semvec/pypi-packages huggingface dataset:
piano-transcription-inference 0.0.6
Piano transcription inference toolbox
Requires Python: >=3.6

# Piano transcription inference

This toolbox is a piano transcription inference package that can be easily installed. Users can transcribe their favorite piano recordings to MIDI files after installation. To see how the piano transcription system is trained, please visit: https://github.com/bytedance/piano_transcription.

## Demos
Here is a demo of our piano transcription system: https://www.youtube.com/watch?v=5U-WL0QvKCg

## Installation
The piano transcription system is developed with Python 3.7 and PyTorch 1.4.0 (Should work with other versions, but not fully tested).
Install PyTorch following https://pytorch.org/. Users should have **ffmpeg** installed to transcribe mp3 files.

```bash
pip install piano_transcription_inference
```

Installation is finished! 

## Usage
Want to try it out but don't want to install anything? We have set up a [Google Colab](https://colab.research.google.com/github/qiuqiangkong/piano_transcription_inference/blob/master/resources/inference.ipynb).

```python
python3 example.py --audio_path='resources/cut_liszt.mp3' --output_midi_path='cut_liszt.mid' --cuda
```

This will download the pretrained model from https://zenodo.org/record/4034264. 

Users could also execute the inference code line by line:

```python
import librosa
from piano_transcription_inference import PianoTranscription, sample_rate

# Load audio
audio, _ = librosa.load(path=audio_path, sr=sample_rate, mono=True)

# Transcriptor
transcriptor = PianoTranscription(device='cuda', checkpoint_path=None)  # device: 'cuda' | 'cpu'

# Transcribe and write out to MIDI file
transcribed_dict = transcriptor.transcribe(audio, 'cut_liszt.mid')
```

## Visualization of piano transcription

**Demo.** Lang Lang: Franz Liszt - Love Dream (Liebestraum) [[audio]](resources/cut_liszt.mp3) [[transcribed_midi]](resources/cut_liszt.mid)

<img src="resources/cut_liszt.png">

## FAQs
This repo support Linux and Mac. Windows has not been tested.

If users met "audio.exceptions.NoBackendError", then check if ffmpeg is installed.

If users met the problem of "Killed". This is caused by there are not sufficient memory.

## Applications

We have built a large-scale classical piano MIDI dataset https://github.com/bytedance/GiantMIDI-Piano using our piano transcription system.

## Cite
[1] High-resolution Piano Transcription with Pedals by Regressing Onsets and Offsets Times, [To appear], 2020
nettlesome 0.7.1
simplified semantic reasoning
Requires Python: >=3.8

# Nettlesome

Simplified semantic reasoning in Python

[![An Ethical Open Source Project](https://img.shields.io/badge/open-ethical-%234baaaa)](https://ethicalsource.dev/licenses/) [![Tests](https://github.com/mscarey/nettlesome/actions/workflows/python-package.yml/badge.svg)](https://github.com/mscarey/nettlesome/actions) [![Coverage Status](https://coveralls.io/repos/github/mscarey/nettlesome/badge.svg?branch=master)](https://coveralls.io/github/mscarey/nettlesome?branch=master) [![Documentation Status](https://readthedocs.org/projects/nettlesome/badge/?version=latest)](https://nettlesome.readthedocs.io/en/latest/?badge=latest) [![PyPI - Python Version](https://img.shields.io/pypi/pyversions/nettlesome)](https://pypi.org/project/nettlesome/)

Nettlesome is a Python
library defining a limited grammar of natural-language statements
that can be compared programmatically for implication or contradiction.

Nettlesome is intended for use where there is a limited schema of statements
that can be used to annotate a dataset with categories, numbers, quantities,
and dates. One example of such a schema is
the [National Information Exchange Model](https://github.com/NIEM/NIEM-Releases/tree/niem-5.0).

Although Nettlesome was designed to be used for legal annotations in
the [AuthoritySpoke](https://github.com/mscarey/AuthoritySpoke) library,
Nettlesome itself doesn't depend on any legal concepts or specialized knowledge.

Find [Nettlesome's documentation](https://nettlesome.readthedocs.io/) and an [introductory guide with examples](https://nettlesome.readthedocs.io/en/latest/guides/intro.html) on ReadTheDocs.
tsmtool 1.2.7
Top-level package for tsmtool.
Keywords: tsmtool

# Tarsnap Status Monitor Reporting Tool


[![Image](https://img.shields.io/github/license/rstms/tsmtool)](https://raw.githubusercontent.com/rstms/tsmtool/master/LICENSE)

[![Image](https://img.shields.io/pypi/v/tsmtool.svg)](https://pypi.org/project/tsmtool/)

[![Image](https://circleci.com/gh/rstms/tsmtool/tree/master.svg?style=shield)](https://app.circleci.com/pipelines/github/rstms/tsmtool?branch=master&filter=all)

[![Image](https://readthedocs.org/projects/tsmtool/badge/?version=latest)](http://tsmtool.readthedocs.io/)

[![Image](https://pyup.io/repos/github/rstms/tsmtool/shield.svg)](https://pyup.io/account/repos/github/rstms/tsmtool/)

Tarsnap Status Monitor

## Introduction 
The most excellent backup service [Tarsnap](https://www.tarsnap.com) provides a clean
and functional interface for managing one's account.  This tool connects to that web
interface and queries data, producing a report as a table or JSON.  The current balance is
read, and an estimated monthly cost is calculated based on the site's daily cost data.

### Example Output
Here's an example of output from the author's tarsnap account:
```
(tsmtool) mkrueger@beaker:~/src/tsmtool$ tsmtool --json rstms
{
  "balance": 32.51,
  "account": "mkrueger@rstms.net",
  "monthly_cost": 23.51
}
```

## Configuration 
A config file may be used for account data, or the email account / password may be passed as command line options.
The config file is a whitespace delimited text file with one line per account.
Each line has these fields:

`~/.tsmtool`: 
```
ACCOUNT_NAME    EMAIL_ADDRESS   PASSWORD
```

* Free software: MIT license
* Documentation: https://tsmtool.readthedocs.io.



## Credits

[Tarsnap](https://www.tarsnap.com) 

This package was created with Cookiecutter and `rstms/cookiecutter-python-cli`, a fork of the `audreyr/cookiecutter-pypackage` project template.

[audreyr/cookiecutter](https://github.com/audreyr/cookiecutter)
[audreyr/cookiecutter-pypackage](https://github.com/audreyr/cookiecutter-pypackage)
[rstms/cookiecutter-python-cli](https://github.com/rstms/cookiecutter-python-cli)
```
```
pyideai 0.1.0
A module to interact with ideai.dev using Selenium WebDriver.
Requires Python: >=3.6

# 🐍 PyIdeAI

Welcome to **PyIdeAI**! This Python module allows you to interact with the [ideai.dev](https://ideai.dev) website using Selenium WebDriver. With PyIdeAI, you can easily retrieve similar products to your ideas, thanks to our friends at [ideai.dev](https://ideai.dev) & power of web scraping.

## 🚀 Features

- **Browser Compatibility**: Choose between Firefox and Chrome for your preference.
- **Easy to Use**: Simple methods to retrieve project information based on user prompts.
- **Headless Mode**: Run the browser in headless mode for faster execution without a GUI.

## 📦 Installation

You can install PyIdeAI directly from PyPI using pip:

```bash
pip install pyideai
```

Alternatively, if you want to install it from the source, follow these steps:

1. Clone the repository:
   ```bash
   git clone https://gitlab.com/mutkuoz/pyideai.git
   cd pyideai
   ```

2. Install the required packages:
   ```bash
   pip install -r requirements.txt
   ```

3. Install the module:
   ```bash
   pip install .
   ```

## 🛠️ Usage

Here's how to use the PyIdeAI module in your Python scripts:

```python
from pyideai import PyIdeAI

# Initialize the PyIdeAI class
ideai = PyIdeAI(browser="c", is_shown=True)  # Use "f" for Firefox

# Retrieve similar projects based on your idea
user_input = "Your innovative project idea"
result = ideai.retrieve_similar_projects(user_input)

# Print the results
for project in result:
    print(f"Title: {project['title']}")
    print(f"Description: {project['description']}")
    print(f"Link: {project['link']}")
    print(f"Tags: {', '.join(project['tags'])}\n")
```

### 🌐 Example

If you want to find projects similar to "AI-Powered Chatbot", you can run:

```python
result = ideai.retrieve_similar_projects("AI-Powered Chatbot")
```

## 📄 Documentation

### Class: `PyIdeAI`

- **`__init__(self, browser="f", driver_options=None, is_shown=False)`**: Initializes the PyIdeAI class with the specified browser and options.
  - `browser`: Choose "f" for Firefox or "c" for Chrome.
  - `driver_options`: Options for the selected browser.
  - `is_shown`: Set to `True` to run the browser in visible mode.

- **`retrieve_similar_projects(user_prompt)`**: Navigates to ideai.dev, submits a user prompt, and returns a list of projects extracted from the resulting page.

## 🤝 Contributing

We welcome contributions! If you have suggestions or improvements, feel free to open an issue or submit a pull request.

## 📄 License

This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.

## 📞 Contact

For any inquiries, please reach out to [Mehmet Utku ÖZTÜRK](mailto:mutkuoz@proton.me).

---

Happy coding! 🎉
fastapi-cache-plus 0.2.0
FastAPI simple cache
Requires Python: >=3.6
Keywords: aioredis, asyncio, cache, fastapi, redis, starlette

# FastAPI Cache Plus

![Static Badge](https://img.shields.io/badge/FastAPI%20Cache-Successor-blue) ![GitHub License](https://img.shields.io/github/license/leynier/fastapi-cache-plus?label=License) ![GitHub Actions Workflow Status](https://img.shields.io/github/actions/workflow/status/leynier/fastapi-cache-plus/tests.yaml?label=Tests) [![codecov](https://codecov.io/github/leynier/fastapi-cache-plus/branch/master/graph/badge.svg?token=EGBM54K25J)](https://codecov.io/github/leynier/fastapi-cache-plus) ![PyPI - Version](https://img.shields.io/pypi/v/fastapi-cache-plus?label=Version)

> This project is a continuation of the project [fastapi_cache](https://github.com/comeuplater/fastapi_cache). Many thanks to Ivan Sushkov (the original author) for their work and contributions.

Implements simple lightweight cache system as dependencies in FastAPI.

## Installation

```sh
pip install fastapi-cache-plus
```

## Usage example

```python
from fastapi import Depends, FastAPI

from fastapi_cache_plus import caches, close_caches
from fastapi_cache_plus.backends.redis import CACHE_KEY, RedisCacheBackend

app = FastAPI()


def redis_cache():
    return caches.get(CACHE_KEY)


@app.get("/")
async def hello(cache: RedisCacheBackend = Depends(redis_cache)):
    in_cache = await cache.get("some_cached_key")
    if not in_cache:
        await cache.set("some_cached_key", "new_value", 5)

    return {"response": in_cache or "default"}


@app.on_event("startup")
async def on_startup() -> None:
    rc = RedisCacheBackend("redis://redis")
    caches.set(CACHE_KEY, rc)


@app.on_event("shutdown")
async def on_shutdown() -> None:
    await close_caches()
```