From bf662d4349060df3951061cf8c92c34b94f835bc Mon Sep 17 00:00:00 2001
From: Oscar Dowson <odow@users.noreply.github.com>
Date: Wed, 31 Jul 2024 19:01:09 +1200
Subject: [PATCH] [docs] clarify where to type installation commands (#3795)

---
 docs/src/installation.md | 36 ++++++++++++++++++++++--------------
 1 file changed, 22 insertions(+), 14 deletions(-)

diff --git a/docs/src/installation.md b/docs/src/installation.md
index 2a5159c47ca..2d385c9bd78 100644
--- a/docs/src/installation.md
+++ b/docs/src/installation.md
@@ -35,10 +35,12 @@ frequently.
 
 ## Install JuMP
 
-From Julia, JuMP is installed using the built-in package manager:
+JuMP is installed using the built-in Julia package manager. Launch Julia, and
+then enter the following at the `julia>` prompt:
 ```julia
-import Pkg
-Pkg.add("JuMP")
+julia> import Pkg
+
+julia> Pkg.add("JuMP")
 ```
 
 !!! tip
@@ -49,8 +51,9 @@ Pkg.add("JuMP")
 
 When we release a new version of JuMP, you can update with:
 ```julia
-import Pkg
-Pkg.update("JuMP")
+julia> import Pkg
+
+julia> Pkg.update("JuMP")
 ```
 
 ## Install a solver
@@ -58,21 +61,26 @@ Pkg.update("JuMP")
 JuMP depends on solvers to solve optimization problems. Therefore, you will need
 to install one before you can solve problems with JuMP.
 
-Install a solver using the Julia package manager, replacing `"Clp"` by the
+Install a solver using the Julia package manager, replacing `"HiGHS"` by the
 Julia package name as appropriate.
 ```julia
-import Pkg
-Pkg.add("Clp")
+julia> import Pkg
+
+julia> Pkg.add("HiGHS")
 ```
 
-Once installed, you can use Clp as a solver with JuMP as follows, using
+Once installed, you can use HiGHS as a solver with JuMP as follows, using
 [`set_attribute`](@ref) to set solver-specific options:
 ```julia
-using JuMP
-using Clp
-model = Model(Clp.Optimizer)
-set_attribute(model, "LogLevel" => 1)
-set_attribute(model, "PrimalTolerance" => 1e-7)
+julia> using JuMP
+
+julia> using HiGHS
+
+julia> model = Model(HiGHS.Optimizer);
+
+julia> set_attribute(model, "output_flag" => false)
+
+julia> set_attribute(model, "primal_feasibility_tolerance" => 1e-8)
 ```
 
 !!! note