⚡ Awesome Panel Lightning

Repository demonstrating the power of combining Panel and lightning.ai to build, scale and deploy powerful machinelearning and deeplearning data apps.

Check out the live Example App.

⚙️ Install Locally

git clone https://github.com/MarcSkovMadsen/awesome-panel-lightning.git
cd awesome-panel-lightning

Create and activate your local environment.

Then install the requirements via

pip install -r requirements.txt

Finally you can update the name of the app in the .lightning file.

🏃 Run Locally

Activate your virtual environment and run

lightning run app app.py

☁️ Run in lightning.ai cloud

Activate your virtual environment and run

lightning run app app.py --cloud

and follow the instructions

Add or Update the App Pages

The different pages of the app of configured in the app.py file.

Most pages are configured as files. But you can also use functions that return a Panel Viewable like the introduction function.

class LitApp(lapp.LightningFlow):
    def __init__(self):
        super().__init__()
        self.lit_intro = LitPanelPage(page=introduction, parallel=True)
        self.lit_big_data_viz = LitPanelPage(page="pages/big_data_viz.py", parallel=True)
        self.lit_crossfilter = LitPanelPage(page="pages/cross_filter.py", parallel=True)
        self.lit_streaming = LitPanelPage(page="pages/streaming.py", parallel=True)

    def run(self):
        self.lit_intro.run()
        self.lit_big_data_viz.run()
        self.lit_crossfilter.run()
        self.lit_streaming.run()

    def configure_layout(self):
        return [
            self.lit_intro.get_tab(name="Introduction"),
            self.lit_crossfilter.get_tab(name="Crossfiltering"),
            self.lit_streaming.get_tab(name="Streaming"),
            self.lit_big_data_viz.get_tab(name="Big Data Viz"),
        ]

app = lapp.LightningApp(LitApp())

🐛 Active issues

• LightningFlow expects too fast an initial response from other servers