https://github.com/deepentropy/lwcharts
TradingView Lightweight Charts™ integration in Jupyter
https://github.com/deepentropy/lwcharts
jupyter-notebook lightweight-charts
Last synced: 5 months ago
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TradingView Lightweight Charts™ integration in Jupyter
- Host: GitHub
- URL: https://github.com/deepentropy/lwcharts
- Owner: deepentropy
- License: mit
- Created: 2025-11-10T20:35:52.000Z (7 months ago)
- Default Branch: main
- Last Pushed: 2025-11-12T11:07:58.000Z (7 months ago)
- Last Synced: 2025-12-15T04:13:09.292Z (6 months ago)
- Topics: jupyter-notebook, lightweight-charts
- Language: Jupyter Notebook
- Homepage:
- Size: 95.7 KB
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# lwcharts - Lightweight Charts for Jupyter
Ultra-simple TradingView Lightweight Charts integration for Jupyter notebooks. No widget infrastructure, no build steps, just works.
## Why lwcharts?
**lwcharts** takes a radically simple approach to displaying charts in Jupyter:
- ✅ **No JavaScript build required** - Uses inline HTML with CDN-loaded libraries
- ✅ **No widget infrastructure** - Just pure IPython HTML display
- ✅ **Works everywhere** - PyCharm, JupyterLab, VS Code, Colab, anywhere Jupyter runs
- ✅ **Zero configuration** - Install and use immediately
- ✅ **Tiny package** - Less than 2KB, only depends on IPython
## Installation
```bash
pip install lwcharts
```
That's it! No additional setup, no extensions to install, no build steps.
## Quick Start
### Line Chart
```python
from lwcharts import Chart
chart = Chart(chart_type='line', width=800, height=400)
chart.data = [
{'time': '2025-01-01', 'value': 100},
{'time': '2025-01-02', 'value': 110},
{'time': '2025-01-03', 'value': 105},
{'time': '2025-01-04', 'value': 120},
]
chart # Display the chart
```
### Candlestick Chart
```python
from lwcharts import Chart
chart = Chart(chart_type='candlestick', width=800, height=400)
chart.data = [
{'time': '2025-01-01', 'open': 100, 'high': 110, 'low': 95, 'close': 105},
{'time': '2025-01-02', 'open': 105, 'high': 115, 'low': 100, 'close': 112},
{'time': '2025-01-03', 'open': 112, 'high': 120, 'low': 108, 'close': 115},
]
chart
```
## Supported Chart Types
### 1. Line Chart
```python
chart = Chart(chart_type='line')
chart.data = [{'time': '2025-01-01', 'value': 100}, ...]
```
### 2. Area Chart
```python
chart = Chart(chart_type='area')
chart.data = [{'time': '2025-01-01', 'value': 100}, ...]
```
### 3. Candlestick Chart
```python
chart = Chart(chart_type='candlestick')
chart.data = [
{'time': '2025-01-01', 'open': 100, 'high': 110, 'low': 95, 'close': 105},
...
]
```
### 4. Bar Chart
```python
chart = Chart(chart_type='bar')
chart.data = [
{'time': '2025-01-01', 'open': 100, 'high': 110, 'low': 95, 'close': 105},
...
]
```
### 5. Histogram Chart
```python
chart = Chart(chart_type='histogram')
chart.data = [
{'time': '2025-01-01', 'value': 50000, 'color': '#26a69a'},
...
]
```
## Customization
### Chart Dimensions
```python
chart = Chart(chart_type='line', width=1000, height=600)
```
### Chart Options
```python
chart = Chart(chart_type='candlestick')
# Customize appearance
chart.chart_options = {
'layout': {
'background': {'color': '#1e1e1e'},
'textColor': '#d1d4dc',
},
'grid': {
'vertLines': {'color': '#2a2a2a'},
'horzLines': {'color': '#2a2a2a'},
},
}
```
### Series Options
```python
# Customize candlestick colors
chart.series_options = {
'upColor': '#26a69a',
'downColor': '#ef5350',
'wickUpColor': '#26a69a',
'wickDownColor': '#ef5350',
}
```
## Real-World Example: Stock Data
```python
import pandas as pd
import yfinance as yf
from lwcharts import Chart
# Download stock data
ticker = yf.Ticker('AAPL')
df = ticker.history(period='1mo')
# Convert to lwc format
data = [
{
'time': index.strftime('%Y-%m-%d'),
'open': row['Open'],
'high': row['High'],
'low': row['Low'],
'close': row['Close'],
}
for index, row in df.iterrows()
]
# Display chart
chart = Chart(chart_type='candlestick', width=1000, height=600)
chart.data = data
chart
```
## Supported Environments
Works in **any** Jupyter environment:
| Environment | Status |
|------------|--------|
| **PyCharm Professional** | ✅ Works |
| **JupyterLab** | ✅ Works |
| **Jupyter Notebook** | ✅ Works |
| **VS Code** | ✅ Works |
| **Google Colab** | ✅ Works |
| **Kaggle Notebooks** | ✅ Works |
| **Databricks** | ✅ Works |
## API Reference
### Chart Class
```python
Chart(
chart_type='line', # 'line', 'area', 'candlestick', 'bar', 'histogram'
width=800, # Chart width in pixels
height=400 # Chart height in pixels
)
```
#### Properties
- `data` (list): Chart data points
- `chart_type` (str): Type of chart
- `width` (int): Chart width in pixels
- `height` (int): Chart height in pixels
- `chart_options` (dict): Chart configuration
- `series_options` (dict): Series configuration
#### Methods
- `display()`: Explicitly display the chart
- `set_data(data)`: Set chart data
- `add_data_point(point)`: Add a single data point
## How It Works
Unlike traditional Jupyter widgets that require complex JavaScript builds and widget infrastructure, **lwcharts** uses a simple approach:
1. Creates HTML with embedded JavaScript
2. Loads lightweight-charts library from CDN (unpkg.com)
3. Generates inline JavaScript to create and populate the chart
4. Returns HTML via `_repr_html_()` for Jupyter display
This means:
- ✅ No RequireJS/AMD module loading issues
- ✅ No widget registration needed
- ✅ No nbextension installation
- ✅ Works immediately after `pip install`
## Examples
See the [examples.ipynb](./examples.ipynb) notebook for more usage examples including all chart types and customization options.
## Requirements
- Python 3.7+
- IPython (automatically installed with Jupyter)
- Internet access (to load lightweight-charts from CDN)
## Documentation
For chart options and customization, see the [TradingView Lightweight Charts documentation](https://tradingview.github.io/lightweight-charts/).
## License
Apache License 2.0 - See [LICENSE](LICENSE) file for details.
## Acknowledgments
Built on [TradingView Lightweight Charts](https://github.com/tradingview/lightweight-charts)
## Support
- Open an issue on [GitHub](https://github.com/yourusername/lwcharts/issues)
- Check the [examples.ipynb](./examples.ipynb) notebook
- Read the [TradingView docs](https://tradingview.github.io/lightweight-charts/)