Capture un-loadable NetCDF objects instead of discarding/crashing

[trexfeathers]

Closes #5165

User story

• As an: Iris user loading NetCDF files written according to the CF Conventions.
• I want: Iris to capture malformed CF information during loading, instead of crashing or disposing of it.
• So that: I can fix CF problems within my Iris script - avoiding the complexity of multiple scripts/tools.

Why this is hard

There are many ways Iris crashes when it encounters bad CF. It is tempting to think of these crashes as deliberate - with easy-to-modify code blocks for each rule - and there are a few of these, but Iris is not a CF-checker. Instead we have used CF to make assumptions so that the code can be simpler/smaller; barely any of the crashes are raised from dedicated lines, and they are often hard to predict.

Any 'fix' must therefore be a form of generic error handling, which cannot have knowledge of what precisely might go wrong.

The architecture

• iris.LOAD_PROBLEMS - a global object where Iris can capture objects that could not be loaded, and the stack trace error that was raised.
• build_raw_cube() - a routine that will represent any CFVariable as a very basic Cube, with as little interpretation as possible.
• Separate building objects versus adding them to the Cube being loaded.
• Ensure all objects - including names, units, etcetera - are contained within their own building routine.
• _add_or_capture():
  • Can't build the object? Use build_raw_cube() and store in iris.LOAD_PROBLEMS.
  • Object built but can't add to the Cube? Store in iris.LOAD_PROBLEMS.
• Issue a warning at the end of loading if anything is found within iris.LOAD_PROBLEMS.
• Make it easier to convert Cubes - output by raw_cube_from_cf_var() - into other objects e.g. DimCoords? Documentation at the very least.

Note that I have checked cf.py and believe it can remain unchanged. This has a defensive philosophy already, which involves checking if variables can be interpreted as different types, and the remainder are all represented as CfDataVariables, so we already have an existing fallback in place. Anything here that is not formatted correctly just shows up as extra Cube(s) in the loaded CubeList.

More specifics on implementation

For reference when writing #6318 and #6319

• ✔ Iris __init__.py:
  • Create the LOAD_PROBLEMS object
  • Example structure: {"file/path/1": [(problem_object_1, error_or_stacktrace), (problem_object_1, error_or_stacktrace)]}
• helpers.py:
  • ✔ Introduce a new function - _add_or_capture() - that:
    • Attempts to call a build_ routine (passed as an argument) in a try-except
    • On failure: falls back on build_raw_cube().
    • Attempts to add successfully built objects (e.g. DimCoord) to a Cube (passed as an argument) in a try-except
    • On failure: adds the built objects to iris.LOAD_PROBLEMS instead.
  • ✔ Create the build_raw_cube function
  • Separate as much as possible into build_ routines. We already have many, but even getting hold of standard names etcetera should be separated in this way.
  • Refactor build_ routines to only perform the building - returning the built object rather than adding it to the Cube.
  • Make the build routines private - _build... - and call them from build_and_add... routines, which prepare the necessary arguments for _add_or_capture(). Here are examples that have already been completed:
    • build_and_add_dimension_coordinate
    • build_and_add_names
• actions.py:
  • Three action_ routines have success criteria and failure information. These should be refactored so that a failure falls back to build_raw_cube(). The failure reason (already being recorded) should be captured in iris.LOAD_PROBLEMS. See Tolerant handling of standard_name and dimension coordinate loading #6338 for how this was done with dimension coordinates
  • ALL action_ routines should be refactored to call the new build_and_add routines.
• Tests
• Confirm this can fix known cases (Common agreement on loading CF non-compliant NetCDF files #5165)
• Docstrings
• What's New