Please refer to the Static Image Export section for general information on creating static images from plotly.py figures. We now recommend Kaleido, as described in the Static Image Export section. To build and install Xvfb, Xnest, Xephyr, and Xfake instead of.As of plotly version 4.9, Orca is no longer the recommended way to do static image export. In Linux we need to find the relevant package names for the package manager and install them (e.g., apt-get install xvfb firefox for Debian based systems like Ubuntu, yum install Xvfb firefox for RedHat based systems, etc.).Starting with Leopard (Mac OS-X 10.5), the version of X11 shipped with Apples OS has. The attached Portfile, xorg-server1.4.2-10.lenny4.debian-only-changes.diff and xvfb-run.diff patches produce a xvfb-run package which installs the debian xvfb-run script and manpage for automating the execution of programs on the Xvfb server during packaging (in order to avoid errors about a missing X11 display).This section covers the lower-level details of how plotly.py can use orca to perform static image generation.apt-get install libgtk2.0-0 libgtk-3-0 libgbm-dev libnotify-dev libgconf-2-4 libnss3 libxss1 libasound2 libxtst6 xauth xvfb CentOS yum install -y xorg-x11-server-Xvfb gtk2-devel gtk3-devel libnotify-devel GConf2 nss libXScrnSaver alsa-libBefore we can use Xvfb, we need to install it (along with the browser we want if it's not already loaded).Installing orca ¶There are 3 general approaches to installing orca and its Python dependencies. Because of this, the first image export operation in an interactive session will typically take a couple of seconds, but then all subsequent export operations will be significantly faster, since the server is already running. See for more information.By default, plotly.py launches the orca server process the first time an image export operation is performed, and then leaves it running until the main Python process exits. In order to provide the fastest possible image export experience, plotly.py launches orca in server mode, and communicates with it over a local port. Orca can run as a command-line utility or as a long-running server process.server_url: The URL to an externally running instance of Orca. You can do this as follows:If you're still having trouble, feel free to ask for help on the forums atIf this happens, follow the instructions in the error message and specify the full path to you orca executable using the plotly.io.orca.config.executable configuration property.In addition to the executable property, the plotly.io.orca.config object can also be used to configure the following options: For example:> plotly.io.orca.config.executable = '/path/to/orca'After updating this executable property, try the export operation again.If it is successful then you may want to save this configuration so that itWill be applied automatically in future sessions. In this case, set the `plotly.io.orca.config.executable`Property to the full path to your orca executable. If plotly.py is unable to find the executable, you'll get an error message that looks something like this: -The orca executable is required in order to export figures as static images,But it could not be found on the system path.Searched for executable 'orca' on the following path:If you haven't installed orca yet, you can do so using conda as follows:$ conda install -c plotly plotly-orca=1.2.1Alternatively, see other installation methods in the orca project README atAfter installation is complete, no further configuration should be needed.If you have installed orca, then for some reason plotly.py was unable toLocate it.For example, if timeout is set to 20, then the orca server will shutdown once is has not been used for at least 20 seconds. timeout: The number of seconds of inactivity required before the orca server is shut down. port: The specific port to use to communicate with the orca server, or None if the port will be chosen automatically.
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