Package: teal-lang
The Teal Programming LanguageTeal hides the complexity of AWS Lambda + SQS, so you can build serverless data
workflows without managing infrastructure.Describe your workflows in areal programming languagewith first-class
functions, concurrency, and native Python inter-op. Test end-to-end locally,
then deploy to serverless AWS infrastructure in under 60s and start workflows
from anything that can invoke Lambda.Like AWS Step Functions but cheaper and much nicer to use (overheads: a little
Lambda runtime, and a DynamoDB for Teal state).Like Serverless Framework, but handles runtime glue logic in addition to
deployment.Status: Teal works well for small workflows: 5-10 Lambda invocations. Larger
workflows may cause problems, and there is a known issue caused by DynamoDB
restrictions (#12).Get started in 2 minutes.Read the documentation.PyCon Africa 2020 Demos!.ContributingTeal is growing rapidly, and contributions arewarmly welcomed.Is Teal for me?Tealisfor you if:You use Python for processing data, or writing business process workflows.You want an alternative to AWS Step Functions.You don't want to to deploy and manage a task platform (Airflow, Celery, etc).Data in: You can invoke Teal like any Lambda function (AWS cli, S3 trigger,
API gateway, etc).Data out: Use the Python libraries you already have for database access.
Teal just connects them together.Development: Teal runs locally, so you can thoroughly test Teal programs
before deployment (using minio and localstack for any additional infrastructure
that your code uses.Operating: Teal enables contextual cross-thread logging and stacktraces out
of the box, since the entire application is described in one place.Teal Cloud(coming soon) will make this even easier,
with a graphical console, one-click rollbacks of entire serverless applications,
and more. Sign up to the mailing list to hear about this first:https://www.condense9.com/.Teal is like...But...AWS Step FunctionsTeal programs aren't bound to AWS and don't use Step Functions under the hood (just plain Lambda + DynamoDB).Orchestrators (Apache Airflow, etc)You don't have to manage infrastructure, or think in terms of DAGs, and you can test everything locally.Task runners (Celery, etc)You don't have to manage infrastructure.Azure Durable FunctionsWhile powerful, Durable Functions (subjectively) feel complex - their behaviour isn't always obvious.Read more...Why should I learn a new language?Because it'll give you a new way tothinkabout cloud software.Teal is not a Python replacement. It has one specific goal: eliminate the need
toimplementinfrastructure.Writing your own infrastructure is like writing assembly code - only do it if
you really have extreme or unusual requirements. Otherwise, use a high-level
language (Teal!) that hides the complexity and compiles to "soft
infrastructure".Up and running in 2 minutesAll you need:An AWS account, andAWS CLIconfigured.A Python 3.8 virtual environmentTeal is built with Python, and distributed as a Python package. To install it,
run:$pipinstallteal-langThis gives you thetealexecutable. Tryteal -h.Copy the following snippet into a file calledservice.tl:// service.tl

fn main() {
  print("Hello World!");
}Run it (-f mainis optional, andmainis the default):~/new_project$>tealservice.tl-fmainInitialise the project (required for deployment):~/new_project$>tealinitAnd deploy the service to your AWS account (requires AWS credentials andAWS_DEFAULT_REGIONto be defined):~/new_project$>tealdeployFinally, invoke it in AWS (-f mainis optional, as before):~/new_project$>tealinvoke-fmainThat's it! You now have a Teal instance configured in your AWS account, built on
the AWS serverless platform (S3 + Lambda + DynamoDB).More info...Explore a more complex example:Fractals.Create an issueif none of this
makes sense, or you'd like help getting started.Read more...about the languageabout the development processabout configuring TealThings Teal can doWhen running in AWS, Teal threads run in separate lambda invocations.Concurrency & SynchronisationThis is useful when a set computations are related, and must be kept together./*** Return f(x) + g(x), computing f(x) and g(x) in parallel in two separate* threads (Lambda invocations in AWS).*/fncompute(x){a=asyncf(x);// Start computing f(x) in a new threadb=asyncg(x);// Likewise with g(x)awaita+awaitb;// Stop this thread, and resume when {a, b} are ready}Traditional approach: Manually store intermediate results in an external
database, and build the synchronisation logic into the cloud functionsfandg, or use an orchestrator service.Read more...Trivial PipelinesUse this approach when each individual function may take several minutes (and
hence, together would break the 5 minute AWS Lambda limit)./*** Compute f(g(h(x))), using a separate lambda invocation for each* function call.*/fnpipeline(x){a=asynch(x);b=asyncg(awaita);f(awaitb);}Traditional approach:This is functionally similar to a "chain" of AWS Lambda
functions and SQS queues.Mapping / reducingTeal functions are first-class, and can be passed around (closures and anonymous
functions are planned, giving Teal object-oriented capabilities)./*** Compute [f(element) for element in x], using a separate lambda invocation for* each application of f.*/fnmap(f,x,accumulator){ifnullp(x){accumulator}else{// The Teal compiler has tail-recursion optimisationmap(func,rest(x),append(accumulator,asyncf(first(x))))}}This could be used like:fnadd2(x){x+2}fnmain(){futures=map(add2,[1,2,3,4],[]);// ...}Read more...Notes about syntaxThe syntax should look familiar, but there are a couple of things to point out.No 'return' statementEvery expression must return a value, so there is noreturnstatement. The
last expression in a 'block' (expressions between{and}) is returned
implicitly.fnfoo(){"something"}fnmain(){print(foo())// -> prints "something"}Semi-colons are required...... when there is more than one expression in a block.This is ok:fnmain(){print("done")}So is this:fnmain(){print("one");print("two")}And this:fnmain(){print("one");print("two");}But this is not ok:fnmain(){print("one")// <- missing semicolon!print("two")}'print' returns the value printedIn this snippet, "Hello Worlds!" is actually printed twice. First inbar, then
inmain.fnbar(){print("Hello Worlds!")}fnmain(){print(bar())}$>teal-qservice.tl
HelloWorlds!
HelloWorlds!'if' is an expression, and returns a valueThink about it like this: Anifexpression represents a choice betweenvalues.v=ifsomething{true_value}else{false_value};// if 'something' is not true, v is set to nullv=ifsomething{value};FAQWhy is this not a library/DSL in Python?When Teal threads wait on a Future, they stop completely. The Lambda function
saves the machine state and then terminates. When the Future resolves, the
resolving thread restarts any waiting threads by invoking new Lambdas to pick up
execution.To achieve the same thing in Python, the framework would need to dump the entire
Python VM state to disk, and then reload it at a later point -- this may be
possible, but would certainly be non-trivial. An alternative approach would be
to build a langauge on top of Python that looked similar to Python, but feltwrongbecause it was really faking things under the hood.How is Teal like Go?Goroutines are very lightweight, while Tealasyncfunctions are pretty heavy --
they involve creating a new Lambda (or process, when running locally).Teal's concurrency model is similar to Go's, but channels are not fully
implemented so data can only be sent to/from a thread at call/return points.Is this an infrastructure-as-code tool?No, Teal does not do general-purpose infrastructure management. There are
already great tools to do that (Terraform,Pulumi,Serverless
Framework, etc).Instead, Teal reduces the amount of infrastructure you need. Instead of a
distinct Lambda function for every piece of application logic, you only need the
core Teal interpreter (purely serverless) infrastructure.Teal will happily manage that infrastructure for you (throughteal deployandteal destroy), or you can set it up with your in-house custom system.Current Limitations and RoadmapTeal is beta quality, which means that it's not thoroughly tested or feature
complete. This is a non-exhaustive list.LibrariesOnly one Teal program file is supported, but a module/package system isplanned.Error HandlingThere's no error handling - if your function fails, you'll have to restart the
whole process manually. An exception handling system isplanned.TypingFunction inputs and outputs aren't typed. This is a limitation, and will be
fixed soon, probably usingProtoBufsas the interface
definition language.Calling Arbitrary ServicesCurrently you can only call Teal or Python functions -- arbitrary microservices
can't be called. Before Teal v1.0 is released, this will be possible. You will
be able to call a long-running third party service (e.g. an AWS ML service) as a
normal Teal function andawaiton the result.AboutTeal is maintained byCondense9 Ltd.. Get in touch
withric@condense9.comfor help getting running, or if you
need enterprise deployment.Teal started because we couldn't find any data engineering tools that were
productive andfeltlike software engineering. As an industry, we've spent
decades growing a wealth of computer science knowledge, but building data
pipelines in $IaC, or manually crafting workflow DAGs with $AutomationTool,just isn't software.LicenseApache License (Version 2.0). SeeLICENSEfor details.