Merge branch '21744-trainee-interface' of github.com:howsoai/howso-en…

…gine-ts into 21744-trainee-interface

MIGRATION.md

@@ -4,7 +4,7 @@
 
 This major change refactors the client and types for all Howso Engine operations.
 
-### Typing Changes
+### Typing changes
 
 - Most of all the types are now autogenerated from the Engine API, and will have a different naming schema across
   the board. However, most of the type's properties should remain the same.
@@ -13,7 +13,7 @@ This major change refactors the client and types for all Howso Engine operations
 - The existing `Trainee` type has been renamed to `BaseTrainee` and no longer has a `features` property. Request
   features via the method `getFeatureAttributes` instead.
 
-### Client Changes
+### Client changes
 
 - `BaseClient` has been renamed to `AbstractBaseClient`.
 - `WasmClient` has been renamed to `HowsoWorkerClient`.
@@ -33,6 +33,23 @@ This major change refactors the client and types for all Howso Engine operations
 - The `react` method now uses `context_values` instead of `context` and `action_values` instead of `actions`.
 - `local_*` react features have been removed. Use their unqualified versions instead.
 
+### Utilities changes
+
+- The options of `inferFeatureAttributes`'s `service.infer`'s `InferFeatureAttributesOptions` have been updated to
+  a subset of standard [engine options](https://docs.howso.com/en/release-latest/api_reference/_autosummary/howso.utilities.html#howso.utilities.infer_feature_attributes). Please remap to the following:
+
+```ts
+type InferFeatureAttributesOptions = {
+  dependent_features?: Record<string, string[]>;
+  features?: FeatureAttributesIndex;
+  include_sample?: boolean;
+  infer_bounds?: boolean;
+  mode_bound_features?: string[];
+  ordinal_feature_values?: Record<string, string[]>;
+  tight_bounds?: boolean;
+};
+```
+
 ## 5.x
 
 The `inferFeatureAttributes` function now requires a `sourceFormat` argument, and is strongly typed through a union.

src/features/base.ts

@@ -2,24 +2,20 @@ import type { FeatureAttributesIndex } from "../types";
 
 export type FeatureSourceFormat = "unknown" | "array" | "parsed_array";
 
-export interface InferFeatureBoundsOptions {
-  tightBounds?: boolean | string[];
-  modeBounds?: boolean | string[];
-}
-
-export interface InferFeatureTimeSeriesOptions {
-  timeFeature: string;
-  idFeatureName?: string;
-}
-
-export interface InferFeatureAttributesOptions {
-  defaults?: FeatureAttributesIndex;
-  inferBounds?: boolean | InferFeatureBoundsOptions;
-  timeSeries?: InferFeatureTimeSeriesOptions;
-  ordinalFeatureValues?: Record<string, string[]>;
-  dependentFeatures?: Record<string, string[]>;
-  includeSample?: boolean;
-}
+/**
+ * A subset of supported options.
+ * Full options are available only when using the Python direct client or Platform installation.
+ * @see https://docs.howso.com/en/release-latest/api_reference/_autosummary/howso.utilities.html#howso.utilities.infer_feature_attributes
+ **/
+export type InferFeatureAttributesOptions = {
+  dependent_features?: Record<string, string[]>;
+  features?: FeatureAttributesIndex;
+  include_sample?: boolean;
+  infer_bounds?: boolean;
+  mode_bound_features?: string[];
+  ordinal_feature_values?: Record<string, string[]>;
+  tight_bounds?: boolean;
+};
 
 export interface ArrayData<T = any, C extends string = string> {
   readonly columns: C[];

src/features/sources/Array.test.ts

@@ -70,7 +70,7 @@ describe("features/sources/Array", () => {
           number: { type: "continuous", data_type: "number" },
           date: { type: "continuous", data_type: "formatted_date_time", date_time_format: "%Y-%m-%dT%h-%m-%s" },
         };
-        const features = await service.infer({ defaults, includeSample: true });
+        const features = await service.infer({ features: defaults, include_sample: true });
         expectFeatureAttributesIndex(features);
 
         // Id

src/features/sources/Array.ts

@@ -1,12 +1,5 @@
 import type { FeatureAttributes } from "../../types";
-import {
-  AbstractDataType,
-  ArrayData,
-  FeatureSourceFormat,
-  InferFeatureBoundsOptions,
-  InferFeatureTimeSeriesOptions,
-  isArrayData,
-} from "../base";
+import { AbstractDataType, ArrayData, FeatureSourceFormat, InferFeatureAttributesOptions, isArrayData } from "../base";
 import * as utils from "../utils";
 import { FeatureSerializerBase, InferFeatureAttributeFeatureStatistics, InferFeatureAttributesBase } from "./Base";
 
@@ -124,7 +117,7 @@ export class InferFeatureAttributesFromArray extends InferFeatureAttributesBase
   public async inferBounds(
     attributes: Readonly<FeatureAttributes>,
     featureName: string,
-    options: InferFeatureBoundsOptions,
+    options: InferFeatureAttributesOptions,
   ): Promise<FeatureAttributes["bounds"]> {
     const { minimum, maximum, hasNulls, samples, uniqueValues, totalValues } = await this.getStatistics(featureName);
 
@@ -167,15 +160,12 @@ export class InferFeatureAttributesFromArray extends InferFeatureAttributesBase
       const actualMax = maxValue;
 
       if (minValue !== undefined && maxValue !== undefined) {
-        if (
-          !options.tightBounds ||
-          (Array.isArray(options.tightBounds) && options.tightBounds.indexOf(featureName) === -1)
-        ) {
+        if (!options.tight_bounds) {
           // Use loose bounds
           [minValue, maxValue] = utils.guessLooseBounds(minValue, maxValue);
 
-          const { modeBounds = true } = options;
-          if (modeBounds || (Array.isArray(modeBounds) && modeBounds.indexOf(featureName) >= 0)) {
+          const { mode_bound_features = [] } = options;
+          if (mode_bound_features.includes(featureName)) {
             // Check for mode bounds
             if (uniqueValues !== totalValues) {
               const [modes, modeCount] = utils.allModes(column);
@@ -234,7 +224,7 @@ export class InferFeatureAttributesFromArray extends InferFeatureAttributesBase
     /* eslint-disable-next-line @typescript-eslint/no-unused-vars*/
     featureName: string,
     /* eslint-disable-next-line @typescript-eslint/no-unused-vars*/
-    options: InferFeatureTimeSeriesOptions,
+    options: InferFeatureAttributesOptions,
   ): Promise<Partial<FeatureAttributes>> {
     // TODO - infer time series
     throw new Error("Method not implemented.");

src/features/sources/Base.ts

@@ -1,11 +1,5 @@
 import { FeatureAttributes, FeatureAttributesIndex, FeatureOriginalType } from "../../types";
-import {
-  AbstractDataType,
-  FeatureSourceFormat,
-  InferFeatureAttributesOptions,
-  InferFeatureBoundsOptions,
-  InferFeatureTimeSeriesOptions,
-} from "../base";
+import { AbstractDataType, FeatureSourceFormat, InferFeatureAttributesOptions } from "../base";
 import { coerceDate } from "../utils";
 
 export type InferFeatureAttributeFeatureStatistics = {
@@ -37,10 +31,10 @@ export abstract class InferFeatureAttributesBase {
     // Loop the columns into attributes immediately to get order assigned. Probably should be a Map...
     const columns = await this.getFeatureNames();
     const attributes: FeatureAttributesIndex = columns.reduce((attributes, column) => {
-      attributes[column] = (options.defaults?.[column] || {}) as FeatureAttributes;
+      attributes[column] = (options.features?.[column] || {}) as FeatureAttributes;
       return attributes;
     }, {} as FeatureAttributesIndex);
-    const { ordinalFeatureValues = {}, dependentFeatures = {} } = options;
+    const { ordinal_feature_values: ordinalFeatureValues = {}, dependent_features: dependentFeatures = {} } = options;
 
     const getFeatureAttributes = async (featureName: string): Promise<FeatureAttributes | undefined> => {
       const originalFeatureType = await this.getOriginalFeatureType(featureName);
@@ -100,7 +94,7 @@ export abstract class InferFeatureAttributesBase {
         }
 
         // Infer bounds
-        const { inferBounds = true } = options;
+        const { infer_bounds: inferBounds = true } = options;
         if (inferBounds && !attributes[featureName].bounds) {
           const bounds = await this.inferBounds(
             attributes[featureName],
@@ -117,7 +111,7 @@ export abstract class InferFeatureAttributesBase {
         // TODO - infer time series
         // }
 
-        if (options.includeSample) {
+        if (options.include_sample) {
           additions.sample = await this.getSample(featureName);
         }
 
@@ -248,12 +242,12 @@ export abstract class InferFeatureAttributesBase {
   public abstract inferBounds(
     attributes: Readonly<FeatureAttributes>,
     featureName: string,
-    options: InferFeatureBoundsOptions,
+    options: InferFeatureAttributesOptions,
   ): Promise<FeatureAttributes["bounds"]>;
   public abstract inferTimeSeries(
     attributes: Readonly<FeatureAttributes>,
     featureName: string,
-    options: InferFeatureTimeSeriesOptions,
+    options: InferFeatureAttributesOptions,
   ): Promise<Partial<FeatureAttributes>>;
 
   protected async getSample(featureName: string): Promise<any | undefined> {

src/features/sources/examples/CSV.test.ts

@@ -60,7 +60,7 @@ describe("features/sources/CSV", () => {
           const service = new InferFeatureAttributesFromCSV(data, serviceOptions);
           expect(service.samples?.length).toBe(serviceOptions.samplesLimit);
 
-          const features = await service.infer({ includeSample: true });
+          const features = await service.infer({ include_sample: true });
           expect(Object.keys(features)).toStrictEqual(columns);
           expectFeatureAttributesIndex(features);
           expectAsteroids(features);