semvec/pypi-packages huggingface dataset:
superanime 1.0.3
The best package in Python to get anime information and anime gifs!

# SuperAnime
The best package in Python to get anime information and anime gifs!

## Installation:
```
pip install superanime
```

## Example Usage:
```py
import asyncio

from superanime import AnimeClient
from superanime.ext.types import SFWGif, SearchType

anime = AnimeClient() 

async def main():
    await anime.start() # Starts the client
    
    gif = anime.gif(
        bucket=SFWGif.KISS, # Also works with strings!
        as_object=True # If you want to send a 'GifResult' object with additional info like anime name. Default to 'True'
    )
    print(gif.url) # Print the GIF URL

    search = await anime.search(
        query="One Piece", # The query to search in kitsu.io
        type=SearchType.ANIME # The type of search you want to search for. ('ANIME' or 'MANGA') If none provided the anime type will be searched.
    )
    print(search.name) # Print the Anime name
    
if __name__ == "main":
    asyncio.run(main())
```


## Methods:

```py
superanime.AnimeClient(print_on_ready: bool = True) -> AnimeClient

AnimeClient.gif(bucket: SFWGif | NSFWGif | str, as_object: bool = True) -> GifResult
Anime.search(query: str, type: SearchType | str = None) -> SearchResult
```
<br/>
    
   _~ Made by Noraa08 for MoonlightGroup_
verifytx 0.3.0
A python library to verify blockchain confirmations and transactions integrated with Excel.


## Introduction
verifytx is a Python library to verify blockchain confirmations and transactions integrated with Excel.
It was born from a lack of existing libraries to verify on-chain transactions automatically and blazingly fast.
All kudos to the openpyxl team and library to read/write natively from Python the Office Open XML format.

## Security
By default verifytx does not guard against quadratic blowup or billion laughs xml attacks. To guard against these install defusedxml.

## Documentation
The documentation is at: https://krpbtc.com

* installation methods
* supported coins/tokens
* how to contribute
slmndr 1.1
Lightning fast python user interfaces created with opengl.
Requires Python: >=2.7

# salamander

![](https://img.shields.io/badge/pypi-slmndr-green)
![](https://img.shields.io/pypi/dm/slmndr?color=green&label=downloads%20per%20month)
![](https://img.shields.io/pypi/status/slmndr)
![](https://img.shields.io/pypi/pyversions/slmndr?color=green)
![](https://img.shields.io/pypi/v/slmndr?color=green&label=latest%20release)
![](https://img.shields.io/pypi/l/slmndr?color=green)


![](https://img.shields.io/badge/github-salamander-green)
![](https://img.shields.io/github/issues-raw/bitpigeon/salamander?color=red&label=open%20issues)
![](https://img.shields.io/github/issues-pr-raw/bitpigeon/salamander?color=red&label=open%20pull%20requests)
![](https://img.shields.io/github/issues-closed-raw/bitpigeon/salamander?color=green&label=closed%20issues)
![](https://img.shields.io/github/issues-pr-closed-raw/bitpigeon/salamander?color=green&label=closed%20pull%20requests)
![](https://img.shields.io/github/commits-since/bitpigeon/salamander/latest?color=green&label=commits%20since%20latest%20release)
![](https://img.shields.io/github/contributors/bitpigeon/salamander?color=green)
![](https://img.shields.io/github/stars/bitpigeon/salamander?color=green)
![](https://img.shields.io/github/downloads/bitpigeon/salamander/total?color=green)
streamtask 0.0.9
Parallel Stream Task for Python
Keywords: Parallel Stream Task

# Streamtask
**Streamtask** is a lightweight python parallel framework for parallelizing the computationally intensive pipelines. It is similar to Map/Reduce, while it is more lightweight. It parallelizes each module in the pipeline with a given processing number to make it possible to leverage the different speeds in different modules. It improves the performance especially there are some heavy I/O operations in the pipeline.

### Example
Suppose we want to process the data in a pipline with 3 blocks, f1, f2 and f3. We can use the following code to  parallelize the processing. We can also directly add a data list or give a file name by using `add_data`.

``` python
def f1(total):
    import time
    for i in range(total):
        time.sleep(0.002)
        yield i * 2

def f2(n, add, third = 0.01):
    time.sleep(0.02)
    return n + add + third

def f3_the_final(n):
    time.sleep(0.03)
    return n + 1

if __name__ == "__main__":
    total = 100000
    stk = StreamTask(total = total)
    stk.add_data(data = range(total), batch_size=10) # Also support directly stream reading file
    #stk.add_module(f1, 1, total = total)
    stk.add_module(f2, 2, args = [0.5], third = 0.02)
    stk.add_module(f3_the_final, 2)
    stk.run(parallel = True)
    stk.join()
    res = stk.get_results()
    print(stk.get_results())
```

```
stream_reader (1/1):  79%|██████████████████████████████████████████████▋            | 7923/10000 [00:05<00:01, 1567.68it/s]
f2 (2/2):  29%|████████████████████▉                                                   | 1927/6635 [00:04<00:09, 476.72it/s]
f3_the_final (2/2): 100%|█████████████████████████████████████████████████████████████▉| 1927/1928 [00:04<00:00, 476.55it/s]
```