diff --git a/README.md b/README.md
index 17fe194..0688261 100644
--- a/README.md
+++ b/README.md
@@ -5,7 +5,7 @@ This program can quickly solve the 2D bin packing problem for any number of any
 ### How to use
 Download the python file, navigate to its location and run it like this:
 
-`python3 polygon_packer.py [n] [nsi] [nsc]`
+`python3 polygon_packer.py -n [n] -nsi [nsi] -nsc [nsc]`
 - Replace `[n]` with the number of inner polygons you want to solve for
 - Replace `[nsi]` with the number of sides of the inner polygons (e.g. 4 for a square)
 - Replace `[nsc]` with the number of sides of the container polygon
diff --git a/polygon_packer.py b/polygon_packer.py
index c67d95a..31d20d9 100644
--- a/polygon_packer.py
+++ b/polygon_packer.py
@@ -5,10 +5,10 @@
 from joblib import Parallel, delayed
 import argparse
 
-arg_parser = argparse.ArgumentParser()
-arg_parser.add_argument("inner_polygons", type=int, help="Number of inner polygons")
-arg_parser.add_argument("inner_sides", type=int, help="Number of sides of the inner polygons")
-arg_parser.add_argument("container_sides", type=int, help="Number of sides of the container polygon")
+arg_parser = argparse.ArgumentParser(formatter_class=argparse.ArgumentDefaultsHelpFormatter)
+arg_parser.add_argument("-n", "--inner_polygons", type=int, required=True, default=argparse.SUPPRESS, help="Number of inner polygons")
+arg_parser.add_argument("-nsi", "--inner_sides", type=int, required=True, default=argparse.SUPPRESS, help="Number of sides of the inner polygons")
+arg_parser.add_argument("-nsc", "--container_sides", type=int, required=True, default=argparse.SUPPRESS, help="Number of sides of the container polygon")
 arg_parser.add_argument("--attempts", type=int, default=1000, help="Number of attempts to run")
 arg_parser.add_argument("--tolerance", type=float, default=1e-8, help="Overlap penalty tolerance. Probably best left at default")
 arg_parser.add_argument("--finalstep", type=float, default=0.0001, help="How small the last theoretical step in container size decrease will be (it gets smaller over time)")