ezhulenev

object DatomicPricing {
  object Schema extends VersionedSchemaComponent("0.0.1") {
    object ns {
      val pricing = new Namespace("Pricing")
    }

    val isIndexed = true
    val isComponent = true

    val quoteId    = Attribute(ns.pricing / "QuoteId",   SchemaType.string,  Cardinality.one).withUnique(Unique.identity)

ezhulenev

import com.google.common.util.concurrent.ThreadFactoryBuilder
import java.io.ByteArrayInputStream
import java.util.concurrent.Executors
import java.util.concurrent.atomic.AtomicInteger
import scala.util.Random
import scalaz.concurrent.Task

object GatherApp extends App   {

  lazy val executor = {

ezhulenev

import com.google.common.util.concurrent.ThreadFactoryBuilder
import java.io.ByteArrayInputStream
import java.util.concurrent.Executors
import java.util.concurrent.atomic.AtomicInteger
import scala.util.Random
import scalaz.concurrent.Task
import scalaz.stream._
import scalaz.stream.io._

object ChannelApp extends App {

ezhulenev

package pellucid.data.util

import java.util.concurrent.Executors
import java.util.concurrent.atomic.AtomicInteger

import org.joda.time.format.DateTimeFormat

import scala.util.Random

import scalaz.concurrent.Task

ezhulenev

import java.io.ByteArrayInputStream

import scalaz.stream.io

import scalaz.std.map._
import scalaz.std.vector._

object CsvParsing extends App {

  val csv =

ezhulenev

  import java.util.concurrent.atomic.AtomicInteger
  import scala.concurrent.ExecutionContext.Implicits.global
  import scala.concurrent.Future
  import scala.concurrent.future
  import scala.util.{Failure, Success}
  import scalaz.concurrent.Task
  import scalaz.stream.Process.End
  import scalaz.stream._
  import scalaz.{-\/, \/-}

ezhulenev

package pellucid.dataloader.datascope

import com.google.common.util.concurrent.ThreadFactoryBuilder
import java.util.concurrent._
import java.util.concurrent.atomic.AtomicInteger
import org.slf4j.LoggerFactory
import scala.concurrent.duration._
import scala.concurrent.{Await, Future}
import scala.util.Random

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/**
 * Mention of focus company
 *
 * @param ticker   ticker of focus company
 * @param source   source of this mention (Twitter, RSS, etc...)
 * @param sourceId source specific id
 * @param time     time
 * @param mentions set of other tickers including focus ticker itself
 */
case class Mention(ticker: Ticker, source: String, sourceId: String, time: DateTime, mentions: Set[Ticker])

ezhulenev

object SVM extends App {

  import org.apache.spark.mllib.classification.SVMWithSGD
  import org.apache.spark.mllib.evaluation.BinaryClassificationMetrics
  import org.apache.spark.mllib.linalg.Vectors
  import org.apache.spark.mllib.regression.LabeledPoint
  import org.apache.spark.{SparkContext, SparkConf}

  import scala.util.Random

ezhulenev

# In case you had some strange python installation
# NOTE: .pydistutils.cfg seems to be not compatible with brew install python
# areas I needed to clean before installation
# clean up ~/Library/Python
# clean up .local

# preconditions:
# xcode with command line tools installed
xcode-select --install