semvec/pypi-packages huggingface dataset:
pomodoro-app-cli 1.3.0
🌟 Pomodoro CLI 🍅⏳ A simple and practical Pomodoro tool for your terminal! 📱💻 Organize your time efficiently with countdowns and sound alerts. Perfect for boosting productivity with focus and breaks! 🚀
License: MIT
Requires Python: <4.0,>=3.9
Keywords: pomodoro, cli, terminal, linux, python, curses, timer

# Pomodoro CLI ⏳

[![Ruff Tests](https://github.com/GussSoares/pomodoro-cli/actions/workflows/test.yml/badge.svg)](https://github.com/GussSoares/pomodoro-cli/actions/workflows/test.yml)
[![Release](https://github.com/GussSoares/pomodoro-cli/actions/workflows/publish.yml/badge.svg)](https://github.com/GussSoares/pomodoro-cli/actions/workflows/publish.yml)

A simple and practical Pomodoro tool for your terminal! 📱💻

Organize your time efficiently with countdowns and sound alerts. Perfect for boosting productivity with focus and breaks! 🚀

## Features:
- Start, pause, and restart  Pomodoro cycles 🍅⏳
- Sound notifications to keep you on track 🔔
- Customizable work and break durations _(coming soon)_ ⏰
- Simple and intuitive terminal interface

## Installation:
You can install Pomodoro CLI directly from PyPI using pip:  
```bash
pip install pomodoro-app-cli
```

## Usage:
Start your Pomodoro session by running:

```bash
pomodoro
```

## License:
This project is licensed under the [MIT License](LICENSE) - see the LICENSE file for details. 📜
epochai 0.1.3
Top-level package for Epoch AI client library.
License: MIT
Requires Python: <4,>=3.9

This repository contains the Python client library of [Epoch AI](https://epoch.ai/). At the moment, only one feature is supported: reading from our database of ML models and benchmark results.

## Installation

```bash
pip install epochai
```

## Usage
### Reading from our Airtable database of ML models and benchmark results
A few preparatory steps are required: 

1. Open our [Airtable base](https://airtable.com/appsyxA7qAp1bvsrl/shroAmbNkK89Jq02c/tblyjKGBmFS5khLdW/viwvuE5MiSv6wcyeW?blocks=hide)
2. Airtable doesn't allow public API access, so you'll have to make a copy of the base (unless you are an Epoch AI team member).
3. Define the `AIRTABLE_BASE_ID` environment variable with the ID of the base you just copied. (The ID is in the URL and starts with `app`.)
4. Create an Airtable API key with access to the base, and the following scopes: `data.records:read`, `schema.bases:read`. Define the `AIRTABLE_API_KEY` environment variable with the key.

You're now ready to use the library. The database models are defined in `epochai.airtable.models`. 

You can get started with our example script [`examples/airtable.py`](examples/airtable.py), or try the snippets below.

```python
from epochai.airtable.models import MLModel, Task, Score, Organization, BenchmarkRun

# Get everything at the start to minimize API calls
scores = Score.all(memoize=True)
runs = BenchmarkRun.all(memoize=True)
models = MLModel.all(memoize=True)
tasks = Task.all(memoize=True)
organizations = Organization.all(memoize=True)
```

Print information about a model:

```python
print_model_info("claude-3-5-sonnet-20240620")
```

<img src="assets/model.png" width="500"/>

Print the highest scores for a benchmark and scorer:

```python
print_high_scores(
    task_path="bench.task.hendrycks_math.hendrycks_math_lvl_5",
    scorer="model_graded_equiv",
    scores=scores
)
```

<img src="assets/highscores.png" width="500"/>

Track the best-performing model to date over time:
```python
print_performance_timeline(
    task_path="bench.task.gpqa.gpqa_diamond",
    scorer="choice",
    scores=scores
)
```

<img src="assets/timeline.png" width="500"/>