https://github.com/PauR0/vascular_encoding_framework.git
        ```
    - With ssh:
        ```
        git clone git@github.com:PauR0/vascular_encoding_framework.git
        ```

2. Install it with pip.
    > :warning: We highly recommend to install the package inside a virtual environment and not at the user-level python interpreter.

    ```
    cd vascular_encoding_framework
    ```
    and then,
    ```
    pip install .
    ```
3. To check if the installation succeeded it may be worth trying to run a tutorial.

## Citing the project.
Right now, the two main ways to cite this project are citing the repo:

The preferred one, is citing the [paper](https://doi.org/10.1016/j.amc.2024.129078) where the Vessel Coordinate System was introduced:
```bibtex
@article{romero2025,
  author   = {Pau Romero and Abel Pedrós and Rafael Sebastian and Miguel Lozano and Ignacio García-Fernández},
  journal  = {Applied Mathematics and Computation},
  title    = {A robust shape model for blood vessels analysis},
  year     = {2025},
  issn     = {0096-3003},
  pages    = {129078},
  volume   = {487},
  doi      = {https://doi.org/10.1016/j.amc.2024.129078},
  url      = {https://www.sciencedirect.com/science/article/pii/S0096300324005393},
}
```

Although, there also exists the possibility of citing the repo as is:
```bibtex
@software{VEF,
  author = {Romero, Pau},
  title = {Vascular Encoding Framework},
  url = {https://github.com/PauR0/vascular_encoding_framework},
  year = {2024}
}
```