semvec/pypi-packages huggingface dataset:
deepss_unsupervised 0.5.1
Tools for unsupervised classification of acoustic signals.
Requires Python: >=3.6

_DeepSS-unsupervised_ has been renamed _DAS-unsupervised_ and can be found on github at [https://github.com/janclemenslab/das_unsupervised]() and on pypi at [https://pypi.org/project/das_unsupervised]().
KakaoV2 1.1.0
Kakaotalk LOCO/HTTP API protocol wrapper for python.

KakaoV2
=======
KakaoV2 is Kakaotalk LOCO/HTTP API protocol wrapper for python.

Introduction
------------
Loco protocol compatible python library
This is discord.py style.

Quick Start
-------
```python
import KakaoV2

client = KakaoV2.Client(device_uuid="DeviceUUID")

@client.event
async def on_ready():
    print("Ready!")

@client.event
async def on_message(msg):
    print(msg.content, msg.author)
    await msg.reply("TEXT")
    await msg.send("TEXT")

client.run("ID", "PW")
```

License
-------
MIT Licence
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wtoolzargs 0.1.0
wtoolzargs contains core filtering and ordering logic for web applications.
Requires Python: >=3.6
Keywords: wtoolzargs

# wtoolzargs

![](https://github.com/e-k-m/wtoolzargs/workflows/main/badge.svg)

> wtoolzargs contains core filtering and ordering logic for web applications

[Installation](#installation) | [Getting Up And Running](#getting-up-and-running) | [Examples](#examples) | [API](#api) | [See Also](#see-also)

wtoolzargs contains core filtering and ordering logic for web applications. The main feature are:

- Filtering and

- ordering for SQLAlchemy models.

## Installation

```bash
pip install wtoolzargs
```

## Getting Up and Running

```bash
nox -l
```

## Examples

```python
import wtoolzargs

# sqlalchemy model
class Hacker(Base):
    __tablename__ = "hacker"
    id = Column(Integer, primary_key=True)
    a = Column(String)
    b = Column(String)
    c = Column(String)
    d = Column(String)
    e = Column(String)

f = wtoolzargs.filter_(Hacker, "a eq 'a' and b eq 'b'")
res = Hacker.query.filter(f).all()

o = wtoolzargs.order(Hacker, "a asc, b desc")
res = Hacker.query.filter(f).order_by(*o).all()    
```

## API

FIXME

## See Also

FIXME
filecomp 0.0.3
Function that finds maximal and minimal sized contents of a directory
Requires Python: >=3.7


  Fcomp - short for file/folder comparison
  
  Function receives the path and analyzes the directory it represents in order to find the files/directories of maximum and minimum sizes that the initial folder contains.
  Then returns paths to those files.
  Necessary info can be taken from returned dictionary with the use of keys "maxs","mins" and "eq"(if somehow all contents of a directory have equal size). 
  In case of a path to an empty directory inputted as argument None is returned.
  
  !!!
  Usage of backslash in paths should be avoided due to it causing the function to fail (SyntaxError).
  Either double backslash or slash should be used instead. Alternatively, the path can be initially inputted as raw, e.g. fcomp(r'C:\Users')