From 2847dc132817c729a5af559a4b3293f5df7f1a30 Mon Sep 17 00:00:00 2001
From: logan <logan@gatlintc.com>
Date: Wed, 31 Jul 2024 18:25:10 -0500
Subject: [PATCH] Updated README.md

---
 README.md | 33 +++++++++++++++++++++++++++++++++
 1 file changed, 33 insertions(+)
 create mode 100644 README.md

diff --git a/README.md b/README.md
new file mode 100644
index 0000000..1a42e0c
--- /dev/null
+++ b/README.md
@@ -0,0 +1,33 @@
+# nrange
+The Rust standard library has a Range type, which represents a bounds for
+a scalar value (i.e. 1 ≤ n ≤ 100). A range can be open ended, iterated over,
+and tested for overlap with other ranges. I designed nrange as an extension
+of the Range type to vector space. This makes code less nested. Below is an
+example comparing an operation on a 3D array using standard Ranges and nrange.
+```rust
+let array3 = [[[0; 128]; 128]; 128];
+// Using standard Ranges
+for x in 0..128 {
+  for y in 0..128 {
+    for z in 0..128 {
+      let element = &array3[x][y][z];
+      // Do something with element
+    }
+  }
+} 
+// Using nrange
+for [x, y, z] in nrange!(0..128, 0..128, 0..128) {
+  let element = &array3[x][y][z];
+  // Do something with element
+}
+```
+## Performance
+My implementation is competitive with similar libraries in the Rust
+ecosystem. While nrange only works for ranges of contiguous
+integers, itertools and cartesian-rs work for any iterators.
+However, by restricting my use case I can extract more performance
+gains and integrate better with the Rust standard library. Below
+are benchmark results comparing my solution to comparable libraries:
+* **itertools** ..... 1,821,573 ns
+* **cartesian-rs**... 989,232 ns
+* **nrange** ........ 968,853 ns