In addition to translating the comment itself, also document the type of the
object returned. This is consistent with generating not only :param: but also
:type: for the parameters documented using @param.
The most important change is to ensure that the "Overload" headers added by
PyDocConverter code are indented correctly, i.e. using the same indent level
as the comment itself, otherwise Sphinx directives such as :param: were not
parsed correctly.
Also add a vertical separator using reST "|" formatting character to increase
separation between the overloads.
This was done for plain functions/methods but not constructors, which don't
have "kind=function" attribute.
Just don't check for "kind" at all, the presence of "sym:overloaded" should be
good enough to indicate that it's an overloaded something.
Also add a test for overloaded constructors documentation.
Enum values are just (integer) constants in Python and so can be used as the
function default values just as well as literal numbers, account for this when
checking whether function parameters can be represented in Python.
Also rename is_primitive_defaultargs() to is_representable_as_pyargs() to
describe better what this function does.
Due to what seems like a bug introduced during Python 3 support merge, all the
generated Python functions used the general "*args" signature instead of using
the named parameters when possible.
This happened due to is_primitive_defaultargs() always returning false for the
functions without any default arguments as "value" passed to convertValue()
was NULL in this case and convertValue() always returns false for NULL.
Fix this by checking for value being non-NULL before calling convertValue().
Doing this exposed several problems with the handling of unnamed, duplicate
(happens for parameters called INOUT, for example) or clashing with keywords
parameter names, so the code dealing with them had to be fixed too. Basically
just use makeParameterName() consistently everywhere.
This method was duplicated more or less identically for 4 languages and will
be needed for another one soon, so put it in the base class from which it can
be simply reused instead.
No changes in the program behaviour whatsoever.
This doesn't play well with PEP8 checks which imposes very strict continuation
line indentation rules which need to be _visually_ aligned, i.e. the subsequent
lines must be indented by the position of the opening bracket in the function
declaration line, but the code generating the parameter lists doesn't have
this information and so it's impossible to do it while avoiding either E128 or
E123 ("continuation line {under,over}-indented for visual indent" respectively)
error from pep8.
Moreover, the wrapping code didn't work correctly anyhow as it only took into
account the length of the parameter list itself and not the total line length,
which should include the function name as well.
So just disable wrapping entirely, long lines shouldn't be a problem anyhow in
auto-generated code.
Make the rules for combining explicitly specified docstring, autodoc one and
the one obtained by translating Doxygen comments implicit in the structure of
the code itself instead of writing complicated conditions checking them.
This results in small changes to the whitespace in the generated Python code
when using autodoc, but this makes it PEP 8-compliant, so it is the right
thing to do anyhow.
Also cache the docstring built from translated Doxygen comments. The existing
code seemed to intend to do it, but didn't, really. This helps with
performance generally speaking (-10% for a relatively big library using a lot
of Doxygen comments) and also makes debugging Doxygen translation code less
painful as it's executed only once instead of twice for each comment.
Finally, avoid putting "r", used for Python raw strings, into docstrings in C
code, it is really not needed there.
It is very useful to be able to click on the parameter types in a function
documentation to go to this parameter description, so always use hyperlink
markup for the parameters of class types, even if not all of them are
necessarily documented -- Sphinx doesn't seem to complain about links to
unknown classes.
This will allow to reuse them in the code that doesn't have access to a
Language object, such as DoxygenTranslator implementation.
These methods didn't really use any of Language object non-static fields
anyhow, the only one they did use (classtypes or enumtypes, respectively), was
only used for caching and can just as well be made local to the function
itself as long as we use other global variables anyhow.
For the parameter documentation to be really taken as such, in its entirety,
by Sphinx, it must be indented relative to the :param: tag. Do this by
appending an extra indent after every line of the output and work around the
unnecessary indent of the last line by removing the trailing whitespace.
This required updating the existing tests and removing the expected but not
present any more whitespace from them, but as trailing whitespace in the
documentation is at best insignificant (and at worst harmful) anyhow, this is
not a big price to pay for simpler translator code.
justifyString() was unused and doesn't seem to be useful as there are no
particular constraints on the line length in Python documentation, so just
preserve whatever is used in the original C++ code.
This is important to preserve the structure of the lists which appear
correctly in Python output without any additional effort if the indentation is
lost.
It is also makes the behaviour consistent for
/**
*
*
*/
comments and those without the asterisks in the middle lines, as now the
indentation is preserved in both cases while it was only preserved when the
asterisks were present previously.
Sphinx doesn't allow sections inside the function documentation and gives tons
of SEVERE warnings for them, so while just emphasizing the "Overload" header
is not ideal, it is better than before because at least the string "Overload"
itself appears in the Sphinx-generated output.
Using C++ types in documentation for Python users is more harmful than
useless, so use Python types whenever possible and allow defining "doctype"
typemap to customize this for the user-defined types.
Enum values are just (integer) constants in Python and so can be used as the
function default values just as well as literal numbers, account for this when
checking whether function parameters can be represented in Python.
Also rename is_primitive_defaultargs() to is_representable_as_pyargs() to
describe better what this function does.
Due to what seems like a bug introduced during Python 3 support merge, all the
generated Python functions used the general "*args" signature instead of using
the named parameters when possible.
This happened due to is_primitive_defaultargs() always returning false for the
functions without any default arguments as "value" passed to convertValue()
was NULL in this case and convertValue() always returns false for NULL.
Fix this by checking for value being non-NULL before calling convertValue().
Doing this exposed several problems with the handling of unnamed, duplicate
(happens for parameters called INOUT, for example) or clashing with keywords
parameter names, so the code dealing with them had to be fixed too. Basically
just use makeParameterName() consistently everywhere.
This method was duplicated more or less identically for 4 languages and will
be needed for another one soon, so put it in the base class from which it can
be simply reused instead.
No changes in the program behaviour whatsoever.
Sphinx is smart enough to use the docstrings following the constant definition
in Python code as its documentation, so doing this is still useful even if
Python itself doesn't support having docstrings for the variables (and this is
why it's impractical to write a unit test for the changes of this commit: we
can't easily extract the generated docstrings).
reST is standard Python markup, so use *...*, ``...`` and so on instead of
_..._, '...' etc.
No other changes even though the mapping of some Doxygen tags to markup used
for them seems suspicions (e.g. \var almost certainly should be the same as
\em).
Use the more or less standard :param:, :type:, :return: and :raises: in the
function/methods descriptions.
Update the output expected from the Python tests accordingly.
Avoid having to pass dummy empty string arguments, just use default value for
the unused last parameter of handleParagraph().
Also get rid of dozens of "" occurrences in the tag map initialization code,
use a helper function instead.
No real changes.
This makes the code more readable and more extensible as more flags are easier
to add in the future than more boolean parameters.
No user-visible changes.
Update Doxygen-specific Python unit tests to work with the new indentation.
Update one of Doxygen-specific Java tests to still build with the new handling
of srcdir.
This doesn't play well with PEP8 checks which imposes very strict continuation
line indentation rules which need to be _visually_ aligned, i.e. the subsequent
lines must be indented by the position of the opening bracket in the function
declaration line, but the code generating the parameter lists doesn't have
this information and so it's impossible to do it while avoiding either E128 or
E123 ("continuation line {under,over}-indented for visual indent" respectively)
error from pep8.
Moreover, the wrapping code didn't work correctly anyhow as it only took into
account the length of the parameter list itself and not the total line length,
which should include the function name as well.
So just disable wrapping entirely, long lines shouldn't be a problem anyhow in
auto-generated code.
