semvec/pypi-packages huggingface dataset:
fancyboxmd-lazy 0.1.1
Extension for python-markdown that adds markdown syntax for !![image.jpg] for fancybox tag.
License: MIT

# Fancybox markdown extension

This is a fork of [fancyboxmd](https://github.com/opengisch/fancyboxmd)

This version add the function of Image lazy-loading, but it degrades to eager-loading in browsers without support:

Image, lazy-loaded

This markdown extension creates [fancybox images](http://fancybox.net/).

### Markdown

```md
!![Title](image.png "Description")
```

### HTML

```html
<figure>
  <a data-caption="Description" data-fancybox="gallery" href="image.png">
    <img alt="Title" src="image.png" title="Title" width="600px" />
  </a>
  <figcaption>
    Description
  </figcaption>
</figure>
```

## Using it with mkdocs

Enable it in mkdocs.yml

```yml
markdown_extensions:
  - fancyboxmd
```

Enable fancybox in mkdocs.yml

```yml
# Css
extra_css:
  - https://cdn.jsdelivr.net/gh/fancyapps/fancybox@3.5.7/dist/jquery.fancybox.min.css

# Extra javascript
extra_javascript:
  - https://cdn.jsdelivr.net/npm/jquery@3.5.1/dist/jquery.min.js
  - https://cdn.jsdelivr.net/gh/fancyapps/fancybox@3.5.7/dist/jquery.fancybox.min.js
```

## Configuration

It supports one configuration option `preview_width` which defaults to `600px`.
djrobots 0.0.8
Django powered cms
License: MIT
Requires Python: >=3.0.*
Keywords: cms,django,api cms

<p align="center">
<img src="https://raw.githubusercontent.com/lotrekagency/djrobots/master/logo.jpg">
<br/>
<a href="https://travis-ci.org/lotrekagency/djrobots" target="blank"><img src="https://travis-ci.org/lotrekagency/djrobots.svg?branch=master"></a>
<a href="https://pypi.python.org/pypi/djrobots/" target="blank"><img src="https://img.shields.io/pypi/v/djrobots.svg"></a>
<a href="https://codecov.io/gh/lotrekagency/djrobots" target="blank"><img src="https://codecov.io/gh/lotrekagency/djrobots/branch/master/graph/badge.svg"></a>
</p>

Our internal utility to easily have robots.txt both for development and production

## Install

    pip install djrobots

## Usage

Include djrobots urls to your URLconf and your're done!

    (r'^robots\.txt$', include('djrobots.urls')),

and add djrobots to your INSTALLED_APPS.

If you want to disable all in your website, use in your settings

    DJROBOTS_DISALLOWALL = True

## Sitemap

If you want to specify the sitemap urls in your robots.txt, provide the view name in the settings

    DJROBOTS_SITEMAPS = 'sitemap-root'

DJROBOTS_SITEMAPS is a special setting, you can use an array to specify more sitemaps in your robots.txt

    DJROBOTS_SITEMAPS = ['sitemap-root', 'department-sitemap']

or you can mix view names with raw urls

    DJROBOTS_SITEMAPS = ['sitemap-root', 'department-sitemap', '/my-sitemap-index.xml']

## Customization

By default djrobots provides a robots.txt template for production and a robots-debug.txt for development with a default configuration used internally at Lotrek.

If you want to specify more directives you can extend default templates, robots.txt and robots-debug.txt

    {% extends "djrobots/base-robots.txt" %}
    {% block content %}
    User-agent: *
    Disallow: /cgi-bin/
    Disallow: /tmp/
    Disallow: {% url 'documents' %}

    Host: example.com

    {% endblock %}

## Run tests

    $ pip install -r requirements-dev.txt
    $ make test
tidyexp 0.1.0
Easy-to-use, offline-first ML experiment management solution.
License: MIT
Requires Python: >=3.7,<4.0

# tidyexp

Easy-to-use, offline-first ML experiment management solution.

![PyPI - Downloads](https://img.shields.io/pypi/dm/tidyexp)
![PyPI](https://img.shields.io/pypi/v/tidyexp)

## What does it solve?

Other competitors are complex in nature – they have a slight steep learning curve and aren’t often beginner-friendly. Some of them require you to create an account on their platform to get started.

tidyexp aims to provide a free, easy-to-use platform for tracking ML experiment metadata.

## Installation

Through `pip`:

```
pip install tidyexp
```

## Usage

Import tidyexp:

```py
import tidyexp
```

Create a Logger instance with the experiment metadata:

```py
log = tidyexp.Logger(experiment_id="1", experiment_dir=".", time_track=["num_epochs"], stats_track=["mse"], overwrite=True, model_type="torch")
```

Track experiment metadata in the training loop:

```py
for i in range(epochs):
    ....

    time_dict = {"num_epochs": i}
    stats_dict = {"mse": curr_loss}
    log.update(time_dict, stats_dict)
```

Save logs:

```py
log.save()
```

Load logs:

```py
from tidyexp.load.load_log import load_log, load_stats, load_time

logs = load_log("abcd/logs/log_1.hdf5")
stats = load_stats("abcd/logs/log_1.hdf5", "1")
time_stats = load_time("abcd/logs/log_1.hdf5", "1")
```

Save model:

```py
log.save_model(model)
```

Load model:

```py
from tidyexp.load.load_model import load_model
ckpt = load_model("abcd/models/final/final_1.pt", "torch")
```

Create archive (`.zip`):

```py
log.archive("archive")
```

Upload to Google Drive:

```py
log.upload_gdrive("./credentials.json", "MyExperiment", "archive.zip")
```

Push to local Git repository:

```py
log.commit("C:\\Users\\ExampleUser\\Experiments", ".\abcd")
```

## License

tidyexp is licensed under the MIT License.