semvec/pypi-packages huggingface dataset:
truewinds 0.0.4
A Python package for estimating true wind speed and direction from anemometers on marine vessels.
Requires Python: >=3.10
Keywords: wind, anemometer, marine, vessel

# truewinds

True winds is still in beta and requires updated documentation, examples, and tests. Function output may change in future releases.

True winds provides vectorized versions of the true winds code provided by [SAMOS](https://samos.coaps.fsu.edu/html/tools_truewinds.php). 
It is important to note that there may be some floating point differences between this numpy-based code and the orignal legacy functions.
These differences occur at digits that are considered insignificant for wind speed and direction (< 1e-10). 

## Installation

`pip install truewinds`


## Documentation

Code documentation for truewinds is available here: https://iantblack.github.io/truewinds/

The code truewinds is based on can be found here: [SAMOS True Winds Tools](https://samos.coaps.fsu.edu/html/tools_truewinds.php)

The original manuscript for true winds computation can be found here: [True Winds Manuscript](`https://doi.org/10.1175/1520-0426(1999)016<0939:EMTITW>2.0.CO;2`)
tcai-churn-x 0.1.1
A Flask-based web app for predicting customer churn using a trained ML model.
Requires Python: >=3.8

# TCAI Churn X

**TCAI Churn X** is a Python package that serves a Flask web interface to predict customer churn using a trained machine learning model. This app allows businesses to analyze customer data and determine the likelihood of churn in an interactive, user-friendly format.

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## 🚀 Features

- Upload CSV files to perform churn predictions
- Interactive web UI powered by Flask and HTML templates
- Uses Scikit-learn models for prediction
- Clean, lightweight architecture
- Installable via `pip`
- Easy to deploy and extend

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## 📦 Installation

Make sure you have Python 3.8+ and `pip` installed.