Should You Create Your Own E-Signature API?

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Is it worth coding your own e-signature API, or is purchasing a ready-made solution a better option? Electronic signatures have become a popular way to verify one’s identity without signing printed forms. They have many benefits over written signatures, such as higher security. 

What’s the best way to implement an API for using e-signatures: buying an API or building one? 

Print photos from Windows98 to HP8025 Laser resolution problem

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I am trying to print out photos from an old Windows98 computer (Dell Inspiron 2400) to a brand new HP8025e Laser printer. Our store has been operating a photo booth on this computer so I don't think I can port it to a newer version of Windows.

We had been using an old HP2200 Business Jet which did the job and had native support under W98, but that finally broke and could not obtain another.

Three questions:

  1. "Properties" under W98 only offers 300dpi, I need better resolution
  2. I did set the printer console to 'photo paper', but when I print the photo on photo paper, it just comes out very overdone and smeary, as if it's using 10 times too much ink. W98 properties doesn't offer a 'photo paper' option
  3. The photos printed somewhat smaller on the old HP (maybe 2 1/2" by 2") whereas they print larger (maybe 4 x 3) on the new 8025, and I need them smaller so all 4 fit in a line on a 3 1/2 x 11 strip of photo paper.

I don't know if this is insoluble (HP support just told me there was no support for W98) but I thought I'd give it a try.

How To Approach Legacy System Modernization

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Legacy modernization aims to meet the organization's current business needs by enhancing business agility with new functionality and appealing features, strengthening customer service, and increasing efficiency.

However, modernizing a legacy system is not child's play, as nearly 74% of enterprises fail to complete legacy modernization processes due to a disconnect between technical and leadership teams.

:has is an unforgiving selector

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A little thing happened on the way to publishing the CSS :has() selector to the ol’ Almanac. I had originally described :has() as a “forgiving” selector, the idea being that anything in its argument is evaluated, even if one or more of the items is invalid.

/* Example: Do not use! */
article:has(h2, ul, ::-scoobydoo) { }

See ::scoobydoo in there? That’s totally invalid. A forgiving selector list ignores that bogus selector and proceeds to evaluate the rest of the items as if it were written like this:

article:has(h2, ul) { }

:has() was indeed a forgiving selector in a previous draft dated May 7, 2022. But that changed after an issue was reported that the forgiving nature conflicts with jQuery when :has() contains a complex selector (e.g. header h2 + p). The W3C landed on a resolution to make :has() an “unforgiving” selector just a few weeks ago.

So, our previous example? The entire selector list is invalid because the bogus selector is invalid. But the other two forgiving selectors, :is() and :where(), are left unchanged.

There’s a bit of a workaround for this. Remember, :is() and :where()are forgiving, even if :has() is not. That means we can nest either of the those selectors in :has() to get more forgiving behavior:

article:has(:where(h2, ul, ::-scoobydoo)) { }

Which one you use might matter because the specificity of :is() is determined by the most specific item in its list. So, if you need to something less specific you’d do better reaching for :where() since it does not add to the specificity score.

/* Specificity: (0,0,1) */
article:has(:where(h2, ul, ::-scoobydoo)) { }

/* Specificity: (0,0,2) */
article:has(:is(h2, ul, ::-scoobydoo)) { }

We updated a few of our posts to reflect the latest info. I’m seeing plenty of others in the wild that need to be updated, so just a little PSA for anyone who needs to do the same.


:has is an unforgiving selector originally published on CSS-Tricks, which is part of the DigitalOcean family. You should get the newsletter.

The Role of Data Governance in Data Strategy: Part 1

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Data volumes are more than tripping every year in the industry, which is making data quality a big concern in many organizations. The information is in high demand but organizing it in a way to make it consumable is a challenge many are trying to solve.

Every organization has its own set of database systems and platforms for storing various types of data in the data warehouse. The stored or ingested data is maintained, but most of them are generally behind the curve in creating organization-wide solutions to manage the data.