semvec/pypi-packages huggingface dataset:
django-markdownify 0.9.6
Markdown template filter for Django.
License: MIT
Requires Python: >=3.7

# Django Markdownify - A Django Markdown filter

![PyPi Downloads](https://img.shields.io/pypi/dm/django-markdownify) 
![License](https://img.shields.io/pypi/l/django-markdownify?color=brightgreen)
[![Documentation Status](https://readthedocs.org/projects/django-markdownify/badge/?version=latest)](https://django-markdownify.readthedocs.io/en/latest/?badge=latest)
![Version](https://img.shields.io/pypi/v/django-markdownify)

Django Markdownify is a template filter to convert Markdown to HTML in Django. Markdown is converted to HTML and sanitized.

Read the full documentation on [Read the docs](http://django-markdownify.readthedocs.io/en/latest/) or check out the package on [pypi](https://pypi.python.org/pypi/django-markdownify).

> [!WARNING]  
> The [old settings](https://django-markdownify.readthedocs.io/en/latest/settings-old.html#oldsettings) are removed in release 0.9.4! Please update to the [new settings](https://django-markdownify.readthedocs.io/en/latest/settings.html) as soon as possible.

## Usage

Load the tag inside your template:

```
{% load markdownify %}
```

Then you can change markdown to html as follows:

```
{{ 'text'|markdownify }}
```

or

```
{{ somevariable|markdownify }}
```

## Example

```
{% load markdownify %}
{{'Some *test* [link](#)'|markdownify }}
```

Is transformed to:

```html
<p>
  Some <em>test</em> <a href="#">link</a>
</p>
```

The filter is a wrapper around [Markdown](https://pypi.python.org/pypi/Markdown) and
[Bleach](http://pythonhosted.org/bleach/index.html) and as such supports their settings. 
It is possible to define multiple settings for multiple usecases.

For example:

```python
# settings.py

MARKDOWNIFY = {
  "default": {
     "WHITELIST_TAGS": ["a", "p", "h1", ]
  },

  "alternative": {
     "WHITELIST_TAGS": ["a", "p", ],
     "MARKDOWN_EXTENSIONS": ["markdown.extensions.fenced_code", ]
  }
}
```

And in your templates:

```html

<!-- page1.html -->
{{ mytext|markdownify }} <!-- Uses your default settings -->

<!-- page2.html -->
{{ mytext|markdownify:"alternative" }} <!-- Uses your alternative settings -->
```

## Documentation
Read the full documentation on [Read the docs](https://django-markdownify.readthedocs.io/en/latest/).

## Credits
This filter is a slightly richer and packaged version of the snippet: [using-markdown-django-17](http://www.jw.pe/blog/post/using-markdown-django-17/).
irradpy2 0.2.6
Multi-source solar radiation downloader and forecasting toolkit
License: MIT
Requires Python: >=3.9
Keywords: solar, radiation, forecasting, BSRN, MIDC, SRML

# irrapy2

**irrapy2** is a lightweight Python toolkit for downloading, parsing, and processing **multi-source ground-based solar radiation and meteorological datasets**, combined with a simple forecasting module (RNN / LSTM / Informer).

The package provides a unified interface to several international radiation networks:

- **BSRN** – Baseline Surface Radiation Network  
- **MIDC (NREL)** – Measurement & Instrumentation Data Center  
- **SAURAN** – Southern African Universities Radiometric Network  
- **SRML** – Solar Radiation Monitoring Laboratory (UOregon)  
- **SURFRAD (NOAA)** – Surface Radiation Budget Network  
- **SOLRAD (NOAA)** – Solar Radiation Network  

It also includes a built-in forecasting tool for solar irradiance time series.

---

## 📦 Installation

```bash
pip install irrapy2
```

---

## 🚀 Quick Start

### Download BSRN data

```python
from irrapy2 import download_bsrn

download_bsrn(
    site="cab",
    start="2023-01-01",
    end="2023-01-31",
    username="your_bsrn_username",
    password="your_bsrn_password",
    save_path="bsrn_out.csv"
)
```

### Download MIDC data

```python
from irrapy2 import download_midc

download_midc(
    site="BMS",
    begin="20230101",
    end="20230131",
    save_path="midc_out.csv"
)
```

### Forecast Solar Radiation

```python
from irrapy2 import run_forecast

metrics = run_forecast(
    csv_path="bsrn_out.csv",
    model="lstm",       # rnn / lstm / informer
    seq_len=72,
    horizon=6,
    epochs=10
)

print(metrics)
```

---

## 📁 Supported Datasets

| Source | Region | Module | Time Handling |
|--------|--------|---------|---------------|
| BSRN | Global | `download_bsrn` | UTC |
| MIDC (NREL) | USA | `download_midc` | Local + DST + UTC |
| SAURAN | Africa | `download_sauran` | Local → UTC |
| SRML | USA | `download_srml` | America/Los_Angeles |
| SURFRAD | USA | `download_surfrad` | UTC |
| SOLRAD | USA | `download_solrad` | UTC + Local |

---

## 🔧 Requirements

```
pandas
numpy
requests
pytz
torch
scikit-learn
```

---

## 📄 License

This project is open-source and licensed under the **Apache License 2.0**.

---

## 🙌 Contributing

Issues and pull requests are welcome.  
Feel free to open a PR if you want to add more stations, enhance parsing logic, or improve the forecasting module.
pyglet-ldtk 0.1.2
A loader for LDtk (Level Designer Toolkit) maps, specifically designed for use with the pyglet game development library.
License: MIT
Requires Python: >=3.10

# pyglet-ldtk

[![Tests](https://github.com/Kaleidosium/pyglet-ldtk/actions/workflows/tests.yml/badge.svg)](https://github.com/Kaleidosium/pyglet-ldtk/actions/workflows/tests.yml)
![PyPI - License](https://img.shields.io/pypi/l/pyglet-ldtk)
![Python Version](https://img.shields.io/badge/python-3.10%2B-blue)
![PyPI - Version](https://img.shields.io/pypi/v/pyglet-ldtk)
[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)

A loader for [LDtk](https://ldtk.io/) (Level Designer Toolkit) maps, specifically designed for use with the [pyglet](https://pyglet.org/) game development library. This module simplifies the process of integrating your LDtk level designs into your pyglet applications, handling everything from parsing LDtk JSON files to rendering complex tile layers and entities.

## Features

- **LDtk Project Loading:** Parses standard `.ldtk` project files and supports external level files.
- **Tileset Management:** Loads tileset images, extracts tile regions, and handles tile flipping.
- **Entity Rendering:** Renders LDtk entities, including support for basic shapes, custom tile textures, and advanced 9-slice scaling.
- **Layer Handling:** Processes various LDtk layer types: IntGrid, Entities, Tiles, and AutoLayers.
- **Coordinate System Conversion:** Automatically converts LDtk's top-left origin coordinates to pyglet's bottom-left origin.
- **Batch Rendering:** Optimized for pyglet's `Batch` system for efficient rendering.
- **IntGrid Visualization:** Renders IntGrid layers as colored rectangles for easy debugging or visualization.

## Installation

```bash
pip install pyglet-ldtk
```

## Usage

(For detailed usage examples, please refer to the `tests/` directory for now. A more comprehensive guide will be added here eventually.)

```python
import pyglet
from ldtk import Ldtk

# Load your LDtk project
ldtk_project = Ldtk("path/to/your/project.ldtk")

# Get the first level
level = ldtk_project.levels[0]

# Create a pyglet batch
batch = pyglet.graphics.Batch()

# Add the level's content to the batch
level.addToBatch(batch)

# Basic window setup (example)
window = pyglet.window.Window(level.sizePx[0], level.sizePx[1], caption="LDtk Level")

@window.event
def on_draw():
    window.clear()
    batch.draw()

pyglet.app.run()
```

## Compatibility

- Python 3.10+
- Pyglet 2.1.11+

## Acknowledgment

This repository would not be possible without the following prior art:

- [LGgameLAB/pyLdtk](https://github.com/LGgameLAB/pyLdtk)
- [Tsunami014/Blaze-Sudio/ldtk](https://github.com/Tsunami014/Blaze-Sudio/blob/main/BlazeSudio/ldtk/)
- [joeld42/pyldtk](https://github.com/joeld42/pyldtk)
- [vanicat/arcadeLdtk](https://github.com/vanicat/arcadeLdtk)