Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Jump to bottom

Remove outdated description of set_default_backend! #352

Merged
merged 1 commit into from
Jul 9, 2024
Merged

Remove outdated description of set_default_backend! #352

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
16 changes: 0 additions & 16 deletions docs/src/backends.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -50,22 +50,6 @@ For those who haven't had the pleasure of hacking on 15 different plotting APIs:
However, you will probably have a hard time choosing the right backend for your task at hand.
This document is meant to be a guide and introduction to make that choice.

# Persistent backend selection

Plots uses the [Preferences](https://github.com/JuliaPackaging/Preferences.jl) mechanism to make the default backend choice persistent across julia restart.

```julia
$ JULIA_PKG_PRECOMPILE_AUTO=0 julia -e 'import Plots; Plots.set_default_backend!(:pythonplot)'
$ julia # restart, show persistent mode
julia> using Plots
[ Info: Precompiling Plots [91a5bcdd-55d7-5caf-9e0b-520d859cae80]
[ Info: PythonPlot # precompiles for this backend
julia> plot(1:2) |> display # uses `PythonPlot` by default
```

You can clear preferences with `Plots.set_default_backend!()`.
Alternatively, one can use the environment variable `PLOTS_DEFAULT_BACKEND` to select the default backend (but this will need to trigger manual precompilation using `Base.compilecache(Plots)`).

# At a glance

My favorites: `GR` for speed, `Plotly(JS)` for interactivity, `UnicodePlots` for REPL/SSH and `PythonPlot` otherwise.
Expand Down
Loading