semvec/pypi-packages huggingface dataset:
helltml 0.0.1
Write you frontend using YAML
Requires Python: >=3.12

# HellTML
Ever wondered how to transform your frontend development into a never-ending nightmare?

Introducing my brainchild: "HellTML"! It's a frontend framework that gleefully crams all your HTML and CSS into a YAML file, where indentation errors and misplaced colons reign supreme. Forget about the joys of live reloading or intuitive debugging— with "HellTML", you'll be diving headfirst into a labyrinth of indents gone wild and inexplicable syntax errors. Embrace the chaos and discover a whole new level of frontend development frustration!

<!-- Have you ever thought how could you achive the worst development experience writing frontend?

Well, I did and I gladly want to present you my abomination: `HellTML` a frontend framework that moves all your html and css into a YAML file! -->

## How to use
first you will need to install HellTML:

`> pip install helltml`

the only command you will need is `build`:

`> python -m helltml build --filename=your_yaml_file.yml`

## YAML file format:

### HTML

Each key under the html key represents either an attribute or an element within an HTML document.

for example:

```YAML
pages:
    example_1:
        html:
            head:
                children:
                    title:
                        children_text: "example"
            body:
                children:
                    div:
                        class: "example_class"
```
Explanation:

* Keys such as `head`, `body`, `div`, and `title` correspond to specific HTML tags.

* The `children` key signifies the nested elements or content within each HTML tag.

* The `children_text` key is used to specify plain text content within an element.

* Attributes like `class` denote standard attributes that can be applied to html tags.

and after building we should get the following html file:
```html
<html>
    <head>
        <title>example</title>
    </head>
    <body>
        <div class="example_class"></div>
    </body>
</html>
```

### CSS

Each key under the css key represents a class and its attributes


for example:
```YAML
pages:
    your_page_1:
        html:
        ...
        css:
            "*":
              margin: 0

            body:
                display: flex

            "@media (max-width: 900px)" :
                children: 
                  section span:
                    width: "calc(10vw - 2px)"
                    height: "calc(10vw - 2px)"
```
Explanation:
* Keys such as `"*"`, `"@media (max-width: 900px)"`, `section span`, and `body` represent class selectors in a CSS file.

* The `children`  key indicates nested classes or elements within the respective CSS selectors.

* any other attributes like `margin`, and `display` correspond to standard  css properties.

## Example
open the `examples/login page` folder

run the following command:

`> python -m helltml convert --filename="login_page.yml"`

now you should see a new directory `outdir/login_page` with a files inside named `login_page.css` and `login_page.html`
ltempy 1.6.0
Utilities for Lorentz TEM data analysis and simulation.
Requires Python: >=3.6

# ltempy
ltempy is a set of tools for Lorentz TEM data analysis, simulation, and presentation.

# Features

* Single Image Transport of Intensity Equation (SITIE) reconstruction
* simulations - calculations of phase, B, A, image
* basic image processing - high_pass, low_pass, clipping
* a matplotlib.pyplot wrapper tailored to presenting induction maps and Lorentz data
* an implementation of the CIELAB colorspace
* module-wide unit scaling (i.e., working in nm rather than m)

## Installation

```Bash
python -m pip install ltempy
```

## Documentation

Documentation is available at [https://mcmorranlab.github.io/ltempy/](https://mcmorranlab.github.io/ltempy/).

## Tests

Tests are split into two subdirectories:

1. `tests`
	These are typical unit tests, that assert that functions return the right shape, beam parameters return the right values, etc. Run with `pytest`.
2. `devtests`
	These are tests of the actual functionality, that require a trained eye to evaluate. Run as normal `.py` scripts.

The rationale for `devtests` is that this package is math-heavy, so it's highly possible for the code to run fine, but be wrong. The easiest way to test for this is to check base cases where the developer knows what to look for.
ndfetcher 0.1.1
Fetching nuclear data
Requires Python: >=3.7

A tool to download ENDF6 nuclear data files from the [IAEA website](https://www-nds.iaea.org/public/download-endf/).

## Installation

You can install NDFetcher with `pip`:
```bash
pip install git+https://github.com/nplinden/ndfetcher.git
```

## Examples

You can use the `ndfetch` command to download ENDF6 nuclear data files.

To download all available sublibraries from JEFF-3.3:

```bash
ndfetch jeff33
```

To download a specific set of sublibraries from ENDF-B/VIII.0:

```bash
ndfetch endfb8 decay sfpy
```

Running those two commands in the same directory will result in the following
directory structure:

```
endf6
├── endfb8
│   ├── decay
│   └── sfpy
└─── jeff33
    ├── decay
    ├── n
    ├── nfpy
    ├── sfpy
    └── tsl
```

You can then set the `$ENDF6_PATH` environment variable to the top directory's
path to use the `ndfind` command. This command will search for nuclear data file
paths for you:

```bash
$ ndfind jeff33 n Pu239
/home/nlinden/workspace/NuclearData/endf6/jeff33/n/n_9437_94-Pu-239.dat
```