[Python] (scalar) vector reading speedup via numpy (#4390)

* Add numpy accessor to python flatbuffers scalar vectors

* Update python tests to test numpy vector accessor

* Update appveyor CI to run Python tests, save generated code as artifact

* Update example generated python code

* Add numpy info to python usage docs

* Update test schema and python tests w/ multi-byte vector

* did not mean to push profiling code

* adding float64 numpy tests

1 files changed, 27 insertions, 0 deletions

diff --git a/docs/source/PythonUsage.md b/docs/source/PythonUsage.md
index 2a0cddee..f338cda4 100755
--- a/docs/source/PythonUsage.md
+++ b/docs/source/PythonUsage.md
@@ -64,6 +64,33 @@ Now you can access values like this:
     pos = monster.Pos()
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 
+## Support for Numpy arrays
+
+The Flatbuffers python library also has support for accessing scalar
+vectors as numpy arrays. This can be orders of magnitude faster than
+iterating over the vector one element at a time, and is particularly
+useful when unpacking large nested flatbuffers. The generated code for
+a scalar vector will have a method `<vector name>AsNumpy()`. In the
+case of the Monster example, you could access the inventory vector
+like this:
+
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~{.py}
+    inventory = monster.InventoryAsNumpy()
+    # inventory is a numpy array of type np.dtype('uint8')
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+instead of
+
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~{.py}
+    inventory = []
+    for i in range(monster.InventoryLength()):
+        inventory.append(int(monster.Inventory(i)))
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+Numpy is not a requirement. If numpy is not installed on your system,
+then attempting to access one of the `*asNumpy()` methods will result
+in a `NumpyRequiredForThisFeature` exception.
+
 ## Text Parsing
 
 There currently is no support for parsing text (Schema's and JSON) directly