semvec/pypi-packages huggingface dataset:
ttvsplit 0.3
A Train Test Val Split library


# ttsvsplit - Train, Test, Validation Splitter

A simple utility designed to seamlessly split datasets into train, test, and validation sets, inspired by `sklearn`'s `train_test_split`.

## Installation

To install `ttvsplit`, use pip:

```
pip install ttsvsplit
```

## Usage

Using `ttvsplit` is straightforward. Import the `train_test_val_split` function and apply it on your features (`X`) and labels (`y`).

Here's a basic example:

```python
import numpy as np
from ttsvsplit import train_test_val_split

# Sample data
X = np.array([[1, 2], [3, 4], [5, 6], [7, 8], [9, 10], [11, 12]])
y = np.array([1, 0, 1, 0, 1, 0])

X_train, y_train, X_test, y_test, X_val, y_val = train_test_val_split(X, y)
```

## Functions

The library provides the following function:

- `train_test_val_split(X, y, train_size=0.6, test_size=0.2, random_state=None)`: 
  - **X**: Features to be split.
  - **y**: Labels corresponding to the features.
  - **train_size**: Proportion of the data to be used as training data (default: 0.6).
  - **test_size**: Proportion of the data to be used as testing data (default: 0.2).
  - **random_state**: Seed for reproducibility.

## License

This project is licensed under the MIT License - see the LICENSE.txt file for details.
pyProcessAutom 0.2
A Train Test Val Split library


# ttsvsplit - Train, Test, Validation Splitter

A simple utility designed to seamlessly split datasets into train, test, and validation sets, inspired by `sklearn`'s `train_test_split`.

## Installation

To install `ttvsplit`, use pip:

```
pip install ttsvsplit
```

## Usage

Using `ttvsplit` is straightforward. Import the `train_test_val_split` function and apply it on your features (`X`) and labels (`y`).

Here's a basic example:

```python
import numpy as np
from ttsvsplit import train_test_val_split

# Sample data
X = np.array([[1, 2], [3, 4], [5, 6], [7, 8], [9, 10], [11, 12]])
y = np.array([1, 0, 1, 0, 1, 0])

X_train, y_train, X_test, y_test, X_val, y_val = train_test_val_split(X, y)
```

## Functions

The library provides the following function:

- `train_test_val_split(X, y, train_size=0.6, test_size=0.2, random_state=None)`: 
  - **X**: Features to be split.
  - **y**: Labels corresponding to the features.
  - **train_size**: Proportion of the data to be used as training data (default: 0.6).
  - **test_size**: Proportion of the data to be used as testing data (default: 0.2).
  - **random_state**: Seed for reproducibility.

## License

This project is licensed under the MIT License - see the LICENSE.txt file for details.
streamlit-audio-rec 0.0.2
Official PyPI Package for [steamlit-audio-recorder by stefanrmmr] <br>Streamlit Custom Component that enables recording audio from the client's mic in apps that are deployed to the web. (via browser Media-API, REACT-based)
Requires Python: >=3.7

# streamlit_audio_recorder (Custom Component)

[![Streamlit App](https://static.streamlit.io/badges/streamlit_badge_black_white.svg)](https://audiorecorder.streamlit.app/)


Implemented by [Stefan Rummer](https://www.linkedin.com/in/stefanrmmr/) <br/>
Based on [doppelgunner](https://github.com/doppelgunner/audio-react-recorder)'s [Audio-React-Recorder](https://www.npmjs.com/package/audio-react-recorder)<br/>

![Screenshot 2022-05-16 at 16 58 36](https://user-images.githubusercontent.com/82606558/168626886-de128ffa-a3fe-422f-a748-395c29fa42f9.png)<br/>

## Features & Outlook
- Managing access to your microphone via the browser's Media-API
- Record, playback and revert audio-captures within the streamlit app
- Download the final recording to your local system (WAV, 16 bit, 44.1 kHz)
- Directly return audio recording-data to Python backend! (arrayBuffer)<br><br>
- **NEW:** Reduced repo size by removal of redundant node-modules! (~~393Mb~~ --> 70Mb)
- **NEW:** Simplified SETUP TUTORIAL, that will get you to record audio within no time!
- **NEW:** **PIP-INSTALL**, Add streamlit-audio-recorder to your project using PyPI

## Component Setup - PIP Install 
1. asfasdflksdf WIP

## Component Setup - Manual
**1.** Import and install relevant libraries to your Python project. :D
```
import os
import numpy as np
import streamlit as st
from io import BytesIO
import streamlit.components.v1 as components
```
**2.** Add the folder `/st_audiorec` to the top level directory of your project.<br><br>
**3.** Add the file `component.py` (or its contents) to your project wherever you like.<br><br>
**4.** Import the function `st_audiorec()` to your main streamlit application code.
```
from component import st_audiorec
```
**5.** Add an instance of the audio recorder component to your streamlit app's code.
```
wav_audio_data = st_audiorec()

if wav_audio_data is not None:
    # display audio data as received on the backend
    st.audio(wav_audio_data, format='audio/wav')
    
# INFO: by calling the function an instance of the audio recorder is created
# INFO: once a recording is completed, audio data will be saved to wav_audio_data
```
**6. Enjoy recording audio inside your streamlit app! 🎈**

Feel free to reach out to me in case you have any questions! <br>
Pls consider leaving a `star` ☆ with this repository to show your support.
tellus-traveler 0.3.0
Client for Tellus Traveler API
Requires Python: >=3.10

# tellus-traveler-python

Unofficial Python client for [Tellus Traveler API](https://www.tellusxdp.com/docs/travelers/).

## Getting Started

https://tellus-traveler.readthedocs.io/

## Development

This project uses [Rye](https://rye-up.com/) for package management.

### Install dependencies

    $ rye sync

### Run the test suite

    $ rye run test

### Publish a new version

1. Bump the version in [`pyproject.toml`](pyproject.toml) and update [`CHANGELOG.md`](CHANGELOG.md).
2. Create a git commit, push it, and ensure that the CI passes.
3. Create a git tag for the new version and push it, then the [PyPI workflow](https://github.com/sankichi92/tellus-traveler-python/actions/workflows/pypi.yml) starts.

## License

[MIT License](LICENSE)
pyticketfood 0.2.0
Get transactions from ticket food card (ticket.pt)
Requires Python: >=3.7
Keywords: api,parser,transactions

# pyticketfood

The `pyticketfood` package is a simple wrapper to fetch transactions from Ticket food card.

# TODO

[ ] add simple CLI tool to show current balance and transactions
[ ] create pypi package
[ ] test login unsuccessfull, creds wrong (NOTE - ALL SUCCESSFULL TESTS REQUIRE VALID CRED)
[ ] test login successfull
[ ] test balance
[ ] test transactions