semvec/pypi-packages huggingface dataset:
py-starter-auto-template 0.0.2
Creating a template Python package with a CLI interface.
Requires Python: >3.11
Keywords: python starter template cli version control python-starter python-starter-template python-starter-cli

# PythonStarter
 Auto-generate starter template of python3 and create env

# Install
```bash
 pip install py-starter-auto-template
```

# Usage
## To create a project base template with bump2version managing versioning
```bash
  pyinit -m create <project_name> 
```
In your project folder, it will create 
```bash
  package_name/
  |-- src/
  |   |-- __init__.py
  |-- tests/
  |   |-- test_placeholder.py
  |-- .bumpversion.cfg
  |-- .gitattributes
  |-- .girigore
  |-- MANIFEST.in
  |-- pytest.ini
  |-- setup.py
```

## To create github/workflows
```bash
  pyinit -m create <project_name> -i ci 
```

It will create
```bash
.github/
  |-- workflows/
  |   |-- <project_name>_ci.yml

```
revel2d2l 0.3.0
Import Revel grade data into D2L LMS
Requires Python: >=3.7

=========
revel2d2l
=========


.. image:: https://img.shields.io/pypi/v/revel2d2l.svg
        :target: https://pypi.python.org/pypi/revel2d2l

.. image:: https://img.shields.io/travis/datagazing/revel2d2l.svg
        :target: https://travis-ci.com/datagazing/revel2d2l

.. image:: https://readthedocs.org/projects/revel2d2l/badge/?version=latest
        :target: https://revel2d2l.readthedocs.io/en/latest/?version=latest
        :alt: Documentation Status



Import Revel grade data into D2L LMS

Features
--------

* Converts Revel csv file to D2L csv file
* Matches user data based on a reference file from D2L and several heuristics
* Default options should probably just work, apart from which files to process
* See the command line utility usage message for description of heuristics
* The script is quiet apart from warnings by default (use -v for more info)

Examples
--------

.. code-block:: console

  revel2d2l -h  # Print usage message and exit

  revel2d2l -v -i revel.csv -u d2l_users.xlsx -o upload_this_to_d2l_grades.csv

License
-------

* Free software: MIT license

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.

Credits
-------

This package was created with Cookiecutter_ and the `audreyr/cookiecutter-pypackage`_ project template.

.. _Cookiecutter: https://github.com/audreyr/cookiecutter
.. _`audreyr/cookiecutter-pypackage`: https://github.com/audreyr/cookiecutter-pypackage
excel-framework 0.4.5
A framework for creating excel files declaratively.
Requires Python: >=3.7

A framework for creating excel files declaratively.

[openpyxl](https://pypi.org/project/openpyxl/) is a different library that is often used for creating excel files. However, it only provides very rudementary controls forcing you to access, style and fill every cell individually in an imperative manner. This can get unwieldy and difficult to maintain very quickly which is the problem solved by this package.  
[excel-framwork](https://pypi.org/project/excel-framework/) builds on top of [openpyxl](https://pypi.org/project/openpyxl/) providing you with a large set of ui components that you can compose into new ones to create excel files in an easy, readable and maintainable way.  
The archictecture of [excel-framwork](https://pypi.org/project/excel-framework/) was inspired by the cross platform ui development framework [flutter](https://flutter.dev/).

## Quickstart
An excel file with one cell containing hello world in bold:
```python
ExcelFile(
    "hello.xlsx", 
    sheets=[
        ExcelSheet(
            "first sheet",
            child=Styler(
                child=ExcelCell("Hello World!"),
                style=Style(
                    text_style=TextStyle(bold=True)
                )
            )
        )
    ]
).create()
```
mailez 1.0.5
Mass mail sender with custom tweaks
Keywords: email,mail

A package to make sending mails to multiple people while adding their names to each message automaticly easy. I tested it with Gmail but it might work with some other e-mail service providers.
Usage:
```
from mailez import functions as mz
my_gmail_address = "supercoolemailofsupercoolperson@gmail.com"
my_password = "heyheyheyiamverycool12345"
my_subject = "Asking How The Recipient Is Feeling At The Moment"
my_csv_path = "path/to/csv/file.csv"
my_message = "Dear {name},\nHow are you?"
obj = mz.Mail(my_gmail_address, my_password, my_subject, my_csv_path, my_message)
obj.Send()
```
The format for CSV file is given below:
```
email,name
supercoolguy@coolmail.com,Jake Peralta
anothersupercoolguy@mail.com,Joey Tribbiani
supercoolbusinessmail@coolbusiness.com,CoolBusiness LTD.
```
steamship 2.17.34
The fastest way to add language AI to your product.

<picture>
  <source media="(prefers-color-scheme: dark)" srcset="./docs/nextra/_static/Steamship-symbol-light.png">
  <img alt="Steamship Logo" src="./docs/nextra/_static/Steamship-symbol-dark.png" width="100">
</picture>

# Steamship Python SDK

🚢 [Steamship](https://steamship.com) is the fastest way to Build, Scale, and Monitor AI Agents.

This library is for:
- Building and deploying `Agents`, `Packages`, and `Plugins` on Steamship
- Making client calls to a Steamship `Package` from a Python environment

**Are you trying to build a Bot or Agent? Please check out our starter project and guidebook here:**

[Multimodal Agent Starter](https://github.com/steamship-core/multimodal-agent-starter)

[Agent Guidebook](https://www.steamship.com/learn/agent-guidebook)

**Are you trying to host a LangChain agent you've written?  Check out our LangChain compatibility library here:**

🚢 🦜️🔗 [Steamship-Langchain](https://github.com/steamship-core/steamship-langchain)

## Installing

Install via pip:

```
pip install steamship
```

## Documentation

[Full Documentation](https://docs.steamship.com/)

## Support and Discussion

Join our [Discord](https://steamship.com/discord)
audio-sleuth 0.0.2
an open-source framework for detecting audio generated from generative systems


<p align="center">
  <img src="assets/header.gif" alt="animated" />
</p>


# Audio Sleuth 

A torch based open-source framework for detecting audio generated from generative systems. The overarching goal of this repository is to be a toolbox for datasets, augmentations, and pretrained baseline models to assist researchers in the task of audio deepfake detection.

## Install

To install, simply use pip:

```
pip install audio-sleuth
```

## Usage

The goal of this package is to contain augmentations, models, and losses all as a `torch.nn.Module` class. Each augmentation contains an internal `LabelAlignment` such that you can implement various time-frequency transformations to automatically translate the sample-wise labels as well. 

Here is an example of how to chain together augmentations on the Half Truth Dataset.

```python
from audio_sleuth.augmentations import Resample, LFCC, Augmentations
from audio_sleuth.data.datasets import HalfTruthDataset 

# Augmentation chain
transform = Augmentations(
  [
    Resample(input_sr=48000, new_sr=16000, return_original_sr=False), # Downsample block
    LFCC(
      fs=16000, n_fft=512, hop_size=128, win_size=128, n_filters=128, n_lfcc=40 # LFCC augmentation
    )
  ]
)

# Returns torch Dataset that can be fed into DataLoader
dataset = HalfTruthDataset(
  path_to_txt, # Initialize to your txt file of filepaths and labels from dataset
  fs=16000,
  transform = transform
)
```