semvec/pypi-packages huggingface dataset:
OOPyGame 0.0.5
An object oriented python library for building user interfaces based on pygame

# OOPyGame

Object oriented wrapper on pygame to simplify making UI for pygame applications.
Supported layouts:
- Absolute layout (default one)
- Horizontal layout
- Vertical layout

Supported widgets:
- Widget
- Button
- Label
- ImageBox
- Slider
- List
- MenuBar
- Menu
- Action

To use the library, import the windowmanager and the needed widgets from PyGameUI

```python
from OOPyGame import WindowManager, Button, List, MenuBar, Menu, Action, MenuSeparator, HorizontalLayout, VerticalLayout, ImageBox, Slider
import pygame
# ===== Build pygame window and populate with widgets ===================
pygame.init()
class MainWindow(WindowManager):
    def __init__(self):
        # Initialize the window manager
        WindowManager.__init__(self, "Face box", (800,600))
        self.mn_bar = self.build_menu_bar()
        self.file = Menu(self.mn_bar,"File")
        new = Action(self.file,"New")
        sep = MenuSeparator(self.file)
        quit = Action(self.file,"Quit")
        quit.clicked_event_handler = self.fn_quit
        self.edit = Menu(self.mn_bar,"Edit")

        self.layout_1 = HorizontalLayout()
        self.layout_2 = VerticalLayout()

        # Build an image Box
        self.main_video = ImageBox()

        # Build a slider
        self.time_slider = Slider()
        self.time_slider.value=0.5
        self.time_slider.valueChanged_callback = self.slider_updated
        self.time_slider.mouse_down_callback = self.slider_mouse_down

        # Build a list of items
        self.test_ui1 = List(list=[f"item {i}" for i in range(100)])
        self.test_ui3 = Button("Hello 3")

        self.layout_1.addWidget(self.test_ui1,0.2)
        self.layout_1.addWidget(self.layout_2,0.8)

        self.layout_2.addWidget(self.main_video,0.7)
        self.layout_2.addWidget(self.time_slider,0.05)

        self.layout_2.addWidget(self.test_ui3,0.25)

        self.addWidget(self.layout_1)

        # Build a timer that repeats every 1/24 secondes
        self.timer = self.build_timer(self.do_stuf,1/24)
        self.timer.start()

    def slider_mouse_down(self):
        # when the slider is pressed with mouse this callback is triggered
        pass

    def slider_updated(self, val):
        # When slider value changed this callback is triggered
        pass

    def do_stuf(self):
        # Here do something that will be executed every timer tick
        pass

    def fn_quit(self):
        self.Running=False

# =======================================================================

#
#clip.preview()
if __name__=="__main__":
    mw = MainWindow()
    mw.loop()
```
pybet-peaky76 0.1.0
A library of betting utilities to assist with calculation of bets, stakes and markets
Requires Python: >=3.9

# pybet
pybet is a library of betting utilities to assist with calculation of bets, stakes and markets

## Installation

`pip install pybet`

## Usage

This initial release contains an Odds class which enables conversion from and to the following types of odds or odds-equivalent:

* Decimal odds, e.g. 2.5
* Fractional odds, e.g. 6/4
* American moneyline odds, e.g. +150 
* Implied percentage, e.g. 40 
* Implied probability, e.g. 0.4

Internally, the value of an Odds instance is stored as a Decimal, making decimal odds the effective default. 
Odds can be instantiated directly as decimals or via a class method, specifying the type of odds being instantiated from. 
Any Odds instance can then be output to any type with a to_{type} method, e.g.

```
from pybet import Odds

o = Odds(2.5)
o.to_moneyline()    # +150
o.to_percentage()   # 40

o = Odds.fractional(6, 4)
o.to_probability()  # 0.4
```

The to_fractional() method requires a set of fractional odds to work from. It will then select the closest matching value 
from that set. For convenience, a set of standard odds, representing those most typically found in the UK, has been provided.

```
o.to_fractional('5/4', '6/4', '7/4', '2/1') # 6/4
o.to_fractional(Odds.STANDARD_FRACTIONALS) # 6/4
```

Comparisons can be made between Odds instances. It is possible to check if one Odds instance is shorter (<)
or longer (>) than another, e.g.

```
Odds(2.5) < Odds.fractional(11, 4)        # True
Odds.probability(50) > Odds(3)            # False
```

There are properties to compare Odds instances to evens, and a convenience method for evens itself, e.g.

```
o.is_odds_against   # True
o.is_odds_on        # True
Odds.evens() == 2   # True
```

There are also operators to perform calculations with Odds instances, though this is more useful in some cases than others.
For example, it is possible to calculate the combined odds of two 3/1 shots as follows:

```
Odds.fractional(3, 1) + Odds.fractional(3, 1) == Odds.evens  # True
```
flask-redmail 0.1.0
Email sending for Flask
Requires Python: >=3.6.0


# Flask Red Mail: Email Sending for Flask
> Flask extension for Red Mail

---

## What is it?
Flask Red Mail is Flask extension for Red Mail email sending library.
Red Mail is a powerful email sender library capable of including
attachments from various formats, embedding images, parametrization
with Jinja etc. This library harness Red Mail's power in order to 
make it trivial to:

- Send verification emails to users
- Create email based *forgot password* functionality
- Create Flask based email news letters


---

## Author

* **Mikael Koli** - [Miksus](https://github.com/Miksus) - koli.mikael@gmail.com
ImagineS 0.0.1
ImagineS (Image Engine Search) tool augments an image dataset by searching a series of queries in Google Images.
Requires Python: >=3.7


# ImagineS

ImagineS (Image Engine Search) tool augments an image dataset by searching a series of queries in Google Images.

## Install

---

* Create a new Conda environment

    `conda create -n data_aug python=3.7`

* Activate environment

    `source activate data_aug`

* Install library

    `pip install dataset_augmentation`

## Usage

---

**Example:** Download `apple` and `water` related images by adding the query searches that would belong to each class.

```python
from imagines import DatasetAugmentation
dataset_augmentation = DatasetAugmentation(
    driver_type='chrome',
    driver_path='path_to/chromedriver',
)
label_queries = {
    'apple': ['apple'],
    'water': ['water', 'water bottle'],
}
max_links_to_fetch = 3
sleep_between_interactions = 1
image_shape = (224, 224)
resize_images = True
output_dir = 'images/'

dataset_augmentation.augment_dataset(
    label_queries,
    output_dir,
    max_links_to_fetch,
    image_shape,
    resize_images,
    sleep_between_interactions
)
```

## License

---

[MIT License](LICENSE)