411 lines
12 KiB
Markdown
411 lines
12 KiB
Markdown
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---
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title: Sheets with PostgreSQL
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sidebar_label: PostgreSQL
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pagination_prev: demos/desktop/index
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pagination_next: demos/local/index
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sidebar_custom_props:
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sql: true
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---
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import current from '/version.js';
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import CodeBlock from '@theme/CodeBlock';
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[PostgreSQL](https://postgresql.org/) (colloquially referenced as "Postgres") is
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an open source object-relational database system.
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[SheetJS](https://sheetjs.com) is a JavaScript library for reading and writing
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data from spreadsheets.
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This demo uses SheetJS to exchange data between spreadsheets and PostgreSQL
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databases. We'll explore how to use save tables from a database to spreadsheets
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and how to add data from spreadsheets into a database.
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:::caution pass
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**It is strongly recommended to use PostgreSQL with a query builder or ORM.**
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While it is possible to generate SQL statements directly, there are many subtle
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details and pitfalls. Battle-tested solutions generally provide mitigations
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against SQL injection and other vulnerabilities.
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:::
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:::note
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This demo was last tested on 2023 October 30 with PostgreSQL 16.0.1. The demo
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uses `pg` connector module version 8.11.3.
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:::
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## Integration Details
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The [SheetJS NodeJS module](/docs/getting-started/installation/nodejs) can be
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loaded in NodeJS scripts that connect to PostgreSQL databases.
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This demo uses the `pg` connector module[^1], but the same mechanics apply to
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other PostgreSQL libraries.
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### Exporting Data
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`Client#query` returns a Promise that resolves to a result set. The `rows`
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property of the result is an array of objects.
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The SheetJS `json_to_sheet` method[^2] can generate a worksheet object[^3] from
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the array of objects:
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```js
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const table_name = "Tabeller1"; // name of table
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/* fetch all data from specified table */
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const res = await client.query(`SELECT * FROM ${table_name}`);
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/* generate a SheetJS worksheet object from the data */
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const worksheet = XLSX.utils.json_to_sheet(res.rows);
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```
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A workbook object can be built from the worksheet using utility functions[^4].
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The workbook can be exported using the SheetJS `writeFile` method[^5]:
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```js
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/* create a new workbook and add the worksheet */
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const wb = XLSX.utils.book_new();
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XLSX.utils.book_append_sheet(wb, worksheet, "Sheet1");
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/* export workbook to XLSX */
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XLSX.writeFile(wb, "SheetJSPGExport.xlsx");
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```
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### Importing Data
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The SheetJS `sheet_to_json` function[^6] takes a worksheet object and generates
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an array of objects.
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Queries must be manually generated from the objects. Assuming the field names
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in the object match the column headers, a loop can generate `INSERT` queries.
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:::warning pass
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**PostgreSQL does not allow parameterized queries with variable column names**
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```sql
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INSERT INTO table_name (?) VALUES (?);
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-- ---------------------^ variable column names are not valid
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```
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Queries are generated manually. To help prevent SQL injection vulnerabilities,
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the `pg-format`[^7] module escapes identifiers and fields.
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:::
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```js
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/* generate an array of arrays from the worksheet */
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const aoo = XLSX.utils.sheet_to_json(ws);
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const table_name = "Blatte1"; // name of table
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/* loop through the data rows */
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for(let row of aoo) {
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/* generate format helper strings */
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const ent = Object.entries(row);
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const Istr = Array.from({length: entries.length}, ()=>"%I").join(", ");
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const Lstr = Array.from({length: entries.length}, ()=>"%L").join(", ");
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/* generate INSERT statement */
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let query = format.withArray(
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`INSERT INTO %I (${Istr}) VALUES(${Lstr})`,
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[ table_name, ...ent.map(x => x[0]), ...ent.map(x => x[1]) ]
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);
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/* execute INSERT statement */
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await client.query(query);
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}
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```
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### Creating a Table
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The array of objects can be scanned to determine column names and types. With
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the names and types, a `CREATE TABLE` query can be written.
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<details><summary><b>Implementation Details</b> (click to show)</summary>
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The `aoo_to_pg_table` function:
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- scans each row object to determine column names and types
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- drops and creates a new table with the determined column names and types
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- loads the entire dataset into the new table
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```js
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/* create table and load data given an array of objects and a PostgreSQL client */
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async function aoo_to_pg_table(client, aoo, table_name) {
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/* define types that can be converted (e.g. boolean can be stored in float) */
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const T_FLOAT = ["float8", "boolean"];
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const T_BOOL = ["boolean"];
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/* types is a map from column headers to Knex schema column type */
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const types = {};
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/* names is an ordered list of the column header names */
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const names = [];
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/* loop across each row object */
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aoo.forEach(row =>
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/* Object.entries returns a row of [key, value] pairs */
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Object.entries(row).forEach(([k,v]) => {
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/* If this is first occurrence, mark unknown and append header to names */
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if(!types[k]) { types[k] = ""; names.push(k); }
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/* skip null and undefined values */
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if(v == null) return;
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/* check and resolve type */
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switch(typeof v) {
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/* change type if it is empty or can be stored in a float */
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case "number": if(!types[k] || T_FLOAT.includes(types[k])) types[k] = "float8"; break;
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/* change type if it is empty or can be stored in a boolean */
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case "boolean": if(!types[k] || T_BOOL.includes(types[k])) types[k] = "boolean"; break;
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/* no other type can hold strings */
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case "string": types[k] = "text"; break;
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default: types[k] = "text"; break;
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}
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})
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);
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/* Delete table if it exists in the DB */
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const query = format("DROP TABLE IF EXISTS %I;", table_name);
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await client.query(query);
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/* Create table */
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{
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const entries = Object.entries(types);
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const Istr = entries.map(e => format(`%I ${e[1]}`, e[0])).join(", ");
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let query = format.withArray(`CREATE TABLE %I (${Istr});`, [ table_name ]);
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await client.query(query);
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}
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/* Insert each row */
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for(let row of aoo) {
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const ent = Object.entries(row);
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const Istr = Array.from({length: ent.length}, ()=>"%I").join(", ");
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const Lstr = Array.from({length: ent.length}, ()=>"%L").join(", ");
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let query = format.withArray(
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`INSERT INTO %I (${Istr}) VALUES (${Lstr});`,
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[ table_name, ...ent.map(x => x[0]), ...ent.map(x => x[1]) ]
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);
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await client.query(query);
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}
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return client;
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}
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```
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</details>
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## Complete Example
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0) Install and start the PostgreSQL server.
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<details><summary><b>Installation Notes</b> (click to show)</summary>
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On macOS, install the `postgresql` formula with Homebrew:
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```bash
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brew install postgresql@16
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```
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The last few lines of the installer explains how to start the database:
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```text
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Or, if you don't want/need a background service you can just run:
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// highlight-next-line
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LC_ALL="C" /usr/local/opt/postgresql@16/bin/postgres -D /usr/local/var/postgresql@16
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```
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Run the command to start a local database instance.
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</details>
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1) Drop any existing database with the name `SheetJSPG`:
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```bash
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dropdb SheetJSPG
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```
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:::info pass
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If the server is running elsewhere, or if the username is different from the
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current user, command-line flags can override the defaults.
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| Option | Explanation
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|:--------------|:--------------------------|
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| `-h HOSTNAME` | Name of the server |
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| `-p PORT` | specifies the port number |
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| `-U USERNAME` | specifies the username |
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:::
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2) Create an empty `SheetJSPG` database using the `createdb` command:
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```bash
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createdb SheetJSPG
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```
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:::note pass
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`createdb` supports the same `-h`, `-p`, and `-U` flags as `dropdb`.
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:::
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### Connector Test
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3) Create a project folder:
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```bash
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mkdir sheetjs-pg
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cd sheetjs-pg
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npm init -y
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```
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4) Install the `pg` connector module:
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```bash
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npm i --save pg@8.11.3
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```
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5) Save the following example codeblock to `PGTest.js`:
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```js title="PGTest.js"
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const pg = require("pg");
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const client = new pg.Client({
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database:"SheetJSPG",
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// highlight-start
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host: "127.0.0.1", // localhost
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port: 5432,
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//user: "",
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//password: ""
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// highlight-end
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});
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(async() => {
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await client.connect();
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const res = await client.query('SELECT $1::text as message', ['Hello world!']);
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console.log(res.rows[0].message); // Hello world!
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await client.end();
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})();
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```
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6) Edit the new `PGTest.js` script and modify the highlighted lines from the
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codeblock to reflect the database deployment settings.
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The settings in the codeblock match the default configuration for macOS Homebrew
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PostgreSQL server. For other deployments:
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- If the server is not running on your computer, set `host` and `port` to the
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correct host name and port number.
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- If the server expects a different username and password, uncomment the `user`
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and `password` lines and replace the values with the username and password.
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7) Run the script:
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```bash
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node PGTest.js
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```
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It should print `Hello world!`
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:::caution pass
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If the output is not `Hello world!` or if there is an error, please report the
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issue to the `pg` connector project for further diagnosis[^8]
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:::
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### Add SheetJS
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8) Install dependencies:
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<CodeBlock language="bash">{`\
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npm i --save https://cdn.sheetjs.com/xlsx-${current}/xlsx-${current}.tgz pg-format@1.0.4`}
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</CodeBlock>
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9) Download [`SheetJSPG.js`](pathname:///postgresql/SheetJSPG.js):
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```bash
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curl -LO https://docs.sheetjs.com/postgresql/SheetJSPG.js
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```
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This script will:
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- read and parse the test file `pres.numbers`
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- create a connection to the `SheetJSPG` database on a local PostgreSQL server
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- load data from the first worksheet into a table with name `Presidents`
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- disconnect and reconnect to the database
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- dump data from the table `Presidents`
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- export the dataset to `SheetJSPG.xlsx`
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10) Edit the `SheetJSPG.js` script.
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The script defines an `opts` object:
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```js title="SheetJSPG.js (configuration lines)"
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const XLSX = require("xlsx");
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const opts = {
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database:"SheetJSPG",
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// highlight-start
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host: "127.0.0.1", // localhost
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port: 5432,
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//user: "",
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//password: ""
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// highlight-end
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};
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```
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The settings in the codeblock match the default configuration for macOS Homebrew
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PostgreSQL server. For other deployments:
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- If the server is not running on your computer, set `host` and `port` to the
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correct host name and port number.
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- If the server expects a different username and password, uncomment the `user`
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and `password` lines and replace the values with the username and password.
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11) Run the script:
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```bash
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node SheetJSPG.js
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```
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12) Verify the result:
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- `SheetJSPG.xlsx` can be opened in a spreadsheet app or tested in the terminal
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```bash
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npx xlsx-cli SheetJSPG.xlsx
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```
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- The database server can be queried using the `psql` command line tool.
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If the server is running locally, the command will be:
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```bash
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psql SheetJSPG -c 'SELECT * FROM "Presidents";'
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```
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:::note pass
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`psql` supports the same `-h`, `-p`, and `-U` flags as `dropdb` and `createdb`.
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:::
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[^1]: See [the official `pg` website](https://node-postgres.com/) for more info.
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[^2]: See [`json_to_sheet` in "Utilities"](/docs/api/utilities/array#array-of-objects-input)
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[^3]: See ["Sheet Objects"](/docs/csf/sheet) in "SheetJS Data Model" for more details.
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[^4]: See ["Workbook Helpers" in "Utilities"](/docs/api/utilities/wb) for details on `book_new` and `book_append_sheet`.
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[^5]: See [`writeFile` in "Writing Files"](/docs/api/write-options)
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[^6]: See [`sheet_to_json` in "Utilities"](/docs/api/utilities/array#array-output)
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[^7]: The [`pg-format`](https://npm.im/pg-format) package is available on the public NPM registry. Even though the project is marked as deprecated, the official [`pg` website still recommends `pg-format`](https://node-postgres.com/features/queries#parameterized-query:~:text=use%20pg%2Dformat%20package%20for%20handling%20escaping)
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[^8]: The official [issue tracker](https://github.com/brianc/node-postgres/issues) is hosted on GitHub
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