feat: 🎸 Add indexedDb parser (#2068)
* feat: 🎸 Add indexedDb parser ✅ Closes: https://hashicorp.atlassian.net/browse/ICU-12164 --------- Co-authored-by: Lisbet Alvarez <lisbet.alvarez@hashicorp.com>
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/**
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* Copyright (c) HashiCorp, Inc.
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* SPDX-License-Identifier: MPL-2.0
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*/
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import { get } from '@ember/object';
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import { modelIndexes } from '../services/indexed-db';
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/**
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* Takes a POJO representing a filter query and builds a query to
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* query indexedDb with. Note that the first filter is important as that
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* will use the actual index in indexedDb while any subsequent ones will be less efficient.
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*
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* @example
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* const filter = queryIndexedDb(indexedDb, type, {
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* search: generated',
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* filters: {
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* scope_id: {
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* logicalOperator: 'and',
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* values: [{ notEquals: 'scope1' }, { notEquals: 'scope2' }],
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* },
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* },
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* });
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*/
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export async function queryIndexedDb(indexedDb, resource, query) {
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let { search, filters = {} } = query ?? {};
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let filterCollection = indexedDb[resource];
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search = getSearchObject(search, resource);
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filters = cleanObject(filters);
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if (Object.keys(filters).length) {
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// Remove the first item to use as the initial collection and then reduce the remaining ones
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const entries = Object.entries(filters);
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const [firstKey, firstFilterArrayOrObject] = entries.shift();
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filterCollection = await entries.reduce(
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async (currCollection, [key, filterArrayOrObject]) => {
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// Grab the results from the set of one filters to be `AND` together with the rest of the filters
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const filterResults = await buildInitialWhereClause({
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table: indexedDb[resource],
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key,
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filterArrayOrObject,
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}).primaryKeys();
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const resultIdsSet = new Set(filterResults);
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return (await currCollection).and((record) => {
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return resultIdsSet.has(record.id);
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});
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},
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buildInitialWhereClause({
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key: firstKey,
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table: indexedDb[resource],
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filterArrayOrObject: firstFilterArrayOrObject,
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}),
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);
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}
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if (search) {
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const { text, fields } = search;
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filterCollection = filterCollection.filter((record) =>
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fields
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.map((key) => get(record, key))
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.some((element) => {
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if (typeof element === 'string') {
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return element?.toLowerCase().includes(text?.toLowerCase());
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}
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}),
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);
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}
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// OrderBy has to be used on where clauses while if it's a
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// collection already we have to use sortBy. We'll also sort by
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// descending order based on created time to match the API as any
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// "or" clause can change the order
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if (filterCollection.orderBy) {
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return filterCollection.orderBy(getKey('created_time')).reverse().toArray();
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}
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return filterCollection.reverse().sortBy(getKey('created_time'));
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}
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const buildInitialWhereClause = ({ filterArrayOrObject, table, key }) => {
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const filterValueArray = Array.isArray(filterArrayOrObject)
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? filterArrayOrObject
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: filterArrayOrObject.values;
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const { logicalOperator } = filterArrayOrObject;
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// Short circuit if all the filter types were equals or notEquals since indexedDb
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// can more efficiently query if we pass all values at once
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const checkAllFilterType = (type) =>
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filterValueArray.every((obj) => Object.keys(obj)[0] === type);
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if (checkAllFilterType('equals')) {
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return table
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.where(getKey(key))
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.anyOf(filterValueArray.map((obj) => obj['equals']));
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}
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if (checkAllFilterType('notEquals')) {
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return table
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.where(getKey(key))
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.noneOf(filterValueArray.map((obj) => obj['notEquals']));
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}
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// Remove the first item to use as the initial where clause and then reduce the remaining ones
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const [firstOperation, firstFilterValue] = Object.entries(
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filterValueArray[0],
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)[0];
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// Not all are filters are equals or notEquals,
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// manually build the initial where clause and resulting collections
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return filterValueArray.slice(1).reduce(
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(result, currObj) => {
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const [operation, value] = Object.entries(currObj)[0];
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return buildIndexedDbCollection({
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key: getKey(key),
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value,
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collection: result,
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operation,
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logicalOperator,
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});
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},
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buildIndexedDbWhere({
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table,
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key: getKey(key),
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operation: firstOperation,
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value: firstFilterValue,
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}),
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);
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};
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/**
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* Builds the initial where clause for indexed DB to filter on. Note that this makes
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* the first filter important as that will do the real filtering from indexed DB while
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* any subsequent filter has to be done in memory.
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*/
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const buildIndexedDbWhere = ({ table, key, value, operation }) => {
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const baseWhereClause = table.where(key);
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switch (operation) {
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case 'contains':
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// We return an error due to not being able to support contains on first filter due to performance.
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throw new Error('Contains is not supported as the first filter.');
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case 'gt':
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return baseWhereClause.above(value);
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case 'gte':
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return baseWhereClause.aboveOrEqual(value);
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case 'lt':
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return baseWhereClause.below(value);
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case 'lte':
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return baseWhereClause.belowOrEqual(value);
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case 'notEquals':
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return baseWhereClause.notEqual(value);
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default:
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return baseWhereClause.equals(value);
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}
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};
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/**
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* Continues building the queries for indexed DB to filter on. Note that these are not true
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* indexed DB queries and in fact just standard JS filters for logical "and" queries and parallel queries
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* to indexed DB for logical "or" queries that get deduped.
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*/
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const buildIndexedDbCollection = ({
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key,
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value,
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collection,
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operation,
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logicalOperator,
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}) => {
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if (logicalOperator === 'and') {
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switch (operation) {
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case 'contains':
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return collection.and((record) => get(record, key)?.includes(value));
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case 'gt':
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return collection.and((record) => get(record, key) > value);
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case 'gte':
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return collection.and((record) => get(record, key) >= value);
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case 'lt':
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return collection.and((record) => get(record, key) < value);
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case 'lte':
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return collection.and((record) => get(record, key) <= value);
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case 'notEquals':
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return collection.and((record) => get(record, key) !== value);
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default:
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return collection.and((record) => get(record, key) === value);
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}
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}
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switch (operation) {
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case 'contains':
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// We return an error due to not being able to support contains on this filter due to performance.
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throw new Error(
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'Contains is not supported as a filter option with "or" operator.',
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);
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case 'gt':
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return collection.or(key).above(value);
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case 'gte':
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return collection.or(key).aboveOrEqual(value);
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case 'lt':
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return collection.or(key).below(value);
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case 'lte':
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return collection.or(key).belowOrEqual(value);
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case 'notEquals':
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return collection.or(key).notEqual(value);
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default:
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return collection.or(key).equals(value);
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}
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};
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/**
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* Translates the fields passed in from the UI for resources to the keys indexed DB knows them as.
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* Usually it's the path of the actual normalized model.
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*/
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const getKey = (key) => {
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switch (key) {
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case 'scope_id':
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return `attributes.scope.${key}`;
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case 'id':
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return key;
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default:
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return `attributes.${key}`;
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}
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};
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/**
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* Cleans the object to remove any keys that have a value of an empty array. This makes
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* it easier so we don't have to worry about empty arrays getting queried in indexed db.
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*/
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const cleanObject = (obj) => {
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if (!obj) {
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return {};
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}
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return Object.entries(obj).reduce((result, [key, value]) => {
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if (Array.isArray(value)) {
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if (value.length > 0) {
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result[key] = value;
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}
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} else if (value.values.length > 0) {
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result[key] = value;
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}
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return result;
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}, {});
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};
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/**
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* Makes the search object that is expected when a user searches. Uses
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* the indexes we setup in indexed db.
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*/
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const getSearchObject = (text, resource) => {
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if (!text) {
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return null;
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}
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return {
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text,
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fields: modelIndexes[resource]
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.split(', ')
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.map((index) => index.replace('&', '')),
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};
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};
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@@ -9,8 +9,8 @@
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*
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* @example
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* const filter = generateMQLFilterExpression({
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* name: [{ contains: 'search text' }],
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* scope: [{ equals: 'scope1'}, { equals: 'scope2' }],
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* name: { logicalOperator: 'and', values: [{ notEquals: 'search text' }, { notEquals: 'test' }] },
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* scope_id: [{ equals: 'scope1'}, { equals: 'scope2' }],
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* });
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*
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* // (name % "search text") and (scope_id = "scope1" or scope_id = "scope2")
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@@ -21,10 +21,10 @@ export function generateMQLFilterExpression(filterObj) {
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}
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const expressions = Object.entries(filterObj)
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.map(([key, filterObjValue]) => {
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const filterValueArray = Array.isArray(filterObjValue)
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? filterObjValue
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: filterObjValue.values;
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.map(([key, filterArrayOrObject]) => {
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const filterValueArray = Array.isArray(filterArrayOrObject)
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? filterArrayOrObject
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: filterArrayOrObject.values;
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let clauses;
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const filterValues = filterValueArray.map((filterObjValue) => {
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@@ -53,7 +53,7 @@ export function generateMQLFilterExpression(filterObj) {
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});
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// Default to `or` if we don't have a logical operator
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const { logicalOperator } = filterObjValue;
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const { logicalOperator } = filterArrayOrObject;
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if (logicalOperator === 'and') {
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clauses = and(filterValues);
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} else {
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@@ -0,0 +1,24 @@
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/**
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* Takes an array and the current page and pagesize to calculate the correct
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* number of results to return to the caller.
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*
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* @param array
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* @param page
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* @param pageSize
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* @returns {[*]}
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*/
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export const paginateResults = (array, page, pageSize) => {
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const length = array?.length;
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if (!array || length === 0) {
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return [];
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}
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if (!page || !pageSize) {
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return array;
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}
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const offset = (page - 1) * pageSize;
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const start = Math.min(length - 1, offset);
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const end = Math.min(length, offset + pageSize);
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return array.slice(start, end);
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};
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