@observablehq/stdlib - npm Package Compare versions

Comparing version 5.0.2 to 5.1.0

dist/stdlib.js

@@ -1,2 +0,2 @@
-// @observablehq/stdlib v5.0.2 Copyright 2022 Observable, Inc.
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wt([e,t]){return[e,{value:t,writable:!0,enumerable:!0}]}e.AbstractFile=he,e.FileAttachments=function(e){return Object.assign((t=>{const n=e(t+="");if(null==n)throw new Error(`File not found: ${t}`);if("object"==typeof n&&"url"in n){const{url:e,mimeType:r}=n;return new FileAttachment(e,t,r)}return new FileAttachment(n,t)}),{prototype:FileAttachment.prototype})},e.Library=pt,e.applyDataTableOperations=ht,e.arrayIsPrimitive=Xe,e.getArrowTableSchema=Ce,e.isArrowTable=Oe,e.isDataArray=Qe,e.isDatabaseClient=Je,e.loadDataSource=async function(e,t,n){switch(t){case"table":return at(e,n);case"sql":return ot(e,n)}return e},e.makeQueryTemplate=ct}));

package.json

 {
   "name": "@observablehq/stdlib",
-  "version": "5.0.2",
+  "version": "5.1.0",
   "author": {
@@ -5,0 +5,0 @@ "name": "Observable, Inc.",

src/arrow.js

@@ -0,1 +1,4 @@
+import {arrow9 as arrow} from "./dependencies.js";
+import {cdn} from "./require.js";
+
 // Returns true if the vaue is an Apache Arrow table. This uses a “duck” test
@@ -59,1 +62,5 @@ // (instead of strict instanceof) because we want it to work with a range of
 }
+
+export async function loadArrow() {
+  return await import(`${cdn}${arrow.resolve()}`);
+}

src/duckdb.js

@@ -1,3 +0,3 @@
-import {getArrowTableSchema, isArrowTable} from "./arrow.js";
-import {arrow9 as arrow, duckdb} from "./dependencies.js";
+import {getArrowTableSchema, isArrowTable, loadArrow} from "./arrow.js";
+import {duckdb} from "./dependencies.js";
 import {FileAttachment} from "./fileAttachment.js";
@@ -114,3 +114,3 @@ import {cdn} from "./require.js";
   async describeColumns({table} = {}) {
-    const columns = await this.query(`DESCRIBE ${table}`);
+    const columns = await this.query(`DESCRIBE ${this.escape(table)}`);
     return columns.map(({column_name, column_type, null: nullable}) => ({
@@ -173,5 +173,7 @@ name: column_name,
       case "text/csv":
+      case "text/tab-separated-values":
         return await connection.insertCSVFromPath(file.name, {
           name,
           schema: "main",
+          delimiter: file.mimeType === "text/csv" ? "," : "\t",
           ...options
@@ -207,7 +209,5 @@ });
 async function insertArrowTable(database, name, table, options) {
-  const arrow = await loadArrow();
-  const buffer = arrow.tableToIPC(table);
   const connection = await database.connect();
   try {
-    await connection.insertArrowFromIPCStream(buffer, {
+    await connection.insertArrowTable(table, {
       name,
@@ -247,6 +247,2 @@ schema: "main",
 
-async function loadArrow() {
-  return await import(`${cdn}${arrow.resolve()}`);
-}
-
 // https://duckdb.org/docs/sql/data_types/overview
@@ -261,2 +257,3 @@ function getDuckDBType(type) {
     case "REAL":
+    case "FLOAT":
       return "number";
@@ -263,0 +260,0 @@ case "INTEGER":

src/index.js

 export {FileAttachments, AbstractFile} from "./fileAttachment.js";
 export {Library} from "./library.js";
 export {getArrowTableSchema, isArrowTable} from "./arrow.js";
-export {makeQueryTemplate, loadDataSource, arrayIsPrimitive, isDataArray, isDatabaseClient} from "./table.js";
+export {
+  makeQueryTemplate,
+  loadDataSource,
+  arrayIsPrimitive,
+  isDataArray,
+  isDatabaseClient,
+  __table as applyDataTableOperations
+} from "./table.js";

src/table.js

 import {ascending, descending, reverse} from "d3-array";
 import {FileAttachment} from "./fileAttachment.js";
+import {isArrowTable, loadArrow} from "./arrow.js";
+import {DuckDBClient} from "./duckdb.js";
 
@@ -144,4 +146,4 @@ const nChecks = 20; // number of values to check in each array
 export const __query = Object.assign(
-  async (source, operations, invalidation) => {
-    source = await loadDataSource(await source, "table");
+  async (source, operations, invalidation, name) => {
+    source = await loadTableDataSource(await source, name);
     if (isDatabaseClient(source)) return evaluateQuery(source, makeQueryTemplate(operations, source), invalidation);
@@ -153,5 +155,5 @@ if (isDataArray(source)) return __table(source, operations);
   {
-    sql(source, invalidation) {
+    sql(source, invalidation, name) {
       return async function () {
-        return evaluateQuery(await loadDataSource(await source, "sql"), arguments, invalidation);
+        return evaluateQuery(await loadSqlDataSource(await source, name), arguments, invalidation);
       };
@@ -162,21 +164,82 @@ }
 
-export async function loadDataSource(source, mode) {
+export async function loadDataSource(source, mode, name) {
+  switch (mode) {
+    case "table": return loadTableDataSource(source, name);
+    case "sql": return loadSqlDataSource(source, name);
+  }
+  return source;
+}
+
+// We use a weak map to cache loaded data sources by key so that we don’t have
+// to e.g. create separate SQLiteDatabaseClients every time we’re querying the
+// same SQLite file attachment. Since this is a weak map, unused references will
+// be garbage collected when they are no longer desired. Note: the name should
+// be consistent, as it is not part of the cache key!
+function sourceCache(loadSource) {
+  const cache = new WeakMap();
+  return (source, name) => {
+    if (!source) throw new Error("data source not found");
+    let promise = cache.get(source);
+    if (!promise) {
+      // Warning: do not await here! We need to populate the cache synchronously.
+      promise = loadSource(source, name);
+      cache.set(source, promise);
+    }
+    return promise;
+  };
+}
+
+const loadTableDataSource = sourceCache(async (source, name) => {
   if (source instanceof FileAttachment) {
-    if (mode === "table") {
-      switch (source.mimeType) {
-        case "text/csv": return source.csv({typed: true});
-        case "text/tab-separated-values": return source.tsv({typed: true});
-        case "application/json": return source.json();
-      }
+    switch (source.mimeType) {
+      case "text/csv": return source.csv({typed: true});
+      case "text/tab-separated-values": return source.tsv({typed: true});
+      case "application/json": return source.json();
+      case "application/x-sqlite3": return source.sqlite();
     }
-    if (mode === "table" || mode === "sql") {
-      switch (source.mimeType) {
-        case "application/x-sqlite3": return source.sqlite();
-      }
+    if (/\.(arrow|parquet)$/i.test(source.name)) return loadDuckDBClient(source, name);
+    throw new Error(`unsupported file type: ${source.mimeType}`);
+  }
+  if (isArrowTable(source)) return loadDuckDBClient(source, name);
+  return source;
+});
+
+const loadSqlDataSource = sourceCache(async (source, name) => {
+  if (source instanceof FileAttachment) {
+    switch (source.mimeType) {
+      case "text/csv":
+      case "text/tab-separated-values":
+      case "application/json": return loadDuckDBClient(source, name);
+      case "application/x-sqlite3": return source.sqlite();
     }
+    if (/\.(arrow|parquet)$/i.test(source.name)) return loadDuckDBClient(source, name);
     throw new Error(`unsupported file type: ${source.mimeType}`);
   }
+  if (isDataArray(source)) return loadDuckDBClient(await asArrowTable(source, name), name);
+  if (isArrowTable(source)) return loadDuckDBClient(source, name);
   return source;
+});
+
+async function asArrowTable(array, name) {
+  const arrow = await loadArrow();
+  return arrayIsPrimitive(array)
+    ? arrow.tableFromArrays({[name]: array})
+    : arrow.tableFromJSON(array);
 }
 
+function loadDuckDBClient(
+  source,
+  name = source instanceof FileAttachment
+    ? getFileSourceName(source)
+    : "__table"
+) {
+  return DuckDBClient.of({[name]: source});
+}
+
+function getFileSourceName(file) {
+  return file.name
+    .replace(/@\d+(?=\.|$)/, "") // strip Observable file version number
+    .replace(/\.\w+$/, ""); // strip file extension
+}
+
 async function evaluateQuery(source, args, invalidation) {
@@ -248,5 +311,5 @@ if (!source) throw new Error("missing data source");
     throw new Error("at least one column must be selected");
-  const columns = select.columns ? select.columns.map((c) => `t.${escaper(c)}`) : "*";
+  const columns = select.columns ? select.columns.map(escaper).join(", ") : "*";
   const args = [
-    [`SELECT ${columns} FROM ${formatTable(from.table, escaper)} t`]
+    [`SELECT ${columns} FROM ${formatTable(from.table, escaper)}`]
   ];
@@ -304,4 +367,5 @@ for (let i = 0; i < filter.length; ++i) {
     return from;
+  } else {
+    return escaper(table);
   }
-  return table;
 }
@@ -315,3 +379,3 @@
 function appendOrderBy({column, direction}, args, escaper) {
-  appendSql(`t.${escaper(column)} ${direction.toUpperCase()}`, args);
+  appendSql(`${escaper(column)} ${direction.toUpperCase()}`, args);
 }
@@ -401,3 +465,3 @@
   if (o.type === "column") {
-    appendSql(`t.${escaper(o.value)}`, args);
+    appendSql(escaper(o.value), args);
   } else {
@@ -425,3 +489,5 @@ args.push(o.value);
 // This function applies table cell operations to an in-memory table (array of
-// objects); it should be equivalent to the corresponding SQL query.
+// objects); it should be equivalent to the corresponding SQL query. TODO Use
+// DuckDBClient for data arrays, too, and then we wouldn’t need our own __table
+// function to do table operations on in-memory data?
 export function __table(source, operations) {
@@ -428,0 +494,0 @@ const input = source;

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increased by2.38%

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2079

increased by3.64%

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