This change fixes a few things:
* Most importantly, we need to place a leading "." in the paths
to Gometalinter, otherwise some sub-linters just silently skip
the directory altogether. errcheck is one such linter, which
is a very important one!
* Use an explicit Gometalinter.json file to configure the various
settings. This flips on a few additional linters that aren't
on by default (line line length checking). Sadly, a few that
I'd like to enable take waaaay too much time, so in the future
we may consider a nightly job (this includes code similarity,
unused parameters, unused functions, and others that generally
require global analysis).
* Now that we're running more, however, linting takes a while!
The core Lumi project now takes 26 seconds to lint on my laptop.
That's not terrible, but it's long enough that we don't want to
do the silly "run them twice" thing our Makefiles were previously
doing. Instead, we shall deploy some $$($${PIPESTATUS[1]}-1))-fu
to rely on the fact that grep returns 1 on "zero lines".
* Finally, fix the many issues that this turned up.
I think(?) we are done, except, of course, for needing to drive
down some of the cyclomatic complexity issues (which I'm possibly
going to punt on; see pulumi/lumi#259 for more details).
After 233c5a8 landed, I noticed there are a few things to be fixed up:
* Run gometalinter in all the right places. We need to run both in
lint and lint_quiet targets. I've also cleaned up some of the logic
around what to suppress so there's less repetition.
* We currently @ meaningful commands, which is unfortunate, since it
makes debugging Makefiles tough (especially when looking at CI build
logs). Going forward, we should only use @ for meaningless commands,
like @echo.
* The AWS project wasn't actually running tslint, because it needs to
say `tslint './pack/**/*.ts' --exclude='./pack/node_modules/**'`.
The current script of `tslint lib/aws/pack/...` wasn't actually
running lint, hence we missed a lot of AWS lint issues.
* Fix up the issues that these fixes uncovered. Mostly err shadowing.
LumiJS lambdas can now be serialized when they include calls to other LumiJS lambdas. The chain of lambda dependencies is jointly serialized into the target Lambda.
Also, LumiJS lambdas now include `node_modules` automatically in the AWS Lambda, ensuring the the runtime execution environment more closely matches the deployment time environment.
An early version of the gh-cicd example supporting #134 is added which uses these capabilities, currently including a mocked GitHub resource provider.
This change modifies the existing resource provider RPC interface slightly.
Instead of the Create API returning the bag of output properties, we will
rely on the Get API to do so. As a result, this change takes an initial
whack at implementing Get on all existing AWS resources. The Get API needs
to return a fully populated structure containing all inputs and outputs.
Believe it or not, this is actually part of pulumi/lumi#90.
This was done because just returning output properties is insufficient.
Any input properties that weren't supplied may have default values, for
example, and it is wholly reasonable to expect Lumi scripts to depend on
those values in addition to output values.
This isn't fully functional in its current form, because doing this
change turned up many other related changes required to enable output
properties. For instance, at the moment resource properties are defined
in terms of `resource.URN`s, and yet unfortunately the provider side
knows nothing of URNs (instead preferring to deal in `resource.ID`s).
I am going to handle that in a subsequent isolated change, since it will
have far-reaching implications beyond just modifying create and get.
Our initial implementation of assets was intentionally naive, because
they were limited to single-file assets. However, it turns out that for
real scenarios (like lambdas), we want to support multi-file assets.
In this change, we introduce the concept of an Archive. An archive is
what the term classically means: a collection of files, addressed as one.
For now, we support three kinds: tarfile archives (*.tar), gzip-compressed
tarfile archives (*.tgz, *.tar), and normal zipfile archives (*.zip).
There is a fair bit of library support for manipulating Archives as a
logical collection of Assets. I've gone to great length to avoid making
copies, however, sometimes it is unavoidable (for example, when sizes
are required in order to emit offsets). This is also complicated by the
fact that the AWS libraries often want seekable streams, if not actual
raw contiguous []byte slices.
This change includes a first basic whack at implementing S3 bucket
objects. It leverages the assets infrastructure put in place in the
last commit, supporting uploads from text, files, or arbitrary URIs.
Most of the interesting object properties remain unsupported for now,
but with this we can upload and delete basic S3 objects, sufficient
for a lot of the lambda functions management we need to implement.
This change introduces the basic concept of assets. It is far from
fully featured, however, it is enough to start adding support for various
storage kinds that require access to I/O-backed data (files, etc).
The challenge is that Coconut is deterministic by design, and so you
cannot simply read a file in an ad-hoc manner and present the bytes to
a resource provider. Instead, we will model "assets" as first class
entities whose data source is described to the system in a more declarative
manner, so that the system and resource providers can manage them.
There are three ways to create an asset at the moment:
1. A constant, in-memory string.
2. A path to a file on the local filesystem.
3. A URI, whose scheme is extensible.
Eventually, we want to support byte blobs, but due to our use of a
"JSON-like" type system, this isn't easily expressible just yet.
The URI scheme is extensible in that file://, http://, and https://
are supported "out of the box", but individual providers are free to
recognize their own schemes and support them. For instance, copying
one S3 object to another will be supported simply by passing a URI
with the s3:// protocol in the usual way.
Many utility functions are yet to be written, but this is a start.
