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Comments (7)

bashtage avatar bashtage commented on July 23, 2024

The splitting seems too fine grained IMO. Why not split by data vendor only?

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bashtage avatar bashtage commented on July 23, 2024

I think the utility functions, which is anything that isn't vendor specific, should also be collected in shared, rather than having one file per function.

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femtotrader avatar femtotrader commented on July 23, 2024

what utility function will you put in "shared" ?
I will personally move function to "shared" only if they are actually shared.

I used this fine grained split because it will be easier for me to add caching (see #48 ) this way like I did in https://github.com/femtotrader/pandas_datareaders_unofficial .

Moreover it will be easier to see what is done and what need to be done.

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femtotrader avatar femtotrader commented on July 23, 2024

A vendor can decide to deprecate one API and not other ones.
Is Yahoo Finance Components deprecated ?
With one file per reader it will be IMHO easier and could also avoid spaghettis.

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bashtage avatar bashtage commented on July 23, 2024

I've never some across a package that has one function per file (or anything close). With modern editors it doesn't matter how large the files is since you can always use folding to hide anything you don't want to see.

In terms of caching, is there some reason now to use django-style @cache decorator that assumes the exact same set of inputs produces the same output, so that only the final result is cached, and the reader doesn't need to be modified?

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davidastephens avatar davidastephens commented on July 23, 2024

I'm fine with splitting by API. I agree with @bashtage though, I don't think we need one file per shared function. Just one shared file works.

Any benefit of using subpackages by vendor?
Ie: pandas_datareader/yahoo/options.py
Ie: pandas_datareader/yahoo/actions.py

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bashtage avatar bashtage commented on July 23, 2024

@davidastephens subpackage suggestion looks reasonable and seems to be more canonical Python packaging.

So something like pdr/vendor/datatype plus pdr/common.py where common is anything that isn't vendor specific.

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