semvec/pypi-packages huggingface dataset:
tomato-clock 0.1.2
Tomato Clock is a straightforward command-line Pomodoro application.
License: MIT
Keywords: pomodoro tomato tomato-timer terminal terminal-app pomodoro-timer

# 🍅 Tomato Clock

[![Publish to PyPI](https://github.com/coolcode/tomato-clock/actions/workflows/package.yml/badge.svg)](https://github.com/coolcode/tomato-clock/actions/workflows/package.yml)
[![PyPI tomato-clock](https://badge.fury.io/py/tomato-clock.svg)](https://pypi.python.org/pypi/tomato-clock/)

Tomato Clock is a straightforward command-line Pomodoro application.

- [Pomodoro Technique](https://en.wikipedia.org/wiki/Pomodoro_Technique)
- [番茄工作法](https://zh.wikipedia.org/zh-cn/%E7%95%AA%E8%8C%84%E5%B7%A5%E4%BD%9C%E6%B3%95)

## Installation

[Install python](https://www.python.org)

- Install via pip:

```sh
pip install tomato-clock
```

- Install via source code:

```sh
git clone https://github.com/coolcode/tomato-clock.git
cd tomato-clock
chmod +x tomato.py 
```

## How to use

- if you install via pip

```sh
tomato         # start a 25 minutes tomato clock + 5 minutes break
tomato -t      # start a 25 minutes tomato clock
tomato -t <n>  # start a <n> minutes tomato clock
tomato -b      # take a 5 minutes break
tomato -b <n>  # take a <n> minutes break
tomato -h      # help
```

- if you install via source code

```sh
./tomato.py         # start a 25 minutes tomato clock + 5 minutes break
./tomato.py -t      # start a 25 minutes tomato clock
./tomato.py -t <n>  # start a <n> minutes tomato clock
./tomato.py -b      # take a 5 minutes break
./tomato.py -b <n>  # take a <n> minutes break
./tomato.py -h      # help
```

## Terminal Output

```sh
🍅 tomato 25 minutes. Ctrl+C to exit
 🍅🍅---------------------------------------------- [8%] 23:04 ⏰ 
```

## Desktop Notification

- MacOS

```sh
brew install terminal-notifier 
```

`terminal-notifier` actually is a cross-platform desktop notifier, please refer to ➜ [terminal-notifier](https://github.com/julienXX/terminal-notifier#download)

<img src="https://github.com/coolcode/tomato-clock/blob/master/img/screenshot-macos.png?raw=true" alt="terminal-notifier" width="300"/>

- Ubuntu

`notify-send`

<img src="https://github.com/coolcode/tomato-clock/blob/master/img/screenshot-ubuntu.png?raw=true" alt="ubuntu-notification" width="300"/>


## Voice Notifications

Tomato Clock uses `say`(text-to-speech) for voice notifications.

- MacOS

MacOS already has `say`. see [here](https://ss64.com/osx/say.html) or [more detail](https://gist.github.com/mculp/4b95752e25c456d425c6)  

- Ubuntu

See this link: [say](http://manpages.ubuntu.com/manpages/trusty/man1/say.1.html)

```sh
sudo apt-get install gnustep-gui-runtime
```

- Windows

Check this one: https://github.com/SeanBracksDev/tomato-clock
JP-Consumer-Theory 0.1
A Python package for consumer theory optimization and plotting
License: MIT

Package Name: JP_Consumer-Theory

Description:

The JP_Consumer-Theory package is a Python library designed to assist economists and students in the field of consumer theory. It provides functions and utilities for optimizing consumer choices and visualizing the solutions, all based on the Cobb-Douglas utility function.

Key Features:

Utility Optimization: The package includes a utility optimization function that allows users to find the optimal consumption of two goods (A and B) given their prices and the consumer's income. It employs the Lagrangian method to calculate the optimal quantities that maximize utility.

Optimization Plotting: The package offers a plotting function that visualizes the solutions obtained from the optimization process. It creates graphical representations of the consumer's budget constraint, indifference curves, and the optimal consumption point.

Intention:

The intention behind the JP_Consumer-Theory package is to serve as a valuable tool for economists, economics students, and anyone interested in consumer theory. Consumer theory is a fundamental concept in economics, and practicing exercises related to utility maximization and budget constraints is crucial for understanding economic decision-making.

This package aims to simplify the process of solving consumer theory exercises by providing an efficient and Pythonic way to optimize consumer choices and visualize the results. It promotes hands-on learning and experimentation in consumer theory, making it easier for users to grasp economic concepts and apply them in real-world scenarios.

Whether you're a student looking to improve your understanding of consumer theory or a researcher exploring utility optimization, the JP_Consumer-Theory package offers a user-friendly and practical solution to enhance your economic analysis skills.