typical | Data interchange with algebraic data types | Functional Programming library

You can create a new interface that extends NextApiRequest and adds the typings for the two fields.

XlaBuilder is the C++ API for building up XLA computations -- conceptually this is like building up a function, full of various operations, that you could execute over and over again on different input data.

Some background, XLA serves as an abstraction layer for creating executable blobs that run on various target accelerators (CPU, GPU, TPU, IPU, ...), conceptually kind of an "accelerator virtual machine" with conceptual similarities to earlier systems like PeakStream or the line of work that led to ArBB.

The XlaBuilder is a way to enqueue operations into a "computation" (similar to a function) that you want to run against the various set of accelerators that XLA can target. The operations at this level are often referred to as "High Level Operations" (HLOs).

The returned XlaOp represents the result of the operation you've just enqueued. (Aside/nerdery: this is a classic technique used in "builder" APIs that represent the program in "Static Single Assignment" form under the hood, the operation itself and the result of the operation can be unified as one concept!)

XLA computations are very similar to functions, so you can think of what you're doing with an XlaBuilder like building up a function. (Aside: they're called "computations" because they do a little bit more than a straightforward function -- conceptually they are coroutines that can talk to an external "host" world and also talk to each other via networking facilities.)

So the fact XlaOps can't be used across XlaBuilders may make more sense with that context -- in the same way that when building up a function you can't grab intermediate results in the internals of other functions, you have to compose them with function calls / parameters. In XlaBuilder you can Call another built computation, which is a reason you might use multiple builders.

As you note, you can choose to inline everything into one "mega builder", but often programs are structured as functions that get composed together, and ultimately get called from a few different "entry points". XLA currently aggressively specializes for the entry points it sees API users using, but this is a design artifact similar to inlining decisions, XLA can conceptually reuse computations built up / invoked from multiple callers if it thought that was the right thing to do. Usually it's most natural to enqueue things into XLA however is convenient for your description from the "outside world", and allow XLA to inline and aggressively specialize the "entry point" computations you've built up as you execute them, in Just-in-Time compilation fashion.

The following method avoids overflow and should result in fairly efficient assembly (example) without depending on non-standard features:

According to the language reference, chapter 3 "Data model" (see here):

An object’s type determines the operations that the object supports (e.g., “does it have a length?”) and also defines the possible values for objects of that type. The type() function returns an object’s type (which is an object itself). Like its identity, an object’s type is also unchangeable.[1]

which, to my mind states that the type must never change, and changing it would be illegal as it would break the language specification. The footnote however states that

[1] It is possible in some cases to change an object’s type, under certain controlled conditions. It generally isn’t a good idea though, since it can lead to some very strange behaviour if it is handled incorrectly.

I don't know of any method to change the type of an object from within python itself, so the "possible" may indeed refer to the CPython function.

As far as I can see a PyObject is defined internally as a

Unfortunately, this is how CategoryChannels work in discord.js...
When the category is deleted, discord.js sends a request to the API to delete the channel. Only then, Discord sends you the event after the category is deleted.
What happens next is that the children are not located in the category anymore! So you will not be able to get the children inside the CategoryChannel object.

This is the code for the children property

The most basic form of the kind language contains only * (or Type in more modern Haskell; I suspect we'll eventually move away from *) and ->.

But there are more things you can build with that language than you can express by just "counting the number of *s". It's not just the number of * or -> that matter, but how they are nested. For example * -> * -> * is the kind of things that take two type arguments to produce a type, but (* -> *) -> * is the kind of things that take a single argumemt to produce a type where that argument itself must be a thing that takes a type argument to produce a type. data ThreeStars a b = Cons a b makes a type constructor with kind * -> * -> *, while data AlsoThreeStars f = AlsoCons (f Integer) makes a type constructor with kind (* -> *) -> *.

There are several language extensions that add more features to the kind language.

PolyKinds adds kind variables that work exactly the same way type variables work. Now we can have kinds like forall k. (* -> k) -> k.

ConstraintKinds makes constraints (the stuff to the left of the => in type signatures, like Eq a) become ordinary type-level entities in a new kind: Constraint. Rather than the stuff left of the => being special purpose syntax fairly disconnected from the rest of the language, now what is acceptable there is anything with kind Constraint. Classes like Eq become type constructors with kind * -> Constraint; you apply it to a type like Eq Bool to produce a Constraint. The advantage is now we can use all of the language features for manipulating type-level entities to manipulate constraints (including PolyKinds!).

DataKinds adds the ability to create new user-defined kinds containing new type-level things, in exactly the same way that in vanilla Haskell we can create new user-defined types containing new term-level things. (Exactly the same way; the way DataKinds actually works is that it lets you use a data declaration as normal and then you can use the resulting type constructor at either the type or the kind level)

There are also kinds used for unboxed/unlifted types, which must not be ever mixed with "normal" Haskell types because they have a different memory layout; they can't contain thunks to implement lazy evaluation, so the runtime has to know never to try to "enter" them as a code pointer, or look for additional header bits, etc. They need to be kept separate at the kind level so that ordinary type variables of kind * can't be instantiated with these unlifted/unboxed types (which would allow you to pass these types that need special handling to generic code that doesn't know to provide the special handling). I'm vaguely aware of this stuff but have never actually had to use it, so I won't add any more so I don't get anything wrong. (Anyone who knows what they're talking about enough to write a brief summary paragraph here, please feel free to edit the answer)

There are probably some others I'm forgetting. But certainly the kind language is richer than the OP is imagining just with the basic Haskell features, and there is much more to it once you turn on a few (quite widely used) extensions.

With dict[str:int] the hint you are passing is dict whose keys are slices, because x:y is a slice in python.

The dict[str, int] passes the correct key and value hints, previously there also was a typing.Dict but it has been deprecated.

You are using a wrong locator. It brings you a lot of irrelevant elements.
Instead of find_elements_by_class_name('thumb-img') please try find_elements_by_css_selector('.collections-page .thumb-img') so your code will be

I used yield and re.finditer.

The yield expression is used when defining a generator function or an asynchronous generator function and thus can only be used in the body of a function definition. Using a yield expression in a function’s body causes that function to be a generator function

Return an iterator yielding match objects over all non-overlapping matches for the RE pattern in string. The string is scanned left-to-right, and matches are returned in the order found. Empty matches are included in the result.
If there are no groups, return a list of strings matching the whole pattern. If there is exactly one group, return a list of strings matching that group. If multiple groups are present, return a list of tuples of strings matching the groups. Non-capturing groups do not affect the form of the result.

The regular expression ([^\r\n]*)(\r\n|\r|\n)? can be divided into two parts to match (that is, two groups). The first group matches the data without \r and \n, and the second group matches \r, \n or \r\n.