1-FixedDomain.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "ce2109f4-b7dd-4013-8df1-ce7a93bb88f7",
   "metadata": {
    "jp-MarkdownHeadingCollapsed": true,
    "tags": []
   },
   "source": [
    "# Preamble"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ded01359-9cef-4d8c-87e3-397683500aec",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "import $ivy.`org.http4s::http4s-ember-client:0.23.23`\n",
    "import $ivy.`org.http4s::http4s-dsl:0.23.23`\n",
    "import $ivy.`org.http4s::http4s-circe:1.0.0-M40`\n",
    "import $ivy.`co.fs2::fs2-core:3.8.0`\n",
    "import $ivy.`co.fs2::fs2-io:3.8.0`\n",
    "import $ivy.`io.circe::circe-parser:0.15.0-M1`\n",
    "import $ivy.`io.circe::circe-generic:0.15.0-M1`\n",
    "import $ivy.`org.slf4j:slf4j-nop:2.0.9`\n",
    "import $ivy.`io.circe::circe-optics:0.15.0`\n",
    "import $ivy.`dev.optics::monocle-macro:3.2.0`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7056ddf6-a00a-4784-a113-c11e50e359a8",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "import fs2.{Pipe, Pull, Stream}\n",
    "import cats.effect.{IO, Async}\n",
    "import cats.effect.unsafe.implicits.global\n",
    "import org.http4s.*, org.http4s.implicits._\n",
    "import io.circe.Json\n",
    "import io.circe.{`export` as _, Json, *}\n",
    "import io.circe.parser._\n",
    "import io.circe.syntax._\n",
    "import io.circe.optics.JsonPath._"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ea08b439-9041-4e5b-8cde-86d7f8d863c9",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "import fs2.{Pipe, Pull, Stream}\n",
    "import cats.effect.{IO, Async}\n",
    "import cats.effect.unsafe.implicits.global\n",
    "import org.http4s.*, org.http4s.implicits._\n",
    "import io.circe.Json\n",
    "import io.circe.{`export` as _, Json, *}\n",
    "import io.circe.parser._\n",
    "import io.circe.syntax._\n",
    "import io.circe.optics.JsonPath._"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "5e794b95-fa51-4af1-bf84-b11646003c71",
   "metadata": {},
   "outputs": [],
   "source": [
    "object IsArray: \n",
    "    def unapply(v: Json): Option[Vector[Json]] = \n",
    "        v.asArray"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "54a0b1d3-2b0d-4fd3-8e63-97f1d5ab88bb",
   "metadata": {},
   "outputs": [],
   "source": [
    "object IsObject: \n",
    "    def unapply(v: Json): Option[JsonObject] = \n",
    "        v.asObject"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f46ea943-fc21-4f3b-b5d3-3e86d7a52c07",
   "metadata": {},
   "outputs": [],
   "source": [
    "object IsString: \n",
    "    def unapply(v: Json): Option[String] = \n",
    "        v.asString"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8a92e71e-723e-4476-b893-4ed525bc3977",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "def stream[F[_]: cats.effect.kernel.Async](u: org.http4s.Uri): Stream[F, Json] = \n",
    "    import org.http4s.ember.client.EmberClientBuilder\n",
    "    import io.circe.jawn.CirceSupportParser\n",
    "    import org.http4s.headers.Authorization\n",
    "    import org.http4s.{Method, Request}\n",
    "    import org.typelevel.jawn.Facade\n",
    "    import org.typelevel.jawn.fs2._\n",
    "\n",
    "    given Facade[Json] = new CirceSupportParser(None, false).facade\n",
    "    val bearerToken = scala.util.Properties.envOrElse(\"BEARER_GITHUB_TOKEN\", \"undefined\")\n",
    "    val authHeader =  Authorization(Credentials.Token(AuthScheme.Bearer, bearerToken))\n",
    "    Stream.resource(EmberClientBuilder.default[F].build).flatMap{\n",
    "        _.stream(Request[F](Method.GET, u).withHeaders(authHeader))\n",
    "         .flatMap(_.body.chunks.parseJsonStream)\n",
    "    }"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0b8dd4a4-8ca8-4d9d-9cd1-789510e1e923",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "extension [A](st: Stream[IO, A])\n",
    "    def run: List[A] = \n",
    "        st.compile.toList.unsafeRunSync()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a925c8de-ab42-41a8-92cd-5461c08bf199",
   "metadata": {},
   "outputs": [],
   "source": [
    "def allCommitPages[F[_]: Async](repo: String): Stream[F, Json] =\n",
    "\n",
    "    def newPage(i: Int): Stream[F, Json] = \n",
    "        stream(Uri.unsafeFromString(s\"$repo/commits?page=$i\"))\n",
    "    \n",
    "    def go(i: Int, s: Stream[F,Json]): Pull[F, Json, Unit] =\n",
    "        s.pull.uncons.flatMap:\n",
    "            case Some((hd,tl)) =>\n",
    "                hd(0) match\n",
    "                    case IsArray(Vector()) => Pull.done\n",
    "                    case _ => Pull.output(hd) >> go(i+1, tl ++ newPage(i))\n",
    "            case None => Pull.done\n",
    "\n",
    "    go(1, newPage(0)).stream"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e1a81dc9-ff3f-4f62-812b-14b3e10e3f7f",
   "metadata": {
    "tags": []
   },
   "source": [
    "# How to embed `jq`? "
   ]
  },
  {
   "attachments": {
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"
    }
   },
   "cell_type": "markdown",
   "id": "8eabd49a-4dc5-441a-b81d-5a4435645f26",
   "metadata": {},
   "source": [
    "![image.png](attachment:ab73e986-e9f6-45a2-88ad-00967e3e8b95.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a3455d31-23f1-4438-8e5b-8be6067ec2fb",
   "metadata": {},
   "source": [
    "### Ad-hoc implementation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d91903c7-b1d7-4524-8f7b-fd31ddcba5f9",
   "metadata": {},
   "outputs": [],
   "source": [
    "class Fs2_Jq[F[_]]: \n",
    "\n",
    "    type Filter = fs2.Pipe[F, Json, Json]\n",
    "\n",
    "    def iterator: Filter = \n",
    "        _ flatMap: \n",
    "            case IsArray(v) => Stream(v*)\n",
    "            case _ => Stream(Json.Null)\n",
    "\n",
    "    extension (f1: Filter)\n",
    "\n",
    "        def |(f2: Filter): Filter = \n",
    "            _ flatMap: json => \n",
    "                f1(Stream(json)).flatMap: json2 => \n",
    "                    f2(Stream(json2)) \n",
    "\n",
    "    def arr(filters: Filter*): Filter = \n",
    "\n",
    "        def concat(f1: Filter, f2: Filter): Filter = \n",
    "            _.flatMap: json => \n",
    "                f1(Stream(json)) ++ f2(Stream(json))\n",
    "\n",
    "        _ flatMap: json => \n",
    "            filters.reduce(concat)(Stream(json))\n",
    "                .fold(List[Json]())(_ :+ _)\n",
    "                .map(Json.arr(_*))\n",
    "\n",
    "    extension (sc: StringContext)\n",
    "\n",
    "        private def index0(k: String): Filter =\n",
    "            _ map:\n",
    "                case IsObject(obj) => obj(k).getOrElse(Json.Null)\n",
    "                case _ => Json.Null\n",
    "\n",
    "        def i(args: Filter*): Filter = \n",
    "            sc.s().split('.').map(index0).reduce(_ | _)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "469a675a-e597-45bf-964f-2cbe584e582f",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "def extractInfo[F[_]]: Pipe[F, Json, Json] = \n",
    "    val Fs2_Jq_F = Fs2_Jq[F]; import Fs2_Jq_F._\n",
    "    iterator | arr(i\"author.login\", i\"commit.author.date\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ece2d6bd-452b-40d7-b37e-7c1cf764f3a7",
   "metadata": {},
   "outputs": [],
   "source": [
    "val commitInfoResults: List[Json] = \n",
    "    allCommitPages[IO](\"https://api.github.com/repos/hablapps/doric\")\n",
    "        .take(2)\n",
    "        .through(extractInfo)\n",
    "        .run"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "831ef77a-86fe-4fc6-92b4-af921f463526",
   "metadata": {},
   "source": [
    "### Deep vs. surface syntax"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2054f1c5-f460-421c-b27f-d345f1acea05",
   "metadata": {},
   "outputs": [],
   "source": [
    "class Fs2_Jq[F[_]]: \n",
    "\n",
    "    type Filter = Pipe[F, Json, Json]\n",
    "\n",
    "    /* Primitive filters */\n",
    "\n",
    "    def id: Filter = \n",
    "        identity[Stream[F, Json]]\n",
    "\n",
    "    def str(s: String): Filter = \n",
    "        _.map(_ => Json.fromString(s))\n",
    "\n",
    "    def iterator: Filter = \n",
    "        _ flatMap: \n",
    "            case IsArray(v) => Stream(v*)\n",
    "            case _ => Stream(Json.Null)\n",
    "\n",
    "    extension (f1: Filter)\n",
    "\n",
    "        def |(f2: Filter): Filter = \n",
    "            _ flatMap: json => \n",
    "                f1(Stream(json)).flatMap: json2 => \n",
    "                    f2(Stream(json2)) \n",
    "\n",
    "        def concat(f2: Filter): Filter = \n",
    "            _ flatMap: json => \n",
    "                f1(Stream(json)) ++ f2(Stream(json))\n",
    "\n",
    "        private def indexObj(key: String)(v: Json): Stream[F, Json] = \n",
    "            f1(Stream(v)) map:\n",
    "                case IsObject(obj) => obj(key).getOrElse(Json.Null)\n",
    "                case _ => Json.Null\n",
    "\n",
    "        def index(f2: Filter): Filter = \n",
    "            _ flatMap: v => \n",
    "                f2(Stream(v)) flatMap:\n",
    "                    case IsString(s) => indexObj(s)(v)\n",
    "                    case _ => Stream(Json.Null)\n",
    "\n",
    "    def array(f: Filter): Filter = \n",
    "        _ flatMap: json => \n",
    "            f(Stream(json))\n",
    "                .fold(List[Json]())(_ :+ _)\n",
    "                .map(Json.arr(_*))\n",
    "\n",
    "    /* Syntactic sugar */\n",
    "\n",
    "    def arr(f: Filter*): Filter = \n",
    "        array(f.reduce(_ concat _))\n",
    "\n",
    "    extension (sc: StringContext)\n",
    "        def i(args: Filter*): Filter = \n",
    "            sc.s().split('.').map(key => id.index(str(key))).reduce(_ | _)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a26548cb-66f2-4a63-99d6-fb9c571452ab",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "def extractInfo[F[_]]: Pipe[F, Json, Json] = \n",
    "    val Fs2_Jq_F = Fs2_Jq[F]; import Fs2_Jq_F._\n",
    "    iterator | arr(i\"author.login\", i\"commit.author.date\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b3017d5a-18d7-439f-b991-7212769b47fc",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "val commitInfoResults: List[Json] = \n",
    "    allCommitPages[IO](\"https://api.github.com/repos/hablapps/doric\")\n",
    "        .take(2)\n",
    "        .through(extractInfo)\n",
    "        .run"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "eff6b840-1e26-4c64-aa7d-9d6a55924798",
   "metadata": {},
   "source": [
    "### Built-in functions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0d5ee6a1-93e2-441f-b205-2e0224197641",
   "metadata": {},
   "outputs": [],
   "source": [
    "class Fs2_Jq[F[_]]: \n",
    "\n",
    "    type Filter = Pipe[F, Json, Json]\n",
    "\n",
    "    /* Primitive filters */\n",
    "\n",
    "    def id: Filter = \n",
    "        identity[Stream[F, Json]]\n",
    "\n",
    "    def str(s: String): Filter = \n",
    "        _.map(_ => Json.fromString(s))\n",
    "\n",
    "    def iterator: Filter = \n",
    "        _ flatMap: \n",
    "            case IsArray(v) => Stream(v*)\n",
    "            case _ => Stream(Json.Null)\n",
    "\n",
    "    extension (f1: Filter)\n",
    "\n",
    "        def |(f2: Filter): Filter = \n",
    "            _ flatMap: json => \n",
    "                f1(Stream(json)).flatMap: json2 => \n",
    "                    f2(Stream(json2)) \n",
    "\n",
    "        def concat(f2: Filter): Filter = \n",
    "            _ flatMap: json => \n",
    "                f1(Stream(json)) ++ f2(Stream(json))\n",
    "\n",
    "        private def indexObj(key: String)(v: Json): Stream[F, Json] = \n",
    "            f1(Stream(v)) map:\n",
    "                case IsObject(obj) => obj(key).getOrElse(Json.Null)\n",
    "                case _ => Json.Null\n",
    "\n",
    "        def index(f2: Filter): Filter = \n",
    "            _ flatMap: v => \n",
    "                f2(Stream(v)) flatMap:\n",
    "                    case IsString(s) => indexObj(s)(v)\n",
    "                    case _ => Stream(Json.Null)\n",
    "\n",
    "    def array(f: Filter): Filter = \n",
    "        _ flatMap: json => \n",
    "            f(Stream(json))\n",
    "                .fold(List[Json]())(_ :+ _)\n",
    "                .map(Json.arr(_*))\n",
    "\n",
    "    /* derived functions */\n",
    "\n",
    "    def map(f: Filter): Filter = \n",
    "        array(iterator | f)\n",
    "    \n",
    "    /* \n",
    "    def map_adhoc(f: Filter): Filter = \n",
    "        _ flatMap { \n",
    "            case j if j.isArray => \n",
    "                Stream(j.asArray.get:_*)\n",
    "                    .flatMap{ j => f(Stream(j)) }\n",
    "                    .fold(List[Json]())(_ :+ _)\n",
    "                    .map(Json.arr(_:_*))\n",
    "            case _ => Stream()\n",
    "        }\n",
    "    */\n",
    "\n",
    "    /* Syntactic sugar */\n",
    "\n",
    "    def arr(f: Filter*): Filter = \n",
    "        array(f.reduce(_ concat _))\n",
    "\n",
    "    extension (sc: StringContext)\n",
    "        def i(args: Filter*): Filter = \n",
    "            sc.s().split('.').map(key => id.index(str(key))).reduce(_ | _)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1d0cac48-99c9-4a37-9ace-b01bd2763cdf",
   "metadata": {},
   "outputs": [],
   "source": [
    "def test[F[_]: cats.effect.Async] = \n",
    "    val Fs2_Jq_F = Fs2_Jq[F]; import Fs2_Jq_F._\n",
    "    commitsStr[F].through(map(i\"author.login\"))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "89caf8af-6437-4a69-9de0-20f2a89f703c",
   "metadata": {},
   "source": [
    "### What if we want another semantics, e.g. akka stream?"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3e3f09ee-bdbd-4f99-8201-51f7f9efa5f8",
   "metadata": {},
   "source": [
    "We have to repeat a lot of things: namely, the signatures of the primitive functions, the derived combinators, the syntactic sugar ... "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "08818495-d055-4913-8eae-9260083d97b2",
   "metadata": {},
   "outputs": [],
   "source": [
    "import $ivy.`com.typesafe.akka::akka-stream:2.8.5`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "da5d5b6b-7484-46b8-8199-3dc3a547fa7e",
   "metadata": {},
   "outputs": [],
   "source": [
    "import akka.stream._\n",
    "import akka.stream.scaladsl._\n",
    "import akka.{ Done, NotUsed }"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "583b5bac-5542-4fcf-be1b-29004b3b8809",
   "metadata": {},
   "outputs": [],
   "source": [
    "object Akka_Jq: \n",
    "\n",
    "    type Filter = Flow[Json, Json, akka.NotUsed]\n",
    "\n",
    "    /* Primitive filters */\n",
    "\n",
    "    def id: Filter = \n",
    "        Flow[Json]\n",
    "\n",
    "    def str(s: String): Filter = \n",
    "        Flow.fromFunction(_ => Json.fromString(s))\n",
    "\n",
    "    def iterator: Filter = \n",
    "        ???\n",
    "\n",
    "    extension (f1: Filter)\n",
    "\n",
    "        def |(f2: Filter): Filter = \n",
    "            ???\n",
    "\n",
    "        def concat(f2: Filter): Filter = \n",
    "            ???\n",
    "\n",
    "        private def indexObj(key: String)(v: Json): Stream[IO, Json] = \n",
    "            ???\n",
    "\n",
    "        def index(f2: Filter): Filter = \n",
    "            ???\n",
    "\n",
    "    def array(f: Filter): Filter = \n",
    "        ???\n",
    "\n",
    "    /* derived functions */\n",
    "\n",
    "    def map(f: Filter): Filter = \n",
    "        array(iterator | f)\n",
    "    \n",
    "    /* Syntactic sugar */\n",
    "\n",
    "    def arr(f: Filter*): Filter = \n",
    "        array(f.reduce(_ concat _))\n",
    "\n",
    "    extension (sc: StringContext)\n",
    "        def i(args: Filter*): Filter = \n",
    "            sc.s().split('.').map(key => id.index(str(key))).reduce(_ | _)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e4340884-dd5f-4208-b4aa-b8bbde03ad4e",
   "metadata": {},
   "source": [
    "Also programs are the same: "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "98f5719d-17c2-4e81-949b-bf466505c3de",
   "metadata": {},
   "outputs": [],
   "source": [
    "def extractAuthorInfo: Akka_Jq.Filter = \n",
    "    import Akka_Jq._\n",
    "    iterator | arr(i\"author.login\", i\"commit.author.date\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "094003c7-cdc4-43a5-965b-9c3ed5861920",
   "metadata": {},
   "source": [
    "# References\n",
    "\n",
    "* Scala 3 extension methods: https://docs.scala-lang.org/scala3/book/ca-extension-methods.html\n",
    "* Conversion type class: https://docs.scala-lang.org/scala3/reference/contextual/conversions.html"
   ]
  }
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