housekeeping and docs working locally

.JuliaFormatter.toml

@@ -0,0 +1 @@
+style = "sciml"

.gitignore

@@ -1,6 +1,2 @@
-<<<<<<< HEAD
-/Manifest.toml
-docs/build
-=======
 Manifest.toml
->>>>>>> docs
+docs/build

.pre-commit-config.yaml

@@ -0,0 +1,6 @@
+repos:
+  - repo: https://github.com/qiaojunfeng/pre-commit-julia-format
+    rev: v0.2.0                # use the most recent version
+    hooks:
+    - id: julia-format         # formatter for Julia code
+      args: [--project=.]

docs/make.jl

@@ -1,22 +1,20 @@
 using Documenter, e3nn
 
 mathengine = MathJax3()
+prettyurls = get(ENV, "CI", nothing) == "true"
 
 makedocs(
     modules = [e3nn],
     doctest = false,
     clean = true,
-    sitename="e3nn.jl",
-    format = Documenter.HTML(
-        canonical = "https://dsantra92.github.io/e3nn.jl/stable/",
+    sitename = "e3nn.jl",
+    format = Documenter.HTML(;
         mathengine,
+        prettyurls,
         assets = ["assets/favicon.ico"],
-        prettyurls = get(ENV, "CI", nothing) == "true",
-        collapselevel=3,
+        collapselevel = 3
     ),
-        pages = ["Home" => "Index.md",
-             "API Reference" => [
-                 "o3" => "api/o3.md",
-             ],
-    ]
-    )
+    pages = ["Home" => "index.md", "API Reference" => ["o3" => "api/o3.md"]]
+)
+
+deploydocs(repo = "github.com/Dsantra92/e3nn.jl.git")

docs/src/index.md

@@ -1,3 +1,3 @@
-# e3nn.jl
+# e3nn
 
-E(3) equivariant neural networks in Julia.
+Julia implementation of e3nn python library.

src/e3nn.jl

@@ -3,5 +3,4 @@ module e3nn
 # o3
 include("o3/o3.jl")
 
-
 end