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Plotly-gif



PyPI downloads license

A simple python package to generate .gif from your plotly figures. It works for both 2D and 3D figures. It can even create_gif motion for you in 3D plots.

Installation

pip install plotly-gif

Dependencies

If you are already using plotly, then you should be good. But, just in case, these are the dependencies:

  • plotly (5.9.0)
    • Plots molecules
  • kaleido (0.1.0post1)
    • Converts plotly graphs to images (png, svg, etc.)
    • I am not using the most recent version of kaleido as it does not play nice with my computer. Try the newest version, but if you are having issues install this specific version.
  • Pillow (9.2.0)
    • Used to convert png to gif.
  • numpy (1.23.1)
    • Used for math

Usage

There are three common methods:

Built-in Functions/ Macros

Currently, we have the follow:

  • two_d_time_series
  • three_d_scatter_rotate
  • more to come... or submit your own
import plotly.graph_objs as go
from plotly_gif import GIF, two_d_time_series

fig = go.Figure()
# add your traces()
# add your formatting()

gif = GIF()
two_d_time_series(gif, fig)

Decorator

If you have a function that is changing the `go.Figure' with each loop, you can add the decorator to the func.

import plotly.graph_objs as go
from plotly_gif import GIF, capture

gif = GIF()

@capture(gif)
def plot_(x_, y_):
    fig = go.Figure()
    # add your traces()
    # add your formatting()
    
    return fig

gif.create_gif() # generate gif

In-Line

This very similar to the decorator option, but you can call the image capture function directly.

import plotly.graph_objs as go
from plotly_gif import GIF, capture

gif = GIF()

def plot_(x_, y_):
    fig = go.Figure()
    # add your traces()
    # add your formatting()
    
    gif.create_image(fig)  # create_gif image for gif
    
    return fig

gif.create_gif() # generate gif

Examples

See examples folder

2d gif

3d gif

Time to generate gif (60 images per gif)

  • Simple 2D plots with small data sets (100 pts): ~10 sec
  • Simple 3D plots with small data sets (100 pts): ~1.5 min

Warning

  • If your code 'hangs' or 'gets stuck and doesn't complete' try changing kaleido versions pip install kaleido==0.1.0post1