26.11.20 19:07, Guido van Rossum пише:
> This reminds me of something in C++. Does it exist in other languages?
Indeed, this is a term from C++. In older C++ you could pass argument by
value, which makes a copy, and by reference, which is equivalent to
passing a pointer by value plus syntax sugar. Passing by value may be
inefficient if you need to copy more than several bytes. Passing by
reference has other problems. It was a source of errors, so passing
object created on stack by non-constant reference was forbidden. If you
need to modify argument passed by constant reference in the function you
need to create a copy, even if the object is never used after passing to
the function (like in foo(bar()), the returned value of bar() cannot be
used outside of foo(), so it could be allow to modify it). To resolve
this problem the move semantic was introduced.
> Do you have a more realistic example where this would catch an important
> type error?
I seen and used the following example (with variations) multiple times:
class Client:
def send(self, msg, token, headers=None):
if headers is None:
headers = {}
# headers = headers.copy()
headers["Authorization"] = f"Bearer {token}"
headers["Content-Type"] = "text/plain"
headers["X-Hash"] = md5sum(msg.encode())
with self.request('POST', self.url, headers=headers,
data=msg) as resp:
...
client.send('Hello!', mytoken, headers={'X-Type': 'Spam'})
The function sets some standard headers, but you can pass also
additional headers. If you only pass a just created dictionary, the
function can modify it in-place because its value is not used outside.
But if you create the dict once and use it in other places, modifying it
inside the function is a non-desired effect. You need to make a copy in
the function just because you don't know how it will be used in the user
code. If you document that the argument cannot be used after calling the
function and add some marks for static type checking, you could avoid
copying.
Personally I think Python has a little need in such feature. Copied
dicts and lists are usually small, and it adds not much overhead in
comparison with other overhead that Python does have. And if you need to
pass and modify a large collection, documenting this should be enough.
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