Data Science

These examples take quite a long time to run, and they make our documentation CI fail quite frequently due to timeout. It'd be nice to speed the up a little bit.

To contributors: if you want to work on an example, first have a look at the example, and if you think you're comfortable working on it and have found a potential way to speed-up execution time while preserving the educational message

A clear and concise description of what the bug is.
The superset chart table sets the number of pagination rows to select the setting, and add the option of whether to select all

like this
![image](https://user-images.githubusercontent.com/52438024/141405677-f9e25aef-e0d3-4e99-986a

Users might be using pathlib.Path in their code. Currently they have to convert to str before passing into a runtime environment, but we should do this conversion for them.

Summary

Aesthetically trivial, yet I've spotted a discrepancy with font sizes in our tooltip (front-end + back-end screenshots below).
I believe sections #1 and #2 should have the same font size?

![image](https://user-images.githubusercontent.com/27242399/139825179-4d62e3

Proposed refactoring or deprecation

Motivation

Lightning has a utility defined for all gather with gradients here: https://github.com/PyTorchLightning/pytorch-lightning/blob/d515bcac969c2a485ada673e302bfac51f142331/pytorch_lightning/utilities/distributed.py#L200-L222

However, this is already available in torch dist

In recent versions (can't say from exactly when), there seems to be an off-by-one error in dcc.DatePickerRange. I set max_date_allowed = datetime.today().date(), but in the calendar, yesterday is the maximum date allowed. I see it in my apps, and it is also present in the first example on the DatePickerRange documentation page.

E

For regular lists:

In [11]: list(range(50))
Out[11]: 
[0,
 1,
 2,
 3,
 4,
...
 46,
 47,
 48,
 49]

However:

In [13]: collections.UserList(range(50))
Out[13]: [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49]

Documentation Link

https://matplotlib.org/stable/tutorials/text/text_props.html#default-font

Problem

In https://matplotlib.org/stable/tutorials/text/text_props.html#default-font we are told that we can use any "available fonts" for fontfamily. It would be nice if this tutorial, or another, indicated how to get that list of available fonts, and then specfically how to specify them in

In gensim/models/fasttext.py:

    model = FastText(
        vector_size=m.dim,
        vector_size=m.dim,
        window=m.ws,
        window=m.ws,
        epochs=m.epoch,
        epochs=m.epoch,
        negative=m.neg,
        negative=m.neg,
        # FIXME: these next 2 lines read in unsupported FB FT modes (loss=3 softmax or loss=4 onevsall,
        # or model=3 supervi

Is your feature request related to a problem? Please describe.
I typically used compressed datasets (e.g. gzipped) to save disk space. This works fine with AllenNLP during training because I can write my dataset reader to load the compressed data. However, the predict command opens the file and reads lines for the Predictor. This fails when it tries to load data from my compressed files.