future | High-performance Future implementation for the JVM | Reactive Programming library

I think this gets you pretty close; might just need to adjust the various name columns and drop the extra data (I kept the grouping column).

The main idea is to recursively use pd.json_normalize with pd.concat for all availalable children levels.

EDIT: Put everything into a single function and added section to collapse the name columns like the expected output.

From the documentation, pandas.DataFrame.drop has the following parameters:

Parameters

• labels: single label or list-like Index or column labels to drop.

• axis: {0 or ‘index’, 1 or ‘columns’}, default 0 Whether to drop labels from the index (0 or ‘index’) or columns (1 or ‘columns’).

• index: single label or list-like Alternative to specifying axis (labels, axis=0 is equivalent to index=labels).

• columns: single label or list-like Alternative to specifying axis (labels, axis=1 is equivalent to columns=labels).

• level: int or level name, optional For MultiIndex, level from which the labels will be removed.

• inplace: bool, default False If False, return a copy. Otherwise, do operation inplace and return None.

• errors: {‘ignore’, ‘raise’}, default ‘raise’ If ‘ignore’, suppress error and only existing labels are dropped.

Moving forward, only labels (the first parameter) can be positional.

So, for this example, the drop code should be as follows:

I have solved it by forcing update flutter_math_fork adding to pubspec:

The thread sanitizer currently doesn't support std::atomic_thread_fence. (GCC and Clang use the same thread sanitizer, so it applies to both.)

GCC 12 (currently trunk) warns about it:

You can define your own renderOption that can return the list item with a correct key value. Your code complains about the duplicated keys because by default, Autocomplete uses the getOptionLabel(option) to retrieve the key:

For this specific case (which is a relatively common one), the answer would be to use a Supplier::Preserving:

If you are using Python elasticsearch client, you need to downgrade or install version before 7.14.0.

pip install 'elasticsearch<7.14.0'

I don't think there is a single right answer to this, but here is a couple of points to consider.

• First, I think real-world functional code often has a "sandwich structure" with some input handling, followed by purely functional transformation and some output handling. The I/O parts in F# often involve interfacing with imperative and OO .NET libraries. So, the key lesson is to keep the I/O to the outside and keep the core functional handling separate from that. In other words, it makes perfect sense to use some imperative OO code on the outside for input handling.

• Second, I think the idea of decoupling is something that is more valuable in OO code where you expect to have complex interfaces with intertwined logic. In functional code, this is (I think) much less of a concern. In other words, I think it is perfectly reasonable not to worry about this for I/O, because it is only the outer side of the "sandwich structure". If you need to change it, you can just change it without touching the core functional transformation logic (which you can test independently of I/O).

• Third, on the practical side, it is perfectly reasonable to use interfaces in F#. If you really wanted to do the decoupling, you could just define an interface: