semvec/pypi-packages huggingface dataset:
omnipyseed 0.0.4
A tiny package for seeding all the RNGs in numerical experiments
Requires Python: >=3.6

# omnipyseed
Omnipyseed is a minimal Python package that seeds all the basic Random Number
Generators (RNGs) in a Python script. The purpose of omnipyseed is to simplify
the process of seeding numerical simulations which use packages such as 
Numpy and Pytorch.


## Dependencies

**omnipyseed** does not depend on any non-essential Python package.


## Installation

You can install **omnipyseed** using pip:
```
pip3 (or pip) install omnipyseed
```
Or you can clone this repository to any of your local directories and install
it from there.
```
$ git clone https://github.com/gdetor/omnipyseed.git
$ cd omnipyseed/
$ pip install .
```

## How to use

```
import numpy as np
from omnipyseed import set_manual_seeds    # import the seeding module from omnipyseed


if __name__ == '__main__':
    set_manual_seeds.universal_seed(13)     # call the universal_seed function to seed
                                            # Python and Numpy
    x = np.linspace(-1, 1, 10)
    y = np.sin(2*np.pi*5*x)
    print(y)
```

## Caveat

Please do not use **omnipyseed** if you'd like to use different random states
for different random parts of your project. Instead you should instantiate 
generator objects with a seed and pass it around (*e.g.*, 
numpy.random.default_rng(*seed*)).
ezbar 1.6
A simple progress bar for loop progress measurement and time estimation.
Requires Python: >=3.7

# EZ Bar

[![PyPI release](https://github.com/erlete/ezbar/actions/workflows/python-publish.yml/badge.svg)](https://github.com/erlete/ezbar/actions/workflows/python-publish.yml)

A simple progress bar for loop progress measurement and time estimation.

_The original idea and base script for this repository was created by @carlospuenteg. I just decided to refactor the code and add some nice features such as remaining and elapsed time counting._

## Features

* Simple and easy to use (create a progress bar and update it)
* Colorful output so that you always see how your loop is progressing
* Estimated time of completion prediction. No need to stare at the screen for minutes!
* Elapsed time display. Know the efficiency of your loops!

https://user-images.githubusercontent.com/76848729/203905732-99d3c091-f375-499d-b990-0893130d106b.mp4

## Installation

The installation of this module is performed via the Python Package Index (PyPI).

### macOS / UNIX

```bash
python3 -m pip install ezbar
```

### Windows

*This operating system is not supported yet.*

## Usage

Just import the `ProgressBar` class and it will be ready to go!

```python
from ezbar import ProgressBar
```

## Example

```python
from time import sleep
from ezbar import ProgressBar

ITERATIONS = 100

# Use default settings:

pb = ProgressBar(ITERATIONS)

for i in range(ITERATIONS):
    sleep(0.05)
    pb.update(i)

# Or customize them all you want!

pb = ProgressBar(ITERATIONS, text="Loading...", width=30)

for i in range(ITERATIONS):
    sleep(0.05)
    pb.update(i)
```

## Disclaimer

This progress bar does not serve a performance counting purpose. It is only meant to be used for orientative loop progress measurement and time estimation. Do not use it for strict performance measurements.
csvtickerlist 0.0.2
Generate a CSV of all current tickers
Keywords: python,stocks,tickers,algo-trading,finance


**csvtickerlist**

A simple package that allows users the ability to generate a CSV file that contains a full list of all active ticker symbols on the marketplace. This package uses a headless, Selenium Chrome browser to fetch this CSV file.


The CSV file contains ticker symbols, along with some basic information (i.e. Share price, count, industry, etc.) NASDAQ hosts this information in its entirety for free and this module only requires making one page request to retrieve the CSV file.


## Example


```python
from csvtickerlist import GetCSV

def GetDataFolder():
	return filedialog.askdirectory(title = 'Select Folder')

def main():
	folder = GetDataFolder()
	GetCSV.GetCSVFile(folder, 10)

	#arg1 (folder) represents the output folder
	#arg2 (10) represents the seconds to wait before closing the web driver.
	#10 seconds is recommended, but increase this when facing connectivity issues.

```



To-Do:

- Add functionality for a filtered output (i.e. valuation range, industry selections, etc.)