What are the drawbacks of using autospec in python unittest module - python-2.7

I don't see any major drawbacks for not using autospecs.
I have gone through the documentation, but I am still not clear: https://docs.python.org/3.3/library/unittest.mock.html#auto-speccing
Can someone please explain what this line means with an example.
If any of your specced objects have properties or descriptors that can trigger code execution then you may not be able to use autospec.

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Can't use lldbbridge.py to inspect Qt objects because error in "wrapper prefix"

A little configuration information to start:
Xcode 13
Qt 5.15.5
iOS 14.7.1 (18G82) (I'm running on a device, not a
simulator)
Host MacOS Big Sur 11.6
I'm debugging a large Qt app, all written in C++, except for the necessary few files to make it work in iOS (so it's really an Objective-C++ app with an enormous amount of native C++ linked to it, everything of Qt it needs). I have a break point within the LoadApplication method - Qt has been built from source for development (that is, in debug configuration with symbols). There are a number of native Qt QUrl objects whose values I'd like to inspect. I have successfully installed lldbbridge.py, but I think the problem may be unrelated to that, because I saw it when I was using other tricks to see the data without the bridge. There is a method called toString on the QUrl class that produces a text representation of the URL (and another called toDisplayString that may be more human readable). These methods produce (of course) QString objects. So here are the failure modes:
First the bridge should be helping me to inspect the QUrl and all I see are the raw object descriptions that hide all the private interfaces. It isn't.
before I installed the lldbbridge.py script, I was able to view some of these objects (local variables, but not parameters), using code like expr url.toString().toStdString().c_str(). It still might work on local variables, but I would really like to be able to inspect parameters as well.
the error feedback I get is
error: <lldb wrapper prefix>:21198:9: module 'std' not found
#import std;
~~~~~~~^~~
this is a pretty legit error, because I have scoured my system and the internet for evidence of this std.framework whose existence is implied, and cannot find it, though its name suggests that it would be an assist to Objective-C or Swift to deal with std::string and the like. Possibly it was a thing in Xcode 12 that has been dropped in Xcode 13, but if so, it has no footprint on the web that I can find. Still, presumably Qt 5.15.5's lldbbridge.py was compiled and run and against it at some point in the recent past.
this isn't the only trick that doesn't work when inspecting a QString, with or without the bridge. I also tried expr (const wchar_t*)url.toString().toUtf16() and expr (const char*)url.toString().toUtf8() and so forth. The same error feedback results, complaining about the mysterious "std" framework or module.
and don't get too hung up on QUrl objects, because I get the same result with other QStrings.
one more symptom: if I do an expr #import std; in the lldb command line, it appears to work. That is, it gives no error feedback and appears to complete. This just makes the world weirder, because if exists, it must be hiding somewhere inside Xcode's contents, but I've done file searches in there, and see no evidence of such a thing. And if it does exist, why is the lldb wrapper prefix giving me grief? Could the wrapper be underspecified in terms of framework search paths, but the lldb command line not?
So as if it's not too obvious, here are my questions (besides WTF???):
Am I the first to see this? I've seen some forum talk about string inspection no longer working for others in Xcode 13 lldb, but the specific failure mode is different. Anyone else see this?
Does anyone have any idea about this mysterious "std" framework or module? Could its functionality have been sucked up into some other module or framework for Xcode 13?
Any ideas about work-arounds that I haven't thought of? I'm not a complete lldb novice, but I'm not an expert either.
I'd like to turn up the log levels look at those for clues, but I've never used that feature before, and I don't really even know where to FIND the logs.
I notice that the feedback suggests that there are at least 21198 lines in this "wrapper" BEFORE we get to the failing import statement. Seems a little excessive to wrap a request to view the contents of a string. Perhaps the whole wrapper is corrupted in some way. Any thoughts on how to test that hypothesis? How about a way to inspect the contents of the wrapper prefix itself?
Could the #import std; be a red herring and just co-lateral damage in some other unrelated failure mode? It's tempting to imagine it's some kind of std library support thing, but I don't want to assume too much at this point.
one more things about "std", whatever it is - lldb is super dynamic. It's always compiling inline code on-the-fly to support its functionality. That's the whole llvm magic. Is it possible it exists only as some inline text within lldb's source? And again, if so, why is it only selectively available?
Well, that's my nightmare. Unless my setup is horribly corrupted in some way and it's my unique curse, I'm sure this problem will show up for others, so cogent answers will make you a hero. Any pointers are appreciated. Thanks.

How to use the `cc_common.create_link_variables` API?

I'm trying to write some complex Starlark rules that link and build multiple dynamic libraries on Linux using the (relatively) new cc_common APIs.
There seems to be 2 different ways you can create compile/link actions using this API:
Using the compile()/link() methods, which are relatively "high-level", and
Using the create_compile_variables()/create_link_variables() along with get_memory_inefficient_command_line() and then calling actions.run() directly with the generated command line.
In particualr, I'm trying to get #2 to work. My question is, how can I create the param_file to pass into create_link_variables? There doesn't seem to be any Starlark API for this.
https://docs.bazel.build/versions/1.1.0/skylark/lib/cc_common.html#create_link_variables
agoessling I have shared a couple of source files for you here
It should give you a pretty good idea of how this lower level cc_common API can be used end to end.
There are still known holes in this API, i.e. not everything possible with the built-in cc rules also possible through cc_common, but I would say 90% is available.
I am not associated with the Bazel team and the code is the result of my own digging and sniffing. No warranties, but it works for me. Let me know if you get stuck on something - I will try to help.
If you get an idea of how to do some of it better (prettier, more compatible with the built-in rules, more platform-independent, etc.) I am all ears. Good luck!

Python Sub-Process Coverage

Situation:
I'm attempting to get coverage reports for a project that uses both C++ and Python. I'm using LCOV/GCOV for C++, and attempting to use Coverage.py for the python stuff. The only issue is, most of the python code that's being used is simply utility functions being called one function at a time. No initialization, no real life-cycle, or exit. So no real way to use the API to start/stop/save, or use the coverage command line to measure.
With this, I thought the easiest way to accomplish this would be using the sitecustomize.py method like outlined here. I have gotten that to work, and it measures all configured python code as expected. Now I'm looking at how to accomplish this with compiled python code (.pyc).
I can get it to work if I keep source(.py) and (.pyc) in the same directory when running, and then reporting. However, I'm looking for a way to RUN the files and generate the measurement data. Then at a later time point to the actual source files, and run the actual reports. Ideally I wouldn't need the source(.py) files at all, but I haven't found a way to accomplish this.
Objective:
In the end I want to be able to compile the python files(.pyc), install them on the target, and run coverage like stated above. It will generate coverage data files, then pull those files to my host machine which houses the source(.py) .. and do the actual coverage reporting.
Is this possible currently?
[Edit] Thanks to Ned's advice, I looked into the [paths] usage, and it worked exactly how I needed it to.

Testing the opening of files using QTestLib

I am new to unit testing and the Qt framework. I have been assigned to write a unit test to test the opening of text files.
I have looked the the tutorials for Qt test. But I have no idea how to proceed. (I have to use QTestLib). Please guide me what I should do.
Boost libraries are being used to open the csv and delimited text-files to import the data in the application.
By testing, I am assuming that you want to check if the files are being read properly.
1) To get a better understanding about the Qt Project structure, check out this link
2) Locate the class that is actually calling the boost libraries to read the data, you might want to test this class (It depends on you how you want to implement, without any details, I cannot give a better explanation)
3) Create the corresponding object and invoke the reading of the file. After the file has been read, you can QVERIFY or QCOMPARE the data read by the class and the actual values. To use custom datatypes in the previous functions, look at this link. It is explained in the website, how to create and use custom datatypes for the above functions.
4) To run multiple tests in a single Test project (Qt), look at this github repo (I'm unable to find the website where it was originally posted).
I hope this gives an idea of how to get started with writing the test. It really depends on what your requirements are, without knowing the details, I might not be able to help more

c++: program settings - boost.PropertyTree or boost.program_options?

I was looking for a solution to store program settings or options or configuration in C++. These could be settings that are exposed in a GUI and need to be saved between runs of my code.
In my search I came across boost.PropertyTree which seemed to be a good choice. I know boost is well respected code so I'm comfortable using it and so I started developing using this. Then I come across boost.program_options which seems to allow you to do the same thing but also looks more specialized for the specific use-case of program settings.
Now I'm wondering which is the most appropriate for the job? (or is there a 3rd option that is better than both)
EDIT:
fyi this is for a plugin so it will not use command line options (as in, it's not even possible).
UPDATE
I ended up sticking with boost.PropertyTree. I needed to be able to save changed options back to the INI, and I didn't see a way of doing that with boost.program_options.
Use boost::program_options. It's exactly what it's for. In one library you get command line options, environment variables options and an INI-like configuration file parser. And they're all integrated together in the Right way, so when then the user specifies the same option in more than one of these sources the library knows the Right priority order to consider.
boost::property_tree on the other hand is a more generalized library. The library parses the text stream into a uniform data model. But You need to do the real parsing -- that of making sense of the blob of data for your needs. The library doesn't know when to expect a parameter when it sees a particular option string, or to disallow specific values or types of values for a particular option.
After some digging around I think boost.PropertyTree is still the best solution because it gives me the capability to save the options after changing them from within the program which is a requirement.
There is a non-Boost possibility too. Config4Cpp is a robust, simple-to-use and comprehensively documented configuration-file parser library that I wrote. It is available at www.config4star.org.
I suggest you read Chapter 3 (Preferences for a GUI Application) of the Practical Usage Guide manual to read an overview of how Config4Cpp can do what you want. Then open the Getting Started Guide manual, and skim-read Chapters 2 and 3, and Section 7.4 (you might prefer to read the PDF version of that manual). Doing that should give you sufficient details to help you decide if Config4Cpp suits your needs better or worse than Boost.
By the way, the indicated chapters and sections of documentation are short, so they shouldn't take long to read.