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Consider the following JSON object: { "sides": 4, "colour": "red", "sides": 5, "colour": "blue" } Notice that sides and colour both appear twice. This looks invalid, but I learnt recently that this is actually legal JSON syntax! It’s unusual and discouraged, but it’s not completely forbidden. This was a big surprise to me. I think of JSON objects as key/value pairs, and I associate them with data structures like a dict in Python or a Hash in Ruby – both of which only allow unique keys. JSON has no such restriction, and I started thinking about how to handle it. What does the JSON spec say about duplicate names? JSON is described by several standards, which Wikipedia helpfully explains for us: After RFC 4627 had been available as its “informational” specification since 2006, JSON was first standardized in 2013, as ECMA‑404. RFC 8259, published in 2017, is the current version of the Internet Standard STD 90, and it remains consistent with ECMA‑404. That same year, JSON was also standardized as ISO/IEC 21778:2017. The ECMA and ISO/IEC standards describe only the allowed syntax, whereas the RFC covers some security and interoperability considerations. All three of these standards explicitly allow the use of duplicate names in objects. ECMA‑404 and ISO/IEC 21778:2017 have identical text to describe the syntax of JSON objects, and they say (emphasis mine): An object structure is represented as a pair of curly bracket tokens surrounding zero or more name/value pairs. […] The JSON syntax does not impose any restrictions on the strings used as names, does not require that name strings be unique, and does not assign any significance to the ordering of name/value pairs. These are all semantic considerations that may be defined by JSON processors or in specifications defining specific uses of JSON for data interchange. RFC 8259 goes further and strongly recommends against duplicate names, but the use of SHOULD means it isn’t completely forbidden: The names within an object SHOULD be unique. The same document warns about the consequences of ignoring this recommendation: An object whose names are all unique is interoperable in the sense that all software implementations receiving that object will agree on the name-value mappings. When the names within an object are not unique, the behavior of software that receives such an object is unpredictable. Many implementations report the last name/value pair only. Other implementations report an error or fail to parse the object, and some implementations report all of the name/value pairs, including duplicates. So it’s technically valid, but it’s unusual and discouraged. I’ve never heard of a use case for JSON objects with duplicate names. I’m sure there was a good reason for it being allowed by the spec, but I can’t think of it. Most JSON parsers – including jq, JavaScript, and Python – will silently discard all but the last instance of a duplicate name. Here’s an example in Python: >>> import json >>> json.loads('{"sides": 4, "colour": "red", "sides": 5, "colour": "blue"}') {'colour': 'blue', 'sides': 5} What if I wanted to decode the whole object, or throw an exception if I see duplicate names? This happened to me recently. I was editing a JSON file by hand, and I’d copy/paste objects to update the data. I also had scripts which could update the file. I forgot to update the name on one of the JSON objects, so there were two name/value pairs with the same name. When I ran the script, it silently erased the first value. I was able to recover the deleted value from the Git history, but I wondered how I could prevent this happening again. How could I make the script fail, rather than silently delete data? Decoding duplicate names in Python When Python decodes a JSON object, it first parses the object as a list of name/value pairs, then it turns that list of name value pairs into a dictionary. We can see this by looking at the JSONObject function in the CPython source code: it builds a list pairs, and at the end of the function, it calls dict(pairs) to turn the list into a dictionary. This relies on the fact that dict() can take an iterable of key/value tuples and create a dictionary: >>> dict([('sides', 4), ('colour', 'red')]) {'colour': 'red', 'sides': 4} The docs for dict() tell us that it` will discard duplicate keys: “if a key occurs more than once, the last value for that key becomes the corresponding value in the new dictionary”. >>> dict([('sides', 4), ('colour', 'red'), ('sides', 5), ('colour', 'blue')]) {'colour': 'blue', 'sides': 5} We can customise what Python does with the list of name/value pairs. Rather than calling dict(), we can pass our own function to the object_pairs_hook parameter of json.loads(), and Python will call that function on the list of pairs. This allows us to parse objects in a different way. For example, we can just return the literal list of name/value pairs: >>> import json >>> json.loads( ... '{"sides": 4, "colour": "red", "sides": 5, "colour": "blue"}', ... object_pairs_hook=lambda pairs: pairs ... ) ... [('sides', 4), ('colour', 'red'), ('sides', 5), ('colour', 'blue')] We could also use the multidict library to get a dict-like data structure which supports multiple values per key. This is based on HTTP headers and URL query strings, two environments where it’s common to have multiple values for a single key: >>> from multidict import MultiDict >>> md = json.loads( ... '{"sides": 4, "colour": "red", "sides": 5, "colour": "blue"}', ... object_pairs_hook=lambda pairs: MultiDict(pairs) ... ) ... >>> md <MultiDict('sides': 4, 'colour': 'red', 'sides': 5, 'colour': 'blue')> >>> md['sides'] 4 >>> md.getall('sides') [4, 5] Preventing silent data loss If we want to throw an exception when we see duplicate names, we need a longer function. Here’s the code I wrote: import collections import typing def dict_with_unique_names(pairs: list[tuple[str, typing.Any]]) -> dict[str, typing.Any]: """ Convert a list of name/value pairs to a dict, but only if the names are unique. If there are non-unique names, this function throws a ValueError. """ # First try to parse the object as a dictionary; if it's the same # length as the pairs, then we know all the names were unique and # we can return immediately. pairs_as_dict = dict(pairs) if len(pairs_as_dict) == len(pairs): return pairs_as_dict # Otherwise, let's work out what the repeated name(s) were, so we # can throw an appropriate error message for the user. name_tally = collections.Counter(n for n, _ in pairs) repeated_names = [n for n, count in name_tally.items() if count > 1] assert len(repeated_names) > 0 if len(repeated_names) == 1: raise ValueError(f"Found repeated name in JSON object: {repeated_names[0]}") else: raise ValueError( f"Found repeated names in JSON object: {', '.join(repeated_names)}" ) If I use this as my object_pairs_hook when parsing an object which has all unique names, it returns the normal dict I’d expect: >>> json.loads( ... '{"sides": 4, "colour": "red"}', ... object_pairs_hook=dict_with_unique_names ... ) ... {'colour': 'red', 'sides': 4} But if I’m parsing an object with one or more repeated names, the parsing fails and throws a ValueError: >>> json.loads( ... '{"sides": 4, "colour": "red", "sides": 5}', ... object_pairs_hook=dict_with_unique_names ... ) Traceback (most recent call last): […] ValueError: Found repeated name in JSON object: sides >>> json.loads( ... '{"sides": 4, "colour": "red", "sides": 5, "colour": "blue"}', ... object_pairs_hook=dict_with_unique_names ... ) Traceback (most recent call last): […] ValueError: Found repeated names in JSON object: sides, colour This is precisely the behaviour I want – throwing an exception, not silently dropping data. Encoding non-unique names in Python It’s hard to think of a use case, but this post feels incomplete without at least a brief mention. If you want to encode custom data structures with Python’s JSON library, you can subclass JSONEncoder and define how those structures should be serialised. Here’s a rudimentary attempt at doing that for a MultiDict: class MultiDictEncoder(json.JSONEncoder): def encode(self, o: typing.Any) -> str: # If this is a MultiDict, we need to construct the JSON string # manually -- first encode each name/value pair, then construct # the JSON object literal. if isinstance(o, MultiDict): name_value_pairs = [ f'{super().encode(str(name))}: {self.encode(value)}' for name, value in o.items() ] return '{' + ', '.join(name_value_pairs) + '}' return super().encode(o) and here’s how you use it: >>> md = MultiDict([('sides', 4), ('colour', 'red'), ('sides', 5), ('colour', 'blue')]) >>> json.dumps(md, cls=MultiDictEncoder) {"sides": 4, "colour": "red", "sides": 5, "colour": "blue"} This is rough code, and you shouldn’t use it – it’s only an example. I’m constructing the JSON string manually, so it doesn’t handle edge cases like indentation or special characters. There are almost certainly bugs, and you’d need to be more careful if you wanted to use this for real. In practice, if I had to encode a multi-dict as JSON, I’d encode it as a list of objects which each have a key and a value field. For example: [ {"key": "sides", "value": 4 }, {"key": "colour", "value": "red" }, {"key": "sides", "value": 5 }, {"key": "colour", "value": "blue"}, ] This is a pretty standard pattern, and it won’t trip up JSON parsers which aren’t expecting duplicate names. Do you need to worry about this? This isn’t a big deal. JSON objects with duplicate names are pretty unusual – this is the first time I’ve ever encountered one, and it was a mistake. Trying to account for this edge case in every project that uses JSON would be overkill. It would add complexity to my code and probably never catch a single error. This started when I made a copy/paste error that introduced the initial duplication, and then a script modified the JSON file and caused some data loss. That’s a somewhat unusual workflow, because most JSON files are exclusively modified by computers, and this wouldn’t be an issue. I’ve added this error handling to my javascript-data-files library, but I don’t anticipate adding it to other projects. I use that library for my static website archives, which is where I had this issue. Although I won’t use this code exactly, it’s been good practice at writing custom encoders/decoders in Python. That is something I do all the time – I’m often encoding native Python types as JSON, and I want to get the same type back when I decode later. I’ve been writing my own subclasses of JSONEncoder and JSONDecoder for a while. Now I know a bit more about how Python decodes JSON, and object_pairs_hook is another tool I can consider using. This was a fun deep dive for me, and I hope you found it helpful too. [If the formatting of this post looks odd in your feed reader, visit the original article]
I support dark mode on this site, and as part of the dark theme, I have a colour-inverted copy of the default background texture. I like giving my website a subtle bit of texture, which I think makes it stand out from a web which is mostly solid-colour backgrounds. Both my textures are based on the “White Waves” pattern made by Stas Pimenov. I was setting these images as my background with two CSS rules, using the prefers-color-scheme: dark media feature to use the alternate image in dark mode: body { background: url('https://alexwlchan.net/theme/white-waves-transparent.png'); } @media (prefers-color-scheme: dark) { body { background: url('https://alexwlchan.net/theme/black-waves-transparent.png'); } } This works, mostly. But I prefer light mode, so while I wrote this CSS and I do some brief testing whenever I make changes, I’m not using the site in dark mode. I know how dark mode works in my local development environment, not how it feels as a day-to-day user. Late last night I was using my phone in dark mode to avoid waking the other people in the house, and I opened my site. I saw a brief flash of white, and then the dark background texture appeared. That flash of bright white is precisely what you don’t want when you’re using dark mode, but it happened anyway. I made a note to work it out in the morning, then I went to bed. Now I’m fully awake, it’s obvious what happened. Because my only background is the image URL, there’s a brief gap between the CSS being parsed and the background image being loaded. In that time, the browser doesn’t have anything to put in the background, so you just get pure white. This was briefly annoying in the moment, but it would be even more worse if the background texture never loaded. I have light text on black in dark mode, but without the background image it’s just light text on white, which is barely readable: I never noticed this in local development, because I’m usually working in a well-lit room where that white flash would be far less obvious. I’m also using a local version of the site, which loads near-instantly and where the background image is almost certainly saved in my browser cache. I’ve made two changes to prevent this happening again. I’ve added a colour to use as a fallback until the image loads. The CSS background property supports adding a colour, which is used until the image loads, or as a fallback if it doesn’t. I already use this in a few places, and now I’ve added it to my body background. body { background: url('https://…/white-waves-transparent.png') #fafafa; } @media (prefers-color-scheme: dark) { body { background: url('https://…/black-waves-transparent.png') #0d0d0d; } } This avoids the flash of unstyled background before the image loads – the browser will use a solid dark background until it gets the texture. I’ve added rel="preload" elements to the head of the page, so the browser will start loading the background textures faster. These elements are a clue to the browser that these resources are going to be useful when it renders the page, so it should start loading them as soon as possible: <link rel="preload" href="https://alexwlchan.net/theme/white-waves-transparent.png" as="image" type="image/png" media="(prefers-color-scheme: light)" /> <link rel="preload" href="https://alexwlchan.net/theme/black-waves-transparent.png" as="image" type="image/png" media="(prefers-color-scheme: dark)" /> This means the browser is downloading the appropriate texture at the same time as it’s downloading the CSS file. Previously it had to download the CSS file, parse it, and only then would it know to start downloading the texture. With the preload, it’s a bit faster! The difference is probably imperceptible if you’re on a fast connection, but it’s a small win and I can’t see any downside (as long as I scope the preload correctly, and don’t preload resources I don’t end up using). I’ve seen a lot of sites using <link rel="preload"> and I’ve only half-understood what it is and why it’s useful – I’m glad to have a chance to use it myself, so I can understand it better. This bug reminds me of a phenomenon called flash of unstyled text. Back when custom fonts were fairly new, you’d often see web pages appear briefly with the default font before custom fonts finished loading. There are well-understood techniques for preventing this, so it’s unusual to see that brief unstyled text on modern web pages – but the same issue is affecting me in dark mode I avoided using custom fonts on the web to avoid tackling this issue, but it got me anyway! In these dark times for the web, old bugs are new again. [If the formatting of this post looks odd in your feed reader, visit the original article]
I’m a big fan of keyring, a Python module made by Jason R. Coombs for storing secrets in the system keyring. It works on multiple operating systems, and it knows what password store to use for each of them. For example, if you’re using macOS it puts secrets in the Keychain, but if you’re on Windows it uses Credential Locker. The keyring module is a safe and portable way to store passwords, more secure than using a plaintext config file or an environment variable. The same code will work on different platforms, because keyring handles the hard work of choosing which password store to use. It has a straightforward API: the keyring.set_password and keyring.get_password functions will handle a lot of use cases. >>> import keyring >>> keyring.set_password("xkcd", "alexwlchan", "correct-horse-battery-staple") >>> keyring.get_password("xkcd", "alexwlchan") "correct-horse-battery-staple" Although this API is simple, it’s not perfect – I have some frustrations with the get_password function. In a lot of my projects, I’m now using a small function that wraps get_password. What do I find frustrating about keyring.get_password? If you look up a password that isn’t in the system keyring, get_password returns None rather than throwing an exception: >>> print(keyring.get_password("xkcd", "the_invisible_man")) None I can see why this makes sense for the library overall – a non-existent password is very normal, and not exceptional behaviour – but in my projects, None is rarely a usable value. I normally use keyring to retrieve secrets that I need to access protected resources – for example, an API key to call an API that requires authentication. If I can’t get the right secrets, I know I can’t continue. Indeed, continuing often leads to more confusing errors when some other function unexpectedly gets None, rather than a string. For a while, I wrapped get_password in a function that would throw an exception if it couldn’t find the password: def get_required_password(service_name: str, username: str) -> str: """ Get password from the specified service. If a matching password is not found in the system keyring, this function will throw an exception. """ password = keyring.get_password(service_name, username) if password is None: raise RuntimeError(f"Could not retrieve password {(service_name, username)}") return password When I use this function, my code will fail as soon as it fails to retrieve a password, rather than when it tries to use None as the password. This worked well enough for my personal projects, but it wasn’t a great fit for shared projects. I could make sense of the error, but not everyone could do the same. What’s that password meant to be? A good error message explains what’s gone wrong, and gives the reader clear steps for fixing the issue. The error message above is only doing half the job. It tells you what’s gone wrong (it couldn’t get the password) but it doesn’t tell you how to fix it. As I started using this snippet in codebases that I work on with other developers, I got questions when other people hit this error. They could guess that they needed to set a password, but the error message doesn’t explain how, or what password they should be setting. For example, is this a secret they should pick themselves? Is it a password in our shared password vault? Or do they need an API key for a third-party service? If so, where do they find it? I still think my initial error was an improvement over letting None be used in the rest of the codebase, but I realised I could go further. This is my extended wrapper: def get_required_password(service_name: str, username: str, explanation: str) -> str: """ Get password from the specified service. If a matching password is not found in the system keyring, this function will throw an exception and explain to the user how to set the required password. """ password = keyring.get_password(service_name, username) if password is None: raise RuntimeError( "Unable to retrieve required password from the system keyring!\n" "\n" "You need to:\n" "\n" f"1/ Get the password. Here's how: {explanation}\n" "\n" "2/ Save the new password in the system keyring:\n" "\n" f" keyring set {service_name} {username}\n" ) return password The explanation argument allows me to explain what the password is for to a future reader, and what value it should have. That information can often be found in a code comment or in documentation, but putting it in an error message makes it more visible. Here’s one example: get_required_password( "flask_app", "secret_key", explanation=( "Pick a random value, e.g. with\n" "\n" " python3 -c 'import secrets; print(secrets.token_hex())'\n" "\n" "This password is used to securely sign the Flask session cookie. " "See https://flask.palletsprojects.com/en/stable/config/#SECRET_KEY" ), ) If you call this function and there’s no keyring entry for flask_app/secret_key, you get the following error: Unable to retrieve required password from the system keyring! You need to: 1/ Get the password. Here's how: Pick a random value, e.g. with python3 -c 'import secrets; print(secrets.token_hex())' This password is used to securely sign the Flask session cookie. See https://flask.palletsprojects.com/en/stable/config/#SECRET_KEY 2/ Save the new password in the system keyring: keyring set flask_app secret_key It’s longer, but this error message is far more informative. It tells you what’s wrong, how to save a password, and what the password should be. This is based on a real example where the previous error message led to a misunderstanding. A co-worker saw a missing password called “secret key” and thought it referred to a secret key for calling an API, and didn’t realise it was actually for signing Flask session cookies. Now I can write a more informative error message, I can prevent that misunderstanding happening again. (We also renamed the secret, for additional clarity.) It takes time to write this explanation, which will only ever be seen by a handful of people, but I think it’s important. If somebody sees it at all, it’ll be when they’re setting up the project for the first time. I want that setup process to be smooth and straightforward. I don’t use this wrapper in all my code, particularly small or throwaway toys that won’t last long enough for this to be an issue. But in larger codebases that will be used by other developers, and which I expect to last a long time, I use it extensively. Writing a good explanation now can avoid frustration later. [If the formatting of this post looks odd in your feed reader, visit the original article]
I’ve been writing some internal dashboards recently, and one hard part is displaying timestamps. Our server does everything in UTC, but the team is split across four different timezones, so the server timestamps aren’t always easy to read. For most people, it’s harder to understand a UTC timestamp than a timestamp in your local timezone. Did that event happen just now, an hour ago, or much further back? Was that at the beginning of your working day? Or at the end? Then I remembered that I tried to solve this five years ago at a previous job. I wrote a JavaScript snippet that converts UTC timestamps into human-friendly text. It displays times in your local time zone, and adds a short suffix if the time happened recently. For example: today @ 12:00 BST (1 hour ago) In my old project, I was using writing timestamps in a <div> and I had to opt into the human-readable text for every date on the page. It worked, but it was a bit fiddly. Doing it again, I thought of a more elegant solution. HTML has a <time> element for expressing datetimes, which is a more meaningful wrapper than a <div>. When I render the dashboard on the server, I don’t know the user’s timezone, so I include the UTC timestamp in the page like so: <time datetime="2025-04-15 19:45:00Z"> Tue, 15 Apr 2025 at 19:45 UTC </time> I put a machine-readable date and time string with a timezone offset string in the datetime attribute, and then a more human-readable string in the text of the element. Then I add this JavaScript snippet to the page: window.addEventListener("DOMContentLoaded", function() { document.querySelectorAll("time").forEach(function(timeElem) { // Set the `title` attribute to the original text, so a user // can hover over a timestamp to see the UTC time. timeElem.setAttribute("title", timeElem.innerText); // Replace the display text with a human-friendly date string // which is localised to the user's timezone. timeElem.innerText = getHumanFriendlyDateString( timeElem.getAttribute("datetime") ); }) }); This updates any <time> element on the page to use a human friendly date string, which is localised to the user’s timezone. For example, I’m in the UK so that becomes: <time datetime="2025-04-15 19:45:00Z" title="Tue, 15 Apr 2025 at 19:45 UTC"> Tue, 15 Apr 2025 at 20:45 BST </time> In my experience, these timestamps are easier and more intuitive for people to read. I always include a timezone string (e.g. BST, EST, PDT) so it’s obvious that I’m showing a localised timestamp. If you really need the UTC timestamp, it’s in the title attribute, so you can see it by hovering over it. (Sorry, mouseless users, but I don’t think any of my team are browsing our dashboards from their phone or tablet.) If the JavaScript doesn’t load, you see the plain old UTC timestamp. It’s not ideal, but the page still loads and you can see all the information – this behaviour is an enhancement, not an essential. To me, this is the unfulfilled promise of the <time> element. In my fantasy world, web page authors would write the time in a machine-readable format, and browsers would show it in a way that makes sense for the reader. They’d take into account their language, locale, and time zone. I understand why that hasn’t happened – it’s much easier said than done. You need so much context to know what’s the “right” thing to do when dealing with datetimes, and guessing without that context is at the heart of many datetime bugs. These sort of human-friendly, localised timestamps are very handy sometimes, and a complete mess at other times. In my staff-only dashboards, I have that context. I know what these timestamps mean, who’s going to be reading them, and I think they’re a helpful addition that makes the data easier to read. [If the formatting of this post looks odd in your feed reader, visit the original article]
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<![CDATA[It has been a year since I set up my System76 Merkaat with Linux Mint. In July of 2024 I migrated from ChromeOS and the Merkaat has been my daily driver on the desktop. A year later I have nothing major to report, which is the point. Despite the occasional unplanned reinstallation I have been enjoying the stability of Linux and just using the PC. This stability finally enabled me to burn bridges with mainstream operating systems and fully embrace Linux and open systems. I'm ready to handle the worst and get back to work. Just a few years ago the frustration of troubleshooting a broken system would have made me seriously consider the switch to a proprietary solution. But a year of regular use, with an ordinary mix of quiet moments and glitches, gave me the confidence to stop worrying and learn to love Linux. linux a href="https://remark.as/p/journal.paoloamoroso.com/my-first-year-since-coming-back-to-linux"Discuss.../a Email | Reply @amoroso@oldbytes.space !--emailsub--]]>
The mystery In the previous article, I briefly mentioned a slight difference between the ESP-Prog and the reproduced circuit, when it comes to EN: Focusing on EN, it looks like the voltage level goes back to 3.3V much faster on the ESP-Prog than on the breadboard circuit. The grid is horizontally spaced at 2ms, so … Continue reading Overanalyzing a minor quirk of Espressif’s reset circuit → The post Overanalyzing a minor quirk of Espressif’s reset circuit appeared first on Quentin Santos.
Explaining nil interface{} gotcha in Go A footgun In Go empty interface is an interface without any methods, typed as interface{}. A zero value of interface{} is nil: var v interface{} // compiler sets this to nil, you could explicitly write = nil if v == nil { fmt.Printf("v is nil\n") } else { fmt.Printf("v is NOT nil\n") } Try online This prints: v is nil. However, this sometimes trips people up: type Foo struct { } var v interface{} var nilFoo *Foo // implicilty initialized by compiler to nil if nilFoo == nil { fmt.Printf("nilFoo is nil.") } else { fmt.Printf("nilFoo is NOT nil.") } v = nilFoo if v == nil { fmt.Printf("v is nil\n") } else { fmt.Printf("v is NOT nil\n") } Try online This prints: nilFoo is nil. v is NOT nil. On surface level, this is wrong: t is a nil. We assigned a nil to v but it doesn’t equal to nil? How to check if interface{} is nil of any pointer type? func isNilPointer(i interface{}) bool { if i == nil { return false // interface itself is nil } v := reflect.ValueOf(i) return v.Kind() == reflect.Ptr && v.IsNil() } type Foo struct { } var pf *Foo var v interface{} = pf if isNilPointer(v) { fmt.Printf("v is nil pointer\n") } else { fmt.Printf("v is NOT nil pointer\n") } Try online Why There’s a reason for this perplexing behavior. nil is an abstract value. If you come from C/C++ or Java/C#, you might think that this is equivalent of NULL pointer or null reference. It isn’t. nil is a symbol that represents a zero value of pointers, channels, maps, slices. Logically interface{} combines type and value. You can think of it as a tuple (type, value). An uninitialized value of interface{} is a tuple without a type and value (no type, no value). In Go uninitialized value is zero value and since nil is an abstract value representing zero value for several types, it makes sense to use it for zero value of interface{}. So: zero value of interface{} is nil which is (no type, no value). When we assigned nilFoo to v, the value is (*Foo, nil). Are you surprised that (no type, no value) is not the same as (*Foo, nil)? To understand this gotcha, you have to understand two things. One: nil is an abstract value that only has a meaning in context. Consider this: var ch chan (bool) var m map[string]bool if ch == m { fmt.Printf("ch is equal to m\n") } Try online This snippet doesn’t even compile: Error:./prog.go:8:11: invalid operation: ch == m (mismatched types chan bool and map[string]bool). Both ch and m are nil but you can’t compare them because they are of different types. nil != nil because nil is an abstract concept, not an actual value. Two: nil value of interface{} is (no type, no value). Once you understand the above, you’ll understand why nil doesn’t compare to (type, nil) e.g. (*Foo, nil) or (map[string]bool, nil) or (int, 0) or (string, ""). Bad design or inevitable consequence of previous decisions? Many claim it’s a bad design. No-one describes what a better design would look like. Let’s play act a Go language designer. You’ve already designed concrete types, you came up with notion of zero value and created nil to denote zero value for pointers, channels, maps, slices. You’re now designing interface{} as a logical tuple of (type, value). The zero value is obviously (no type, no value). You have to figure how to represent the zero value. A different symbol for interface{} zero value Instead of using nil you could create a different symbol e.g. zeroInteface. You could then write: var v interface{} var v2 interface{} = &Foo{nil} var v3 interface{} = int(0) if v == zeroInteface { // this is true } if v2 == nil { // tihs is true } if v3 == nil { // is it true or not? } Is this a better design? I don’t think so. We don’t have zeroPointer, zeroMap, zeroChanel etc. so this breaks consistency. It sticks out like a sore zeroInterface. And v == nil is subtle. Not all values wrapped in an interface{} have zero value of nil. What should happen if you compare to (int, 0) given that 0 is zero value of int? Damn the consistency, let’s do what user expects You could ditch the strict logic of nil values and special case the if v == nil for interface{} to do what people superficially expect to happen. You then have to answer the question below: what happens when you do if (int, 0) == nil? The biggest issue is that you’ve lost ability to distinguish between (no type, no value) and (type, nil). They both compare to nil so how would you test for (no type, no value) but not (type, nil)? It doesn’t seem like a better design either. Your proposal Now that you understand the problem and seen two ideas for how to fix it, it’s your turn to design a better solution. I tried and the above 2 are the only ideas I had. We are boxed by existing notions of zero values and using nil to represent them. We could explore designs that re-think those assumptions but would that be Go anymore? It’s easy to complain that something is a bad design. It’s much harder, often impossible, to design something better.
I signed up for Hinge. Holy shit with the boosts. How does someone who works on this wake up every morning and feel okay about themselves? Similarly with the tip screens, Uber algorithm, all the zero sum bullshit using all the tricks of psychology to extract a little bit more from every interaction in society. Nudge. Nudge. NUDGE. Want to partake in normal society like buying a coffee, going on a date, getting a ride, paying a friend. Oh, there’s a middle man now. An evil ominous middleman using state of the art AI algorithms to extract just a little bit more from you. But eventually the market will fix this, right? People will feel sick of being manipulated and move elsewhere? Ahhh, but they see that coming long before you do. They have dashboards. Quick Jeeves, tune the AI to make people feel less manipulated. Give them a little bit more for now, we have to think about maximizing lifetime customer value here. Oh the AI already did this on its own? Jeeves you’ve been replaced! People perpetually on the edge. You want to opt out of this all you say? Good luck running a competitive business! Every metric is now a target. You better maximize engagement or you will lose engagement this is a red queen’s race we can’t afford to lose! Burn all the social capital, burn all your values, FEED IT ALL TO MOLOCH! Someday, people will have to realize we live in a society. What will it take? A complete self cannibalization to the point you can’t eat your own mouth? It sure as hell isn’t going to be people opting out, that’s a collective action problem you can’t solve. Democracy, haha, you think the algorithms will let you vote to kill them? Your vote is as decoupled from action as the amount Uber pays the driver is decoupled from the fare that you pay. There’s no reform here, there’s only revolution. Will it simply be a huge financial collapse? Or do we need World War 3? And even World War 3 is on a spectrum. Will mass starvation fix this? Or will the attitude of thinking it’s okay to manipulate others at scale persist even past that? He’s got his, and I’ve got mine… If you open a government S&P 500 account for everyone with $1,000 at birth that’ll pay their social security cause it like…goes up…wait who’s creating this value again? It’s not okay. Advertising is not okay. Price discrimination is not okay. Using big data, machine learning, and psychology to manipulate others at scale is not okay. But you aren’t going to learn this lesson until you have fed a huge majority of your customers to Moloch. Modern capitialism is wireheading. Release the hypnodrones. How many cans of Pepsi did you want them to consume an hour again?
I've never seen so many developers curious about leaving the Mac and giving Linux a go. Something has really changed in the last few years. Maybe Linux just got better? Maybe powerful mini PCs made it easier? Maybe Apple just fumbled their relationship with developers one too many times? Maybe it's all of it. But whatever the reason, the vibe shift is noticeable. This is why the future is so hard to predict! People have been joking about "The Year of Linux on the Desktop" since the late 90s. Just like self-driving cars were supposed to be a thing back in 2017. And now, in the year of our Lord 2025, it seems like we're getting both! I also wouldn't underestimate the cultural influence of a few key people. PewDiePie sharing his journey into Arch and Hyprland with his 110 million followers is important. ThePrimeagen moving to Arch and Hyprland is important. Typecraft teaching beginners how to build an Arch and Hyprland setup from scratch is important (and who I just spoke to about Omarchy). Gabe Newell's Steam Deck being built on Arch and pushing Proton to over 20,000 compatible Linux games is important. You'll notice a trend here, which is that Arch Linux, a notoriously "difficult" distribution, is at the center of much of this new engagement. Despite the fact that it's been around since 2003! There's nothing new about Arch, but there's something new about the circles of people it's engaging. I've put Arch at the center of Omarchy too. Originally just because that was what Hyprland recommended. Then, after living with the wonders of 90,000+ packages on the community-driven AUR package repository, for its own sake. It's really good! But while Arch (and Hyprland) are having a moment amongst a new crowd, it's also "just" Linux at its core. And Linux really is the star of the show. The perfect, free, and open alternative that was just sitting around waiting for developers to finally have had enough of the commercial offerings from Apple and Microsoft. Now obviously there's a taste of "new vegan sees vegans everywhere" here. You start talking about Linux, and you'll hear from folks already in the community or those considering the move too. It's easy to confuse what you'd like to be true with what is actually true. And it's definitely true that Linux is still a niche operating system on the desktop. Even among developers. Apple and Microsoft sit on the lion's share of the market share. But the mind share? They've been losing that fast. The window is open for a major shift to happen. First gradually, then suddenly. It feels like morning in Linux land!