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System information

• Have I written custom code (as opposed to using a stock
  example script provided in TensorFlow): Yes

currently, some of the programs use static type checking like this program but some of the programs did not use static typing.

it's a good practice to use static typing as it makes code more clear and readable, should we make it a standard for this repository.we can use mypy for

(e.g. for links and images), because some of these examples are now being rendered in the docs.

Added by @fchollet in requests for contributions.

Describe the issue linked to the documentation

https://scikit-learn.org/stable/developers/contributing.html#guidelines-for-writing-documentation specifies how to write parameters with a shape attribute in a docstring, e.g.

array_parameter : {array-like, sparse matrix, dataframe} of shape (n_samples, n_features) or (n_samples,)
    This parameter accepts data in either of the mentio

The goal of this issue is to replace all instances of whitelist and blacklist in torch/quantization/quantize.py. See issue #41443 for more information.

Description

When I scrape without proxy, both https and http urls work.
Using proxy through https works just fine. My problem is when I try http urls.
In that moment I get the twisted.web.error.SchemeNotSupported: Unsupported scheme: b'' error

As I see, most of the people have this issue the other way around.

Steps to Reproduce

1. Scrape a http link with proxy

**Expected

At some point we moved from using mocha as a test runner to using jest, and jest out of the box started reporting much more warnings than mocha did.

No one went to clean up this output. In many cases it may just be about passing an extra prop in a component or setting a proper default value for a component's prop, or adding up to an existing fixture.

[optional] please roll out in chu

Copied from #7991:

If you look at https://certbot.eff.org/docs/api/certbot.compat.filesystem.html, you'll notice many formatting errors which should be fixed.

That's the bare minimum which I think should be done, but I think we should also see what we can do to avoid these problems from happening in the future. Is there a way we could build the docs in CI and check for these problems?

Location of the documentation

https://pandas.pydata.org/docs/dev/reference/api/pandas.to_numeric.html?highlight=to_numeric#pandas.to_numeric

Documentation problem

The documentation declares that the downcast argument of pd.to_numeric can use the value int. However, only integer is working in the real code:

In [8]: pd.to_numeric(["42"], downcast="int", errors="coe