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Get the most recent info and news about Unsplash on HackerNoon, where 10k+ technologists publish stories for 4M+ monthly readers.

In 2013, Unsplash launched as a modest Tumblr blog. Since then, Unsplash has evolved into one of the most impactful online communities. Today, over 10 billion Unsplash images are seen every month. A photo featured on Unsplash will now be viewed more than the front page of The New York Times. The Unsplash community is fueled by contributors who offer their images freely for anyone to use, inspiring hundreds of millions of creators from 13-year-old graphic designers to multi-platinum recording artists. Unsplash is a special community, where the powerful principles of sharing and openness have taken the place of strict copyright and legal red tape. The web was meant to connect, inform, and inspire us in unprecedented ways. The Unsplash community embodies this philosophy fully. Unsplash has become a place where the impact of our connected world is on full display. Instead of images being hoarded and shut down, images on Unsplash are fuel for creativity. At Unsplash, our mission is to enable everyone to create. You don’t need to know someone, or have an agent, or have a name to be great on Unsplash. We're a place where creators meet their audience. A place where individuals become a community. And a source of inspiration for millions of people from every country in the world. We’ve seen how the willingness to give a single image unlocks the creative potential that exists in us all.

Unsplash

Introduction I often want to add visually interesting elements to my projects and struggle with content. Let’s say you have a subpage that shows all the posts/any other information related to a city. It would be great to have a photo of said city in the header, wouldn’t it? You may think that the way to go is to generate something with AI. It may work, but there are many issues with this approach. There are great free stock photo sites like Pexels or Unsplash. But how to find the right picture? I stumbled upon this problem while working on one of my side projects. It turns out Unsplash has a great API. In Python, we need to call it manually but there are client packages for JS, Ruby, PHP, mobile, etc. Unsplash API The API basically allows you to find photos matching your search query. A few caveats: Make sure you use direct links from Unsplash. Downloading and re-hosting images is not allowed.


You must attribute Unsplash and the author.


The API is rate limited to 50 requests per hour for unverified apps, 5k after approval and more if you need it. More on usage guidelines: Unsplash. Getting started (in-depth guide): Sign up for an account: https://unsplash.com/oauth/applications


Go to your apps: https://unsplash.com/oauth/applications


Create a “New application.”


Go to your app and save Access key; we’ll need it in the following steps Fetching an Image Have a look at this sample function; you can adapt it to your needs. import requests
import os

# Load Unsplash API key from environment variables
UNSPLASH_ACCESS_KEY = os.getenv('UNSPLASH_ACCESS_KEY')

def fetch_image_info(query):
    url = "<https://api.unsplash.com/search/photos>"
    params = {
        "query": query,
        "client_id": UNSPLASH_ACCESS_KEY,
        "per_page": 1,
        "orientation": "landscape",
    }
    response = requests.get(url, params=params)

    if response.status_code == 200:
        data = response.json()
        if data['results']:
            return data['results'][0]
    elif response.status_code == 403:
		    raise ConnectionError("Rate limited or not authorized")

    return None When you call this function for a “New York” query, you should receive an object like that: {
   "id": "string",
   "slug": "string",
   "created_at": "string",
   "width": "integer",
   "height": "integer",
   "color": "string",
   "blur_hash": "string",
   "alt_description": "string",
   "breadcrumbs": "array",
   "urls": "object",
   "links": "object",
   "likes": "integer",
   "user": "object",
   "tags": "array",
   "...": "..."
} You should pay attention to three of them really. First, urls - this is what you will use in your app. "urls": {
    "raw": "<https://images.unsplash.com/photo-1496442226666-8d4d0e62e6e9?ixid=M3w2MjA1MzR8MHwxfHNlYXJjaHwxfHxOZXclMjBZb3JrfGVufDB8MHx8fDE3MjA5MDAxMTd8MA&ixlib=rb-4.0.3>",
    "full": "<https://images.unsplash.com/photo-1496442226666-8d4d0e62e6e9?crop=entropy&cs=srgb&fm=jpg&ixid=M3w2MjA1MzR8MHwxfHNlYXJjaHwxfHxOZXclMjBZb3JrfGVufDB8MHx8fDE3MjA5MDAxMTd8MA&ixlib=rb-4.0.3&q=85>",
    "regular": "<https://images.unsplash.com/photo-1496442226666-8d4d0e62e6e9?crop=entropy&cs=tinysrgb&fit=max&fm=jpg&ixid=M3w2MjA1MzR8MHwxfHNlYXJjaHwxfHxOZXclMjBZb3JrfGVufDB8MHx8fDE3MjA5MDAxMTd8MA&ixlib=rb-4.0.3&q=80&w=1080>",
    "small": "<https://images.unsplash.com/photo-1496442226666-8d4d0e62e6e9?crop=entropy&cs=tinysrgb&fit=max&fm=jpg&ixid=M3w2MjA1MzR8MHwxfHNlYXJjaHwxfHxOZXclMjBZb3JrfGVufDB8MHx8fDE3MjA5MDAxMTd8MA&ixlib=rb-4.0.3&q=80&w=400>",
    "thumb": "<https://images.unsplash.com/photo-1496442226666-8d4d0e62e6e9?crop=entropy&cs=tinysrgb&fit=max&fm=jpg&ixid=M3w2MjA1MzR8MHwxfHNlYXJjaHwxfHxOZXclMjBZb3JrfGVufDB8MHx8fDE3MjA5MDAxMTd8MA&ixlib=rb-4.0.3&q=80&w=200>",
    "small_s3": "<https://s3.us-west-2.amazonaws.com/images.unsplash.com/small/photo-1496442226666-8d4d0e62e6e9>",
 }, Second, user - you will use this info for proper attribution, namely: user.name : Author name


user.links.html : Link to their profile, you must use. Make sure to append utm_source=your_app_name&utm_medium=referral to it, per guidelines. Third, alt_description , make sure to add it to your final IMG tags for accessibility and SEO. This piece of code is really everything you need to get going. With one caveat. Watching for Rate Limit When you’re in initial demo mode, you will only have 50 requests per hour. When trying to fetch more images, hitting rate limit is a given. What to do? Simply wait for a bit if the function above throws ConnectionError. I wait for around 70 seconds. Also mind that if no results are found, you will receive None. In this case, I am using a simplified query (country instead of city). Once the website is online, you can request higher quota in the dashboard. Summary We've covered how to use Python and the Unsplash API to automatically fetch photos for your apps and websites. I hope you’ll build something cool with it. Send your projects my way in the comments or on Twitter. Subscribe to my profile by filling in your email address on the left, and be up-to-date with my articles! I will soon be releasing a crazy interesting project that uses this solution! Don't forget to follow me on Twitter @horosin, and subscribe to my blog’s newsletter for more tips and insights! Introduction I often want to add visually interesting elements to my projects and struggle with content. Let’s say you have a subpage that shows all the posts/any other information related to a city. It would be great to have a photo of said city in the header, wouldn’t it? You may think that the way to go is to generate something with AI. It may work, but there are many issues with this approach. There are great free stock photo sites like Pexels or Unsplash. But how to find the right picture? I stumbled upon this problem while working on one of my side projects. It turns out Unsplash has a great API. In Python, we need to call it manually but there are client packages for JS, Ruby, PHP, mobile, etc. Unsplash API The API basically allows you to find photos matching your search query. A few caveats: Make sure you use direct links from Unsplash. Downloading and re-hosting images is not allowed. You must attribute Unsplash and the author. The API is rate limited to 50 requests per hour for unverified apps, 5k after approval and more if you need it. Make sure you use direct links from Unsplash. Downloading and re-hosting images is not allowed. Make sure you use direct links from Unsplash. Downloading and re-hosting images is not allowed. You must attribute Unsplash and the author. You must attribute Unsplash and the author. The API is rate limited to 50 requests per hour for unverified apps, 5k after approval and more if you need it. The API is rate limited to 50 requests per hour for unverified apps, 5k after approval and more if you need it. More on usage guidelines: Unsplash . Unsplash Getting started ( in-depth guide ): in-depth guide Sign up for an account: https://unsplash.com/oauth/applications Go to your apps: https://unsplash.com/oauth/applications Create a “New application.” Go to your app and save Access key; we’ll need it in the following steps Sign up for an account: https://unsplash.com/oauth/applications Sign up for an account: https://unsplash.com/oauth/applications https://unsplash.com/oauth/applications Go to your apps: https://unsplash.com/oauth/applications Go to your apps: https://unsplash.com/oauth/applications https://unsplash.com/oauth/applications Create a “New application.” Create a “New application.” Go to your app and save Access key; we’ll need it in the following steps Go to your app and save Access key; we’ll need it in the following steps Fetching an Image Have a look at this sample function; you can adapt it to your needs. import requests
import os

# Load Unsplash API key from environment variables
UNSPLASH_ACCESS_KEY = os.getenv('UNSPLASH_ACCESS_KEY')

def fetch_image_info(query):
    url = "<https://api.unsplash.com/search/photos>"
    params = {
        "query": query,
        "client_id": UNSPLASH_ACCESS_KEY,
        "per_page": 1,
        "orientation": "landscape",
    }
    response = requests.get(url, params=params)

    if response.status_code == 200:
        data = response.json()
        if data['results']:
            return data['results'][0]
    elif response.status_code == 403:
		    raise ConnectionError("Rate limited or not authorized")

    return None import requests
import os

# Load Unsplash API key from environment variables
UNSPLASH_ACCESS_KEY = os.getenv('UNSPLASH_ACCESS_KEY')

def fetch_image_info(query):
    url = "<https://api.unsplash.com/search/photos>"
    params = {
        "query": query,
        "client_id": UNSPLASH_ACCESS_KEY,
        "per_page": 1,
        "orientation": "landscape",
    }
    response = requests.get(url, params=params)

    if response.status_code == 200:
        data = response.json()
        if data['results']:
            return data['results'][0]
    elif response.status_code == 403:
		    raise ConnectionError("Rate limited or not authorized")

    return None When you call this function for a “New York” query, you should receive an object like that: {
   "id": "string",
   "slug": "string",
   "created_at": "string",
   "width": "integer",
   "height": "integer",
   "color": "string",
   "blur_hash": "string",
   "alt_description": "string",
   "breadcrumbs": "array",
   "urls": "object",
   "links": "object",
   "likes": "integer",
   "user": "object",
   "tags": "array",
   "...": "..."
} {
   "id": "string",
   "slug": "string",
   "created_at": "string",
   "width": "integer",
   "height": "integer",
   "color": "string",
   "blur_hash": "string",
   "alt_description": "string",
   "breadcrumbs": "array",
   "urls": "object",
   "links": "object",
   "likes": "integer",
   "user": "object",
   "tags": "array",
   "...": "..."
} You should pay attention to three of them really. First, urls - this is what you will use in your app. urls "urls": {
    "raw": "<https://images.unsplash.com/photo-1496442226666-8d4d0e62e6e9?ixid=M3w2MjA1MzR8MHwxfHNlYXJjaHwxfHxOZXclMjBZb3JrfGVufDB8MHx8fDE3MjA5MDAxMTd8MA&ixlib=rb-4.0.3>",
    "full": "<https://images.unsplash.com/photo-1496442226666-8d4d0e62e6e9?crop=entropy&cs=srgb&fm=jpg&ixid=M3w2MjA1MzR8MHwxfHNlYXJjaHwxfHxOZXclMjBZb3JrfGVufDB8MHx8fDE3MjA5MDAxMTd8MA&ixlib=rb-4.0.3&q=85>",
    "regular": "<https://images.unsplash.com/photo-1496442226666-8d4d0e62e6e9?crop=entropy&cs=tinysrgb&fit=max&fm=jpg&ixid=M3w2MjA1MzR8MHwxfHNlYXJjaHwxfHxOZXclMjBZb3JrfGVufDB8MHx8fDE3MjA5MDAxMTd8MA&ixlib=rb-4.0.3&q=80&w=1080>",
    "small": "<https://images.unsplash.com/photo-1496442226666-8d4d0e62e6e9?crop=entropy&cs=tinysrgb&fit=max&fm=jpg&ixid=M3w2MjA1MzR8MHwxfHNlYXJjaHwxfHxOZXclMjBZb3JrfGVufDB8MHx8fDE3MjA5MDAxMTd8MA&ixlib=rb-4.0.3&q=80&w=400>",
    "thumb": "<https://images.unsplash.com/photo-1496442226666-8d4d0e62e6e9?crop=entropy&cs=tinysrgb&fit=max&fm=jpg&ixid=M3w2MjA1MzR8MHwxfHNlYXJjaHwxfHxOZXclMjBZb3JrfGVufDB8MHx8fDE3MjA5MDAxMTd8MA&ixlib=rb-4.0.3&q=80&w=200>",
    "small_s3": "<https://s3.us-west-2.amazonaws.com/images.unsplash.com/small/photo-1496442226666-8d4d0e62e6e9>",
 }, "urls": {
    "raw": "<https://images.unsplash.com/photo-1496442226666-8d4d0e62e6e9?ixid=M3w2MjA1MzR8MHwxfHNlYXJjaHwxfHxOZXclMjBZb3JrfGVufDB8MHx8fDE3MjA5MDAxMTd8MA&ixlib=rb-4.0.3>",
    "full": "<https://images.unsplash.com/photo-1496442226666-8d4d0e62e6e9?crop=entropy&cs=srgb&fm=jpg&ixid=M3w2MjA1MzR8MHwxfHNlYXJjaHwxfHxOZXclMjBZb3JrfGVufDB8MHx8fDE3MjA5MDAxMTd8MA&ixlib=rb-4.0.3&q=85>",
    "regular": "<https://images.unsplash.com/photo-1496442226666-8d4d0e62e6e9?crop=entropy&cs=tinysrgb&fit=max&fm=jpg&ixid=M3w2MjA1MzR8MHwxfHNlYXJjaHwxfHxOZXclMjBZb3JrfGVufDB8MHx8fDE3MjA5MDAxMTd8MA&ixlib=rb-4.0.3&q=80&w=1080>",
    "small": "<https://images.unsplash.com/photo-1496442226666-8d4d0e62e6e9?crop=entropy&cs=tinysrgb&fit=max&fm=jpg&ixid=M3w2MjA1MzR8MHwxfHNlYXJjaHwxfHxOZXclMjBZb3JrfGVufDB8MHx8fDE3MjA5MDAxMTd8MA&ixlib=rb-4.0.3&q=80&w=400>",
    "thumb": "<https://images.unsplash.com/photo-1496442226666-8d4d0e62e6e9?crop=entropy&cs=tinysrgb&fit=max&fm=jpg&ixid=M3w2MjA1MzR8MHwxfHNlYXJjaHwxfHxOZXclMjBZb3JrfGVufDB8MHx8fDE3MjA5MDAxMTd8MA&ixlib=rb-4.0.3&q=80&w=200>",
    "small_s3": "<https://s3.us-west-2.amazonaws.com/images.unsplash.com/small/photo-1496442226666-8d4d0e62e6e9>",
 }, Second, user - you will use this info for proper attribution, namely: user user.name : Author name user.links.html : Link to their profile, you must use. Make sure to append utm_source=your_app_name&utm_medium=referral to it, per guidelines. user.name : Author name user.name : Author name user.name user.links.html : Link to their profile, you must use. Make sure to append utm_source=your_app_name&utm_medium=referral to it, per guidelines. user.links.html : Link to their profile, you must use. Make sure to append utm_source=your_app_name&utm_medium=referral to it, per guidelines. user.links.html utm_source=your_app_name&utm_medium=referral Third, alt_description , make sure to add it to your final IMG tags for accessibility and SEO. alt_description This piece of code is really everything you need to get going. With one caveat. Watching for Rate Limit When you’re in initial demo mode, you will only have 50 requests per hour. When trying to fetch more images, hitting rate limit is a given. What to do? Simply wait for a bit if the function above throws ConnectionError. I wait for around 70 seconds. Also mind that if no results are found, you will receive None. In this case, I am using a simplified query (country instead of city). Once the website is online, you can request higher quota in the dashboard. Summary We've covered how to use Python and the Unsplash API to automatically fetch photos for your apps and websites. I hope you’ll build something cool with it. Send your projects my way in the comments or on Twitter. Subscribe to my profile by filling in your email address on the left, and be up-to-date with my articles! I will soon be releasing a crazy interesting project that uses this solution! Don't forget to follow me on Twitter @horosin , and subscribe to my blog’s newsletter for more tips and insights! @horosin newsletter

How to Programatically Get Photos Matching Content in Your Apps With Python and Unsplash API

1.4+ million freely usable photos now available in your Hacker Noon editor Unsplash started as a side project. Hacker Noon started as a side project. Unsplash was first funded by the revenue of the soon to be previous business (Crew). Hacker Noon was first funded by the revenue of the soon to be previous business (ArtMap Inc.).  Results - and not intentions - are what makes the world go round. Both companies saw early results, and identified them as an opportunity greater than their existing business. Both companies had the perseverance to run with it. I’m very excited to work with a game changer in the photo distribution space, Unsplash. With this API integration, we are giving our 10k+ contributing writers access to 1.4M+ quality freely usable images within the Hacker Noon editor. The Unsplash library is leveling up the blogging experience on Hacker Noon. To try it out, , start , click on the Unplash logo within the flyout menu and search whatever your curious heart desires. create an account writing a new story Unsplash is now the most visited site in the world. Hacker Noon is now the most visited site in the world. So yeah, they’re a good bit more well known, but we’re headed in the right direction. Since we , we’ve moved up 2,200+ spots, ahead of sites I read and respect tremendously, such as , , , and . 308th 3,048th removed our Medium content management system and replaced it with our own ProductHunt Futurism Dev.to Coindesk To date, thousands of Unsplash photos have already appeared on Hacker Noon stories. This integration builds on existing behaviors to better the workflow for contributing writers. Building a digital product is always a trade off between inventing the wheel, re-inventing the wheel and figuring out a way to plug in an existing solution — all while making the thing feel like just one quality thing. The reality is that the entire internet industry is built atop the keystrokes of nerds. Did the world need another content management system? Who’s to say. No software on the market could do what I wanted the software to do, and more importantly, if it’s not your own software your rate of digital iteration will never reach its potential. With how the internet has evolved, imagery often serves as the story’s second headline. However you slice curation, the accompaniment of quality images serves the distribution of quality words. This integration will save time for our contributing writers, improving the process of finding great imagery to embody their technology stories. P.S. Check out Hacker Noon photos on Unsplash!

📷 📸 Unsplash Integration 📷 📸 

TL;DR We ended the year with our highest quarterly revenue in company history while building some important product integrations (with Google Analytics , Algolia , Unsplash & GUN ), and dark mode . Our Alexa ranking is at 3.5k worldwide, up from a 5.2k ranking before removing Medium, proving the overall success of the move into our own infrastructure. We also had a company wide year end review where 100% of the team answered “yes” to the question “are you happy?” Traffic In 2019, Hacker Noon had 38M total site visitors, an increase of 35% from 2018 year over year. From Nov 2016 through early Dec 2019, Hacker Noon totaled ≈77M visitors. Redacted We closed the year as a top , which is up from worldwide Alexa ranking of 5.2k at the time of from our site. From mid July (launch of our software) through December 2019, we published 4,523 stories, which is an average of 27 stories per day, and our library created . 3.5k site in the world removing the Medium infrastructure 48+ years of time reading Internally, we have promoted from Technology Editor to Managing Editor, and expanded the editorial team with the part-time hiring of top community commenter as Software Editor. Natasha’s voice and data driven approach will be important to scaling our brand voice and rate of publishing. Natasha Nel Arthur Tkachenko Over the course of the year, Hacker Noon stories have been featured in , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , and elsewhere around the internet. Forbes ReadWrite VICE Coin tele graph Coindesk The Next Web CSO Tech Startups MarTechSeries TheNews.Asia Real Vail Decrypt Entrepreneur.com Code Opinion NewsBTC Tokenist Network World Robotics Online Silicon Republic Salon ProductHunt Stories GiveBat Reddit Crypto Daily The Block Seeking Alpha JJ’s Javascript Blog Connecticut Post Inverse Sociable Metafilter Inside Blogging JB Supra Crypto Briefing Business.com PR Daily Daily Hodl, Yahoo Yahoo Finance Value Walk Security Boulevard Merca 2.0 Tech Republic CNN CCN Newsmax Windows Club Aithority Packt Wright State University KingsCrowd Wikipedia Everipedia Dice CBS University World News IAB Tech Lab News Click Common Dreams Detailed CryptoNewsZ Tech Story Bitcoinist Interesting Engineering Study International Tech Advocate Blockonomi Hackaday, Singapore Fintech News Torrent Freak SiteJabber Business2Community TechDirt KeenGamer, Popular Mechanics GitHub G2 Jaxenter MarTech Today Irish Times Digital Journal, StackOverflow Blog Thrive Global Thomas ZDnet @Jack @Naval Tech Domains a number of Books Revenue Our 2019 revenue (over ) increased by 73% a year from 2018 year over year. accounted for the majority of our revenue at 55%, even though we could only start serving sponsors mid July after launched. The rest of our yearly revenue was made up of podcast sponsorships at 14% (which ends up breaking-even after expenses), program at 12%, at 6%, at 5%, and events/ /interest/ accounting for 8%. redacted The Top Navigation Billboard sponsorship Hacker Noon 2.0 brand as author newsletter sponsorships The Noonies shirts other In the less than five months of running the brand as author program and newsletter sponsorships, we totaled over 100 paying customers. For 2019 Q4 (pictured below), the ordered revenue by program breakdown was top navigation (64%), brand as author (18%), newsletters (14%), followed by interest and schwag sales for the rest (4%). Redacted Our largest two customers for the year are and . We have a number of six digit sponsorship deals in our pipeline, and will be investing in scaling our sales programs in 2020. In 2019, some of our more notable customers also include , , , , , , , , , , , , , , , , and . Seen by Indeed Heroku by Salesforce Google Cloud Codacy Passbase Stream Kloudless Nodle Polyient Labs Vettery PubNub Mabl Radix LogDNA ByBit SurrveySparrow Snyk Digital Ocean Kin We’ve done a lot of optimization work with our top navigation ad and expect to increase the revenue per day from this. Additionally, we plan to explore sponsorship packages by (i.e. placement by content relevancy) in 2020. tags Product Q4 2019, we integrated with , , , and the . We also . The GUN integration is our first use of blockchain technology in the Hacker Noon publishing platform. Starting in Q1 2020, this open source decentralized database will power our annotations and inline commenting. For the first time, we will be putting some content on the blockchain. With this integration, users browsers can contribute storage and anyone can also run their own “miner” on their computer or a cloud, distributing some of our hosting costs to our readership. Unsplash Algolia Google Analytics GUN blockchain launched dark mode For the full view of our year in product development, please read our CPO Dane Lyons’ . In summary, we now have the initial experience live for our core users: writers, readers, editors, sponsors and admins; and integrated with many great technologies like: Google Cloud, SlateJS, Algolia, Filestack, Unsplash, Google Analytics, Discourse, GUN, Twitter, and more. Product Update 2019-2020 Building a digital product is always a trade-off between inventing the wheel, re-inventing the wheel and figuring out a way to plug in an existing solution — all while making the thing feel like just one quality thing. We're getting there. Very excited to build more this year. We will continue investing heavily in improving and iterating on the core product experience, reading and writing, while also launching more curation tools, such as annotations and collections, to drive account creation and micro contributions. Profit & Loss Redacted Business Development Redacted Outlook and how you can help Redacted

State Of The Noonion Q4 2019: On Dark Mode, Integration With Unsplash and GUN

At , we’re all about building apps faster on blended teams of developers and content editors. In the past, editors using third-party stock photography sites have been encouraged to utilize to save these third-party tools to their Dashboard. Now editors can use the new to find and add stock photography to their media library, all from the comfort of their Bucket Dashboard without having to interface with a third-party website like Unsplash. Cosmic JS Cosmic JS Quick Links Cosmic JS Unsplash Photos Extension TL;DR: Unsplash Photos Extension Unsplash Photos Extension Codebase Unsplash Photos Extension on Product Hunt You can now Search and Add Unsplash Photos to your Bucket, all from your Bucket Dashboard. Simply navigate to the and click to install the . Cosmic JS Cosmic JS Extensions Page Photos Extension Once installed, you will see the “Photos” tab on your left hand navigation bar within your Dashboard. Click the “Photos” tab and start typing in your query to find and add photos to your Media Library for immediate or later use. Cosmic JS I hope that you’ve found this tutorial helpful. If you have questions or comments about Content Editor Features in the system, I’d love to hear about them. You can refer to my for additional content on how to intuitively navigate the Cosmic JS Dashboard. Cosmic JS Cosmic JS Profile

How to Search and Add Unsplash Photos to your Cosmic JS Bucket

Hello World is a weekly newsletter—delivered every Saturday morning—that goes deep into our original reporting and the questions we put to big thinkers in the field. Browse the archive here. Hello World is a weekly newsletter—delivered every Saturday morning—that goes deep into our original reporting and the questions we put to big thinkers in the field. Browse the archive here. Browse the archive here Hello again, readers! My name is Jon Keegan, and I’m an investigative data journalist here at The Markup. You may have read my reporting on the companies that collect your personal information while you do pretty much anything in your life—whether you are driving in your car, standing in line to vote, shopping at the supermarket, or just checking to see where your kids are. driving in your car standing in line to vote shopping at the supermarket where your kids are When I am researching the companies that collect, analyze, and monetize your information, I pay close attention to the marketing language they use when advertising their data stores to other companies in this vast ecosystem. All of these companies are eager to boast about how many billions of users’ data they have, what categories of information they collect, and how far back it goes. But right after these claims, there’s always a reassuring line about how rigorously they respect the privacy of the people whose data they buy, sell, and trade. billions of users’ data Recently, one term that I have started to see alongside these promises of privacy is “data clean room,” so let’s take a closer look and see what that means. What Is a Data Clean Room? While the term conjures up images of engineers working in white “bunny” suits out of a ’90s Intel Pentium commercial, data clean rooms aren’t actual facilities but rather a particular scheme of data sharing between servers. Pentium commercial The Interactive Advertising Bureau (IAB), a leading ad industry group, defines a data clean room as “a secure collaboration environment which allows two or more participants to leverage data assets for specific, mutually agreed upon uses, while guaranteeing enforcement of strict data access limitations.” The goal here is to ensure that personal customer data is not leaked from the first party (the company that has a direct relationship with the consumer) to the third party (the company seeking to access this customer data for insights) or any other party. By protecting the first-party data while still allowing some controlled access to it, a clean room theoretically allows third parties to safely access the data to create audience segments for advertising, identify overlapping customers in multiple datasets, perform data enrichment with other datasets, and derive insights, all while not having direct access to the personal data itself. But there are many implementations of these clean rooms, and there isn’t one true standard. Earlier this year, the IAB published a guide to best practices for working with clean rooms. The guide describes some of the features you might find in a data clean room implementation, including the ability to limit the types of queries and level of detail available to the third party as well as which users have access to the information and for how long. guide to best practices To further protect privacy, a range of different “privacy enhancing technologies” may be employed, such as double-blind encryption of data and adding statistical “noise” to the query results to prevent the reidentification of individuals. Why Are These Becoming More Popular? Data clean rooms have been around for years, but recent changes in the broader industry have increased adoption of the technology. The consumer data industry is operating in what some are calling a time of “data deprecation.” In the past few years, Apple and Google have greatly limited the ability of companies to slurp up your location data, browsing habits, and app usage from your phone. Google has been preparing the industry for the imminent end of the third-party cookie (for several years now). some are calling for several years now Adding to this, data firms need to comply with increasingly tight restrictions imposed by privacy laws in the EU, California, Colorado, Connecticut, and Virginia, and six other states that have comprehensive privacy laws due to take effect in the next few years. And the specter of a potential U.S. federal privacy law looms large. Data clean rooms give the consumer data industry a defense against many of the privacy concerns that have resulted in regulatory scrutiny. six other states federal privacy law Are Clean Rooms a Silver Bullet? “So there is no silver bullet,” said privacy lawyer Daniel Goldberg, chair of the Privacy & Data Security Group at law firm Frankfurt Kurnit Klein & Selz, in an interview with The Markup. “Every clean room operates somewhat differently. It’s all subject to what the vendor is actually doing. So just like anything, it’s a marketing buzzword in a lot of ways, and the devil is in the details.” Goldberg, who is also a member of IAB, says he thinks that the use of clean rooms is a positive thing and believes a lot of good work has been done to integrate their use in the industry. But he cautions that simply using a clean room does not relieve companies of their regulatory responsibilities. While the use of clean rooms may reduce their risks, “it can’t just be like, ‘Oh, we use it, therefore we don’t have to comply with anything because we’re no longer subject to privacy law.’ ” A recent IAB survey of brands, agencies, and publishers using data clean rooms found that while clean rooms have become essential tools for working with data—with two-thirds saying they were satisfied with the technology—they also require significant financial investment as well as infrastructure and staff. One-third of the companies surveyed that did use data clean rooms reported that privacy was one of their challenges when working with the technology. IAB survey Privacy Concerns While there are many strong privacy protections that come with the use of data clean rooms, there are still areas where privacy is a concern. IAB’s best practices guide lists several common privacy attacks that should be defended against when planning a clean room solution, including “membership inference,” “outlier injection,” “dictionary,” and “manufactured data join” attacks, techniques that could potentially allow an attacker to reidentify consumers and their personal data. Data security also becomes a huge privacy concern when data clean rooms are in control of so much data. Of particular importance is how the data is stored in the clean room. If a breach were to happen, it is critical that the method of data encryption is robust enough to prevent any personal information from being reidentified. “I would say the number one concern is the lack of knowledge from consumers that this is actually happening,” said Goldberg, who noted that he recommends that the use of data clean rooms should be disclosed in a company’s privacy policy. “There’s an issue where these clean rooms don’t have a direct relationship for the most part with consumers.… How could a consumer ever figure this out?” Goldberg said consumers should not only be notified about the use of a clean room but also given a choice. “If you’re going to engage in data clean room activities, you need to make sure that you’re giving users choice about this. And if they want to be able to opt out, you should allow them to opt out,” Goldberg said. For now, there may not be an easy way to tell if the companies you interact with are using data clean rooms. It is always a good idea to be familiar with the privacy rights you may have depending upon which state you live in. which state you live in You may be able to request a copy of the data that has been collected from you, and you may have the right to opt out of such data collection in the future. Whenever you sign up for a new app, platform, or service, it is worth taking a moment to think about what information you are comfortable sharing. And for the brave, while the experience may overwhelm you, I do recommend a quick read through of the privacy policy, as it is one of the main places companies are legally obligated to disclose some details about their data collection practices. As always, thanks for reading. Jon Keegan Investigative Data Journalist The Markup Credits: Jon Keegan Credits: Jon Keegan Jon Keegan Also published here Also published here here Photo by Phil on Unsplash Photo by Phil on Unsplash Phil Unsplash

Data Clean Rooms: What Are They?

Subscribe to Hello World Subscribe to Hello World Hello World is a weekly newsletter—delivered every Saturday morning—that goes deep into our original reporting and the questions we put to big thinkers in the field. Browse the archive here. Hello World is a weekly newsletter—delivered every Saturday morning—that goes deep into our original reporting and the questions we put to big thinkers in the field. Browse the archive here. Browse the archive here Hi, everyone, On dark days, in the midst of a mental health emergency, many Americans look to a federal government program for help. You might be familiar with it: Since 2005, counselors have been answering calls through the National Suicide Prevention Line, offering help to people in severe emotional distress. Last year, the program relaunched as the 988 Suicide and Crisis Lifeline, allowing callers to connect with the service through the simple three-digit number 988. It’s a vital service. About 50,000 people died by suicide in the United States in 2021, a rate of one death every 11 minutes. More than 12 million others seriously thought about taking their lives that year, according to survey statistics from the Substance Abuse and Mental Health Services Administration. died by suicide survey statistics For ethical reasons related to running control groups with people in crisis, it’s difficult to track how many lives have been saved by crisis lines, but the available evidence strongly suggests people feel better able to cope after reaching out through the program. strongly suggests The launch of the 988 hotline has so far been successful in making that help more accessible than ever. The service routed more than two million calls, texts, and chats to local and regional crisis centers in its first six months, according to a CNN analysis. Those numbers represented a major year-over-year increase since the launch of the 988 line. (More recently, a survey found that only 13 percent of adults knew about the 988 line, however.) a CNN analysis a survey found But while the service has been crucial to many, it’s not without controversy. We recently explored one issue here at The Markup, reporting on how dozens of websites for local crisis centers tied to the 988 line were tracking visitors through a tool called the Meta Pixel. We found some websites using the tool were sending visitors’ page views, button clicks, and even names and email addresses to Facebook. (A handful of the centers have since stopped or changed their practices, and some said they weren’t aware the data was being sent at all.) explored one issue Another debate around tracking has been playing out even more publicly. Last year, the Federal Communications Commission held a hearing on automatically geolocating callers who dial 988. While the details are under discussion, the plan would broadly mean people who answer calls would be able to see exactly where a caller is and to provide that information to emergency services. held a hearing The potential benefits are clear. Right now, when a person calls 988, they’re routed to a local crisis center based on the area code they’re calling from, so a person with an out-of-state area code will be sent to a counselor in a different state. Through geolocation, the service could automatically detect where a person is and route the call to the center nearest to them. There are also emergency situations where being able to trace a call could save lives. If a person wants help but can’t describe precisely where they are, a counselor could still direct help to them. Already, according to a U.S. Department of Health & Human Services FAQ on 988, some calls—fewer than 2 percent—trigger contact with 911 when operators believe there’s a risk of harm. In those cases emergency services can track the location of a call through 911 technology, although the practice can be cumbersome. FAQ track the location of a call can be cumbersome While the FAQ says counselors make an effort to provide help in “the least restrictive setting possible,” it doesn’t rule out the possibility of a call leading to an outcome like forced hospitalization. The nonprofit group Mad in America has published documents and harrowing anecdotes detailing the stories of callers who had police sent to them without consent after calling for help. published documents and harrowing anecdotes Some advocates are pushing back against the proposal to track calls, arguing that automatically tracing 988 calls would expand the use of nonconsensual intervention and violate the trust that callers place in the program. Yana Calou, director of advocacy at the Trans Lifeline, explained that their organization launched a campaign for explicitly anonymous hotlines in response to concerns about call tracking. “We really saw the writing on the wall with the FCC 988 [hearing],” Calou told The Markup recently. anonymous hotlines While some say that nonconsensual intervention is a necessary last resort, to advocates like Calou, the moral calculus looks different. They point to research suggesting forced hospitalization may ultimately increase a person’s risk for suicide in the long term and argue that the trauma of a forced intervention from police can leave lifelong damage. “We don’t have emergency infrastructure in our country that is not harmful,” Calou said. increase a person’s risk In response to a request for comment about the concerns, Katie Gorscak, an FCC spokesperson, said last year’s hearing was meant “to discuss the pros and cons of geolocation” and the agency “is considering various recommendations for next steps that are in line with our rules.” But based on the tenor of the experts in that hearing, the agency seems likely to adopt some form of automatic tracking one day in the future. Also under discussion, however, are what safeguards to put in place for callers concerned about forced intervention, meaning the future of 988 geolocation technology is still open for debate. Thanks for reading. Colin Lecher Reporter The Markup Credits: Colin Lecher Credits: Colin Lecher Colin Lecher Also published here Also published here here Photo by Quino Al on Unsplash Photo by Quino Al on Unsplash Quino Al Unsplash

Mental Health Crisis Calls: The Government's Controversial Idea to Track Them

This article is coreported with KFF Health News KFF Health News Read on our collaborator's site Read on our collaborator's site This article was coreported with KFF Health News, a national newsroom that produces in-depth journalism about health issues and is one of the core operating programs at KFF. Sign up for KFF Health News’s newsletters. This article was coreported with KFF Health News, a national newsroom that produces in-depth journalism about health issues and is one of the core operating programs at KFF. Sign up for KFF Health News’s newsletters. KFF Health News’s newsletters Looking for an at-home HIV test on CVS’s website is not as private an experience as one might think. An investigation by The Markup and KFF Health News found trackers on CVS.com telling some of the biggest social media and advertising platforms the products customers viewed. And CVS is not the only pharmacy sharing this kind of sensitive data. We found trackers collecting browsing- and purchase-related data on websites of 12 of the U.S.’s biggest drugstores, including grocery store chains with pharmacies, and sharing the sensitive information with companies like Meta (formerly Facebook), Google, through its advertising and analytics products, and Microsoft, through its search engine, Bing. The tracking tools, popularly called “pixels,” collect information while a website runs. That information is often sent to social media firms and used to target ads, either to you personally or to groups of people that resemble you in demographics or habits. In previous investigations, The Markup found pixels transmitting information from the U.S. Department of Education, prominent hospitals, telehealth startups, and major tax preparation companies. the U.S. Department of Education prominent hospitals telehealth startups major tax preparation companies Pharmacy retailer websites’ pixels send a shopper’s IP address—a sort of mailing address for a person’s computer or household internet—to social media giants and other firms. They also send cookies, a way of storing information in a user’s browser that in this case helps track a user from page to page as the user browses a retailer’s site. Cookies can sometimes also associate individuals on a site with their account on a social media platform. In addition to the IP address and cookies, the pixels often send information about what you’ve clicked or bought, including sensitive items such as HIV tests. “HIV testing is the gateway to HIV prevention and treatment services,” said Oni Blackstock, the founder of Health Justice and a former assistant commissioner for New York City’s Bureau of HIV/AIDS Prevention and Control, in an interview. “People living with HIV should have control over whether someone knows their status,” she said. Many retailers shared other detailed interaction data with advertising platforms as well. Ten of the retailers we examined alerted at least one tech platform when shoppers clicked “add to cart” as they shopped for retail goods, a capacious category that included sensitive products like prenatal vitamins, pregnancy tests, and Plan B emergency contraception. Supermarket giant Kroger, for instance, informed Meta, Bing, Twitter, Snapchat, and Pinterest when a shopper added Plan B to the cart, and informed Google and Nextdoor, a social media platform on which people from the same neighborhood gather in forums, that a shopper had visited the page for the item. Walmart informed Google’s advertising service when a shopper browsed the page of an HIV test, and Pinterest when that shopper added it to the cart. A previous investigation from The Markup found that Kroger used loyalty cards to track, analyze, and sell an array of data about customers to advertisers. previous investigation Using Chrome DevTools, a tool built into Google’s Chrome browser, The Markup and KFF Health News visited the websites of 12 of the U.S.’s biggest drugstores and examined their network traffic. This monitoring tool allowed us to see what information about shopping habits and, in some cases, prescriptions were sent to third parties. Over the course of the investigation, retailers frequently changed their trackers—sometimes activating them, sometimes removing them. Some retailers appeared to be taking steps to limit tracking on sensitive items. For example, Walgreens’ website prevented some trackers from activating on the pages of some products, which included Plan B and HIV tests. This code didn’t prevent all tracking, though: Walgreens’ site continued sending Pinterest information about those sensitive items a user added to the cart. Walgreens shared a new policy after learning of The Markup and KFF Health News’s findings. Spokesperson Fraser Engerman said that while the chain already had a “robust privacy program,” it would no longer share browsing data related to reproductive health and HIV testing. Engerman also told us that “Pinterest confirmed that the data will be deleted and that it has not been used for advertising purposes.” Crystal Espinosa, a spokesperson for Pinterest, said the company “can confirm that we will be deleting the data Walgreens requested.” The Pharmacy vs. the Pharmacy Aisle In the U.S., drugstores and grocery stores with associated pharmacies are only partially covered by the Health Insurance Portability and Accountability Act, or HIPAA. The prescriptions picked up from the pharmacy counter do have this protection. But in a separate section, sometimes confusingly called the pharmacy aisle, stores also often sell over-the-counter medications, tests, and other health-related products. Consumers might think such purchases have similar protections to their prescriptions, but HIPAA only covers the pharmacy counter’s clinical operations, such as dispensing prescriptions and answering patients’ questions about medication. This distinction can be confusing enough inside the brick-and-mortar location of a retailer. But the line can become even harder to make out on a website, which lacks the clarifying delineations of physical space. What’s more, descriptions about what will happen with retail data are generally in retailers’ privacy policies, which can usually be found in a link at the bottom of their webpages. The Markup and KFF Health News found them murky at best, and none of them were specific about the parts of the site that were covered by HIPAA and the parts that weren’t. In the “Privacy Notice for California Residents” part of its privacy policy, Kroger says it processes “personal information collected and analyzed concerning a consumer’s health.” But, the policy continues, the company does not “sell or share” that information. Other information is sold: According to the policy, in the last 12 months, the company sold or shared “protected classification characteristics” to outside entities like data brokers. privacy policy Kroger spokesperson Erin Rolfes said the company strives to be transparent and that “[i]n many cases, we have provided more information to our customers in our privacy notices than our peers.” Brokering of general retail data is widespread. Our investigation found, though, that some websites shared sensitive clinical data with third parties even when that information would be protected at a HIPAA-covered pharmacy counter. Users attempting to schedule a vaccine appointment at Rite Aid, for example, must answer a survey first to gauge eligibility. This investigation found that Rite Aid has sent Facebook responses to questions such as: Do you have a neurological disorder such as seizures or other disorders that affect the brain or have had a disorder that resulted from a vaccine?
Do you have cancer, leukemia, AIDS, or any other immune system problem?
Are you pregnant or could you become pregnant in the next three months? Do you have a neurological disorder such as seizures or other disorders that affect the brain or have had a disorder that resulted from a vaccine? Do you have cancer, leukemia, AIDS, or any other immune system problem? Are you pregnant or could you become pregnant in the next three months? The Markup and KFF Health News documented Rite Aid sharing this data with Facebook in December 2022. In February of this year, a proposed class action lawsuit based on similar findings was filed against the drugstore chain in California, alleging code on Rite Aid’s website sent Facebook the time of an appointment and an identifier for the appointment location, demographic information, and answers to questions about vaccination history and health conditions. Rite Aid has moved to dismiss the suit. proposed class action After the lawsuit was filed, The Markup and KFF Health News tested Rite Aid’s website again, and it was no longer sending answers to vaccination questions to Facebook. Rite Aid isn’t the only company that sent answers to eligibility questionnaires to social media firms. Supermarkets Albertsons, Acme, and Safeway, which are owned by the same parent company, also sent answers to questions in their vaccination intake form—albeit in a format that requires cross-referencing the questionnaire’s source code to reveal the meaning of the data. Using the Firefox web browser’s Network Monitor tool, and with the help of a patient with an active prescription at Rite Aid, KFF Health News and The Markup also found Rite Aid sending the names of patients’ specific prescriptions to Facebook. Rite Aid kept sharing prescription names even after the company stopped sharing answers to vaccination questions in response to the proposed class action (which did not mention the sharing of prescription information). Rite Aid did not respond to requests for comment, and as of June 23, the pixel was still present and sending the names of prescriptions to Facebook. Network Monitor Other companies shared data about medications from other parts of their sites. Customers of Sam’s Club and Costco, for example, can search names of prescriptions on each retailer’s website to find the local pharmacy with the cheapest prices. But the two websites also sent the name of the medication the user searched for, along with the user’s IP address, to social media companies. Many of the retailers The Markup and KFF Health News looked at did not respond to questions or declined to comment, including Costco and Sam’s Club. Albertsons said the company “continually” evaluates its privacy practices. CVS said it was compliant with “applicable laws.” Kroger’s Rolfes wrote that the company’s “trackers disclose product information, which is not sensitive health information unless one or more inferences are made. Kroger does not make any inferences linking the product information collected or disclosed by trackers to an individual’s health condition.” A Huge Regulatory Challenge Pharmacies are just one facet of a huge health care sector. But the industry as a whole has been roiled by disclosures of tracking pixels picking up sensitive clinical data. After an investigation by The Markup in June 2022 found widespread use of trackers on hospital websites, regulatory and legal attention has homed in on the practice. found widespread use of trackers In December, the Department of Health and Human Services’ Office for Civil Rights published guidance advising health providers and insurers how pixel trackers’ use can be consistent with HIPAA. “Regulated entities are not permitted to use tracking technologies in a manner that would result in impermissible disclosures” of protected health information to tracking technology or other third-party vendors, according to the official bulletin. published guidance If implemented, the guidance would provide a path for the agency to regulate hospitals and other providers and fine those who don’t follow it. In an interview with an industry publication in late April, the director of the Office for Civil Rights said it would be bringing its first enforcement action for pixel use “hopefully soon.” bringing its first enforcement action Lobbying groups are seeking to confine any regulatory fallout: The American Hospital Association, for example, sent a letter on May 22 to the Office for Civil Rights asking that the agency “suspend or amend” its guidance. The office, it claimed, was seeking to protect too much data. asking that the agency This year the Federal Trade Commission has pursued action against companies like GoodRx, which offers prescription price comparisons, and BetterHelp, which offers online therapy, for alleged misuse of data from questionnaires and searches. The companies settled with the agency. companies like GoodRx BetterHelp Health care providers have disclosed to the federal government the potential leakage of nearly 10 million patients’ data to various advertising partners, according to a review by The Markup and KFF Health News of breach notification letters and the Office of Civil Rights’ online database of breaches. That figure could be a low estimate: A new study in the journal Health Affairs found that, as of 2021, almost 99 percent of hospital websites contained tracking technologies. 99 percent of hospital websites One prominent law firm, BakerHostetler, is defending hospitals in 26 legal actions related to the use of tracking technologies, lawyer Paul Karlsgodt, a partner at the firm, said during a webinar this year. “We’ve seen an absolute eruption of cases,” he said. during a webinar Abortion and pregnancy-related data is particularly sensitive and driving regulatory scrutiny. In the same webinar, Lynn Sessions, also with BakerHostetler, said the California attorney general’s office had made specific investigative requests to one of the firm’s clients about whether the client was sharing reproductive health data. It’s unclear whether big tech companies have much interest in helping secure health data. Sessions said BakerHostetler had been trying to get Google and Meta to sign so-called business associate agreements. These agreements would bring the companies under the HIPAA regulatory umbrella, at least when handling data on behalf of hospital clients. “Both of them, at least at this juncture, have not been accommodating in doing that,” Sessions said. Google Analytics’ help page for HIPAA instructs customers to “refrain from using Google Analytics in any way that may create obligations under HIPAA for Google.” help page for HIPAA Meta says it has tools that attempt to prevent the transfer of sensitive information like health data. In a November 2022 letter to Sen. Mark Warner (D-VA) obtained by KFF Health News and The Markup, Meta wrote that “the filtering mechanism is designed to prevent that data from being ingested into our ads.” What’s more, the letter noted, the tech giant reaches out to companies transferring potentially sensitive data and asks them to “evaluate their implementation.” November 2022 letter “I remain concerned the company is too passive in allowing individual developers to determine what is considered sensitive health data that should remain private,” Warner told The Markup and KFF Health News. Meta’s claims in its letter to Warner have been repeatedly questioned. In 2020, the company itself acknowledged to New York State regulators that the filtering system was “not yet operating with complete accuracy.” acknowledged to New York State regulators To test the filtering system, Sven Carlsson and Sascha Granberg, reporters for SR Ekot in Sweden, set up a dummy pharmacy website in Swedish, which sent fake, but plausible, health data to Facebook to see whether the company’s filtering systems worked as stated. “We weren’t warned” by Facebook, Carlsson said in an interview with KFF Health News and The Markup. set up a dummy pharmacy website Carlsson’s and Granberg’s work also found European pharmacies engaged in activities similar to what The Markup and KFF Health News have found. The reporters caught a Swedish state-owned pharmacy sending data to Facebook. And a recent investigation with The Guardian found the U.K.-based pharmacy chain LloydsPharmacy was sending sensitive data—including information about symptoms—to TikTok and Facebook. sending data to Facebook recent investigation In response to questions from KFF Health News and The Markup, Meta spokesperson Emil Vazquez said, “Advertisers should not send sensitive information about people through our Business Tools. Doing so is against our policies and we educate advertisers on properly setting up Business Tools to prevent this from occurring. Our system is designed to filter out potentially sensitive data it is able to detect.” Meta did not respond to questions about whether it considered any of the information KFF Health News and The Markup found retailers sending to be “sensitive information,” whether any was actually filtered by the system, or whether Meta could provide metrics demonstrating the current accuracy of the system. In response to our inquiries, Twitter sent a poop emoji, while TikTok and Pinterest said they had policies instructing advertisers not to pass on sensitive information. LinkedIn and Nextdoor did not respond. Google spokesperson Jackie Berté said the company’s policies “prohibit businesses from using sensitive health information to target and serve ads” and that it worked to prevent such information from being used in advertising, using a “combination of algorithmic and human review” to remedy violations of its policy. KFF Health News and The Markup presented Google with screenshots of its pixel sending the search company our browsing information when we landed on the retailers’ pages where we could purchase an HIV test and prenatal vitamins, and of data showing when we added an HIV test to the cart. In response, Berté said the company had “not uncovered any evidence that the businesses in the screenshots are violating our policies.” Editor’s Note: KFF Health News uses Meta’s pixel on its website to collect information that may be used by third-party websites to measure web traffic and performance data and to target ads on social platforms. You can read KFF’s privacy policy in its entirety. The Markup does not use Meta’s pixel or similar trackers. You can read our full privacy promise here. Editor’s Note: KFF’s privacy policy here Credits: Darius Tahir for KFF Health News, Simon Fondrie-Teitler Credits: Darius Tahir for KFF Health News, Simon Fondrie-Teitler Darius Tahir Simon Fondrie-Teitler Also published here Also published here here Photo by Amanda Dalbjörn on Unsplash Photo by Amanda Dalbjörn on Unsplash Amanda Dalbjörn Unsplash

Need to Buy Plan B or an HIV Test? Facebook Already Knows About It

Don’t let test code sneak into production TL;DR: Avoid adding isTesting or similar flags. Problems 😔 Leaky abstraction
Non-Business code pollution
Fragile Code
Inconsistent behavior
Hidden dependencies
Difficult debugging
Boolean flags
Untrusted tests
Production dependant code Solutions 😃 Remove behavior Ifs
Use dependency injection
Model external services (Don't mock them)
Separate configurations
Isolate test logic
Maintain clean behavior boundaries Refactorings ⚙️ https://hackernoon.com/refactoring-014-how-to-remove-if?embedable=true Context 💬 When you add flags like isTesting, you mix testing and production code. This creates hidden paths that are only active in tests. Also, you don't cover real production code. You risk shipping testing behavior to production, leading to bugs and unpredictable behavior. Sample Code 📖 Wrong ❌ struct PaymentService {
    is_testing: bool,
}

impl PaymentService {
    fn process_payment(&self, amount: f64) {
        if self.is_testing {
            println!("Testing mode: Skipping real payment");
            return;
        }
        println!("Processing payment of ${}", amount);
    }
} Right 👉 trait PaymentProcessor {
    fn process(&self, amount: f64);
}

struct RealPaymentProcessor;
impl PaymentProcessor for RealPaymentProcessor {
    fn process(&self, amount: f64) {
        println!("Processing payment of ${}", amount);
    }
}

struct TestingPaymentProcessor;
impl PaymentProcessor for TestingPaymentProcessor {
    // Notice this is not a mock
    fn process(&self, _: f64) {
        println!("No payment: Skipping real transaction");
    }
}

struct PaymentService<T: PaymentProcessor> {
    processor: T,
}

impl<T: PaymentProcessor> PaymentService<T> {
    fn process_payment(&self, amount: f64) {
        self.processor.process(amount);
    }
} Detection 🔍 [x]Semi-Automatic You can detect this smell by looking for conditional flags like isTesting, environment == 'test', DEBUG_MODE, and idioms like these. These indicate that testing behavior is leaking into the production code. Tags 🏷️ Testing Level 🔋 [x]Intermediate Why the Bijection Is Important 🗺️ You need a clear separation between test and production code. When you mix them, you break the one-to-one Bijection between real-world behavior and the program. Since environments are real-world entities you need to explicitly model them in the MAPPER. AI Generation 🤖 AI-generated code often introduces this smell when you use quick hacks for testing. Some tools suggest flags like isTesting because they prioritize ease over proper design. AI Detection 🥃 AI tools can catch this smell if you configure them to flag conditional logic based on testing states. Try Them! 🛠 Remember: AI Assistants make lots of mistakes Suggested Prompt: Remove IsTesting method and replace it by modeling the environments Without Proper Instructions

With Specific Instructions



ChatGPT

ChatGPT



Claude

Claude



Perplexity

Perplexity



Copilot

Copilot



Gemini

Gemini



DeepSeek

DeepSeek



Meta AI

Meta AI



Qwen

Qwen Conclusion 🏁 Avoid using isTesting flags. Use dependency injection and model the environments to keep test and production logic separate. Relations 👩‍❤️‍💋‍👨 https://hackernoon.com/how-to-find-the-stinky-parts-of-your-code-part-xxii https://hackernoon.com/how-to-find-the-stinky-parts-of-your-code-part-xiii https://hackernoon.com/how-to-find-the-stinky-parts-of-your-code-part-vi-cmj31om https://hackernoon.com/code-smell-242-zombie-feature-flags?embedable=true Disclaimer 📘 Code Smells are my opinion. Credits 🙏 Photo by Christian Gertenbach on Unsplash When you add testing flags, you undermine confidence in production. Ward Cunningham https://hackernoon.com/400-thought-provoking-software-engineering-quotes?embedable=true This article is part of the CodeSmell Series. https://hackernoon.com/how-to-find-the-stinky-parts-of-your-code-part-i-xqz3evd?embedable=true Don’t let test code sneak into production Don’t let test code sneak into production TL;DR: Avoid adding isTesting or similar flags. TL;DR: Avoid adding isTesting or similar flags. isTesting Problems 😔 Leaky abstraction Non-Business code pollution Fragile Code Inconsistent behavior Hidden dependencies Difficult debugging Boolean flags Untrusted tests Production dependant code Leaky abstraction Non-Business code pollution Fragile Code Inconsistent behavior Hidden dependencies Difficult debugging Boolean flags Boolean flags Untrusted tests Production dependant code Production dependant code Solutions 😃 Remove behavior Ifs Use dependency injection Model external services (Don't mock them) Separate configurations Isolate test logic Maintain clean behavior boundaries Remove behavior Ifs behavior Ifs Use dependency injection Model external services (Don't mock them) mock Separate configurations Isolate test logic Maintain clean behavior boundaries Refactorings ⚙️ https://hackernoon.com/refactoring-014-how-to-remove-if?embedable=true https://hackernoon.com/refactoring-014-how-to-remove-if?embedable=true Context 💬 When you add flags like isTesting , you mix testing and production code. isTesting This creates hidden paths that are only active in tests. Also, you don't cover real production code. You risk shipping testing behavior to production, leading to bugs and unpredictable behavior. Sample Code 📖 Wrong ❌ struct PaymentService {
    is_testing: bool,
}

impl PaymentService {
    fn process_payment(&self, amount: f64) {
        if self.is_testing {
            println!("Testing mode: Skipping real payment");
            return;
        }
        println!("Processing payment of ${}", amount);
    }
} struct PaymentService {
    is_testing: bool,
}

impl PaymentService {
    fn process_payment(&self, amount: f64) {
        if self.is_testing {
            println!("Testing mode: Skipping real payment");
            return;
        }
        println!("Processing payment of ${}", amount);
    }
} Right 👉 trait PaymentProcessor {
    fn process(&self, amount: f64);
}

struct RealPaymentProcessor;
impl PaymentProcessor for RealPaymentProcessor {
    fn process(&self, amount: f64) {
        println!("Processing payment of ${}", amount);
    }
}

struct TestingPaymentProcessor;
impl PaymentProcessor for TestingPaymentProcessor {
    // Notice this is not a mock
    fn process(&self, _: f64) {
        println!("No payment: Skipping real transaction");
    }
}

struct PaymentService<T: PaymentProcessor> {
    processor: T,
}

impl<T: PaymentProcessor> PaymentService<T> {
    fn process_payment(&self, amount: f64) {
        self.processor.process(amount);
    }
} trait PaymentProcessor {
    fn process(&self, amount: f64);
}

struct RealPaymentProcessor;
impl PaymentProcessor for RealPaymentProcessor {
    fn process(&self, amount: f64) {
        println!("Processing payment of ${}", amount);
    }
}

struct TestingPaymentProcessor;
impl PaymentProcessor for TestingPaymentProcessor {
    // Notice this is not a mock
    fn process(&self, _: f64) {
        println!("No payment: Skipping real transaction");
    }
}

struct PaymentService<T: PaymentProcessor> {
    processor: T,
}

impl<T: PaymentProcessor> PaymentService<T> {
    fn process_payment(&self, amount: f64) {
        self.processor.process(amount);
    }
} Detection 🔍 [x]Semi-Automatic [x] Semi-Automatic [x] You can detect this smell by looking for conditional flags like isTesting , environment == 'test' , DEBUG_MODE , and idioms like these. isTesting environment == 'test' DEBUG_MODE These indicate that testing behavior is leaking into the production code. Tags 🏷️ Testing Testing Level 🔋 [x]Intermediate [x] Intermediate [x] Why the Bijection Is Important 🗺️ You need a clear separation between test and production code. When you mix them, you break the one-to-one Bijection between real-world behavior and the program. Bijection Since environments are real-world entities you need to explicitly model them in the MAPPER . MAPPER AI Generation 🤖 AI-generated code often introduces this smell when you use quick hacks for testing. Some tools suggest flags like isTesting because they prioritize ease over proper design. isTesting AI Detection 🥃 AI tools can catch this smell if you configure them to flag conditional logic based on testing states. Try Them! 🛠 Remember: AI Assistants make lots of mistakes Remember: AI Assistants make lots of mistakes Suggested Prompt: Remove IsTesting method and replace it by modeling the environments Suggested Prompt: Remove IsTesting method and replace it by modeling the environments Without Proper Instructions

With Specific Instructions



ChatGPT

ChatGPT



Claude

Claude



Perplexity

Perplexity



Copilot

Copilot



Gemini

Gemini



DeepSeek

DeepSeek



Meta AI

Meta AI



Qwen

Qwen Without Proper Instructions

With Specific Instructions ChatGPT

ChatGPT Claude

Claude Perplexity

Perplexity Copilot

Copilot Gemini

Gemini DeepSeek

DeepSeek Meta AI

Meta AI Qwen

Qwen Without Proper Instructions With Specific Instructions Without Proper Instructions Without Proper Instructions With Specific Instructions With Specific Instructions ChatGPT ChatGPT ChatGPT ChatGPT ChatGPT ChatGPT ChatGPT ChatGPT Claude Claude Claude Claude Claude Claude Claude Claude Perplexity Perplexity Perplexity Perplexity Perplexity Perplexity Perplexity Perplexity Copilot Copilot Copilot Copilot Copilot Copilot Copilot Copilot Gemini Gemini Gemini Gemini Gemini Gemini Gemini Gemini DeepSeek DeepSeek DeepSeek DeepSeek DeepSeek DeepSeek DeepSeek DeepSeek Meta AI Meta AI Meta AI Meta AI Meta AI Meta AI Meta AI Meta AI Qwen Qwen Qwen Qwen Qwen Qwen Qwen Qwen Conclusion 🏁 Avoid using isTesting flags. isTesting Use dependency injection and model the environments to keep test and production logic separate. Relations 👩‍❤️‍💋‍👨 https://hackernoon.com/how-to-find-the-stinky-parts-of-your-code-part-xxii https://hackernoon.com/how-to-find-the-stinky-parts-of-your-code-part-xxii https://hackernoon.com/how-to-find-the-stinky-parts-of-your-code-part-xiii https://hackernoon.com/how-to-find-the-stinky-parts-of-your-code-part-xiii https://hackernoon.com/how-to-find-the-stinky-parts-of-your-code-part-vi-cmj31om https://hackernoon.com/how-to-find-the-stinky-parts-of-your-code-part-vi-cmj31om https://hackernoon.com/code-smell-242-zombie-feature-flags?embedable=true https://hackernoon.com/code-smell-242-zombie-feature-flags?embedable=true Disclaimer 📘 Code Smells are my opinion . opinion Credits 🙏 Photo by Christian Gertenbach on Unsplash Christian Gertenbach Unsplash When you add testing flags, you undermine confidence in production. When you add testing flags, you undermine confidence in production. Ward Cunningham Ward Cunningham https://hackernoon.com/400-thought-provoking-software-engineering-quotes?embedable=true https://hackernoon.com/400-thought-provoking-software-engineering-quotes?embedable=true This article is part of the CodeSmell Series. https://hackernoon.com/how-to-find-the-stinky-parts-of-your-code-part-i-xqz3evd?embedable=true https://hackernoon.com/how-to-find-the-stinky-parts-of-your-code-part-i-xqz3evd?embedable=true

UNSPLASH

unsplash.com

51-200 employees

Since 2013

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UNSPLASH

EVERGREEN INDEX #553

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UNSPLASH

unsplash.com

51-200 employees

Since 2013

COMPANY RANKING

UNSPLASH

EVERGREEN INDEX #553

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