semvec/pypi-packages huggingface dataset:
liweather 0.1.4
Add your description here
Requires Python: >=3.13

cd liweather
# 安装构建工具
uv add build twine
# 构建您的Python包
uv run -m build
# 上传您的Python包
uv run -m twine upload dist/***.whl
# 通过inspector快速测试
npx @modelcontextprotocol/inspector uvx liweather
ez-yaml-config 0.4.2
Typed config files
Requires Python: >=3.13

Install with `pip install ez-yaml-config`

Then define some configuration files like so:
```python
from config import Configuration, gsm_secret

class ConfigBase(Configuration):
    CONFIG_FILE = "settings.yaml"
    CONFIG_FILE_PATH_ENV_VAR = "SETTINGS_PATH"


class LoggingConfig(ConfigBase):
    CONFIG_SECTION = "logging"
    level: Literal["info", "warning", "error"]


class BackendConfig(ConfigBase):
    CONFIG_SECTION = "server"
    host: str
    api_key: Annotated[str, gsm_secret(project="my-gcp-project")]
```

The above Configurations will load a file named `settings.yaml` in the cwd, or from the location set in the `SETTINGS_PATH` environment variable (if its been set). The file should look like this:
```yaml
logging:
    level: info
server:
    host: "localhost"
    api_key: gsm:name-of-gsm-key
```
pyformica 0.1.9
Netwotk automation tool
Requires Python: >=3.12

# Formica

A low-code automation tool for network configuration

## Requirements

- Python 3.12 

## Usage

### 1. Initialize the metadata folder

The default path for the metadata folder is `~/formica`. You can change it by setting the `FORMICA_HOME` environment variable.
To initialize the metadata folder, run:

```bash
formica init
```

The metadata folder will be created at the specified path, and it will contain the following files:
- `formica.ini`: Configuration file for Formica.
- `logs/`: Directory for logs.
- `logging_config.json`: Logging configuration file.

You should check the `formica.ini` file to configure before running.

### 2. Run Formica

To run all 3 components of Formica (Webserver, Scheduler and Executor), use this command:

```bash
formica standalone
```

Formica will be available at `http://localhost:8000`. (with default `HOST` and `PORT`)
browser-history-analytics-2 1.0.1
A package to visualize your browser history :D
Requires Python: >=3.10

<h1 align="center">
  Browser History Analytics 2
</h1>
<p align="center">
  A Python package that analyzes and visualizes your browser history data with interactive charts and insights.
</p>

<br>

<table style="width:100%; border-collapse:collapse; font-family:sans-serif;">
  <th>
    Features Overview
  </th>
  <th>
    Preview
  <tr>
    <td style="vertical-align:top; padding:10px; width:60%;">
      <ul>
        <li><strong>Category Analysis</strong>: Automatically categorizes websites (Social Media, Development, Entertainment, etc.)</li>
        <li><strong>Time-based Insights</strong>: Hourly and daily browsing patterns with heatmaps</li>
        <li><strong>Summary Statistics</strong>: Key metrics about your browsing habits</li>
        <li><strong>Interactive Filters</strong>: Filter by date range and categories</li>
        <li><strong>Raw Data View</strong>: Search and export your browsing data</li>
        <li><strong>Multi-browser Support</strong>: Works with Chrome, Firefox, Safari, and more</li>
      </ul>
    </td>
    <td style="vertical-align:top; padding:10px; width:40%;">
      <img src="https://github.com/user-attachments/assets/b60be8bf-f6f3-4b1f-9d1e-311d40587b31" alt="Preview GIF" style="max-width:100%; border-radius:8px; box-shadow:0 0 8px rgba(0,0,0,0.1);">
    </td>
  </tr>
</table>



## Installation

### Option 1: Install from source

```bash
git clone https://github.com/arpy8/browser-history-analytics-2.git
cd browser-history-analytics-2
pip install -e .
```

### Option 2: Install directly

```bash
pip install browser-history-analytics-2
```

## Usage
Type the following command in your terminal: 
```
pip install browser-history-analytics-2 && bha
```

This will launch the web application in your default browser.

## What You'll See

### Dashboard Tabs

1. **Home**: Main dashboard with visualizations and summary statistics
2. **Raw Data**: Searchable table with export functionality
3. **Additional Info**: Detailed insights and browsing habits analytics

### Visualizations

* **Top Domains**: Bar chart of most visited websites
* **Activity Timeline**: Daily visits over time
* **Activity Heatmap**: Browsing patterns by hour and day of week
* **Category Distribution**: Pie chart of website categories
* **Hourly Patterns**: Bar chart showing peak browsing hours

## Requirements

* Python 3.7+
* Browser history data (automatically detected)

## Dependencies

* `streamlit`
* `plotly`
* `pandas`
* `browser-history`

## Privacy Note

This tool only reads your local browser history files. No data is sent to external servers – everything runs locally on your machine.

## Supported Browsers

* Google Chrome
* Mozilla Firefox
* Safari
* Microsoft Edge
* Opera

## Contributing

Feel free to open issues and submit pull requests!

## License

[MIT License](LICENSE)

## Author

Arpit Sengar ([@arpy8](https://github.com/arpy8))