semvec/pypi-packages huggingface dataset:
fasttrader 0.5.0
Welcome to FastTrader, Your Gateway to Innovative Financial Analysis!
License: MIT
Keywords: python,yfinance,trading,backtesting,stock market,trading strategies


# FastTrader: Empowering Financial Analysis

FastTrader is a pioneering tool designed to empower users in the dynamic world of quantitative financial analysis. At its core, FastTrader is built on a commitment to transparency and user-driven functionality. Unlike many other platforms, we provide complete visibility into the inner workings of our system, enabling you not only to utilize but also to comprehend every facet of your trading strategies.

## Democratizing Financial Decision-Making

What truly sets FastTrader apart is our dedication to democratizing financial decision-making. Our open-source approach ensures that everyone, from individual investors to professional analysts, has equal access to sophisticated tools. We foster a community where knowledge and resources are openly shared, creating an environment where financial analysis becomes accessible to all.

## Unmatched Speed

Speed is paramount in financial analysis, and FastTrader excels in this regard. Leveraging the power of Numba, an advanced performance compiler, FastTrader accelerates numerous functions. This technological edge allows you to test potentially thousands of trading strategies in real-time, providing you with a significant advantage in today's fast-paced market.

## Join Us on the Journey

Join us on this journey to reshape financial analysis. With FastTrader, your strategies are limited only by your imagination.

## Disclaimer

**Disclaimer:** None of the research derived from this software constitutes financial advice. The contributors of this software shall not be held liable for its accuracy or the outcome of any decisions derived from the research produced by it.
IconHound 0.0.5
WebIconFinder : An unofficial API for scraping images off IconFinder.com for web development.
License: MIT
Keywords: conversion



<p align="center">WebIconFinder : An unofficial  API for scraping images off <a href="https://www.iconfinder.com/" target="_blank">IconFinder</a> for web development.</p>
<div align="center">
<img src="https://uploads-ssl.webflow.com/5d9ba0eb5f6edb77992a99d0/5e1ef88d24ceb82897e14ec0_182503-512%20(1).png" style="border:1px solid white;" height="100" width="100">
</div>



## Initiate the Class  

```python

#To scrape for normal icons , create an instance of the class IconFinder with the name of the image to search  , for example :

from WebIconFinder import IconFinder # Import the class from the package
find_icon=IconFinder("mail")
```

###  1 : Scrape web links of images

```python

#To scrape for links of images , call the images() function from the initialized class , for example : 

find_icon=IconFinder("mail")
find_icon.images()
```

###  2 : Get Links to download and edit images

```python

#To scrape for links of images to download locally  , call the get_links() function from the initialized class , for example : 

find_icon=IconFinder("mail")
find_icon.get_links()
```

###  3: Show/Display a particular Icon

```python

#To display an Icon   , call the show_image(image_number:int) function from the initialized class , for example : 

find_icon=IconFinder("mail")
find_icon.show_image(2) # Shows the second image from all scraped images
```

###  4 : Download an icon

```python

#To download an icon locally  , call the save_image(path:str,image_number:int) function from the initialized class , for example : 

find_icon=IconFinder("mail")
find_icon.save_image("/Users/myname/Desktop/x.jpeg",6) # Saves the 6th image in the Desktop as x.jpeg
```

<h2 align="center">There is also a class for 3D images.</h2>
<p></p>

```python

#To scrape for links of images , call the images() function from the initialized class , for example : 

from WebIconFinder import IconFinder3D # Import the 3D class
find_icon=IconFinder3D("mail")
#All functions are the same as for the IconFinder Class.....

```

<p align="center">Examples : </p>

<div align="center">
<img src="examples.png" >
</div>

<div align="center">
<img src="bs4.png" height="130" width="300">
  <p align="center">Made with Python and BeautifulSoup</p>
</div>
IconFinderAPI 0.0.5
WebIconFinder : An unofficial API for scraping images off IconFinder.com for web development.
License: MIT
Keywords: conversion



<p align="center">WebIconFinder : An unofficial  API for scraping images off <a href="https://www.iconfinder.com/" target="_blank">IconFinder</a> for web development.</p>
<div align="center">
<img src="https://uploads-ssl.webflow.com/5d9ba0eb5f6edb77992a99d0/5e1ef88d24ceb82897e14ec0_182503-512%20(1).png" style="border:1px solid white;" height="100" width="100">
</div>



## Initiate the Class  

```python

#To scrape for normal icons , create an instance of the class IconFinder with the name of the image to search  , for example :

from WebIconFinder import IconFinder # Import the class from the package
find_icon=IconFinder("mail")
```

###  1 : Scrape web links of images

```python

#To scrape for links of images , call the images() function from the initialized class , for example : 

find_icon=IconFinder("mail")
find_icon.images()
```

###  2 : Get Links to download and edit images

```python

#To scrape for links of images to download locally  , call the get_links() function from the initialized class , for example : 

find_icon=IconFinder("mail")
find_icon.get_links()
```

###  3: Show/Display a particular Icon

```python

#To display an Icon   , call the show_image(image_number:int) function from the initialized class , for example : 

find_icon=IconFinder("mail")
find_icon.show_image(2) # Shows the second image from all scraped images
```

###  4 : Download an icon

```python

#To download an icon locally  , call the save_image(path:str,image_number:int) function from the initialized class , for example : 

find_icon=IconFinder("mail")
find_icon.save_image("/Users/myname/Desktop/x.jpeg",6) # Saves the 6th image in the Desktop as x.jpeg
```

<h2 align="center">There is also a class for 3D images.</h2>
<p></p>

```python

#To scrape for links of images , call the images() function from the initialized class , for example : 

from WebIconFinder import IconFinder3D # Import the 3D class
find_icon=IconFinder3D("mail")
#All functions are the same as for the IconFinder Class.....

```

<p align="center">Examples : </p>

<div align="center">
<img src="examples.png" >
</div>

<div align="center">
<img src="bs4.png" height="130" width="300">
  <p align="center">Made with Python and BeautifulSoup</p>
</div>
aiter-timeouts 1.1.0
Timeout functionality for asynchronous iterators
License: MIT
Requires Python: >=3.7

# aiter-timeouts

![GitHub Workflow Status](https://img.shields.io/github/actions/workflow/status/thearchitector/aiter-timeouts/ci.yaml?label=tests&style=flat-square)
![PyPI - Downloads](https://img.shields.io/pypi/dw/aiter-timeouts?style=flat-square)

Timeout functionality for asynchronous iterators. Supports timeouts on the total time to exhaust an asynchronous iterator, or the time it takes for any given step.

Supports Python 3.7+.

## Example

Just wrap your async iterator in a call to `with_timeout`, like so:

```python
from aiter_timeouts import with_timeout

async def async_iter():
    for i in range(10):
        await asyncio.sleep(0.5)
        yield i

try:
    async for val in with_timeout(async_iter(), timeout=6, timeout_per_step=1):
        ...
except IterationTimeoutError as e:
    print(f"step {e.step} took too long")
except IteratorTimeoutError as e:
    print(f"only reached step {e.step} before timing out")
```

## License

MIT License
Copyright (c) 2023 Elias Gabriel
mvc-flask 2.9.0
turn standard Flask into mvc
License: MIT
Requires Python: >=3.8.0,<4.0.0
Keywords: flask,flask extensions,flask mvc,flask-mvc,mvc flask,flask design pattern

![GitHub code size in bytes](https://img.shields.io/github/languages/code-size/marcuxyz/mvc_flask) ![GitHub Workflow Status](https://img.shields.io/github/workflow/status/marcuxyz/mvc_flask/unit%20test) ![GitHub](https://img.shields.io/github/license/marcuxyz/mvc_flask) ![PyPI - Downloads](https://img.shields.io/pypi/dm/mvc_flask) ![PyPI - Python Version](https://img.shields.io/pypi/pyversions/mvc_flask) ![PyPI](https://img.shields.io/pypi/v/mvc_flask)

You can use the MVC pattern in your Flask application using this extension.

## Installation

Run the follow command to install `mvc_flask`:

```shell
$ pip install mvc_flask
```

## Basic Usage

To start the `mvc_flask` you need to import and register in your application.


```python
from flask import Flask
from mvc_flask import FlaskMVC

app = Flask(__name__)
FlaskMVC(app)
```

Or use `application factories`, e.g:

```python
mvc = FlaskMVC()

def create_app():
  ...
  mvc.init_app(app)
```

**By default the `mvc_flask` assumes that your application directory will be `app` and if it doesn't exist, create it!**
**If you can use other directories, you can use the `path` parameter when the instance of FlaskMVC is initialized. E.g:**

```python
mvc = FlaskMVC()

def create_app():
  ...
  mvc.init_app(app, path='src')
```

Now, you can use `src` as default directory for prepare your application.

You structure should be look like this:

```text
app
├── __ini__.py
├── controllers
│   └── home_controller.py
├── routes.py
└── views
    ├── index.html
```

Please visit the documentation to check more details https://marcuxyz.github.io/mvc-flask
getdominantcolor 0.10
Extracts the dominant color from an image represented by an array.
License: MIT
Keywords: rgb,find


# Extracts the dominant color from an image represented by an array.

## pip install getdominantcolor

### Tested against Windows / Python 3.11 / Anaconda




```python

Parameters:
- x (numpy.ndarray): The input image represented as a NumPy array with shape (height, width, channels - 3).

Returns:
tuple: A tuple representing the dominant color in the RGB format (red, green, blue).

The function reshapes the input array to a two-dimensional array and calculates a numerical code for each pixel
based on its RGB values. The dominant color is then determined by counting the occurrences of these codes and
returning the RGB values of the code with the highest frequency.

Example:
	from getdominantcolor import get_dom_color
	import numpy as np
	np.random.seed(0)
	x = np.random.randint(0, 255, (4000, 4000, 3))
	get_dom_color(x)
	# (81, 101, 238)
```