API reference information isn’t always given much attention in development processes.
Teams often generate reference for commands or endpoints and assume that this is enough for developers to consume their API.
However, we know that complete API reference includes much more information than just a list of commands or endpoints.
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tl;dr: Does your company use Workday? Ever wish you could see your company’s entire org chart in a single view? You can use OpenTree to fill this gap.
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Lots of people are familiar with downloading Shutterstock images directly from shutterstock.com to use in marketing, advertising, and news content. What most of our small and medium-sized customers don’t know is that when they search for images or download images from the website, they’re using the same computer interface that our enterprise customers use to connect their huge systems and applications to our media catalog. The only difference is that enterprise customers access Shutterstock directly through a computer interface called a REST API, cutting out the need to visit shutterstock.com.
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Introduction
At Shutterstock, we continuously work to add new features and improve functionality of our website for our users. In order to keep up with the rapid pace of development without compromising quality, we need to have a solid testing toolkit that allows developers to test the front-end application in isolation while gathering faster feedback on their code. In this post, we will talk about our integration testing toolkit and the benefits we have seen since implementing it.
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Sometimes it’s the little things that make working with a software tool effortless, like editors that have smart auto-complete and programs that provide precise error messages that help you work through problems.
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While Shutterstock supports 21 languages, our image editing tool, Shutterstock Editor, initially launched in English only. In order to deliver the same quality of experience for all 21 languages on Shutterstock Editor, we needed to make adjustments to how the tool handled characters in those languages.
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Clear definition of levels and active enablement of individual career development are cornerstones of healthy, high-performing, highly-engaged engineering organizations. At any given point in time, it is important for engineers and managers of engineers to comprehend where they stand, the possible paths before them, and the specific behaviors and impact expected of them at each level from both performance and career progression perspectives.
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Shutterstock turned 15 this year and anniversaries like this give us an opportunity to reflect back on (and appreciate) how far we’ve come and where we’re going.
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In Part 1, we discussed how using joint embeddings to rank images can help address the cold start problem. We showed that the joint embedding ranker exposes more new images than our existing ranker. This difference was even more pronounced for popular queries, where our existing ranker tends to favor older images that have more behavioral data.
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On the Shutterstock search team, our focus is serving the best possible images for a given query. To do this, we use behavioral data from our customers such as downloads to help us rank the quality of an image for a given search. While this approach often works very well because it allows us to harness the collective intelligence of our great users, it does have one very serious drawback: new content from our contributors is more challenging to surface in search results. This is commonly known as the cold start problem.
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