Toward a “Kernel Python”

The life changing magic of a minimal standard library.

Prompted by Amber Brown’s presentation at the Python Language Summit last month, Christian Heimes has followed up on his own earlier work on slimming down the Python standard library, and created a proper Python Enhancement Proposal PEP 594 for removing obviously obsolete and unmaintained detritus from the standard library.

PEP 594 is great news for Python, and in particular for the maintainers of its standard library, who can now address a reduced surface area. A brief trip through the PEP’s rogues gallery of modules to deprecate or remove1 is illuminating. The python standard library contains plenty of useful modules, but it also hides a veritable necropolis of code, a towering monument to obsolescence, threatening to topple over on its maintainers at any point.

However, I believe the PEP may be approaching the problem from the wrong direction. Currently, the standard library is maintained in tandem with, and by the maintainers of, the CPython python runtime. Large portions of it are simply included in the hope that it might be useful to somebody. In the aforementioned PEP, you can see this logic at work in defense of the colorsys module: why not remove it? “The module is useful to convert CSS colors between coordinate systems. [It] does not impose maintenance overhead on core development.”

There was a time when Internet access was scarce, and maybe it was helpful to pre-load Python with lots of stuff so it could be pre-packaged with the Python binaries on the CD-ROM when you first started learning.

Today, however, the modules you need to convert colors between coordinate systems are only a pip install away. The bigger core interpreter is just more to download before you can get started.

Why Didn’t You Review My PR?

So let’s examine that claim: does a tiny module like colorsys “impose maintenance overhead on core development”?

The core maintainers have enough going on just trying to maintain the huge and ancient C codebase that is CPython itself. As Mariatta put it in her North Bay Python keynote, the most common question that core developers get is “Why haven’t you looked at my PR?” And the answer? It’s easier to not look at PRs when you don’t care about them. This from a talk about what it means to be a core developer!

One might ask, whether Twisted has the same problem. Twisted is a big collection of loosely-connected modules too; a sort of standard library for networking. Are clients and servers for SSH, IMAP, HTTP, TLS, et. al. all a bit much to try to cram into one package?

I’m compelled to reply: yes. Twisted is monolithic because it dates back to a similar historical period as CPython, where installing stuff was really complicated. So I am both sympathetic and empathetic towards CPython’s plight.

At some point, each sub-project within Twisted should ideally become a separate project with its own repository, CI, website, and of course its own more focused maintainers. We’ve been slowly splitting out projects already, where we can find a natural boundary. Some things that started in Twisted like constantly and incremental have been split out; deferred and filepath are in the process of getting that treatment as well. Other projects absorbed into the org continue to live separately, like klein and treq. As we figure out how to reduce the overhead of setting up and maintaining the CI and release infrastructure for each of them, we’ll do more of this.


But is our monolithic nature the most pressing problem, or even a serious problem, for the project? Let’s quantify it.

As of this writing, Twisted has 5 outstanding un-reviewed pull requests in our review queue. The median time a ticket spends in review is roughly four and a half days.2 The oldest ticket in our queue dates from April 22, which means it’s been less than 2 months since our oldest un-reviewed PR was submitted.

It’s always a struggle to find enough maintainers and enough time to respond to pull requests. Subjectively, it does sometimes feel like “Why won’t you review my pull request?” is a question we do still get all too often. We aren’t always doing this well, but all in all, we’re managing; the queue hovers between 0 at its lowest and 25 or so during a bad month.

By comparison to those numbers, how is core CPython doing?

Looking at CPython’s keyword-based review queue queue, we can see that there are 429 tickets currently awaiting review. The oldest PR awaiting review hasn’t been touched since February 2, 2018, which is almost 500 days old.

How many are interpreter issues and how many are stdlib issues? Clearly review latency is a problem, but would removing the stdlib even help?

For a quick and highly unscientific estimate, I scanned the first (oldest) page of PRs in the query above. By my subjective assessment, on this page of 25 PRs, 14 were about the standard library, 10 were about the core language or interpreter code; one was a minor documentation issue that didn’t really apply to either. If I can hazard a very rough estimate based on this proportion, somewhere around half of the unreviewed PRs might be in standard library code.


So the first reason the CPython core team needs to stop maintaining the standard library because they literally don’t have the capacity to maintain the standard library. Or to put it differently: they aren’t maintaining it, and what remains is to admit that and start splitting it out.

It’s true that none of the open PRs on CPython are in colorsys3. It does not, in fact, impose maintenance overhead on core development. Core development imposes maintenance overhead on it. If I wanted to update the colorsys module to be more modern - perhaps to have a Color object rather than a collection of free functions, perhaps to support integer color models - I’d likely have to wait 500 days, or more, for a review.

As a result, code in the standard library is harder to change, which means its users are less motivated to contribute to it. CPython’s unusually infrequent releases also slow down the development of library code and decrease the usefulness of feedback from users. It’s no accident that almost all of the modules in the standard library have actively maintained alternatives outside of it: it’s not a failure on the part of the stdlib’s maintainers. The whole process is set up to produce stagnation in all but the most frequently used parts of the stdlib, and that’s exactly what it does.

New Environments, New Requirements

Perhaps even more importantly is that bundling together CPython with the definition of the standard library privileges CPython itself, and the use-cases that it supports, above every other implementation of the language.

Podcast after podcast after podcast after keynote tells us that in order to keep succeeding and expanding, Python needs to grow into new areas: particularly web frontends, but also mobile clients, embedded systems, and console games.

These environments require one or both of:

  • a completely different runtime, such as Brython, or MicroPython
  • a modified, stripped down version of the standard library, which elides most of it.

In all of these cases, determining which modules have been removed from the standard library is a sticking point. They have to be discovered by a process of trial and error; notably, a process completely different from the standard process for determining dependencies within a Python application. There’s no install_requires declaration you can put in your setup.py that indicates that your library uses a stdlib module that your target Python runtime might leave out due to space constraints.

You can even have this problem even if all you ever use is the standard python on your Linux installation. Even server- and desktop-class Linux distributions have the same need for a more minimal core Python package, and so they already chop up the standard library somewhat arbitrarily. This can break the expectations of many python codebases, and result in bugs where even pip install won’t work.

Take It All Out

How about the suggestion that we should do only a little a day? Although it sounds convincing, don’t be fooled. The reason you never seem to finish is precisely because you tidy a little at a time. [...] The ultimate secret of success is this: If you tidy up in one shot, rather than little by little, you can dramatically change your mind-set.

— Kondō, Marie.
“The Life-Changing Magic of Tidying Up”
(p. 15-16)

While incremental slimming of the standard library is a step in the right direction, incremental change can only get us so far. As Marie Kondō says, when you really want to tidy up, the first step is to take everything out so that you can really see everything, and put back only what you need.

It’s time to thank those modules which do not spark joy and send them on their way.

We need a “kernel” version of Python that contains only the most absolutely minimal library, so that all implementations can agree on a core baseline that gives you a “python”, and applications, even those that want to run on web browsers or microcontrollers, can simply state their additional requirements in terms of requirements.txt.

Now, there are some business environments where adding things to your requirements.txt is a fraught, bureaucratic process, and in those places, a large standard library might seem appealing. But “standard library” is a purely arbitrary boundary that the procurement processes in such places have drawn, and an equally arbitrary line may be easily drawn around a binary distribution.

So it may indeed be useful for some CPython binary distributions — perhaps even the official ones — to still ship with a broader selection of modules from PyPI. Even for the average user, in order to use it for development, at the very least, you’d need enough stdlib stuff that pip can bootstrap itself, to install the other modules you need!

It’s already the case, today, that pip is distributed with Python, but isn’t maintained in the CPython repository. What the default Python binary installer ships with is already a separate question from what is developed in the CPython repo, or what ships in the individual source tarball for the interpreter.

In order to use Linux, you need bootable media with a huge array of additional programs. That doesn’t mean the Linux kernel itself is in one giant repository, where the hundreds of applications you need for a functioning Linux server are all maintained by one team. The Linux kernel project is immensely valuable, but functioning operating systems which use it are built from the combination of the Linux kernel and a wide variety of separately maintained libraries and programs.

Conclusion

The “batteries included” philosophy was a great fit for the time when it was created: a booster rocket to sneak Python into the imagination of the programming public. As the open source and Python packaging ecosystems have matured, however, this strategy has not aged well, and like any booster, we must let it fall back to earth, lest it drag us back down with it.

New Python runtimes, new deployment targets, and new developer audiences all present tremendous opportunities for the Python community to soar ever higher.

But to do it, we need a newer, leaner, unburdened “kernel” Python. We need to dump the whole standard library out on the floor, adding back only the smallest bits that we need, so that we can tell what is truly necessary and what’s just nice to have.

I hope I’ve convinced at least a few of you that we need a kernel Python.

Now: who wants to write the PEP?

🚀

Acknowledgments

Thanks to Jean-Paul Calderone, Donald Stufft, Alex Gaynor, Amber Brown, Ian Cordasco, Jonathan Lange, Augie Fackler, Hynek Schlawack, Pete Fein, Mark Williams, Tom Most, Jeremy Thurgood, and Aaron Gallagher for feedback and corrections on earlier drafts of this post. Any errors of course remain my own.


  1. sunau, xdrlib, and chunk are my personal favorites. 

  2. Yeah, yeah, you got me, the mean is 102 days. 

  3. Well, as it turns out, one is on colorsys, but it’s a documentation fix that Alex Gaynor filed after reviewing a draft of this post so I don’t think it really counts. 

Tips And Tricks for Shipping a PyGame App on the Mac

A quick and dirty guide to getting that little PyGame hack you did up and running on someone else’s Mac.

I’ve written and spoken at some length about shipping software in the abstract. Sometimes I’ve even had the occasional concrete tidbit, but that advice wasn’t really complete.

In honor of Eevee’s delightful Games Made Quick???, I’d like to help you package your games even quicker than you made them.

Who is this for?

About ten years ago I made a prototype of a little PyGame thing which I wanted to share with a few friends. Building said prototype was quick and fun, and very different from the usual sort of work I do. But then, the project got just big enough that I started to wonder if it would be possible to share the result, and thus began the long winter of my discontent with packaging tools.

I might be the only one, but... I don’t think so. The history of PyWeek, for example, looks to be a history of games distributed as Github repositories, or, at best, apps which don’t launch. It seems like people who participate in game jams with Unity push a button and publish their games to Steam; people who participate in game jams with Python wander away once the build toolchain defeats them.

So: perhaps you’re also a Python programmer, and you’ve built something with PyGame, and you want to put it on your website so your friends can download it. Perhaps many or most of your friends and family are Mac users. Perhaps you tried to make a thing with py2app once, and got nothing but inscrutable tracebacks or corrupt app bundles for your trouble.

If so, read on and enjoy.

What changed?

If things didn’t work for me when I first tried to do this, what’s different now?

  • the packaging ecosystem in general is far less buggy, and py2app’s dependencies, like setuptools, have become far more reliable as well. Many thanks to Donald Stufft and the whole PyPA for that.
  • Binary wheels exist, and the community has been getting better and better at building self-contained wheels which include any necessary C libraries, relieving the burden on application authors to figure out gnarly C toolchain issues.
  • The PyGame project now ships just such wheels for a variety of Python versions on Mac, Windows, and Linux, which removes a whole huge pile of complexity both in generally understanding the C toolchain and specifically understanding the SDL build process.
  • py2app has been actively maintained and many bugs have been fixed - many thanks to Ronald Oussoren et. al. for that.
  • I finally broke down and gave Apple a hundred dollars so I can produce an app that normal humans might actually be able to run.

There are still weird little corner cases you have to work around — hence this post – but mostly this is the story of how years of effort by the Python packaging community have resulted in tools that are pretty close to working out of the box now.

Step 0: Development Setup

Get a good Python. Use Homebrew, and brew install python3. If you need python 2, brew install python2. Don’t use the System python. Probably nothing will work.

You probably also want to use a virtualenv for development. This post is about how to build a for-real thing that other people can download, but part of the magic of Python is the interactive, real-time dynamic nature of everything. Running the full build pipeline every time you change a file or an asset is slow and annoying. However, there’s a weird thing where certain parts of the macOS GUI won’t work right (in PyGame’s case, mostly keyboard focus) unless your code appears to be in an application bundle.

I made this dumb little thing which lets you fake out enough of this that the OS won’t hassle you: you just need to pip install venvdotapp; venvdotapp inside the virtualenv where you’re making your pygame app.

Finally: pip install all your requirements into your virtualenv, including PyGame itself.

Step 1: Make an icon

All good apps need an icon, right?

When I was young, you just popped over into ResEdit Resorcerer MPW CodeWarrior Project Builder Icon Composer Xcode and created a new ICON resource cicn resource .tiff file .icns file. Nowadays there’s some weird opaque stuff with xcassets files and Contents.json and “Copy Bundle Resources” in the default Swift and Objective C project templates and honestly I can’t be bothered to keep track of what’s going on with this nonsense any more.

Luckily the OS ships with the macOS-specific “scriptable image processing system”, which can helpfully convert an icon for you. Make yourself a 512x512 PNG file in your favorite image editor (with an alpha channel!) that you want to use as your icon, then run it something like this:

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$ sips -s format icns Icon.png --out Icon.icns

somewhere in your build process, to produce an icon in the appropriate format.

There’s also one additional wrinkle with PyGame: once you’ve launched the game, PyGame helpfully assigns the cute, but ugly, default PyGame icon to your running process. To avoid this, you’ll need these two lines somewhere in your initialization code, somewhere before pygame.display.init (or, for that matter, pygame.display.<anything>):

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from pygame.sdlmain_osx import InstallNSApplication
InstallNSApplication()

Obviously this is pretty Mac-specific so you probably want this under some kind of platform-detection conditional, perhaps this one.

Step 2: Just Include All The Dang Files, I Don’t Care About Performance

Unfortunately py2app still tries really hard to jam all your code into a .zip file, which breaks the world in various hilarious ways. Your app will probably have some resources you want to load, as will PyGame itself.

Supposedly, packages=["your_package"] in your setup.py should address this, and it comes with a “pygame” recipe, but neither of these things worked for me. Instead, I convinced py2app to just splat out all the files by using the not-quite-public “recipe” plugin API:

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import py2app.recipes
import py2app.build_app

from setuptools import find_packages, setup

pkgs = find_packages(".")

class recipe_plugin(object):
    @staticmethod
    def check(py2app_cmd, modulegraph):
        local_packages = pkgs[:]
        local_packages += ['pygame']
        return {
            "packages": local_packages,
        }

py2app.recipes.my_recipe = recipe_plugin

APP = ['my_main_file.py']
DATA_FILES = []
OPTIONS = {}
OPTIONS.update(
    iconfile="Icon.icns",
    plist=dict(CFBundleIdentifier='com.example.yourdomain.notmine')
)

setup(
    name="Your Game",
    app=APP,
    data_files=DATA_FILES,
    include_package_data=True,
    options={'py2app': OPTIONS},
    setup_requires=['py2app'],
    packages=pkgs,
    package_data={
        "": ["*.gal" , "*.gif" , "*.html" , "*.jar" , "*.js" , "*.mid" ,
             "*.png" , "*.py" , "*.pyc" , "*.sh" , "*.tmx" , "*.ttf" ,
             # "*.xcf"
        ]
    },
)

This is definitely somewhat less efficient than py2app’s default of stuffing the code into a single zip file, but, as a counterpoint to that: it actually works.

Step 3: Build it

Hopefully, at this point you can just do python setup.py py2app and get a shiny new app bundle in dist/$NAME.app. We haven’t had to go through the hell of quarantine just yet, so it should launch at this point. If it doesn’t, sorry :-(.

You can often debug more obvious fail-to-launch issues by running the executable in the command line, by running ./dist/$NAME.app/Contents/MacOS/$NAME. Although this will run in a slightly different environment than double clicking (it will have all your shell’s env vars, for example, so if your app needs an env var to work it might mysteriously work there) it will also print out any tracebacks to your terminal, where they’ll be slightly easier to find than in Console.app.

Once your app at least runs locally, it’s time to...

Step 4: Code sign it

All the tutorials that I’ve found on how to do this involve doing Xcode project goop where it’s not clear what’s happening underneath. But despite the fact that the introductory docs aren’t quite there, the underlying model for codesigning stuff is totally common across GUI and command-line cases. However, actually getting your cert requires Xcode, an apple ID, and a credit card.

After paying your hundred dollars, go into Xcode, go to Accounts, hit “+”, “Apple ID”, then log in. Then, in your shiny new account, go to “Manage Certificates”, hit the little “+”, and (assuming, like me, you want to put something up on your own website, and not submit to the Mac App Store), and choose Developer ID Application. You probably think you want “mac app distribution” because you are wanting to distribute a mac app! But you don’t.

Next, before you do anything else, make sure you have backups of your certificate and private key. You really don’t want to lose the private key associated with that cert.

Now quit Xcode; you’re done with the GUI.

You will need to know the identifier of your signing key though, which should be output from the command:

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$ security find-identity -v -p codesigning | grep 'Developer ID' | sed -e 's/.*"\(.*\)"/\1/'

You probably want to put that in your build script, since you want to sign with the same identity every time. The command to do the signing is:

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$ codesign -fs "${YOUR_DEVELOPER_ID_IDENTITY}" --deep "dist/${NAME}.app"

Step 5: Archive it

The right way to do this is probably to use dmgbuild or something like it, but what I promised here was quick and dirty, not beautiful and best practices.

You have to make an archive that preserves symbolic links. There are a few options for this:

  • open dist/, then in the Finder window that comes up, right click on the app and “compress” it
  • cd dist; tar czf $NAME.app.tgz $NAME.app
  • cd dist; zip -yr $NAME.app.zip $NAME.app

Most importantly, if you use the zip command line tool, you must use the -y option. Without it, your downloadable app bundle will be somewhat mysteriously broken even though the one before you zipped it will be fine.

Step 6: Download it

Ideally, at this point, everything should be working. But to make sure that code-signing and archiving went correctly, you should have either a pristine virtual machine with no dev tools and no Python installed, or a non-programmer friend’s machine that can serve the same purpose. They probably need a relatively recent macOS - I know that apps made using the above technique will definitely work on High Sierra and will definitely break on Yosemite; they probably start working at some OS version between those.

There’s no tooling that I know of that can clearly tell you whether your mac app depends on some detail of your local machine. Even for your dependencies, there’s no auditwheel for macOS. So it’s always a good idea to check your final app build on a fresh computer before you announce it.

Coda

If you were expecting to get to the end and download my cool game, sorry to disappoint! It really is a half-broken prototype that is in no way ready for public consumption, and given my current load of personal and professional responsibilities, you definitely shouldn’t expect anything from me in this area any time soon, or, you know, ever.

But, from years of experience, I know that it’s nearly impossible to summon any motivation to work on small projects like this without the knowledge that the end result will be usable in some way, so I hope that this helps someone else set up their Python game-dev pipeline.

I’d really like to turn this into a 3-part series, with a part for Linux (perhaps using flatpak? is that a good thing?) and a part for Windows. However, given my aforementioned time constraints, I don’t think I’m going to have the time or energy to do that research, so if you’ve got the appropriate knowledge, I’d love to host a guest post on this blog, or even just a link to yours.

If this post helped you, if you have questions or corrections, or if you’d like to write the Linux or Windows version of this post, let me know.

Careful With That PyPI

PyPI credentials are important. Here are some tips for securing them a little better.

Too Many Secrets

A wise man once said, “you shouldn’t use ENV variables for secret data”. In large part, he was right, for all the reasons he gives (and you should read them). Filesystem locations are usually a better operating system interface to communicate secrets than environment variables; fewer things can intercept an open() than can read your process’s command-line or calling environment.

One might say that files are “more secure” than environment variables. To his credit, Diogo doesn’t, for good reason: one shouldn’t refer to the superiority of such a mechanism as being “more secure” in general, but rather, as better for a specific reason in some specific circumstance.

Supplying your PyPI password to tools you run on your personal machine is a very different case than providing a cryptographic key to a containerized application in a remote datacenter. In this case, based on the constraints of the software presently available, I believe an environment variable provides better security, if you use it correctly.

Popping A Shell By Any Other Name

If you upload packages to the python package index, and people use those packages, your PyPI password is an extremely high-privilege credential: effectively, it grants a time-delayed arbitrary code execution privilege on all of the systems where anyone might pip install your packages.

Unfortunately, the suggested mechanism to manage this crucial, potentially world-destroying credential is to just stick it in an unencrypted file.

The authors of this documentation know this is a problem; the authors of the tooling know too (and, given that these tools are all open source and we all could have fixed them to be better about this, we should all feel bad).

Leaving the secret lying around on the filesystem is a form of ambient authority; a permission you always have, but only sometimes want. One of the worst things about this is that you can easily forget it’s there if you don’t use these credentials very often.

The keyring is a much better place, but even it can be a slightly scary place to put such a thing, because it’s still easy to put it into a state where some random command could upload a PyPI release without prompting you. PyPI is forever, so we want to measure twice and cut once.

Luckily, even more secure places exist: password managers. If you use https://1password.com or https://www.lastpass.com, both offer command-line interfaces that integrate nicely with PyPI. If you use 1password, you’ll really want https://stedolan.github.io/jq/ (apt-get install jq, brew install jq) to slice & dice its command-line.

The way that I manage my PyPI credentials is that I never put them on my filesystem, or even into my keyring; instead, I leave them in my password manager, and very briefly toss them into the tools that need them via an environment variable.

First, I have the following shell function, to prevent any mistakes:

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function twine () {
    echo "Use dev.twine or prod.twine depending on where you want to upload.";
    return 1;
}

For dev.twine, I configure twine to always only talk to my local DevPI instance:

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function dev.twine () {
    env TWINE_USERNAME=root \
        TWINE_PASSWORD= \
        TWINE_REPOSITORY_URL=http://127.0.0.1:3141/root/plus/ \
        twine "$@";
}

This way I can debug Twine, my setup.py, and various test-upload things without ever needing real credentials at all.

But, OK. Eventually, I need to actually get the credentials and do the thing. How does that work?

1Password

1password’s command line is a little tricky to log in to (you have to eval its output, it’s not just a command), so here’s a handy shell function that will do it.

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function opme () {
    # Log this shell in to 1password.
    if ! env | grep -q OP_SESSION; then
        eval "$(op signin "$(jq -r '.latest_signin' ~/.op/config)")";
    fi;
}

Then, I have this little helper for slicing out a particular field from the OP JSON structure:

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function _op_field () {
    jq -r '.details.fields[] | select(.name == "'"${1}"'") | .value';
}

And finally, I use this to grab the item I want (named, memorably enough, “PyPI”) and invoke Twine:

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function prod.twine () {
    opme;
    local pypi_item="$(op get item PyPI)";
    env TWINE_USERNAME="$(echo ${pypi_item} | _op_field username)" \
        TWINE_PASSWORD="$(echo "${pypi_item}" | _op_field password)" \
        twine "$@";
}

LastPass

For lastpass, you can just log in (for all shells; it’s a little less secure) via lpass login; if you’ve logged in before you often don’t even have to do that, and it will just prompt you when running command that require you to be logged in; so we don’t need the preamble that 1password’s command line did.

Its version of prod.twine looks quite similar, but its plaintext output obviates the need for jq:

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function prod.twine () {
    env TWINE_USERNAME="$(lpass show PyPI --username)" \
        TWINE_PASSWORD="$(lpass show PyPI --password)" \
        twine "$@";
}

In Conclusion

“Keep secrets out of your environment” is generally a good idea, and you should always do it when you can. But, better a moment in your process environment than an eternity on your filesystem. Environment-based configuration can be a very useful stopgap for limiting the lifetimes of credentials when your tools don’t support more sophisticated approaches to secret storage.1

Post Script

If you are interested in secure secret storage, my micro-project secretly might be of interest. Right now it doesn’t do a whole lot; it’s just a small wrapper around the excellent keyring module and the pinentry / pinentry-mac password prompt tools. secretly presents an interface both for prompting users for their credentials without requiring the command-line or env vars, and for saving them away in keychain, for tools that need to pull in an API key and don’t want to make the user manually edit a config file first.


  1. Really, PyPI should have API keys that last for some short amount of time, that automatically expire so you don’t have to freak out if you gave somebody a 5-year-old laptop and forgot to wipe it first. But again, if I wanted that so bad, I should have implemented it myself... 

Photo Flow

How do you edit and share photos when more than one person is involved?

Hello, the Internet. If you don’t mind, I’d like to ask you a question about photographs.

My spouse and I both take pictures. We both anticipate taking more pictures in the near future. No reason, just a total coincidence.

We both have iPhones, and we both have medium-nice cameras that are still nicer than iPhones. We would both like to curate and touch up these photos and actually do something with them; ideally we would do this curation collaboratively, whenever either of us has time.

This means that there are three things we want to preserve:

  1. The raw, untouched photographs, in their original resolution,
  2. The edits that have been made to them, and
  3. The “workflow” categorization that has been done to them (minimally, “this photo has not been looked at”, “this photo has been looked at and it’s not good enough to bother sharing”, “this photo has been looked at and it’s good enough to be shared if it’s touched up”, and “this has been/should be shared in its current state”). Generally speaking this is a “which album is it in” categorization.

I like Photos. I have a huge photo library with years of various annotations in it, including faces (the only tool I know of that lets you do offline facial recognition so you can automatically identify pictures of your relatives without giving the police state a database to do the same thing).

However, iCloud Photo Sharing has a pretty major issue; it downscales photographs to “up to 2048 pixels on the long edge”, which is far smaller even than the 12 megapixels that the iPhone 7 sports; more importantly it’s lower resolution than our television, so the image degradation is visible. This is fine for sharing a pic or two on a small phone screen, but not good for a long-term archival solution.

To complicate matters, we also already have an enormous pile of disks in a home server that I have put way too much energy into making robust; a similarly-sized volume of storage would cost about $1300 a year with iCloud (and would not fit onto one account, anyway). I’m not totally averse to paying for some service if it’s turnkey, but something that uses our existing pile of storage would definitely get bonus points.

Right now, my plan is to dump all of our photos into a shared photo library on a network drive, only ever edit them at home, try to communicate carefully about when one or the other of us is editing it so we don’t run into weird filesystem concurrency issues, and hope for the best. This does not strike me as a maximally robust solution. Among other problems, it means the library isn’t accessible to our mobile devices. But I can’t think of anything better.

Can you? Email me. If I get a really great answer I’ll post it in a followup.

Beyond ThunderDock

I Plugged Some Stuff Into A Thunderbolt Dock. You Won’t Believe what Happens Next

This weekend I found myself pleased to receive a Kensington SD5000T Thunderbolt 3 Docking Station.

Some of its functionality was a bit of a weird surprise.

The Setup

Due to my ... accretive history with computer purchases, I have 3 things on my desk at home: a USB-C macbook pro, a 27" Thunderbolt iMac, and an older 27" Dell display, which is old enough at this point that I can’t link it to you. Please do not take this to be some kind of totally sweet setup. It would just be somewhat pointlessly expensive to replace this jumble with something nicer. I purchased the dock because I want to have one cable to connect me to power & both displays.

For those not familiar, iMacs of a certain vintage1 can be jury-rigged to behave as Thunderbolt displays with limited functionality (no access from the guest system to the iMac’s ethernet port, for example), using Target Display Mode, which extends their useful lifespan somewhat. (This machine is still, relatively speaking, a powerhouse, so it’s not quite dead yet; but it’s nice to be able to swap in my laptop and use the big screen.)

The Link-up

On the back of the Thunderbolt dock, there are 2 Thunderbolt 3 ports. I plugged the first one into a Thunderbolt 3 to Thunderbolt 2 adapter which connects to the back of the iMac, and the second one into the Macbook directly. The Dell display plugs into the DisplayPort; I connected my network to the Ethernet port of the dock. My mouse, keyboard, and iPhone were plugged into the USB ports on the dock.

The Problem

I set it up and at first it seemed to be delivering on the “one cable” promise of thunderbolt 3. But then I switched WiFi off to test the speed of the wired network and was surprised to see that it didn’t see the dock’s ethernet port at all. Flipping wifi back on, I looked over at my router’s control panel and noticed that a new device (with the expected manufacturer) was on my network. nmap seemed to indicate that it was... running exactly the network services I expected to see on my iMac. VNCing into the iMac to see what was going on, I popped open the Network system preference pane, and right there alongside all the other devices, was the thunderbolt dock’s ethernet device.

The Punch Line

Despite the miasma of confusion surrounding USB-C and Thunderbolt 32, the surprise here is that apparently Thunderbolt is Thunderbolt, and (for this device at least) Thunderbolt devices connected across the same bus can happily drive whatever they’re plugged in to. The Thunderbolt 2 to 3 adapter isn’t just a fancy way of plugging in hard drives and displays with the older connector; as far as I can tell all the functionality of the Thunderbolt interface remains intact as both “host” and “guest”. It’s like having an ethernet switch for your PCI bus.

What this meant is that when I unplugged everything and then carefully plugged in the iMac before the Macbook, it happily lit up the Dell display, and connected to all the USB devices plugged into the USB hub. When I plugged the laptop in, it happily started charging, but since it didn’t “own” the other devices, nothing else connected to it.

Conclusion

This dock works a little bit too well; when I “dock” now I have to carefully plug in the laptop first, give it a moment to grab all the devices so that it “owns” them, then plug in the iMac, then use this handy app to tell the iMac to enter Target Display mode.

On the other hand, this does also mean that I can quickly toggle between “everything is plugged in to the iMac” and “everything is plugged in to the MacBook” just by disconnecting and reconnecting a single cable, which is pretty neat.


  1. Sadly, not the most recent fancy 5K ones. 

  2. which are, simultaneously, both the same thing and not the same thing.