refactor: stars calculation moved to platforms

src/backend/platforms/_example.ts

@@ -1,7 +1,6 @@
 /* Imports */
 import axios from "axios";
 
-import { calculateStars } from "../utils/stars";
 import { FetchedQuestion, Platform } from "./";
 
 /* Definitions */
@@ -26,7 +25,7 @@ async function processPredictions(predictions) {
   let results = await predictions.map((prediction) => {
     const id = `${platformName}-${prediction.id}`;
     const probability = prediction.probability;
-    const options = [
+    const options: FetchedQuestion["options"] = [
       {
         name: "Yes",
         probability: probability,
@@ -45,9 +44,6 @@ async function processPredictions(predictions) {
       description: prediction.description,
       options,
       qualityindicators: {
-        stars: calculateStars(platformName, {
-          /* some: somex, factors: factors */
-        }),
         // other: prediction.otherx,
         // indicators: prediction.indicatorx,
       },
@@ -68,4 +64,7 @@ export const example: Platform = {
     let results = await processPredictions(data); // somehow needed
     return results;
   },
+  calculateStars(data) {
+    return 2;
+  },
 };

src/backend/platforms/betfair.ts

@@ -2,7 +2,7 @@
 import axios from "axios";
 import https from "https";
 
-import { calculateStars } from "../utils/stars";
+import { average } from "../../utils";
 import { FetchedQuestion, Platform } from "./";
 
 const platformName = "betfair";
@@ -121,17 +121,13 @@ async function processPredictions(data) {
     if (title.includes("of the named")) {
       title = prediction.marketName + ": " + title;
     }
-    const result = {
+    const result: FetchedQuestion = {
       id,
       title,
       url: `https://www.betfair.com/exchange/plus/politics/market/${prediction.marketId}`,
-      platform: platformName,
       description,
       options,
       qualityindicators: {
-        stars: calculateStars(platformName, {
-          volume: prediction.totalMatched,
-        }),
         volume: prediction.totalMatched,
       },
     };
@@ -149,4 +145,25 @@ export const betfair: Platform = {
     const results = await processPredictions(data); // somehow needed
     return results;
   },
+  calculateStars(data) {
+    const volume = data.qualityindicators.volume || 0;
+    let nuno = () => (volume > 10000 ? 4 : volume > 1000 ? 3 : 2);
+    let eli = () => (volume > 10000 ? null : null);
+    let misha = () => null;
+    let starsDecimal = average([nuno()]); //, eli(), misha()])
+
+    const firstOption = data.options[0];
+
+    // Substract 1 star if probability is above 90% or below 10%
+    if (
+      firstOption &&
+      ((firstOption.probability || 0) < 0.1 ||
+        (firstOption.probability || 0) > 0.9)
+    ) {
+      starsDecimal = starsDecimal - 1;
+    }
+
+    let starsInteger = Math.round(starsDecimal);
+    return starsInteger;
+  },
 };

src/backend/platforms/fantasyscotus.ts

@@ -1,7 +1,6 @@
 /* Imports */
 import axios from "axios";
 
-import { calculateStars } from "../utils/stars";
 import { FetchedQuestion, Platform } from "./";
 
 const platformName = "fantasyscotus";
@@ -100,7 +99,6 @@ async function processData(data) {
         ],
         qualityindicators: {
           numforecasts: Number(predictionData.numForecasts),
-          stars: calculateStars(platformName, {}),
         },
       };
       results.push(eventObject);
@@ -120,4 +118,7 @@ export const fantasyscotus: Platform = {
     let results = await processData(rawData);
     return results;
   },
+  calculateStars(data) {
+    return 2;
+  },
 };

src/backend/platforms/foretold.ts

@@ -1,7 +1,7 @@
 /* Imports */
 import axios from "axios";
 
-import { calculateStars } from "../utils/stars";
+import { average } from "../../utils";
 import { FetchedQuestion, Platform } from "./";
 
 /* Definitions */
@@ -68,7 +68,8 @@ export const foretold: Platform = {
       questions = questions.filter((question) => question.previousAggregate); // Questions without any predictions
       questions.forEach((question) => {
         let id = `${platformName}-${question.id}`;
-        let options = [];
+
+        let options: FetchedQuestion["options"] = [];
         if (question.valueType == "PERCENTAGE") {
           let probability = question.previousAggregate.value.percentage;
           options = [
@@ -84,6 +85,7 @@ export const foretold: Platform = {
             },
           ];
         }
+
         const result: FetchedQuestion = {
           id,
           title: question.name,
@@ -92,7 +94,6 @@ export const foretold: Platform = {
           options,
           qualityindicators: {
             numforecasts: Math.floor(Number(question.measurementCount) / 2),
-            stars: calculateStars(platformName, {}),
           },
           /*liquidity: liquidity.toFixed(2),
           tradevolume: tradevolume.toFixed(2),
@@ -104,4 +105,12 @@ export const foretold: Platform = {
     }
     return results;
   },
+  calculateStars(data) {
+    let nuno = () => 2;
+    let eli = () => null;
+    let misha = () => null;
+    let starsDecimal = average([nuno()]); //, eli(), misha()])
+    let starsInteger = Math.round(starsDecimal);
+    return starsInteger;
+  },
 };

src/backend/platforms/givewellopenphil.ts

@@ -2,7 +2,7 @@
 import axios from "axios";
 import fs from "fs";
 
-import { calculateStars } from "../utils/stars";
+import { average } from "../../utils";
 import { Platform } from "./";
 
 const platformName = "givewellopenphil";
@@ -53,9 +53,7 @@ async function main1() {
       platform: platformName,
       description,
       options: [],
-      qualityindicators: {
+      qualityindicators: {},
-        stars: calculateStars(platformName, {}),
-      },
     }; // Note: This requires some processing afterwards
     // console.log(result)
     results.push(result);
@@ -84,4 +82,12 @@ export const givewellopenphil: Platform = {
     }));
     return dataWithDate;
   },
+  calculateStars(data) {
+    let nuno = () => 2;
+    let eli = () => null;
+    let misha = () => null;
+    let starsDecimal = average([nuno()]); //, eli(), misha()])
+    let starsInteger = Math.round(starsDecimal);
+    return starsInteger;
+  },
 };

src/backend/platforms/goodjudgment.ts

@@ -3,8 +3,8 @@ import axios from "axios";
 import { Tabletojson } from "tabletojson";
 import tunnel from "tunnel";
 
+import { average } from "../../utils";
 import { hash } from "../utils/hash";
-import { calculateStars } from "../utils/stars";
 import { FetchedQuestion, Platform } from "./";
 
 /* Definitions */
@@ -103,9 +103,7 @@ export const goodjudgment: Platform = {
           url: endpoint,
           description,
           options,
-          qualityindicators: {
+          qualityindicators: {},
-            stars: calculateStars(platformName, {}),
-          },
           extra: {
             superforecastercommentary: analysis || "",
           },
@@ -120,4 +118,12 @@ export const goodjudgment: Platform = {
 
     return results;
   },
+  calculateStars(data) {
+    let nuno = () => 4;
+    let eli = () => 4;
+    let misha = () => 3.5;
+    let starsDecimal = average([nuno()]); //, eli(), misha()])
+    let starsInteger = Math.round(starsDecimal);
+    return starsInteger;
+  },
 };

src/backend/platforms/goodjudgmentopen.ts

@@ -2,16 +2,16 @@
 import axios from "axios";
 import { Tabletojson } from "tabletojson";
 
+import { average } from "../../utils";
 import { applyIfSecretExists } from "../utils/getSecrets";
-import { calculateStars } from "../utils/stars";
 import toMarkdown from "../utils/toMarkdown";
-import { Platform } from "./";
+import { FetchedQuestion, Platform } from "./";
 
 /* Definitions */
 const platformName = "goodjudgmentopen";
 
-let htmlEndPoint = "https://www.gjopen.com/questions?page=";
+const htmlEndPoint = "https://www.gjopen.com/questions?page=";
-let annoyingPromptUrls = [
+const annoyingPromptUrls = [
   "https://www.gjopen.com/questions/1933-what-forecasting-questions-should-we-ask-what-questions-would-you-like-to-forecast-on-gjopen",
   "https://www.gjopen.com/questions/1779-are-there-any-forecasting-tips-tricks-and-experiences-you-would-like-to-share-and-or-discuss-with-your-fellow-forecasters",
   "https://www.gjopen.com/questions/2246-are-there-any-forecasting-tips-tricks-and-experiences-you-would-like-to-share-and-or-discuss-with-your-fellow-forecasters-2022-thread",
@@ -22,7 +22,7 @@ const id = () => 0;
 
 /* Support functions */
 
-async function fetchPage(page, cookie) {
+async function fetchPage(page: number, cookie: string) {
   let response = await axios({
     url: htmlEndPoint + page,
     method: "GET",
@@ -35,7 +35,7 @@ async function fetchPage(page, cookie) {
   return response;
 }
 
-async function fetchStats(questionUrl, cookie) {
+async function fetchStats(questionUrl: string, cookie: string) {
   let response = await axios({
     url: questionUrl + "/stats",
     method: "GET",
@@ -50,7 +50,7 @@ async function fetchStats(questionUrl, cookie) {
   // Is binary?
   let isbinary = response.includes("binary?":true");
 
-  let options = [];
+  let options: FetchedQuestion["options"] = [];
   if (isbinary) {
     // Crowd percentage
     let htmlElements = response.split("\n");
@@ -107,21 +107,12 @@ async function fetchStats(questionUrl, cookie) {
     .split(",")[0];
   //console.log(numpredictors)
 
-  // Calculate the stars
-  let minProbability = Math.min(...options.map((option) => option.probability));
-  let maxProbability = Math.max(...options.map((option) => option.probability));
-
   let result = {
-    description: description,
+    description,
-    options: options,
+    options,
     qualityindicators: {
       numforecasts: Number(numforecasts),
       numforecasters: Number(numforecasters),
-      stars: calculateStars("Good Judgment Open", {
-        numforecasts,
-        minProbability,
-        maxProbability,
-      }),
     },
     // this mismatches the code below, and needs to be fixed, but I'm doing typescript conversion and don't want to touch any logic for now
   } as any;
@@ -129,7 +120,7 @@ async function fetchStats(questionUrl, cookie) {
   return result;
 }
 
-function isSignedIn(html) {
+function isSignedIn(html: string) {
   let isSignedInBool = !(
     html.includes("You need to sign in or sign up before continuing") ||
     html.includes("Sign up")
@@ -157,7 +148,7 @@ function sleep(ms: number) {
 
 /* Body */
 
-async function goodjudgmentopen_inner(cookie) {
+async function goodjudgmentopen_inner(cookie: string) {
   let i = 1;
   let response = await fetchPage(i, cookie);
 
@@ -243,6 +234,23 @@ export const goodjudgmentopen: Platform = {
   color: "#002455",
   async fetcher() {
     let cookie = process.env.GOODJUDGMENTOPENCOOKIE;
-    return await applyIfSecretExists(cookie, goodjudgmentopen_inner);
+    return (await applyIfSecretExists(cookie, goodjudgmentopen_inner)) || null;
+  },
+  calculateStars(data) {
+    let minProbability = Math.min(
+      ...data.options.map((option) => option.probability || 0)
+    );
+    let maxProbability = Math.max(
+      ...data.options.map((option) => option.probability || 0)
+    );
+
+    let nuno = () => ((data.qualityindicators.numforecasts || 0) > 100 ? 3 : 2);
+    let eli = () => 3;
+    let misha = () =>
+      minProbability > 0.1 || maxProbability < 0.9 ? 3.1 : 2.5;
+
+    let starsDecimal = average([nuno(), eli(), misha()]);
+    let starsInteger = Math.round(starsDecimal);
+    return starsInteger;
   },
 };

src/backend/platforms/guesstimate.ts

@@ -1,12 +1,10 @@
 import axios from "axios";
-import { parseISO } from "date-fns";
 
-/* Imports */
 import { Question } from "@prisma/client";
 
 import { AlgoliaQuestion } from "../../backend/utils/algolia";
 import { prisma } from "../database/prisma";
-import { Platform } from "./";
+import { FetchedQuestion, Platform, prepareQuestion } from "./";
 
 /* Definitions */
 const searchEndpoint =
@@ -14,25 +12,20 @@ const searchEndpoint =
 
 const apiEndpoint = "https://guesstimate.herokuapp.com";
 
-/* Body */
-
 const modelToQuestion = (model: any): Question => {
   const { description } = model;
   // const description = model.description
   //   ? model.description.replace(/\n/g, " ").replace(/  /g, " ")
   //   : "";
-  const stars = description.length > 250 ? 2 : 1;
+  // const timestamp = parseISO(model.created_at);
-  const timestamp = parseISO(model.created_at);
+  const fq: FetchedQuestion = {
-  const q: Question = {
     id: `guesstimate-${model.id}`,
     title: model.name,
     url: `https://www.getguesstimate.com/models/${model.id}`,
-    timestamp,
+    // timestamp,
-    platform: "guesstimate",
     description,
     options: [],
     qualityindicators: {
-      stars,
       numforecasts: 1,
       numforecasters: 1,
     },
@@ -41,6 +34,7 @@ const modelToQuestion = (model: any): Question => {
     },
     // ranking: 10 * (index + 1) - 0.5, //(model._rankingInfo - 1*index)// hack
   };
+  const q = prepareQuestion(fq, guesstimate);
   return q;
 };
 
@@ -68,7 +62,7 @@ async function search(query: string): Promise<AlgoliaQuestion[]> {
   });
 
   // filter for duplicates. Surprisingly common.
-  let uniqueTitles = [];
+  let uniqueTitles: string[] = [];
   let uniqueModels: AlgoliaQuestion[] = [];
   for (let model of mappedModels) {
     if (!uniqueTitles.includes(model.title) && !model.title.includes("copy")) {
@@ -100,4 +94,5 @@ export const guesstimate: Platform & {
   color: "#223900",
   search,
   fetchQuestion,
+  calculateStars: (q) => (q.description.length > 250 ? 2 : 1),
 };

src/backend/platforms/index.ts

@@ -41,11 +41,16 @@ export interface QualityIndicators {
 
 export type FetchedQuestion = Omit<
   Question,
-  "extra" | "qualityindicators" | "timestamp" | "platform"
+  "extra" | "qualityindicators" | "timestamp" | "platform" | "options"
 > & {
   timestamp?: Date;
   extra?: object; // required in DB but annoying to return empty; also this is slightly stricter than Prisma's JsonValue
-  qualityindicators: QualityIndicators; // slightly stronger type than Prisma's JsonValue
+  options: {
+    name?: string;
+    probability?: number;
+    type: "PROBABILITY";
+  }[]; // stronger type than Prisma's JsonValue
+  qualityindicators: Omit<QualityIndicators, "stars">; // slightly stronger type than Prisma's JsonValue
 };
 
 // fetcher should return null if platform failed to fetch questions for some reason
@@ -56,6 +61,7 @@ export interface Platform {
   label: string; // longer name for displaying on frontend etc., e.g. "X-risk estimates"
   color: string; // used on frontend
   fetcher?: PlatformFetcher;
+  calculateStars: (question: FetchedQuestion) => number;
 }
 
 // draft for the future callback-based streaming/chunking API:
@@ -86,6 +92,22 @@ export const platforms: Platform[] = [
   xrisk,
 ];
 
+export const prepareQuestion = (
+  q: FetchedQuestion,
+  platform: Platform
+): Question => {
+  return {
+    extra: {},
+    timestamp: new Date(),
+    ...q,
+    platform: platform.name,
+    qualityindicators: {
+      ...q.qualityindicators,
+      stars: platform.calculateStars(q),
+    },
+  };
+};
+
 export const processPlatform = async (platform: Platform) => {
   if (!platform.fetcher) {
     console.log(`Platform ${platform.name} doesn't have a fetcher, skipping`);
@@ -97,16 +119,6 @@ export const processPlatform = async (platform: Platform) => {
     return;
   }
 
-  const prepareQuestion = (q: FetchedQuestion): Question => {
-    return {
-      extra: {},
-      timestamp: new Date(),
-      ...q,
-      platform: platform.name,
-      qualityindicators: q.qualityindicators as object, // fighting typescript
-    };
-  };
-
   const oldQuestions = await prisma.question.findMany({
     where: {
       platform: platform.name,
@@ -123,7 +135,7 @@ export const processPlatform = async (platform: Platform) => {
   const updatedQuestions: Question[] = [];
   const deletedIds = oldIds.filter((id) => !fetchedIdsSet.has(id));
 
-  for (const q of fetchedQuestions.map((q) => prepareQuestion(q))) {
+  for (const q of fetchedQuestions.map((q) => prepareQuestion(q, platform))) {
     if (oldIdsSet.has(q.id)) {
       updatedQuestions.push(q);
     } else {

src/backend/platforms/infer.ts

@@ -1,9 +1,9 @@
 /* Imports */
 import axios from "axios";
 
+import { average } from "../../utils";
 import { applyIfSecretExists } from "../utils/getSecrets";
 import { measureTime } from "../utils/measureTime";
-import { calculateStars } from "../utils/stars";
 import toMarkdown from "../utils/toMarkdown";
 import { FetchedQuestion, Platform } from "./";
 
@@ -106,7 +106,6 @@ async function fetchStats(questionUrl, cookie) {
       numforecasts: Number(numforecasts),
       numforecasters: Number(numforecasters),
       comments_count: Number(comments_count),
-      stars: calculateStars(platformName, { numforecasts }),
     },
   };
   // console.log(JSON.stringify(result, null, 4));
@@ -177,9 +176,7 @@ async function infer_inner(cookie: string) {
           let question: FetchedQuestion = {
             id: id,
             title: title,
-            description: moreinfo.description,
             url: url,
-            options: moreinfo.options,
             ...moreinfo,
           };
           console.log(JSON.stringify(question, null, 4));
@@ -236,4 +233,12 @@ export const infer: Platform = {
     let cookie = process.env.INFER_COOKIE;
     return await applyIfSecretExists(cookie, infer_inner);
   },
+  calculateStars(data) {
+    let nuno = () => 2;
+    let eli = () => null;
+    let misha = () => null;
+    let starsDecimal = average([nuno()]); //, eli(), misha()])
+    let starsInteger = Math.round(starsDecimal);
+    return starsInteger;
+  },
 };

src/backend/platforms/kalshi.ts

@@ -1,7 +1,7 @@
 /* Imports */
 import axios from "axios";
 
-import { calculateStars } from "../utils/stars";
+import { average } from "../../utils";
 import { FetchedQuestion, Platform } from "./";
 
 /* Definitions */
@@ -23,7 +23,7 @@ async function processMarkets(markets) {
   markets = markets.filter((market) => market.close_date > dateNow);
   let results = await markets.map((market) => {
     const probability = market.last_price / 100;
-    const options = [
+    const options: FetchedQuestion["options"] = [
       {
         name: "Yes",
         probability: probability,
@@ -43,29 +43,26 @@ async function processMarkets(markets) {
       description: `${market.settle_details}. The resolution source is: ${market.ranged_group_name} (${market.settle_source_url})`,
       options,
       qualityindicators: {
-        stars: calculateStars(platformName, {
-          shares_volume: market.volume,
-          interest: market.open_interest,
-        }),
         yes_bid: market.yes_bid,
         yes_ask: market.yes_ask,
         spread: Math.abs(market.yes_bid - market.yes_ask),
         shares_volume: market.volume, // Assuming that half of all buys are for yes and half for no, which is a big if.
         // "open_interest": market.open_interest, also in shares
       },
+      extra: {
+        open_interest: market.open_interest,
+      },
     };
     return result;
   });
-  //console.log(results.length)
+
-  // console.log(results.map(result => result.title))
-  // console.log(results.map(result => result.title).length)
   console.log([...new Set(results.map((result) => result.title))]);
   console.log(
     "Number of unique questions: ",
     [...new Set(results.map((result) => result.title))].length
   );
-  // console.log([...new Set(results.map(result => result.title))].length)
+
-  return results; //resultsProcessed
+  return results;
 }
 
 export const kalshi: Platform = {
@@ -76,4 +73,29 @@ export const kalshi: Platform = {
     let markets = await fetchAllMarkets();
     return await processMarkets(markets);
   },
+  calculateStars(data) {
+    let nuno = () =>
+      ((data.extra as any)?.open_interest || 0) > 500 &&
+      data.qualityindicators.shares_volume > 10000
+        ? 4
+        : data.qualityindicators.shares_volume > 2000
+        ? 3
+        : 2;
+    // let eli = (data) => data.interest > 10000 ? 5 : 4
+    // let misha = (data) => 4
+    let starsDecimal = average([nuno()]); //, eli(data), misha(data)])
+
+    // Substract 1 star if probability is above 90% or below 10%
+    if (
+      data.options instanceof Array &&
+      data.options[0] &&
+      ((data.options[0].probability || 0) < 0.1 ||
+        (data.options[0].probability || 0) > 0.9)
+    ) {
+      starsDecimal = starsDecimal - 1;
+    }
+
+    let starsInteger = Math.round(starsDecimal);
+    return starsInteger;
+  },
 };

src/backend/platforms/manifold.ts

@@ -1,7 +1,7 @@
 /* Imports */
 import axios from "axios";
 
-import { calculateStars } from "../utils/stars";
+import { average } from "../../utils";
 import { FetchedQuestion, Platform } from "./";
 
 /* Definitions */
@@ -25,16 +25,16 @@ async function fetchData() {
 
 function showStatistics(results: FetchedQuestion[]) {
   console.log(`Num unresolved markets: ${results.length}`);
-  let sum = (arr) => arr.reduce((tally, a) => tally + a, 0);
+  let sum = (arr: number[]) => arr.reduce((tally, a) => tally + a, 0);
   let num2StarsOrMore = results.filter(
-    (result) => result.qualityindicators.stars >= 2
+    (result) => manifold.calculateStars(result) >= 2
   );
   console.log(
     `Manifold has ${num2StarsOrMore.length} markets with 2 stars or more`
   );
   console.log(
     `Mean volume: ${
-      sum(results.map((result) => result.qualityindicators.volume7Days)) /
+      sum(results.map((result) => result.qualityindicators.volume7Days || 0)) /
       results.length
     }; mean pool: ${
       sum(results.map((result) => result.qualityindicators.pool)) /
@@ -47,7 +47,7 @@ async function processPredictions(predictions) {
   let results: FetchedQuestion[] = await predictions.map((prediction) => {
     let id = `${platformName}-${prediction.id}`; // oops, doesn't match platform name
     let probability = prediction.probability;
-    let options = [
+    let options: FetchedQuestion["options"] = [
       {
         name: "Yes",
         probability: probability,
@@ -64,13 +64,8 @@ async function processPredictions(predictions) {
       title: prediction.question,
       url: prediction.url,
       description: prediction.description,
-      options: options,
+      options,
       qualityindicators: {
-        stars: calculateStars(platformName, {
-          volume7Days: prediction.volume7Days,
-          volume24Hours: prediction.volume24Hours,
-          pool: prediction.pool,
-        }),
         createdTime: prediction.createdTime,
         volume7Days: prediction.volume7Days,
         volume24Hours: prediction.volume24Hours,
@@ -99,4 +94,17 @@ export const manifold: Platform = {
     showStatistics(results);
     return results;
   },
+  calculateStars(data) {
+    let nuno = () =>
+      (data.qualityindicators.volume7Days || 0) > 250 ||
+      ((data.qualityindicators.pool || 0) > 500 &&
+        (data.qualityindicators.volume7Days || 0) > 100)
+        ? 2
+        : 1;
+    let eli = () => null;
+    let misha = () => null;
+    let starsDecimal = average([nuno()]); //, eli(data), misha(data)])
+    let starsInteger = Math.round(starsDecimal);
+    return starsInteger;
+  },
 };

src/backend/platforms/metaculus.ts

@@ -1,7 +1,7 @@
 /* Imports */
 import axios from "axios";
 
-import { calculateStars } from "../utils/stars";
+import { average } from "../../utils";
 import toMarkdown from "../utils/toMarkdown";
 import { FetchedQuestion, Platform } from "./";
 
@@ -131,7 +131,7 @@ export const metaculus: Platform = {
             let description = descriptionprocessed2;
 
             let isbinary = result.possibilities.type == "binary";
-            let options = [];
+            let options: FetchedQuestion["options"] = [];
             if (isbinary) {
               let probability = Number(result.community_prediction.full.q2);
               options = [
@@ -156,9 +156,6 @@ export const metaculus: Platform = {
               options,
               qualityindicators: {
                 numforecasts: Number(result.number_of_predictions),
-                stars: calculateStars(platformName, {
-                  numforecasts: result.number_of_predictions,
-                }),
               },
               extra: {
                 resolution_data: {
@@ -193,4 +190,14 @@ export const metaculus: Platform = {
 
     return all_questions;
   },
+  calculateStars(data) {
+    const { numforecasts } = data.qualityindicators;
+    let nuno = () =>
+      (numforecasts || 0) > 300 ? 4 : (numforecasts || 0) > 100 ? 3 : 2;
+    let eli = () => 3;
+    let misha = () => 3;
+    let starsDecimal = average([nuno(), eli(), misha()]);
+    let starsInteger = Math.round(starsDecimal);
+    return starsInteger;
+  },
 };

src/backend/platforms/polymarket.ts

@@ -1,7 +1,7 @@
 /* Imports */
 import axios from "axios";
 
-import { calculateStars } from "../utils/stars";
+import { average } from "../../utils";
 import { FetchedQuestion, Platform } from "./";
 
 /* Definitions */
@@ -96,8 +96,8 @@ export const polymarket: Platform = {
           let options = [];
           for (let outcome in moreMarketInfo.outcomeTokenPrices) {
             options.push({
-              name: marketInfo.outcomes[outcome],
+              name: String(marketInfo.outcomes[outcome]),
-              probability: moreMarketInfo.outcomeTokenPrices[outcome],
+              probability: Number(moreMarketInfo.outcomeTokenPrices[outcome]),
               type: "PROBABILITY",
             });
           }
@@ -112,11 +112,6 @@ export const polymarket: Platform = {
               numforecasts: numforecasts.toFixed(0),
               liquidity: liquidity.toFixed(2),
               tradevolume: tradevolume.toFixed(2),
-              stars: calculateStars(platformName, {
-                liquidity,
-                option: options[0],
-                volume: tradevolume,
-              }),
             },
             extra: {
               address: marketInfo.address,
@@ -132,4 +127,33 @@ export const polymarket: Platform = {
     }
     return results;
   },
+  calculateStars(data) {
+    // let nuno = (data) => (data.volume > 10000 ? 4 : data.volume > 1000 ? 3 : 2);
+    // let eli = (data) => data.liquidity > 10000 ? 5 : 4
+    // let misha = (data) => 4
+
+    const liquidity = data.qualityindicators.liquidity || 0;
+    const volume = data.qualityindicators.tradevolume || 0;
+
+    let nuno = () =>
+      liquidity > 1000 && volume > 10000
+        ? 4
+        : liquidity > 500 && volume > 1000
+        ? 3
+        : 2;
+    let starsDecimal = average([nuno()]); //, eli(data), misha(data)])
+
+    // Substract 1 star if probability is above 90% or below 10%
+    if (
+      data.options instanceof Array &&
+      data.options[0] &&
+      ((data.options[0].probability || 0) < 0.1 ||
+        (data.options[0].probability || 0) > 0.9)
+    ) {
+      starsDecimal = starsDecimal - 1;
+    }
+
+    let starsInteger = Math.round(starsDecimal);
+    return starsInteger;
+  },
 };

src/backend/platforms/predictit.ts

@@ -1,6 +1,6 @@
 import axios from "axios";
 
-import { calculateStars } from "../utils/stars";
+import { average } from "../../utils";
 import toMarkdown from "../utils/toMarkdown";
 import { FetchedQuestion, Platform } from "./";
 
@@ -103,7 +103,6 @@ export const predictit: Platform = {
         description,
         options,
         qualityindicators: {
-          stars: calculateStars(platformName, {}),
           shares_volume,
         },
       };
@@ -113,4 +112,12 @@ export const predictit: Platform = {
 
     return results;
   },
+  calculateStars(data) {
+    let nuno = () => 3;
+    let eli = () => 3.5;
+    let misha = () => 2.5;
+    let starsDecimal = average([nuno(), eli(), misha()]);
+    let starsInteger = Math.round(starsDecimal);
+    return starsInteger;
+  },
 };

src/backend/platforms/rootclaim.ts

@@ -1,7 +1,7 @@
 import axios from "axios";
 import { JSDOM } from "jsdom";
 
-import { calculateStars } from "../utils/stars";
+import { average } from "../../utils";
 import toMarkdown from "../utils/toMarkdown";
 import { FetchedQuestion, Platform } from "./";
 
@@ -79,11 +79,18 @@ export const rootclaim: Platform = {
         options: options,
         qualityindicators: {
           numforecasts: 1,
-          stars: calculateStars(platformName, {}),
         },
       };
       results.push(obj);
     }
     return results;
   },
+  calculateStars(data) {
+    let nuno = () => 4;
+    let eli = () => null;
+    let misha = () => null;
+    let starsDecimal = average([nuno() /*, eli(data), misha(data)*/]);
+    let starsInteger = Math.round(starsDecimal);
+    return starsInteger;
+  },
 };

src/backend/platforms/smarkets.ts

@@ -1,6 +1,6 @@
 import axios from "axios";
 
-import { calculateStars } from "../utils/stars";
+import { average } from "../../utils";
 import { FetchedQuestion, Platform } from "./";
 
 /* Definitions */
@@ -166,9 +166,7 @@ export const smarkets: Platform = {
         description: market.description,
         options: options,
         timestamp: new Date(),
-        qualityindicators: {
+        qualityindicators: {},
-          stars: calculateStars(platformName, {}),
-        },
       };
       VERBOSE ? console.log(result) : empty();
       results.push(result);
@@ -176,4 +174,12 @@ export const smarkets: Platform = {
     VERBOSE ? console.log(results) : empty();
     return results;
   },
+  calculateStars(data) {
+    let nuno = () => 2;
+    let eli = () => null;
+    let misha = () => null;
+    let starsDecimal = average([nuno()]); //, eli(), misha()])
+    let starsInteger = Math.round(starsDecimal);
+    return starsInteger;
+  },
 };

src/backend/platforms/wildeford.ts

@@ -1,9 +1,9 @@
 /* Imports */
 import { GoogleSpreadsheet } from "google-spreadsheet";
 
+import { average } from "../../utils";
 import { applyIfSecretExists } from "../utils/getSecrets";
 import { hash } from "../utils/hash";
-import { calculateStars } from "../utils/stars";
 import { FetchedQuestion, Platform } from "./";
 
 /* Definitions */
@@ -76,7 +76,7 @@ async function processPredictions(predictions) {
     let title = prediction["Prediction"].replace(" [update]", "");
     let id = `${platformName}-${hash(title)}`;
     let probability = Number(prediction["Odds"].replace("%", "")) / 100;
-    let options = [
+    let options: FetchedQuestion["options"] = [
       {
         name: "Yes",
         probability: probability,
@@ -95,9 +95,7 @@ async function processPredictions(predictions) {
       description: prediction["Notes"] || "",
       options,
       timestamp: new Date(Date.parse(prediction["Prediction Date"] + "Z")),
-      qualityindicators: {
+      qualityindicators: {},
-        stars: calculateStars(platformName, null),
-      },
     };
     return result;
   });
@@ -125,4 +123,12 @@ export const wildeford: Platform = {
     const GOOGLE_API_KEY = process.env.GOOGLE_API_KEY; // See: https://developers.google.com/sheets/api/guides/authorizing#APIKey
     return await applyIfSecretExists(GOOGLE_API_KEY, wildeford_inner);
   },
+  calculateStars(data) {
+    let nuno = () => 3;
+    let eli = () => null;
+    let misha = () => null;
+    let starsDecimal = average([nuno()]); //, eli(), misha()])
+    let starsInteger = Math.round(starsDecimal);
+    return starsInteger;
+  },
 };

src/backend/platforms/xrisk.ts

@@ -25,4 +25,5 @@ export const xrisk: Platform = {
     });
     return results;
   },
+  calculateStars: () => 2,
 };

src/backend/utils/getSecrets.ts

@@ -1,5 +1,5 @@
 export async function applyIfSecretExists<T>(
-  cookie: string,
+  cookie: string | undefined,
   fun: (cookie: string) => T
 ) {
   if (cookie) {

src/backend/utils/stars.ts

@@ -1,330 +0,0 @@
-let average = (array: number[]) =>
-  array.reduce((a, b) => a + b, 0) / array.length;
-
-function calculateStarsAstralCodexTen(data) {
-  let nuno = (data) => 3;
-  let eli = (data) => null;
-  let misha = (data) => null;
-  let starsDecimal = average([nuno(data)]); //, eli(data), misha(data)])
-  let starsInteger = Math.round(starsDecimal);
-  return starsInteger;
-}
-
-function calculateStarsBetfair(data) {
-  let nuno = (data) => (data.volume > 10000 ? 4 : data.volume > 1000 ? 3 : 2);
-  let eli = (data) => (data.volume > 10000 ? null : null);
-  let misha = (data) => null;
-  let starsDecimal = average([nuno(data)]); //, eli(data), misha(data)])
-  // Substract 1 star if probability is above 90% or below 10%
-  if (
-    data.option &&
-    (data.option.probability < 0.1 || data.option.probability > 0.9)
-  ) {
-    starsDecimal = starsDecimal - 1;
-  }
-
-  let starsInteger = Math.round(starsDecimal);
-  return starsInteger;
-}
-
-function calculateStarsCoupCast(data) {
-  let nuno = (data) => 3;
-  let starsDecimal = average([nuno(data)]); //, eli(data), misha(data)])
-  let starsInteger = Math.round(starsDecimal);
-  return starsInteger;
-}
-
-function calculateStarsCSETForetell(data) {
-  let nuno = (data) => (data.numforecasts > 100 ? 3 : 2);
-  let eli = (data) => 3;
-  let misha = (data) => 2;
-  let starsDecimal = average([nuno(data), eli(data), misha(data)]);
-  let starsInteger = Math.round(starsDecimal);
-  return starsInteger;
-}
-
-function calculateStarsElicit(data) {
-  let nuno = (data) => 1;
-  let eli = (data) => null;
-  let misha = (data) => null;
-  let starsDecimal = average([nuno(data)]); //, eli(data), misha(data)])
-  let starsInteger = Math.round(starsDecimal);
-  return starsInteger;
-}
-
-function calculateStarsEstimize(data) {
-  let nuno = (data) => 2;
-  let eli = (data) => null;
-  let misha = (data) => null;
-  let starsDecimal = average([nuno(data)]); //, eli(data), misha(data)])
-  let starsInteger = Math.round(starsDecimal);
-  return starsInteger;
-}
-
-function calculateStarsForetold(data) {
-  let nuno = (data) => 2;
-  let eli = (data) => null;
-  let misha = (data) => null;
-  let starsDecimal = average([nuno(data)]); //, eli(data), misha(data)])
-  let starsInteger = Math.round(starsDecimal);
-  return starsInteger;
-}
-
-function calculateStarsGiveWellOpenPhil(data) {
-  let nuno = (data) => 2;
-  let eli = (data) => null;
-  let misha = (data) => null;
-  let starsDecimal = average([nuno(data)]); //, eli(data), misha(data)])
-  let starsInteger = Math.round(starsDecimal);
-  return starsInteger;
-}
-
-function calculateStarsGoodJudgment(data) {
-  let nuno = (data) => 4;
-  let eli = (data) => 4;
-  let misha = (data) => 3.5;
-  let starsDecimal = average([nuno(data)]); //, eli(data), misha(data)])
-  let starsInteger = Math.round(starsDecimal);
-  return starsInteger;
-}
-
-function calculateStarsGoodJudgmentOpen(data) {
-  let nuno = (data) => (data.numforecasts > 100 ? 3 : 2);
-  let eli = (data) => 3;
-  let misha = (data) =>
-    data.minProbability > 0.1 || data.maxProbability < 0.9 ? 3.1 : 2.5;
-  let starsDecimal = average([nuno(data), eli(data), misha(data)]);
-  let starsInteger = Math.round(starsDecimal);
-  return starsInteger;
-}
-
-function calculateStarsHypermind(data) {
-  let nuno = (data) => 3;
-  let eli = (data) => null;
-  let misha = (data) => null;
-  let starsDecimal = average([nuno(data)]); //, eli(data), misha(data)])
-  let starsInteger = Math.round(starsDecimal);
-  return starsInteger;
-}
-
-function calculateStarsInfer(data) {
-  let nuno = (data) => 2;
-  let eli = (data) => null;
-  let misha = (data) => null;
-  let starsDecimal = average([nuno(data)]); //, eli(data), misha(data)])
-  let starsInteger = Math.round(starsDecimal);
-  return starsInteger;
-}
-
-function calculateStarsKalshi(data) {
-  let nuno = (data) =>
-    data.interest > 500 && data.shares_volume > 10000
-      ? 4
-      : data.shares_volume > 2000
-      ? 3
-      : 2;
-  // let eli = (data) => data.interest > 10000 ? 5 : 4
-  // let misha = (data) => 4
-  let starsDecimal = average([nuno(data)]); //, eli(data), misha(data)])
-  // Substract 1 star if probability is above 90% or below 10%
-  if (
-    data.option &&
-    (data.option.probability < 0.1 || data.option.probability > 0.9)
-  ) {
-    starsDecimal = starsDecimal - 1;
-  }
-
-  let starsInteger = Math.round(starsDecimal);
-  return starsInteger;
-}
-
-function calculateStarsLadbrokes(data) {
-  let nuno = (data) => 2;
-  let eli = (data) => null;
-  let misha = (data) => null;
-  let starsDecimal = average([nuno(data)]); //, eli(data), misha(data)])
-  let starsInteger = Math.round(starsDecimal);
-  return starsInteger;
-}
-
-function calculateStarsManifold(data) {
-  let nuno = (data) =>
-    data.volume7Days > 250 || (data.pool > 500 && data.volume7Days > 100)
-      ? 2
-      : 1;
-  let eli = (data) => null;
-  let misha = (data) => null;
-  let starsDecimal = average([nuno(data)]); //, eli(data), misha(data)])
-  let starsInteger = Math.round(starsDecimal);
-  // console.log(data);
-  // console.log(starsInteger);
-  return starsInteger;
-}
-
-function calculateStarsMetaculus(data) {
-  let nuno = (data) =>
-    data.numforecasts > 300 ? 4 : data.numforecasts > 100 ? 3 : 2;
-  let eli = (data) => 3;
-  let misha = (data) => 3;
-  let starsDecimal = average([nuno(data), eli(data), misha(data)]);
-  let starsInteger = Math.round(starsDecimal);
-  return starsInteger;
-}
-
-function calculateStarsOmen(data) {
-  let nuno = (data) => 1;
-  let eli = (data) => null;
-  let misha = (data) => null;
-  let starsDecimal = average([nuno(data)]); //, eli(data), misha(data)])
-  let starsInteger = Math.round(starsDecimal);
-  return starsInteger;
-}
-
-function calculateStarsPolymarket(data) {
-  // let nuno = (data) => (data.volume > 10000 ? 4 : data.volume > 1000 ? 3 : 2);
-  // let eli = (data) => data.liquidity > 10000 ? 5 : 4
-  // let misha = (data) => 4
-
-  let nuno = (data) =>
-    data.liquidity > 1000 && data.volume > 10000
-      ? 4
-      : data.liquidity > 500 && data.volume > 1000
-      ? 3
-      : 2;
-  let starsDecimal = average([nuno(data)]); //, eli(data), misha(data)])
-  // Substract 1 star if probability is above 90% or below 10%
-  if (
-    data.option &&
-    (data.option.probability < 0.1 || data.option.probability > 0.9)
-  ) {
-    starsDecimal = starsDecimal - 1;
-  }
-
-  let starsInteger = Math.round(starsDecimal);
-  return starsInteger;
-}
-
-function calculateStarsPredictIt(data) {
-  let nuno = (data) => 3;
-  let eli = (data) => 3.5;
-  let misha = (data) => 2.5;
-  let starsDecimal = average([nuno(data), eli(data), misha(data)]);
-  let starsInteger = Math.round(starsDecimal);
-  return starsInteger;
-}
-
-function calculateStarsRootclaim(data) {
-  let nuno = (data) => 4;
-  let eli = (data) => null;
-  let misha = (data) => null;
-  let starsDecimal = average([nuno(data) /*, eli(data), misha(data)*/]);
-  let starsInteger = Math.round(starsDecimal);
-  return starsInteger;
-}
-
-function calculateStarsSmarkets(data) {
-  let nuno = (data) => 2;
-  let eli = (data) => null;
-  let misha = (data) => null;
-  let starsDecimal = average([nuno(data)]); //, eli(data), misha(data)])
-  let starsInteger = Math.round(starsDecimal);
-  return starsInteger;
-}
-
-function calculateStarsWildeford(data) {
-  let nuno = (data) => 3;
-  let eli = (data) => null;
-  let misha = (data) => null;
-  let starsDecimal = average([nuno(data)]); //, eli(data), misha(data)])
-  let starsInteger = Math.round(starsDecimal);
-  return starsInteger;
-}
-
-function calculateStarsWilliamHill(data) {
-  let nuno = (data) => 2;
-  let eli = (data) => null;
-  let misha = (data) => null;
-  let starsDecimal = average([nuno(data)]); //, eli(data), misha(data)])
-  let starsInteger = Math.round(starsDecimal);
-  return starsInteger;
-}
-
-export function calculateStars(platform: string, data) {
-  let stars = 2;
-  switch (platform) {
-    case "betfair":
-      stars = calculateStarsBetfair(data);
-      break;
-    case "infer":
-      stars = calculateStarsInfer(data);
-      break;
-    case "foretold":
-      stars = calculateStarsForetold(data);
-      break;
-    case "givewellopenphil":
-      stars = calculateStarsGiveWellOpenPhil(data);
-      break;
-    case "goodjudgment":
-      stars = calculateStarsGoodJudgment(data);
-      break;
-    case "goodjudgmentopen":
-      stars = calculateStarsGoodJudgmentOpen(data);
-      break;
-    case "kalshi":
-      stars = calculateStarsKalshi(data);
-      break;
-    case "manifold":
-      stars = calculateStarsManifold(data);
-      break;
-    case "metaculus":
-      stars = calculateStarsMetaculus(data);
-      break;
-    case "polymarket":
-      stars = calculateStarsPolymarket(data);
-      break;
-    case "predictit":
-      stars = calculateStarsPredictIt(data);
-      break;
-    case "rootclaim":
-      stars = calculateStarsRootclaim(data);
-      break;
-    case "smarkets":
-      stars = calculateStarsSmarkets(data);
-      break;
-    case "wildeford":
-      stars = calculateStarsWildeford(data);
-      break;
-
-    // deprecated
-    case "AstralCodexTen":
-      stars = calculateStarsAstralCodexTen(data);
-      break;
-    case "CoupCast":
-      stars = calculateStarsCoupCast(data);
-      break;
-    case "CSET-foretell":
-      stars = calculateStarsCSETForetell(data);
-      break;
-    case "Elicit":
-      stars = calculateStarsElicit(data);
-      break;
-    case "Estimize":
-      stars = calculateStarsEstimize(data);
-      break;
-    case "Hypermind":
-      stars = calculateStarsHypermind(data);
-      break;
-    case "Ladbrokes":
-      stars = calculateStarsLadbrokes(data);
-      break;
-    case "Omen":
-      stars = calculateStarsOmen(data);
-      break;
-    case "WilliamHill":
-      stars = calculateStarsWilliamHill(data);
-      break;
-    default:
-      stars = 2;
-  }
-  return stars;
-}

src/utils.ts

@@ -6,3 +6,6 @@ export const shuffleArray = <T>(array: T[]): T[] => {
   }
   return array;
 };
+
+export const average = (array: number[]) =>
+  array.reduce((a, b) => a + b, 0) / array.length;