semvec/pypi-packages huggingface dataset:
Flask-DebugToolbar-DjangoSQL 0.1.2
A Flask Debug Toolbar panel for Django SQL queries.
License: MIT

# Flask DebugToolbar DjangoSQL Panel

This is a custom panel for Flask DebugToolbar that displays Django SQL queries.

## Installation

Install the package using pip:

```bash
pip install Flask-DebugToolbar-DjangoSQL

## Usage

1. Make sure you have Flask and Flask-DebugToolbar installed in your project.

2. Add DjangoSQLPanel to your Flask DebugToolbar setup by including it in the DEBUG_TB_PANELS configuration:

```python
from flask import Flask
from flask_debugtoolbar import DebugToolbarExtension

app = Flask(__name__)
app.debug = True

# Configuration for Flask-DebugToolbar
app.config['DEBUG_TB_PANELS'] = [
    'flask_debugtoolbar_djangosql.panel.DjangoSQLPanel'
]

toolbar = DebugToolbarExtension(app)

if __name__ == "__main__":
    app.run()
```

3. Access your Flask application with the debug mode enabled (app.run(debug=True)) and open the debug toolbar in your browser to see Django SQL queries.

## Contributing
Feel free to contribute by forking the repository and sending pull requests. Please make sure to add tests for any new features or changes.

## License
This project is licensed under the MIT License - see the LICENSE file for details.
trend-lines-generator 1.0.3
Trend lines generator.
License: MIT
Requires Python: <4.0,>=3.10
Keywords: trendlines, trend lines, trend, ta, resistance, support, technical, indicators, financial

# Trend lines generator

Usage example:
```python
#! pip install trend-lines-generator
import requests
import mplfinance as mpf
from pandas import DataFrame, to_datetime

from trend_lines import generate_trend_lines, Side


def main():
    columns = [
        ("ts", "int"),
        ("volume_quote", "float64"),
        ("open", "float64"),
        ("high", "float64"),
        ("low", "float64"),
        ("close", "float64"),
    ]
    url = "https://api.gateio.ws/api/v4/spot/candlesticks?currency_pair=MOVR_USDT&interval=1h&limit=100"
    response = requests.get(url)

    rows = response.json()

    df = (
        DataFrame([r[: len(columns)] for r in rows], columns=[i[0] for i in columns])
        .astype(dict(columns))
        .set_index("ts")
    )
    df.index = to_datetime(df.index, unit="s")

    lines = generate_trend_lines(low_series=df["low"], high_series=df["high"])

    x1 = df.index[0]
    x2 = df.index[-1]

    mpf.plot(
        df,
        type="candle",
        tight_layout=True,
        alines={
            "alines": [((x1, line.get_y(x1)), (x2, line.get_y(x2))) for line in lines],
            "colors": ["g" if line.side == Side.LOW else "r" for line in lines],
        },
    )


if __name__ == "__main__":
    main()
```

![trend lines](https://github.com/nanvel/trend-lines/raw/master/docs/trend_lines.png)

For each time in the serie:

![trend lines daily](https://github.com/nanvel/trend-lines/raw/master/docs/trend_lines_daily.png)