[BLOG]: Supporting dask arrays in scipy via the Python Array API standard

[lithomas1]

Text styling

• The blog is written with plain language (where relevant).
• If there are headers, they use the proper header tags in order to do so (with only one level-one header).
• All links describe where they link to (for example, check the Quansight labs website).
• Any kind of styling that the author uses (for example, bold for emphasis) is consistent throughout the blog.

Non-text contents

• Blog post featured image is in PNG or JPEG format, not SVG.
• All content is represented as text (for example, images need alt text and videos need captions or descriptive transcripts).
• If there are emojis, there are not more than three in a row.
• Don't use flashing gifs or videos.
• If it were to be read as plain text, the blog still makes sense and no information is missing.

TODO

• Add images (featured and hero)
• Finish perf testing section and resolve remaining todos in text
• Styling

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[lithomas1]

Not done yet, but just wanted to put up a quick draft of my blog post.

The main omission is probably the case study section where I port a scipy.stats workflow to dask arrays and look at performance.

All other sections are basically complete.

[rgommers]

This looks like a good start @lithomas1, thanks. The flow of the story at a high level looks good to me. The case study section is important indeed; the post is still pretty draft now so I didn't review in detail.