lenspy 1.0.0

Plot big data with Python.

LensPy: Plot millions of datapoints

LensPy extends Plotly's Dash to allow you to plot very large datasets (millions of points) while ensuring that figures are still fast, fluid, and responsive.

This is achieved by adjusting the visible data based on the position of the viewport and how zoomed in the figure is. When you're zoomed out, only a subset of the data is shown. When you zoom in, LensPy will render more detail in your plot. By doing this, LensPy can build dynamic figures of very large datasets without overwhelming the browser when viewing the figures.

Features

• Support for the majority Plotly trace types
• Ability to specify number of points to display at once
• Ability to define a custom function for downsampling data
• Ability to run in Jupyter notebooks (see Getting Started: Jupyter for more information)

Installation

Install LensPy using pip

pip install lenspy

Getting Started

Use LensPy by passing any Figure to the DynamicPlot constructor.

fig = go.Figure(
        data=[go.Scatter(x=df["timestamp"],
                         y=df["close"],
                         name="close")])

plot = DynamicPlot(fig)
plot.show()

# Plot will be available in the browser at http://127.0.0.1:8050/

You can still access any of the Plotly Figure methods/attributes and modify them as needed.

Jupyter

LensPy starts a Flask web server, therefore plots won't be rendered in your notebook as widget. You can always access your plot in a seperate tab (default url is http://127.0.0.1:8050/)

Overriding Flask Arguments

Any argumetns passed to DynamicPlot.show will be passed to App.run_server for Plotly's Dash. You can use this to change the endpoint that they plot is hosted at.

plot = DynamicPlot(fig)
plot.show(port="8051")
# Plot will be available in the browser at http://127.0.0.1:8051/ instead of http://127.0.0.1:8050/

Custom Resolution

You can change the maximum number of points rendered at any given point by setting a value for max_points when creating an instance of DynamicPlot. The default value is 10,240 points.

# Display a plot that only shows a maximum of 1,000 points at a time.

plot = DynamicPlot(fig, max_points=1000)
plot.show()

You may need to adjust this parameter based on your hardware.

Custom Aggregators

The default method for downsampling the graph is to use the first point of each downsampled group. You can override this functionality by specifying a different aggregator.

plot = DynamicPlot(fig, agg_func="avg")
plot.show()

The agg_func parameter is used by Panda's GroupBy aggregate method. Any valid Panda's GroupBy func will work.

Blocking Plots

Unlike standard Plotly plots, DynamicPlot.show() is a blocking function. Therefore, if running in a Jupyter notebook, or in a script, the show method will block indefinitely.

Documentation

For the full reference and detailed information, please see the documentation.

License

Copyright (c) 2020 Seran Thirugnanam under the MIT License.

Contributing

Help is always welcome. Feel free to open issues or PRs if there is a feature missing, or a bug to be addressed.