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Build and scale real-time data applications as easily as writing a Python script

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CircleCI GitHub license GitHub version Groups.io

What is Wally?

Wally is a fast stream-processing framework. Wally makes it easy to react to data in real-time. By eliminating infrastructure complexity, going from prototype to production has never been simpler.

When we set out to build Wally, we had several high-level goals in mind:

  • Create a dependable and resilient distributed computing framework
  • Take care of the complexities of distributed computing "plumbing," allowing developers to focus on their business logic
  • Provide high-performance & low-latency data processing
  • Be portable and deploy easily (i.e., run on-prem or any cloud)
  • Manage in-memory state for the application
  • Allow applications to scale as needed, even when they are live and up-and-running

Getting Started

Wally can be installed via our handy Wallaroo Up command. Check out our installation page to learn more.

APIs

The primary API for Wally is written in Pony. Wally applications are written using this Pony API.

Usage

Once you've installed Wally, Take a look at some of our examples. A great place to start are our word_count or market spread examples in Pony.

"""
Word Count App
"""
use "assert"
use "buffered"
use "collections"
use "net"
use "serialise"
use "wallaroo_labs/bytes"
use "wallaroo"
use "wallaroo_labs/logging"
use "wallaroo_labs/mort"
use "wallaroo_labs/time"
use "wallaroo/core/common"
use "wallaroo/core/metrics"
use "wallaroo/core/sink/tcp_sink"
use "wallaroo/core/source"
use "wallaroo/core/source/tcp_source"
use "wallaroo/core/state"
use "wallaroo/core/topology"

actor Main
  new create(env: Env) =>
    Log.set_defaults()
    try
      let pipeline = recover val
        let lines = Wallaroo.source[String]("Word Count",
          TCPSourceConfig[String].from_options(StringFrameHandler,
                TCPSourceConfigCLIParser("Word Count", env.args)?, 1))

        lines
          .to[String](Split)
          .key_by(ExtractWord)
          .to[RunningTotal](AddCount)
          .to_sink(TCPSinkConfig[RunningTotal].from_options(
            RunningTotalEncoder, TCPSinkConfigCLIParser(env.args)?(0)?))
      end
      Wallaroo.build_application(env, "Word Count", pipeline)
    else
      env.err.print("Couldn't build topology")
    end

primitive Split is StatelessComputation[String, String]
  fun name(): String => "Split"

  fun apply(s: String): Array[String] val =>
    let punctuation = """ !"#$%&'()*+,-./:;<=>?@[\]^_`{|}~ """
    let words = recover trn Array[String] end
    for line in s.split("\n").values() do
      let cleaned =
        recover val s.clone().>lower().>lstrip(punctuation)
          .>rstrip(punctuation) end
      for word in cleaned.split(punctuation).values() do
        words.push(word)
      end
    end
    consume words

class val RunningTotal
  let word: String
  let count: U64

  new val create(w: String, c: U64) =>
    word = w
    count = c

class WordTotal is State
  var count: U64

  new create(c: U64) =>
    count = c

primitive AddCount is StateComputation[String, RunningTotal, WordTotal]
  fun name(): String => "Add Count"

  fun apply(word: String, state: WordTotal): RunningTotal =>
    state.count = state.count + 1
    RunningTotal(word, state.count)

  fun initial_state(): WordTotal =>
    WordTotal(0)

primitive StringFrameHandler is FramedSourceHandler[String]
  fun header_length(): USize =>
    4

  fun payload_length(data: Array[U8] iso): USize ? =>
    Bytes.to_u32(data(0)?, data(1)?, data(2)?, data(3)?).usize()

  fun decode(data: Array[U8] val): String =>
    String.from_array(data)

primitive ExtractWord
  fun apply(input: String): Key =>
    input

primitive RunningTotalEncoder
  fun apply(t: RunningTotal, wb: Writer = Writer): Array[ByteSeq] val =>
    let result =
      recover val
        String().>append(t.word).>append(", ").>append(t.count.string())
          .>append("\n")
      end
    wb.write(result)

    wb.done()

Documentation

Are you the sort who just wants to get going? Dive right into our documentation then! It will get you up and running with Wally.

Wally currently exists as a mono-repo. All the source that is Wally is located in this repo. See repo directory structure for more information.

You can also take a look at our FAQ.

Need Help?

Trying to figure out how to get started? Drop us a line:

Contributing

We welcome contributions. Please see our Contribution Guide

For your pull request to be accepted you will need to accept our Contributor License Agreement

License

Wally is licensed under the Apache version 2 license.

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