semvec/pypi-packages huggingface dataset:
youscribe 0.0.3
Library to transcribe YouTube videos using Whisper model
Requires Python: >=3.10

# Transcribe YouTube videos using Whisper models

Adopts [faster_whisperer](https://github.com/SYSTRAN/faster-whisper), a cTransformer's based model for faster transcription.

## Usage

```python
from youscribe import transcribe

transcript = transcribe(url="https://www.youtube.com/watch?v=9bZkp7q19f0")

transcript.text()
```

### Prompting

By default, the video title and description are used as prompts to the transcription model. But you can also specify your own prompt:

```python
transcript = transcribe(
    url="https://www.youtube.com/watch?v=9bZkp7q19f0",
    prompt="Enter prompt here"
)
```

You can also choose not to include prompt by setting `prompt=False`.

```python
transcript = transcribe(
    url="https://www.youtube.com/watch?v=9bZkp7q19f0",
    prompt=False
)
```

### Working with `WhisperTranscript` objects

The `transcribe()` function, if executed successfully, will return a `WhisperTranscript` object. You can view the transcript as plain text, SRT-formatted text, or a Python dictionary.

```python
transcript = transcribe(
    url="https://www.youtube.com/watch?v=9bZkp7q19f0",
    prompt=False
)

transcript.text()
transcript.srt()
transcript.json()
transcript.segment
```

### Customise Whisper model

In the transcribe function, you can pass your own custom Whisper model:

```python
from youtescribe import WhisperTranscriber
from youtescribe import models

custom_transcriber = WhisperTranscriber(model_size = models.TINY_EN, cpu_threads=6, device="auto")

transcript = transcribe(
    url="https://www.youtube.com/watch?v=9bZkp7q19f0",
    transcriber=custom_transcriber
)
transcript.text()
```
FSI-DQ-Fabric 1.0.5
DQ Solution to answer all DQ needs.
Requires Python: >=3.6

Make sure you have upgraded version of pip
Windows

py -m pip install --upgrade pip
Linux/MAC OS

python3 -m pip install --upgrade pip
Create a project with the following structure
packaging_tutorial/
├── LICENSE
├── pyproject.toml
├── README.md
├── setup.cfg
├── src/
│   └── example_package/
│       ├── __init__.py
│       └── example.py
└── tests/
touch LICENSE
touch pyproject.toml
touch setup.cfg
mkdir src/FSI_DQ_Fabric
touch src/FSI_DQ_Fabric/__init__.py
touch src/FSI_DQ_Fabric/main.py
mkdir FSI_DQ_Fabric

#pyproject.toml
This file tells tools like pip and build how to create your project

[build-system]
requires = [
    "setuptools>=42",
    "wheel"
]
build-backend = "setuptools.build_meta"
build-system.requires gives a list of packages that are needed to build your package. Listing something here will only make it available during the build, not after it is installed.

build-system.build-backend is the name of Python object that will be used to perform the build. If you were to use a different build system, such as flit or poetry, those would go here, and the configuration details would be completely different than the setuptools configuration described below.

Setup.cfg setup
Using setup.cfg is a best practice, but you could have a dynamic setup file using setup.py

[metadata]
name = example-pkg-YOUR-USERNAME-HERE
version = 0.0.1
author = Example Author
author_email = author@example.com
description = A small example package
long_description = file: README.md
long_description_content_type = text/markdown
url = https://github.com/pypa/ODP_DQ
project_urls =
    Bug Tracker = https://github.com/pypa/ODP_DQ/issues
classifiers =
    Programming Language :: Python :: 3
    License :: OSI Approved :: MIT License
    Operating System :: OS Independent

[options]
package_dir =
    = src
packages = find:
python_requires = >=3.6

[options.packages.find]
where = src

Running the build
Make sure your build tool is up to date
Windows

py -m pip install --upgrade build
Linux/MAC OS

python3 -m pip install --upgrade build
Create the build
py -m build
References
https://packaging.python.org/tutorials/packaging-projects/