PEP | Pointer Events Polyfill : a unified event system

PEP 660 – Editable installs for pyproject.toml based builds defines how to build projects that only use pyproject.toml. Build tools must implement PEP 660 for editable installs to work. You need a front-end (such as pip ≥ 21.3), backend. The statuses of some popular backends are:

• Setuptools does not yet implement PEP 660.
• Flit implements PEP 660 as of version 3.4.
• Poetry implements PEP 660 as of version 1.08.

You can define a default case in Python. For this you use a wild card (_). The following code demonstrates it:

That's almost as good as it gets, since the C module, if available, overrides all classes defined in the pure Python implementation of the datetime module with the fast C implementation, and there are no hooks.
Reference: python/cpython@cf86e36

Note that:

1. There's an intrinsic sub-microsecond error in the accuracy equal to the time it takes between obtaining the system time in datetime.now() and obtaining the performance counter time.
2. There's a sub-microsecond performance cost to add a datetime and a timedelta.

Depending on your specific use case if calling multiple times, that may or may not matter.

A slight improvement would be:

This is a documented exception to the normal rules that *specifically applies to try-except statements, from the language reference:

When an exception has been assigned using as target, it is cleared at the end of the except clause. This is as if:

As hinted in the comments, the _data_cls attribute could be removed, assuming that it's being used for type hinting purposes. The correct way to annotate a Generic class defined like class MyClass[Generic[T]) is to use MyClass[MyType] in the type annotations.

For example, hopefully the below works in mypy. I only tested in Pycharm and it seems to infer the type well enough at least.

This is currently broken in mypy as it assumes you are creating a method, here is the relevant issue https://github.com/python/mypy/issues/708.

Typing the function in the init works fine as it won't think it's a method on the class, the following code passes type checking properly and func's type is inferred from the parameter. The attribute assignment can also be typed directly if the parameter is not viable.

Seems you need to upgrade pip, see this question.

But there can be multiple pips in a Dataproc cluster, you need to choose the right one.

1. For init actions, at cluster creation time, /opt/conda/default is a symbolic link to either /opt/conda/miniconda3 or /opt/conda/anaconda, depending on which Conda env you choose, the default is Miniconda3, but in your case it is Anaconda. So you can run either /opt/conda/default/bin/pip install --upgrade pip or /opt/conda/anaconda/bin/pip install --upgrade pip.

2. For custom images, at image creation time, you want to use the explicit full path, /opt/conda/anaconda/bin/pip install --upgrade pip for Anaconda, or /opt/conda/miniconda3/bin/pip install --upgrade pip for Miniconda3.

So, you can simply use /opt/conda/anaconda/bin/pip install --upgrade pip for both init actions and custom images.

After some tests I could build a custom module type by copying parts of code from moduleobject.c

Your problem is that your code does create an instance of a subclass of module, but never initializes it and gets random values in key members. Additionaly, modules are expected to be gc collectables, so you have to create your custom module with PyObject_GC_New.

The following code replaces your initial testmod_create function with a full initialization of the module:

Rereading the mypy documentation I believe I have found my answer:

Type aliases can be generic. In this case they can be used in two ways: Subscripted aliases are equivalent to original types with substituted type variables, so the number of type arguments must match the number of free type variables in the generic type alias. Unsubscripted aliases are treated as original types with free variables replaced with Any

So, to answer my question: