semvec/pypi-packages huggingface dataset:
damnlang 0.1.1
Damn
License: MIT
Requires Python: >=3.9,<4.0

# damn

**damn** (desperately agonizing math noobs) is a language to help you write knowledge assessment test generators.

Language will help you in variables constraints declaration and generate unique pairs of data. Then, the generated pair of variables can be evaluated with the formula (via wolframalpha integration).

Syntax:

```damn
1 > x > 10
y in [1, 2, 3]
(a, b) in [(4, 5), (1, 10)]
```

## Example

Constraints:

```damn
10 > a > 20
(v1, v2) in [(1, 2), (4, 8)]
```

Formula:

```damn
a = (v2 - v1)/t
```

Making a test:

```python
from damn import DefinitionSet, Calculator
import asyncio

calculator = Calculator(["DEMO"])

async def main():
    def_set = DefinitionSet.from_expressions([
        "10 < a < 20", 
        "(v1, v2) in [(1, 2), (4, 8)]"
    ])
    data = def_set.get_data()
    print(
        "What is delta t if " + 
        ", ".join(
            (f"{k} = {v.get_common_representation()}" for k, v in data.items())
        )
    )
    result = await calculator.calculate(data, "a = (v2 - v1)/t")
    answer = float(input("your answer > "))
    if answer == result.v:
        print("great!!")
        return
    print(f"BAD student. the right answer is {result.v}")

asyncio.run(main())
```
perfectextractor-ui 0.1.8
A web frontend for perfectextractor
License: MIT
Requires Python: >=3.6

Quick start
-----------
This package provides a user interface for [PerfectExtractor](https://github.com/UUDigitalHumanitieslab/perfectextractor) in the form of a Django web application.
It can be used as part of bigger app (such as [TimeAlign](https://github.com/UUDigitalHumanitieslab/timealign)) or stand-alone.


## How to install inside another Django app:

1. Add "perfectextractor_ui" to your INSTALLED_APPS setting like this:

```
    INSTALLED_APPS = [
        ...
        'widget_tweaks',
        'perfectextractor_ui,
    ]
```

2. Include the perfectextractor_ui URLconf in your project urls.py like this:

```
    path('perfectextractor/', include('perfectextractor_ui.urls')),
```

3. Run ``python manage.py migrate`` to create the required models.

4. Run your app and configure your corpora in the admin panel.

## How to run stand-alone:

1. Create a python virtual environment for running perfectextractor-ui:

```
virtualenv -ppython3 /path/to/venv/
source /path/to/venv/bin/activate
```

2. Install package and requirements:

```
cd /path/to/perfectextractor-ui
pip install -r requirements.txt
pip install .
```

3. Run ``python manage.py migrate`` to create the required models.

4. Start the app:

```
python manage.py runserver
```

5. Configure your corpora in the admin panel (e.g. [http://localhost:8000/admin/](http://localhost:8000/admin))
rubikaClient 1.1.5
rubika client handler
License: MIT
Requires Python: ~=3.5
Keywords: rubika,telegram,rubx,telethon,pyrogram,rubikaClient,rubika-bot,telegram-bot



#rubikaClient

##rubika a messenger for iranina!

###info

rubika.ir and web.rubika.ir


#installing

```pip install rubikaClient```


#examples

'''python

from rubikaClient import Client


with Client(...) as app:

    app.sendMessage(chat_id='', text='hey my bro')
```
arcade-imgui 0.5
IMGUI integration for Python Arcade
License: MIT
Requires Python: >=3.8,<3.12
Keywords: arcade,game,gui

# Arcade ImGui

[The Python Arcade Library](https://arcade.academy/) + [pyimgui](https://github.com/swistakm/pyimgui) = :heart:

:package: [Package](https://pypi.org/project/arcade-imgui/)

## Prerequisite

Get [Poetry](https://python-poetry.org/)

## Clone

```bash
git clone https://github.com/kfields/arcade-imgui.git
cd arcade-imgui
poetry shell
poetry install
```

## Run an example
```bash
cd examples
python basic.py
```

## Run the Demo
```bash
cd imdemo
poetry install
python imdemo
```

## Run the ImFlo Demo
```bash
cd imflo
poetry install
python imflo
```