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plotly:

description:Plotly allows you to save static images of your plots. Save the image

permalink:python/static-image-export/

thumbnail:thumbnail/static-image-export.png

title:Static Image Export | plotly

v4upgrade:true

Plotly's Python library is free and open source by downloading the client and[reading the primer](https://plot.ly/python/getting-started/).

<br>You can set up Plotly to work in[online](https://plot.ly/python/getting-started/#initialization-for-online-plotting) or[offline](https://plot.ly/python/getting-started/#initialization-for-offline-plotting) mode, or in[jupyter notebooks](https://plot.ly/python/getting-started/#start-plotting-online).

<br>We also have a quick-reference[cheatsheet](https://images.plot.ly/plotly-documentation/images/python_cheat_sheet.pdf) (new!) to help you get started!

Note: The static image export API is available in version <b>3.2.0.+</b><br>

import plotly

plotly.__version__

New in version 3.2.0.It's now possible to programmatically export figures as high quality static images while fully offline.

It's possible to programmatically export figures as high quality static images while fully offline.

Static image generation requires the[orca](https://github.com/plotly/orca) commandline utility and the[psutil](https://github.com/giampaolo/psutil) Pythonlibrary. There are 3 general approach to installing these dependencies.

Static image generation requires the[orca](https://github.com/plotly/orca) commandline utility and the[psutil](https://github.com/giampaolo/psutil)and[requests](https://2.python-requests.org/en/master/)Pythonlibraries. There are 3 general approach to installing these dependencies.

Using the[conda](https://conda.io/docs/) package manager, you can install these dependencies in a single command:

**Note:** Even if youdon't want to use conda to manage your Python dependencies, it is still useful as a cross platform tool for managing native libraries and command-line utilities (e.g. git, wget, graphviz, boost, gcc, nodejs, cairo, etc.). For this use-case, start with[Miniconda](https://conda.io/miniconda.html) (~60MB) and tell the installer to add itself to your system`PATH`. Then run`conda install plotly-orca` and the orca executable will be available system wide.

**Note:** Even if youdo not want to use conda to manage your Python dependencies, it is still useful as a cross platform tool for managing native libraries and command-line utilities (e.g. git, wget, graphviz, boost, gcc, nodejs, cairo, etc.). For this use-case, start with[Miniconda](https://conda.io/miniconda.html) (~60MB) and tell the installer to add itself to your system`PATH`. Then run`conda install plotly-orca` and the orca executable will be available system wide.

You can use the[npm](https://www.npmjs.com/get-npm) package manager to install`orca` (and its`electron` dependency), and then use pip to install`psutil`:

If you are unable to install conda or npm, you can install orca as a precompiled binary for your operating system. Follow the instructions in the orca[README](https://github.com/plotly/orca) to install orca and add it to your system`PATH`. Then use pip to install`psutil`.

Now let's create a simple scatter plot with 100 random points of variying color and size.

from plotly.offlineimport iplot, init_notebook_mode

import plotly.graph_objsas go

import plotly.ioas pio

import os

import numpyas np

We'll configure the notebook for use in[offline](https://plot.ly/python/getting-started/#initialization-for-offline-plotting) mode

init_notebook_mode(connected=True)

N=100

x= np.random.rand(N)

y= np.random.rand(N)

colors= np.random.rand(N)

sz= np.random.rand(N)*30

sz= np.random.rand(N)*30

fig= go.Figure()

fig.add_scatter(x=x,

y=y,

mode='markers',

marker={'size': sz,

'color': colors,

'opacity':0.6,

'colorscale':'Viridis'

})

iplot(fig)

fig.add_trace(go.Scatter(

x=x,

y=y,

mode="markers",

marker=go.scatter.Marker(

size=sz,

color=colors,

opacity=0.6,

)

))

fig.show()

The`plotly.io.write_image` function is used to write an image to a file or file-like python object.

The`plotly.io.write_image` function is used to write an image to a file or file-like python object. You can also use the`.write_image` graph object figure method.

Let's first create an output directory to store our images

ifnot os.path.exists('images'):

os.mkdir('images')

import os

ifnot os.path.exists("images"):

os.mkdir("images")

If you are running this notebook live, click to[open the output directory](./images) so you can examine the images as they're written.

If you are running this notebook live, click to[open the output directory](./images) so you can examine the images as they are written.

Orca can output figures to several raster image formats including**PNG**, ...

pio.write_image(fig,'images/fig1.png')

fig.write_image("images/fig1.png")

**JPEG**, ...

pio.write_image(fig,'images/fig1.jpeg')

fig.write_image("images/fig1.jpeg")

and**WebP**

pio.write_image(fig,'images/fig1.webp')

fig.write_image("images/fig1.webp")

Orca can also output figures in several vector formats including**SVG**, ...

pio.write_image(fig,'images/fig1.svg')

fig.write_image("images/fig1.svg")

**PDF**, ...

pio.write_image(fig,'images/fig1.pdf')

fig.write_image("images/fig1.pdf")

and**EPS** (requires the poppler library)

pio.write_image(fig,'images/fig1.eps')

fig.write_image("images/fig1.eps")

**Note:** It is important to note that any figures containing WebGL traces (i.e. of type`scattergl`,`heatmapgl`,`contourgl`,`scatter3d`,`surface`,`mesh3d`,`scatterpolargl`,`cone`,`streamtube`,`splom`, or`parcoords`) that are exported in a vector format will include encapsulated rasters, instead of vectors, for some parts of the image.

The`plotly.io.to_image` function is used to return an image as a bytes object.

The`plotly.io.to_image` function is used to return an image as a bytes object. You can also use the`.to_image` graph object figure method.

Let convert the figure to a**PNG** bytes object...

img_bytes=pio.to_image(fig,format='png')

img_bytes=fig.to_image(format="png")

and then display the first 20 bytes.

In addition to the image format, the`to_image` and`write_image` functions provide arguments to specify the image`width` and`height` in logical pixels. They also provide a`scale` parameter that can be used to increase (`scale` > 1) or decrease (`scale` < 1) the physical resolution of the resulting image.

img_bytes=pio.to_image(fig,format='png',width=600,height=350,scale=2)

img_bytes=fig.to_image(format="png",width=600,height=350,scale=2)

Image(img_bytes)

In summary, to export high-quality static images from plotly.py all you need to do is install orcaandpsutil and then use the`plotly.io.write_image` and`plotly.io.to_image` functions.

In summary, to export high-quality static images from plotly.py, all you need to do is install orca, psutil,andrequests and then use the`plotly.io.write_image` and`plotly.io.to_image` functions (or the`.write_image` and`.to_image` graph object figure methods).

If you want to know more about how the orca integration works, or if you need to troubleshoot an issue, please check out the[Orca Management](../orca-management/) section.

from IPython.displayimport display,HTML

display(HTML('<link href="//fonts.googleapis.com/css?family=Open+Sans:600,400,300,200|Inconsolata|Ubuntu+Mono:400,700" rel="stylesheet" type="text/css" />'))

display(HTML('<link rel="stylesheet" type="text/css" href="http://help.plot.ly/documentation/all_static/css/ipython-notebook-custom.css">'))

! pip install git+https://github.com/plotly/publisher.git--upgrade

import publisher

publisher.publish(

'static-image-export.ipynb','python/static-image-export/','Static Image Export | plotly',

'Plotly allows you to save static images of your plots. Save the image to your local computer, or embed it inside your Jupyter notebooks as a static image.',

title='Static Image Export | plotly',

name='Static Image Export',

thumbnail='thumbnail/static-image-export.png',

language='python',

uses_plotly_offline=True,

page_type='example_index',has_thumbnail='true',display_as='file_settings',order=1,

ipynb='~notebook_demo/252')