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      1 Use in Python    {#flatbuffers_guide_use_python}
      2 =============
      3 
      4 ## Before you get started
      5 
      6 Before diving into the FlatBuffers usage in Python, it should be noted that the
      7 [Tutorial](@ref flatbuffers_guide_tutorial) page has a complete guide to general
      8 FlatBuffers usage in all of the supported languages (including Python). This
      9 page is designed to cover the nuances of FlatBuffers usage, specific to
     10 Python.
     11 
     12 You should also have read the [Building](@ref flatbuffers_guide_building)
     13 documentation to build `flatc` and should be familiar with
     14 [Using the schema compiler](@ref flatbuffers_guide_using_schema_compiler) and
     15 [Writing a schema](@ref flatbuffers_guide_writing_schema).
     16 
     17 ## FlatBuffers Python library code location
     18 
     19 The code for the FlatBuffers Python library can be found at
     20 `flatbuffers/python/flatbuffers`. You can browse the library code on the
     21 [FlatBuffers GitHub page](https://github.com/google/flatbuffers/tree/master/
     22 python).
     23 
     24 ## Testing the FlatBuffers Python library
     25 
     26 The code to test the Python library can be found at `flatbuffers/tests`.
     27 The test code itself is located in [py_test.py](https://github.com/google/
     28 flatbuffers/blob/master/tests/py_test.py).
     29 
     30 To run the tests, use the [PythonTest.sh](https://github.com/google/flatbuffers/
     31 blob/master/tests/PythonTest.sh) shell script.
     32 
     33 *Note: This script requires [python](https://www.python.org/) to be
     34 installed.*
     35 
     36 ## Using the FlatBuffers Python library
     37 
     38 *Note: See [Tutorial](@ref flatbuffers_guide_tutorial) for a more in-depth
     39 example of how to use FlatBuffers in Python.*
     40 
     41 There is support for both reading and writing FlatBuffers in Python.
     42 
     43 To use FlatBuffers in your own code, first generate Python classes from your
     44 schema with the `--python` option to `flatc`. Then you can include both
     45 FlatBuffers and the generated code to read or write a FlatBuffer.
     46 
     47 For example, here is how you would read a FlatBuffer binary file in Python:
     48 First, import the library and the generated code. Then read a FlatBuffer binary
     49 file into a `bytearray`, which you pass to the `GetRootAsMonster` function:
     50 
     51 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~{.py}
     52     import MyGame.Example as example
     53     import flatbuffers
     54 
     55     buf = open('monster.dat', 'rb').read()
     56     buf = bytearray(buf)
     57     monster = example.GetRootAsMonster(buf, 0)
     58 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
     59 
     60 Now you can access values like this:
     61 
     62 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~{.py}
     63     hp = monster.Hp()
     64     pos = monster.Pos()
     65 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
     66 
     67 ## Support for Numpy arrays
     68 
     69 The Flatbuffers python library also has support for accessing scalar
     70 vectors as numpy arrays. This can be orders of magnitude faster than
     71 iterating over the vector one element at a time, and is particularly
     72 useful when unpacking large nested flatbuffers. The generated code for
     73 a scalar vector will have a method `<vector name>AsNumpy()`. In the
     74 case of the Monster example, you could access the inventory vector
     75 like this:
     76 
     77 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~{.py}
     78     inventory = monster.InventoryAsNumpy()
     79     # inventory is a numpy array of type np.dtype('uint8')
     80 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
     81 
     82 instead of
     83 
     84 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~{.py}
     85     inventory = []
     86     for i in range(monster.InventoryLength()):
     87         inventory.append(int(monster.Inventory(i)))
     88 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
     89 
     90 Numpy is not a requirement. If numpy is not installed on your system,
     91 then attempting to access one of the `*asNumpy()` methods will result
     92 in a `NumpyRequiredForThisFeature` exception.
     93 
     94 ## Text Parsing
     95 
     96 There currently is no support for parsing text (Schema's and JSON) directly
     97 from Python, though you could use the C++ parser through SWIG or ctypes. Please
     98 see the C++ documentation for more on text parsing.
     99 
    100 <br>
    101