semvec/pypi-packages huggingface dataset:
job-market-analyzer 0.1.4
A Python package to analyze job market data
License: MIT
Requires Python: >=3.8

# Job Market Analyzer ðŸ“Š

A Python package to analyze job market data for Data Analyst roles.

## Features
- Analyze job postings from CSV
- Identify top required skills
- Calculate salary statistics
- Visualize trends using charts

## Installation
```bash
pip install job-market-analyzer

from job_market_analyzer import load_data, filter_jobs, top_skills

df = load_data("jobs.csv")
filtered = filter_jobs(df, "Data Analyst")
print(top_skills(filtered))


This makes PyPI render it **cleanly**.

---

### ðŸ”§ IMPROVEMENT 2: Do NOT ship `jobs.csv` in real PyPI package (OPTIONAL)

For learning â†’ fine  
For real PyPI â†’ better practice:

- Remove `data/jobs.csv` from package
- Let users provide their own CSV

Later we can:
- move sample data to `examples/`
- or download data via API

But this is **optional** for now.

---

### ðŸ”§ IMPROVEMENT 3: Add version info in code (Optional but nice)

In `__init__.py`:

```python
__version__ = "0.1.0"
pupil-labs-marker-mapper 1.0.0
Marker Mapper
License: MIT
Requires Python: <4.0,>=3.10

# Pupil Labs Marker Mapper

[![ci](https://github.com/pupil-labs/pl-marker-mapper/actions/workflows/main.yml/badge.svg)](https://github.com/pupil-labs/pl-marker-mapper/actions/workflows/main.yml)
[![documentation](https://img.shields.io/badge/docs-mkdocs-708FCC.svg?style=flat)](https://pupil-labs.github.io/pl-marker-mapper/)
[![uv](https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/astral-sh/uv/main/assets/badge/v0.json)](https://github.com/astral-sh/uv)
[![ruff](https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/astral-sh/ruff/main/assets/badge/v2.json)](https://github.com/astral-sh/ruff)
[![pre-commit](https://img.shields.io/badge/pre_commit-black?logo=pre-commit&logoColor=FAB041)](https://github.com/pre-commit/pre-commit)
[![pypi version](https://img.shields.io/pypi/v/pupil-labs-marker-mapper.svg)](https://pypi.org/project/pupil-labs-marker-mapper/)
[![python version](https://img.shields.io/pypi/pyversions/pupil-labs-marker-mapper)](https://pypi.org/project/pupil-labs-marker-mapper/)


This is an implementation of the Marker Mapper functionality as it can be found in e.g. [Pupil Cloud](https://cloud.pupil-labs.com/) and [Neon Player](https://docs.pupil-labs.com/neon/neon-player/). This implementation allows both post hoc and real-time gaze mapping onto surfaces defined by AprilTags.

The examples demonstrate how to interact with the Marker Mapper's interface. There is also an example app that demonstrates the Marker Mapper functionality in real-time in combination with a Neon device.

## Installation

```bash
pip install -e git+https://github.com/pupil-labs/pl-marker-mapper.git
```
ai-offline-cli 0.1.1
Offline AI assistant for code writing, command execution, and chat working with any offline models
License: MIT
Requires Python: >=3.11

# ai-cli

Offline AI assistant for code writing, command execution, and chat working with any offline models.

## Installation

```bash
pip install ai-offline-cli
```

## Usage

```bash
ai-cli --help
```

## Features

- Code generation and assistance
- Command execution
- Chat interface
- Works with any offline models (Ollama, llama.cpp, etc.)
numpy_frame 0.1.0
A lightweight wrapper around numpy arrays for DataFrame-like functionality
License: MIT
Requires Python: >=3.9

# NumpyFrame

A lightweight wrapper around numpy arrays that provides DataFrame-like functionality with minimal dependencies.

## Features
- **Column Selection**: Access columns by name (O(1) lookup).
- **Indexing & Slicing**: 
  - `nf["col"]` -> 1D array
  - `nf[["col1", "col2"]]` -> Sub-frame
  - `nf[0:5]` -> Row slice
  - `nf[[0, 2], ["a", "b"]]` -> Advanced rectangular indexing (Train/Test split friendly!)
- **GroupBy**: Split-Apply-Combine with `.groupby("col").mean()` or `.sum()`.
- **Fast**: Built purely on top of numpy.

## Installation

```bash
pip install numpy_frame
```

## Usage

```python
import numpy as np
from numpy_frame import NumpyFrame

# Create data
data = np.arange(12).reshape(4, 3)
cols = ["a", "b", "c"]
nf = NumpyFrame(data, cols)

# 1. Column Access
print(nf["a"])

# 2. Slicing
subset = nf[:2, ["a", "c"]] 

# 3. Advanced Indexing (e.g. random rows)
random_rows = [0, 3]
train_set = nf[random_rows, ["a", "b"]]

# 4. GroupBy
# Suppose column 'a' has groups
nf_grouped = nf.groupby("a").sum()
print(nf_grouped)
```

## License
MIT
weather-tui 1.4.0
A TUI application for displaying weather forecasts with hour-by-hour graphs
License: MIT
Requires Python: >=3.12
Keywords: forecast, terminal, textual, tui, weather

# Weather TUI

A terminal user interface for displaying weather forecasts with hour-by-hour graphs and multi-day forecasts.

![Python 3.12+](https://img.shields.io/badge/python-3.12+-blue.svg)
![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)
[![CI](https://github.com/benedikt-mayer/weather-tui/actions/workflows/ci.yml/badge.svg)](https://github.com/benedikt-mayer/weather-tui/actions/workflows/ci.yml)

## Features

- Current weather conditions with temperature
- Hourly temperature and precipitation graphs
- 7-day weather forecast with clickable day selection
- Location search powered by OpenWeatherMap Geocoding
- Keyboard-friendly navigation

## Installation

### Using uvx (recommended, no install needed)

```bash
# Run directly without installing
uvx --with weather-tui python -m weather_tui
```

### From PyPI

```bash
pip install weather-tui
```

### From source

```bash
# Clone the repository
git clone https://github.com/benedikt-mayer/weather-tui.git
cd weather-tui

# Install with uv (recommended)
uv sync

# Or with pip
pip install -e .
```

## Usage

```bash
# If installed via pip
python -m weather_tui
```

## Environment Variables

| Variable | Required | Description |
|----------|----------|-------------|
| `OPENWEATHERMAP_API_KEY` | Yes | API key for geocoding. Get a free key at [OpenWeatherMap](https://openweathermap.org/api) |

Create a `.env` file in your working directory:

```bash
OPENWEATHERMAP_API_KEY=your_api_key_here
```

## Keyboard Shortcuts

| Key | Action |
|-----|--------|
| `s` | Search for a new location |
| `r` | Refresh weather data |
| `q` | Quit |
| `Escape` | Cancel search |
| Click | Select a day to view its hourly forecast |

## Development

```bash
# Install dev dependencies
uv sync --extra dev

# Run tests
uv run pytest

# Run linting
uv run ruff check .
uv run ruff format --check .

# Fix linting issues
uv run ruff check --fix .
uv run ruff format .
```

## Tech Stack

- [Textual](https://github.com/Textualize/textual) - TUI framework
- [textual-plotext](https://github.com/Textualize/textual-plotext) - Terminal plotting
- [Open-Meteo](https://open-meteo.com/) - Weather data API (no key required)
- [OpenWeatherMap Geocoding](https://openweathermap.org/api/geocoding-api) - Location search

## License

MIT License - see [LICENSE](LICENSE) for details.
zeushell 1.0.2
A small Python package published to PyPI
License: MIT
Requires Python: >=3.8
Keywords: example, package, pypi

﻿# zeushell

A simple interactive action-shell framework.  
Write functions — run them as shell commands.

## Features

- Function-based command system
- Interactive shell runtime
- Customizable shell prompt
- Safe function registry
## Install

```bash
pip install zeushell
```

## Quick Start

```python
from zeushell import Zeushell

z = Zeushell()
@z.function()
def hi(user):
    return "Hello "+user

z.name("zeushell")
z.run()
```

Shell:

```
zeushell: hi Tom
hi Tom
```

## License

MIT