docs CI: re-clone StochasticDiffEq fresh in env setup (complete #870 fix) (#872)

* docs: build against released (registry) OrdinaryDiffEq/StochasticDiffEq

Drop the `Pkg.develop` of OrdinaryDiffEq and StochasticDiffEq in the docs build
(and the env-setup re-clone dance), resolving them — and all the solver
subpackages — from the registry at their released versions instead of master.

Why:
  - StochasticDiffEq is a subpackage of the OrdinaryDiffEq.jl monorepo as of v7
    (registry `repo = OrdinaryDiffEq.jl`, `subdir = lib/StochasticDiffEq`), so
    `Pkg.develop("StochasticDiffEq")` re-cloned the same monorepo and the stale
    leftover checkout of the old `SciML/StochasticDiffEq.jl` repo (6.100.0) broke
    resolution against the docs `[compat] = "7"`:
        ERROR: empty intersection between StochasticDiffEq@6.100.0 and compat 7
  - `Pkg.develop`ing the monorepo master also risks version skew: the dev'd
    master meta-package's subpackage [compat] must be satisfiable by the
    *registered* subpackages (sources don't propagate to the docs project), which
    breaks whenever master races ahead of the registry.
  - The released packages already ship their `docs/` (OrdinaryDiffEq 7.0.0's
    tarball includes `docs/` with pages.jl + src + common_*_steps.jl), so the API
    docs can be copied from the installed stable packages with no dev checkout.

Net effect: the stable docs reflect released versions, the stale-checkout failure
mode and the monorepo skew are both gone, and env-setup is just instantiate.

(StochasticDiffEq's registered tarball does not yet ship `docs/` — its docs/ needs
to be migrated into lib/StochasticDiffEq in the monorepo; until then the
"StochasticDiffEq.jl API" section stays dropped, as added in #869.)

Co-Authored-By: Chris Rackauckas <accounts@chrisrackauckas.com>
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

* docs: source EnsembleProblem from SciMLBase in the low_dep example

Building against the stable release (previous commit) surfaced that
OrdinaryDiffEq 7.0.0 does not re-export `EnsembleProblem` (master does), so the
low-dependency example's `ODE.EnsembleProblem` was an `UndefVarError`. Source it
from SciMLBase, which defines it — consistent with this page's own point that
"you will always need SciMLBase.jl, since it defines all of the fundamental
types." This is the only docs `@example` affected: across all of docs/src the
only OrdinaryDiffEq-exported-on-master-but-not-7.0.0 symbol used via the alias is
`EnsembleProblem`, here.

Verified locally on the released stack (OrdinaryDiffEq 7.0.0 + OrdinaryDiffEqLowOrderRK
+ DiffEqCallbacks + SciMLBase): the example's ensemble solve runs successfully.

Co-Authored-By: Chris Rackauckas <accounts@chrisrackauckas.com>
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

---------

Co-authored-by: ChrisRackauckas-Claude <accounts@chrisrackauckas.com>
Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

Author: 3 people

.github/workflows/Documentation.yml

@@ -31,14 +31,6 @@ jobs:
           using Pkg
           Pkg.develop(PackageSpec(path=pwd()))
           Pkg.instantiate()
-          println("--- Adding OrdinaryDiffEq from master")
-          # Drop any stale dev checkout a previous run left in ~/.julia/dev so the
-          # current master is cloned fresh; a stale checkout can pin an old version
-          # that conflicts with the docs [compat] (e.g. OrdinaryDiffEq 6.x vs "7").
-          let p = joinpath(Pkg.devdir(), "OrdinaryDiffEq")
-              isdir(p) && rm(p; recursive = true, force = true)
-          end
-          Pkg.develop("OrdinaryDiffEq")
         env:
           DATADEPS_ALWAYS_ACCEPT: true
           JULIA_PKG_PRECOMPILE_AUTO: 0

docs/make.jl

@@ -25,10 +25,11 @@ import ODEProblemLibrary,
     SDEProblemLibrary, DDEProblemLibrary, DAEProblemLibrary, BVProblemLibrary
 using Sundials, DASKR, LSODA, DASSL, SimpleDiffEq, ODEInterfaceDiffEq
 
-# Use development versions for API documentation
-import Pkg
-Pkg.develop("OrdinaryDiffEq")
-Pkg.develop("StochasticDiffEq")
+# OrdinaryDiffEq, StochasticDiffEq and the solver subpackages are resolved from the
+# registry at their released versions — their docs/ ship in the released packages,
+# so the API docs below are copied from the installed (stable) packages with no
+# Pkg.develop of master (which would pin the docs to unreleased code and risk
+# monorepo version skew against the registered subpackages).
 
 cp("./docs/Manifest.toml", "./docs/src/assets/Manifest.toml", force = true)
 cp("./docs/Project.toml", "./docs/src/assets/Project.toml", force = true)

docs/src/features/low_dep.md

@@ -121,6 +121,7 @@ the old `using DifferentialEquations` shape:
 import OrdinaryDiffEq as ODE
 import OrdinaryDiffEqLowOrderRK as ODELow # Euler
 import DiffEqCallbacks as CB              # ProbIntsUncertainty
+import SciMLBase                          # EnsembleProblem
 function fitz(du, u, p, t)
     V, R = u
     a, b, c = p
@@ -132,7 +133,7 @@ tspan = (0.0, 20.0)
 p = (0.2, 0.2, 3.0)
 prob = ODE.ODEProblem(fitz, u0, tspan, p)
 cb = CB.ProbIntsUncertainty(0.2, 1)
-ensemble_prob = ODE.EnsembleProblem(prob)
+ensemble_prob = SciMLBase.EnsembleProblem(prob)
 sim = ODE.solve(ensemble_prob, ODELow.Euler(), trajectories = 100, callback = cb, dt = 1 / 10)
 ```