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Also I need more repos...
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This way I can develop on nixpkgs directly, and directly send patches upstream,
instead of trying to copy files back and forth and work with overlays.
Of course with private stuff that I will never publish, I should use overlays,
but that will probably not be very many things, I imagine.
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I also upstreamed this to nixpkgs-dev
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This allows us to use nix-build as a check that bild is working.
I think bild sometimes hangs because it doesn't get input from nix-build? I'm
not sure, but one workaround is to run nix-build on the target, and then bild
will just get the cached build.
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No build should take longer than 5 minutes; if it does then something is wrong
so let's just die and start over.
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Eventually I'll just upstream these to nixpkgs-dev. I also want to make z into a
gemini-compatible zettlekasten. All in due time.
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- structured log messages
- compact logs rewrite the line on bild completion
- using conduit for streaming output (although I think this isn't working quite
right)
- new Proc type for running subprocesses
- general code cleanup and refactoring
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Part of a larger effort, but doing this iteratively in smaller chunks.
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This makes scanning logs *much* easier. I figure keep it as simple as possible,
just red, yellow, and green.
I also added two spaces between labels in the log messages. It would be nice to
have a more structured logging system, but for now this works.
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This argument will run the tests for an output after building. It's active in
'ci' so running that will ensure tests are passing. This way testing a
namespace and building a namespace are as close together as possible, so
presumably it will be that much easier to write good tests.
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Also changes the --test option to a 'test' command. This is because running the
tests for a namespace/exe should never be combined with anything else: you
either want to run the tests, or not.
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Using lib.pipe for readability. Moved analyze into the public functions so I can
debug things easier by calling bild.analyze from the nix repl.
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There is a bug in nixpkgs where lib.strings.splitString overflows on long lines.
builtins.split performs better, but needs the extra filter for some reason.
https://github.com/NixOS/nixpkgs/issues/68951
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Now bild knows how to determine between modules that require ghcjs and ghc. It
also knows what *not* to build, meaning it won't try to build non-buildable nix
targets, for example (unfortunately this is just hardcoded for now), but it also
won't build scm or py targets that I haven't implemented yet. It just silently
fails, which is fine, because it means I can do `bild **/*` and everything just
works.
Of course, if I want to build scm code then I will have to implement that, but
that's not a priority right now.
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I had to refactor Biz/Bild/Rules.nix. I also had to checkin my patched
hoogle.nix file, but I also upstreamed the patch to nixpkgs-dev so it shouldn't
stick around for too long.
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Move them under the Biz root so that we know they are specific to Biz stuff. Biz
is for proprietary stuff that we own.
I also had to refactor the bild namespace parsing code because it couldn't
handle a namespace with 3 parts. I really need to get that namespace library
written and tested.
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This includes deployment and implementation.
As part of sprint-49, here are the startup progress questions:
- Are you on track?
- Yes? I'm making progress toward a proper launch.
- Are you launched?
- No
- How many weeks to launch?
- I would say 4 but it's probably more like 8
- How many (prospective) users have you talked to in the last week?
- 2, Kyle and his manager, see below
- What have you learned from them?
- Kyle thought the metrics were interesting.
- His manager thought the metrics were kinda useful but didn't think they
really helped people ship higher quality code faster. So that's the rub: I
have to show how this can make devs ship higher quality code faster; or,
develop a set of features that improve those things.
- Kyle pointed out that the clustering feature of devalloc will find optimal
pairings *and* identify team silos that could be improved, so that's
important to remember and might be a good angle in the future.
- On a scale of 1-10, what is your morale?
- 6 maybe
- What most improved your primary metric?
- Well I was able to deploy something within in the week, whereas before I had
zero deploys per week. So that's an improvement.
- What is your biggest obstacle?
- Finding customers to talk to.
- Also the thing isn't really built yet, I just have a python script. I need
to build the real SaaS product
- What are your top 1-3 goals for next week?
- Find a single customer I can work with on an ongoing basis
- I should ask around my network to see if I have any second-order
connections that would be willing to work with me (Asher, Chad,
previous bosses, etc)
- Build out the front-end of the website (it's very simple, would just need a
basic miso module and deployment)
- Figure out how to connect/auth to the Github API so I can start building the
SaaS version of the product
Some user feedback from my friend Kyle. This comes from his engineering manager:
> "Looks neat. If it were priced low enough I could see using it to run reports
> as part of an overall package. A lot of those metrics don't matter too much to
> me as a manager though A lot of these code quality tools are handy info but I
> don't feel like they make people ship code any faster or any higher quality
> Things like CodeClimate work well for Jrs though to avoid obvious static type
> mistakes"
Kyle provided some additional comments:
> he might have been an unusual case. Jared's not big into metrics, Pivotal
> Tracker point estimates, or things like that... He's far more into qualitative
> feedback, like retrospectives and 1:1s
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> I think it's definitely neat data! I certainly like the collaboration analysis
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> It's interesting, we recently had a pair where two devs didn't work well
> together, that could be represented here. Though, we didn't want to avoid
> having them work together, we wanted them to find a work style that worked for
> both of them
And that's a good point: devalloc will find optimal pairings *and* points where
you could improve team cohesiveness.
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