Optimisation (#127)
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2 changed files with 34 additions and 17 deletions
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@ -161,6 +161,10 @@ and then only convert them to C data structures when you have to call the C func
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3. The raylib.* functions are potentially 1.5x faster than the pyray.* equivalents, so if you need a tiny bit more performance
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you can switch your inner loop functions to these.
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4. There is a version of Python that is faster than Pypy: GraalPy. However it's not fully compatible with all Python
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packages. It doesn't work with CFFI and so doesn't work with this binding. But it *is* compatible with the
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*Java* binding, Jaylib! There is an example of this here: https://github.com/electronstudio/megabunny/tree/master/raylib-python-jaylib
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## Bunnymark
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@ -175,6 +179,8 @@ you can switch your inner loop functions to these.
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| Raylib Python CFFI 3.7 | Python 3.9 Nuitka | 8600 | 5.1% |
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| Raylib Python CFFI 3.7 Dynamic | Python 3.9 | 6300 | 3.7% |
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See also https://github.com/electronstudio/megabunny/
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# Packaging your app
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You can create a standalone binary using the Nuitka compiler. For example, here is how to package Bunnymark:
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@ -51,35 +51,46 @@ def pointer(struct):
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# Another way to improve performance might be to special-case simple types before doing the string comparisons
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def _wrap_function(original_func):
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c_args = [str(x) for x in ffi.typeof(original_func).args]
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number_of_args=len(c_args)
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c_arg_is_pointer = [x.kind == 'pointer' for x in ffi.typeof(original_func).args]
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c_arg_is_string = [str(x) == "<ctype 'char *'>" for x in ffi.typeof(original_func).args]
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# print("makefunc ",a, ffi.typeof(a).args)
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def wrapped_func(*args):
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modified_args = []
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for (c_arg, arg) in zip(ffi.typeof(original_func).args, args):
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# print("arg:",str(arg), "c_arg.kind:", c_arg.kind, "c_arg:", c_arg, "type(arg):",str(type(arg)))
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if c_arg.kind == 'pointer':
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if type(arg) is str:
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arg = arg.encode('utf-8')
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# if c_arg is a 'char *' not a 'const char *' then we ought to raise here because its an out
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# parameter and user should supply a ctype pointer, but cffi cant detect const
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args=list(args) # tuple is immutable, converting it to mutable list is faster than constructing new list!
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for i in range(0, number_of_args):
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try:
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arg=args[i]
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except IndexError:
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raise RuntimeError(f"function requires {number_of_args} arguments but you supplied {len(args)}")
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if c_arg_is_pointer[i]:
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if c_arg_is_string[i]: # we assume c_arg is 'const char *'
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try: # if it's a 'char *' then user should be supplying a ctype pointer, not a Python string
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args[i] = arg.encode('utf-8') # in that case this conversion will fail
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except AttributeError: # but those functions are uncommon, so quicker on average to try the conversion
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pass # and ignore the exception
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# if user supplied a Python string but c_arg is a 'char *' not a 'const char *' then we ought to raise
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# exception because its an out
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# parameter and user should supply a ctype pointer, but we cant because cffi cant detect 'const'
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# so we would have to get the info from raylib.json
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elif type(arg) is list and str(c_arg) == "<ctype 'char * *'>":
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arg = [ffi.new("char[]", x.encode('utf-8')) for x in arg]
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elif c_args[i] == "<ctype 'char * *'>" and type(arg) is list:
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args[i] = [ffi.new("char[]", x.encode('utf-8')) for x in arg]
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elif is_cdata(arg) and "*" not in str(arg):
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arg = ffi.addressof(arg)
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args[i] = ffi.addressof(arg)
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elif arg is None:
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arg = ffi.NULL
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args[i] = ffi.NULL
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elif not is_cdata(arg):
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if str(c_arg) == "<ctype '_Bool *'>":
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if c_args[i] == "<ctype '_Bool *'>":
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raise TypeError(
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"Argument must be a ctype bool, please create one with: pyray.ffi.new('bool *', True)")
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elif str(c_arg) == "<ctype 'int *'>":
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elif c_args[i] == "<ctype 'int *'>":
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raise TypeError(
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"Argument must be a ctype int, please create one with: pyray.ffi.new('int *', 1)")
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elif str(c_arg) == "<ctype 'float *'>":
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elif c_args[i] == "<ctype 'float *'>":
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raise TypeError(
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"Argument must be a ctype float, please create one with: pyray.ffi.new('float *', 1.0)")
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modified_args.append(arg)
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result = original_func(*modified_args)
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result = original_func(*args)
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if result is None:
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return
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elif is_cdata(result) and str(result).startswith("<cdata 'char *'"):
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