diff --git a/python/numexpr/README b/python/numexpr/README
index 30cffee3aa..5ef2b91721 100644
--- a/python/numexpr/README
+++ b/python/numexpr/README
@@ -1,12 +1,13 @@
-The numexpr package evaluates multiple-operator array expressions many times
-faster than NumPy can. It accepts the expression as a string, analyzes it,
-rewrites it more efficiently, and compiles it to faster Python code on the
-fly. It's the next best thing to writing the expression in C and compiling
-it with a specialized just-in-time (JIT) compiler, i.e. it does not require
-a compiler at runtime.
+The numexpr package evaluates multiple-operator array expressions
+many times faster than NumPy can. It accepts the expression as a
+string, analyzes it, rewrites it more efficiently, and compiles it to
+faster Python code on the fly. It's the next best thing to writing the
+expression in C and compiling it with a specialized just-in-time (JIT)
+compiler, i.e. it does not require a compiler at runtime.
 
-Also, and since version 1.4, numexpr implements support for multi-threading
-computations straight into its internal virtual machine, written in C. This
-allows to bypass the GIL in Python, and allows near-optimal parallel
-performance in your vector expressions, most specially on CPU-bounded
-operations (memory-bounded were already the strong point of Numexpr).
+Also, and since version 1.4, numexpr implements support for
+multi-threading computations straight into its internal virtual
+machine, written in C. This allows to bypass the GIL in Python, and
+allows near-optimal parallel performance in your vector expressions,
+most specially on CPU-bounded operations (memory-bounded were already
+the strong point of Numexpr).